Read All instruction carefully & must be included selected topic and point & write according to instruction
Due in 2 days
4-5 Pages required
Must be 100% Original Work
Download Attachment
Literature Review (Due in 2 days)/.Literature Review (Required Question).docx
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A. Literature Review Opening Narrative |
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i. Contains a brief discussion of the content of the literature that includes a critical analysis and synthesis of various sources/content of the literature (journals, reports, and scholarly seminal books, etc.) to convince readers of depth of inquiry. |
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ii. Explains the organization of the review. |
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iii.Explains the strategy for searching the literature. |
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iv. The majority of references should be from peer-reviewed sources. |
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v. The majority of references should be current. (should be within the past 4 years). |
Must be 100% Original Work (due in 48 hours)
Read All instruction carefully & must be included all point and do on selected topic
Page requirement: 4 to 5 Pages
Course name: DDBA Doctoral Study Completion
Selected Topic name: Customer Complaint Strategies in the Pharmaceutical Industry
Topic for Literature Review: Customer Complaint Strategies in the Pharmaceutical Industry
References should be peer-reviewed & within the past 4 years.
Peer-reviewed sources (should be use below latest Source)
Kumar, N., & Jha, A. (2019). Application of principles of supply chain management to the Pharmaceutical Good Transportation Practices. International Journal of Pharmaceutical and Healthcare Marketing, 13(3), 306–330. https://doi.org/10.1108/ijphm-09-2017-0048
Song, S. Y., Lee, J. H., Kim, S. C., Choi, J.-W., Bae, J., & Kim, E. Y. (2019). Complaints addressed by regulatory authorities in drug advertising targeted at consumers: Cases across three, different countries. Research in Social and Administrative Pharmacy, 15(10), 1274–1279. https://doi.org/10.1016/j.sapharm.2018.12.001
Omoush, M. M. (2020). Investigation the relationship between supply chain management activities and operational performance: Testing the mediating role of strategic agility-A practical study on the pharmaceutical companies. International Business Research, 13(2), 74. https://doi.org/10.5539/ibr.v13n2p74
Tweehuysen, L., Bemt, B. J., Ingen, I. L., Jong, A. J., Laan, W. H., Hoogen, F. H., & Broeder, A. A. (2017). Subjective complaints as the main reason for biosimilar discontinuation after open‐label transition from reference infliximab to biosimilar infliximab. Arthritis & Rheumatology, 70(1), 60–68. https://doi.org/10.1002/art.40324
Chen, M.-C., Hsu, C.-L., & Lee, L.-H. (2019). Service quality and customer satisfaction in Pharmaceutical Logistics: An analysis based on Kano model and importance-satisfaction model. International Journal of Environmental Research and Public Health, 16(21), 4091. https://doi.org/10.3390/ijerph16214091
Castillo Apraiz, J., Richter, N. F., Matey de Antonio, J., & Gudergan, S. (2020). The role of competitive strategy in the performance impact of exploitation and exploration quality management practices. European Business Review, 33(1). https://doi.org/10.1108/ebr-09-2019-0182
Literature Review (Due in 2 days)/DBA_Doctoral_Study_Rubric_Handbook_08252020 (1).doc
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Doctor of Business Administration
Doctoral Study Rubric and Research Handbook
FOREWORD
Walden University
DBA Doctoral Study Rubric and Research Handbook1 July 2020
This document consists of two components: the Doctoral Study Rubric2 and the Research Handbook. Thus, the purpose of this document is two-fold. First, the purpose of the rubric is to guide DBA students and DBA Doctoral Study supervisory committees as they work together to develop high-quality proposals and Doctoral Study research. The committee will use the rubric to provide on-going and flexible evaluation and reevaluation of the proposal and DBA Doctoral Study drafts. The University Research Reviewer (URR), who reviews the proposal/DBA Doctoral Study on behalf of the University, will also use this rubric to communicate feedback and any required revisions.
Second, the Research Handbook is an accompanying guide to the rubric that provides detailed instructions and knowledge pertaining to corresponding rubric components. The doctoral student is still responsible for utilizing self-identified resources to aid in the understanding and presentation of the rubric requirements. Elements in the Doctoral Study rubric correspond to elements in the Research Handbook. For example, one will find more detailed information on the Problem Statement (Heading # 1.3 in the DBA Rubric) in Heading # 1.3 (Problem Statement) of the Research Handbook. Using the Doctoral Study Rubric in conjunction with the Research Handbook when writing the proposal/Doctoral Study is highly recommended.
In the writing process, use the
DBA Template and Rubric as a suggested outline for the DBA Proposal and Doctoral Study and as a basis for feedback on early drafts.
Before the Proposal Oral Conference or DBA Doctoral Study Oral Conference, the committee and URR will complete the rubric in MyDR and upload the proposal per the process checklist. Find the MyDR Process Checklist at
http://academicguides.waldenu.edu/researchcenter/osra/dba
.The guidance on orals is located at
http://academicguides.waldenu.edu/researchcenter/osra/oraldefense.
After the Proposal Oral Conference or DBA Doctoral Study Oral Conference, and once the student completes any committee or methodologist revision requests for the proposal/Doctoral Study, the committee will review the proposal/Doctoral Study and make any needed modifications. When the committee members agree that the student met all of the rubric requirements for the proposal and passed the oral defense, the chair then notes in MyDR that the student passed the oral defense.
1 The DBA Rubric and Research Handbook video tutorial can be viewed at:
http://youtu.be/KiiDGmLbRN0.
2 The guidance in the rubric supersedes any guidance you might see depicted elsewhere. For example, the Problem Statement video tutorial on YouTube depicts a maximum word count of 250 for the Problem Statement. The Problem Statement is recommended not to be too lengthy (recommended not to exceed 150 words). It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate).
About consensus: For the final copy of the proposal or DBA Doctoral Study, there must be unanimous agreement by the DBA Doctoral Study supervisory committee before the student proceeds to the next step in the process checklist.
Timely Review and Return of Student Work
For research courses (i.e., KAMs, dissertations, and doctoral studies), the guideline for review and return of student research drafts is generally within 2 weeks; or, alternatively, provide a substantive overview of issues and concerns and an estimate of when of the full review will be complete. The 2-week time frame is a guideline and representative of what the university believes to be best practices. It is a desired practice for faculty members to respond to students upon receipt of research drafts and indicate when the draft will be returned. The faculty mentor or committee chair should provide students guidance on activities to work on that support student progress in the meantime. If a review of student research work requires significantly more time, for example, due to the length or complexity of the submission from one or more students, then faculty members are expected to notify the student of the additional time estimated to review their work.
Committee chairs or faculty mentors should set expectations early in the term for deadlines relating to submission and return of specified research documents that provide evidence of substantial academic progress. This is part of the term plan and should include deadlines for submission of designated documents and the final term report. Please note: Faculty members are not expected to review research drafts between terms, outside of what is required for end-of-term grading. Any research draft submitted within 5 days of the final day of the term may not receive detailed feedback until approximately 10 days into the subsequent term.
If the review takes place during any of the official Walden holidays (New Year’s Day; Martin Luther King, Jr. Day; Memorial Day; Independence Day; Labor Day; Thanksgiving Day; day after Thanksgiving; or Christmas Day), the holiday will not count in the review cycle. It is important to note that MyDR, which includes a general 14-day review timeline, does not adjust for holidays and end-of-terms, so any late notices received from the workflow as a result of a holiday are not an accurate reflection of the review time frame.
Note: As you consider your references, it is recommended that in business 85% should be within the past 5 years. Other than data collected from the study site, students cannot use magazines, trade publications, summary textbooks, websites, and blogs as references.
TABLE OF CONTENTS
DBA RESEARCH HANDBOOK
26
SECTION 1: FOUNDATION OF THE STUDY
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1.1 – Abstract
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1.2 – Background of the Problem
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Applied DBA Versus a Speculative/Theoretical PhD
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Preparing the Background of the Problem
29
Strategy for Mapping to the Rubric
31
Aligning the Specific Business Problem With the Purpose Statement and RQ … 33 1.4 – Purpose Statement
35
Six Elements of the Purpose Statement
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Hypothetical Quantitative Example
38
Hypothetical Qualitative Example
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1.6 – Research Question (Quantitative Only)
39
1.7 – Hypotheses (Quantitative/Mixed-Method Only)
40
1.8 – Research Question (Qualitative Only)
40
1.9 – Interview Questions (Qualitative Only)
42
Example Applied DBA Interview Questions
43
1.10 – Theoretical/Conceptual Framework
43
1.11 – Operational Definitions
46
1.12 – Assumptions, Limitations, and Delimitations
46
1.13 – Significance of the Study
47
1.14 – Review of the Professional and Academic Literature
47
1.15 – Transition
49
2.2 – Role of the Researcher
51
Data Saturation in Qualitative Study Designs
53
How to Use Multiple Sources to Support Claims and Decisions
54
2.6 – Population and Sampling (Quantitative Only)
54
2.7 – Population and Sampling (Qualitative Only)
55
Data Saturation and Sampling
56
2.9 – Data Collection—Instruments (Quantitative)
57
2.10 – Data Collection – Instruments (Qualitative)
57
2.11 – Data Collection Technique
60
2.12 – Data Organization Technique (Qualitative Only)
60
2.13 – Data Analysis (Quantitative Only)
60
2.14 – Data Analysis (Qualitative Only)
61
2.15 – Study Validity (Quantitative Only)
63
Internal Validity
63
2.16 – Reliability and Validity (Qualitative Only)
65
2.17 – Transition and Summary
66
SECTION 3: APPLICATION TO PROFESSIONAL PRACTICE AND IMPLICATIONS FOR CHANGE
67
3.2 – Presentation of Findings (Quantitative)
68
3.3 – Presentation of Findings (Qualitative)
74
3.4 – Application to Professional Practice
74
3.5 – Implications for Social Change
74
3.6 – Recommendations for Action
75
3.7 – Recommendations for Further Research
75
3.8 – Reflections
75
3.9 – Conclusion
75
3.10 – Appendices/Table of Contents
75
APPENDIX C: MAJOR QUANTITATIVE DESIGNS
83
APPENDIX D: SAMPLING TYPOLOGIES
84
APPENDIX E: SAMPLE POWER ANALYSIS
85
APPENDIX F: SAMPLE QUANTITATIVE LITERATURE REVIEW OUTLINE
86
APPENDIX G: SAMPLE APA TABLES
89
APPENDIX H: SAMPLE INTERVIEW PROTOCOL
95
BIBLIOGRAPHY: SUGGESTED READINGS LISTS
97
Assumptions, Limitations, and Delimitations
98
Data Saturation and Data Collection Sources
111
Ethical Considerations/IRB
117
Interview Protocol Sources
142
Qualitative Research Foundation
175
Qualitative and Quantitative Sources
180
Reliability, Validity, Transferability, and Generalizability Sources
189
Qualitative Software Analysis Sources
205
DBA DOCTORAL STUDY RUBRIC
Student and Committee Information3
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Student’s Name (Last, First): |
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Student ID (For office use only): |
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Chairperson: |
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Second Committee Member: |
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University Research Reviewer: |
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Student to provide total number of references: (As you consider your references, it is recommended that in business 85% should be within the past 5 years). |
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Note: Provide the required information in the yellow highlighted column.
3 Chair will complete the yellow highlighted fields in this section before submitting the rubric. Be sure to include the names of all members of the committee.
Evaluation4
5Date/Stage of the Rubric:
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Date of Review |
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Before Proposal Oral Defense |
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Before Proposal Oral (Revised)6 |
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Before Doctoral Study Oral Defense |
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Before Doctoral Study Oral (Revised)7 |
Note: Place an “X” in column (yellow highlight) associated with the appropriate stage.
Evaluation of State of the DBA Doctoral Study or Proposal:
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No changes required, advance to next step; rubric requirements met |
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Changes required for resubmission; rubric requirements not met |
Note: Place an “X” in the column (yellow highlight) associated with the appropriate evaluation decision.
Member Information:
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Name of member providing this review |
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Role of the member providing this review |
Note: Enter the information in the yellow highlighted column.
4 Each member of the committee completes the evaluation.
5 Be sure to follow the Process Checklist (located at
http://academicguides.waldenu.edu/researchcenter/osra
) naming convention when sending the document through the review process. Following the naming convention is vital for tracking student progress throughout the doctoral study process.
6 Check when second and subsequent rubrics are needed if previous proposal defense was not passed.
7 Check when second and subsequent rubrics are needed if previous Doctoral Study defense was not passed.
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Section 1 Foundation of the Study (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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Walden Abstract Guidelines:
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a. Background/General Introduction of the Issue (optional)—abstract may begin with research problem. |
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b. Research Problem and Why It’s Important—be clear; who cares if the problem is solved? |
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b. Purpose or Rationale—this is sometimes combined with research questions to avoid redundancy. |
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d. Theoretical Foundations—name the theory OR describe the conceptual framework, if appropriate. |
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e. Research Questions (RQs)/Guiding Question—present these as statements, not questions. |
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f. |
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i. Data Analytic Procedures—explain how data were analyzed to address the research questions. |
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j. |
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k. Implications for Positive Social Change—specify who benefits from the research and in what ways.
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l. |
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m. Ensures the first line in the abstract is not indented and abstract does not exceed one page. |
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n. Use plural verbs with data (e.g., the data were – the word data is the plural of datum). |
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Section 1 Foundation of the Study (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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o. Ensures all numbers are expressed in digits (i.e., 1, 2, 10, 20, etc.) and not spelled out unless beginning a sentence; Ensures Abstract does not include seriation (i.e., (a), (b), (c), etc.). |
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(1.2) Provides a brief and concise overview of the context or background of the problem. DBA Doctoral Studies are focused on applied business research. This sets the stage for the study. This heading should comprise no more than one page in length. |
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Please review the video tutorial located @: |
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a. Provides a |
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b. Provides an |
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c. States the general business problem Note: This element should start as follows: The general business problem is… |
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d. States the specific business problem. Be sure to state |
9 Include an introductory paragraph before the Background of the Problem component. However, do not label this introductory paragraph with a L1 APA heading. The purpose of the background is to introduce the topic and problem you will address. Briefly indicate why the problem deserves new research. More important, the Doctoral Study must address applied research, so you will want to identify the need to solve an applied business problem. The goal of this section is to encourage readers to continue reading, to generate interest in the study, and provide an initial frame of reference for understanding the entire research framework
10 The hook should be a succinct WOW statement to catch the reader’s attention.
11 An anchor comprises a number, percentage, dollar value, ratio, index, etc.
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Section 1 Foundation of the Study (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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e. Ensures the specific business problem aligns with the research question and purpose statement. |
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f. Problem Statement should be clear and succinct (It is recommended to be approximately 150 words). |
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· Check with Ulrich’s Periodical Directory · See Problem Statement Video Tutorial at: |
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Describes the intent of the research13. The Purpose Statement is a mini story and recommended to be approximately 200 words. The Purpose Statement must address the following six elements: |
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a. Identifies the research method as qualitative14, quantitative15, or mixed- method. |
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b. Identifies research design16 (i.e., case study, phenomenological, quasi- experimental, correlational, etc.). |
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c. If quantitative or mixed method: Identifies a minimum of two |
12 Ulrich’s is not 100% correct; the student must verify peer review status via the journal home page.
13 The first sentence of the purpose statement must align with the research question and specific business problem in the problem statement.
14 Visit the Center for Research Quality qualitative methodology tutorial at:
http://academicguides.waldenu.edu/researchcenter/resources/Design
15 See the quantitative Research Primer located at
Appendix B; Visit the Center for Research Quality quantitative methodology tutorial at:
http://academicguides.waldenu.edu/researchcenter/resources/Design
16 See Appendix C for a depiction of basic quantitative designs and their characteristics.
17 Covariates, mediator, and moderator variables are types of independent/predictor variables; be sure to clearly identify these types of variables as applicable.
18 The terms “independent” and “predictor variables are often used interchangeably in correlation studies. Please be consistent with the chosen terminology.
19 See Heading 1.6, Research Questions (Quantitative Only), in the Research Handbook.
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Section 1 Foundation of the Study (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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variables appropriately align with the variables/constructs identified in component 1.10, Theoretical/Conceptual Framework. |
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d. Identifies specific population group for proposed study. |
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e. Identifies geographic location of the study. |
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f. Identifies contribution to social change. |
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g. Ensures the first sentence links/aligns directly with the specific business problem. |
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· See Purpose Statement Video Tutorial at: |
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Section 1 Foundation of the Study (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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(1.5) Provides a brief discussion on the research method (i.e., quantitative or qualitative) and design (i.e., correlation for quantitative study; phenomenological, case study, etc., for a qualitative design); cite a minimum of one source (The method and design will be discussed in detail in Section 2). · Note: A single paragraph is sufficient for each component: one for the method and one for t he design. |
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a. Identifies the selection of one method (qualitative, quantitative, or mixed method) and why other methods would not work (cite a minimum of one source). |
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b. Identifies the selection of the design |
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(1.6)
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a. Lists research question(s) in about 10-15 words. |
20 A single paragraph can be used for each component: one for the method and one for the design.
21 See Appendix C for a brief depiction of the major research designs.
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b. Ensures research question(s)22 align(s) with the specific business problem and first line of the Purpose Statement. |
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c. Includes the independent/predictor and dependent/criterion variables as identified in the Purpose Statement; ensures the independent/predictor variables appropriately align with the constructs/variables identified in component 1.10, Theoretical/Conceptual Framework. |
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(1.7) States, in accurate format, the null and alternative hypotheses for each research question23. |
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(1.8)
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a. Lists overarching research question in approximately 10-15 words. |
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b. Ensures research question aligns with the specific Business Problem and Purpose Statement. |
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Section 1 Foundation of the Study (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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(1.9)
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a. Lists each interview or focus group question. Questions must contribute knowledge to the research question. Questions must be open-ended, and cannot be answered with a Yes or No. |
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b. Ensures interview/focus group questions align with the research question. |
22 The research question(s) must contain the independent/predictor and dependent/criterion variables identified in the Purpose Statement.
23 Hypotheses must include the variables identified in the research question.
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(1.10) Clearly and concisely identify the theoretical/conceptual framework. In quantitative studies, the theoretical framework is the appropriate term and in qualitative studies, the conceptual framework is the appropriate term. The student will articulate the theoretical/conceptual framework with concepts from the literature to ground and complement the applied business study. · This component should not exceed one page. It will be expanded upon in the literature review. See Theoretical/Conceptual Framework Video Tutorial at: |
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a. Identifies and describes the theory or conceptual model for theoretical/conceptual framework. |
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b. Identifies theorist(s) of the theory or conceptual model for theoretical/conceptual framework. |
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c. Identifies date of the theory or conceptual model for theoretical/conceptual framework (if applicable).25 |
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d. Identifies key concepts/propositions/tenets of the theory or conceptual model for theoretical/conceptual framework26. |
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e. Quantitative only – Ensures the theoretical constructs/variables underlying the theory are clearly identified and align with the constructs/variables (independent variables) identified in the Purpose Statement and Research Question(s). Note: The independent variables/constructs represent the underlying concepts of the theoretical framework in quantitative research. |
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· Identifies how/why the theory or conceptual model for theoretical/conceptual framework is applicable and fits/applies to the study. |
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Section 1 Foundation of the Study (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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(1.11)
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24 The theoretical/conceptual framework informs the research (quantitative) and interview (qualitative) questions. Be sure to review the Theoretical/Conceptual Framework Video Tutorial at:
http://youtu.be/P-01xVTIVC8
25 Some literature identifies the specific date the theorist introduced the theory; provide this date if this is the case. If date is missing, then requirement (c) is not applicable.
26 Ensures the independent variables appropriately align with the theoretical framework(s) identified in component 1.10, Theoretical/Conceptual Framework.
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a. Presents technical terms, jargon, or special word used in the study. |
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b. Lists in alphabetical order. Formats in italics followed by an italicized colon. The definition follows on the same line. (This is similar to an APA Level 5 heading with a colon replacing the period.) |
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c. Provides citations (for each definition) from credible sources (peer-reviewed, seminal work/text, government sites, etc). |
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d. Does not include terms found in a basic academic dictionary (i.e., Webster’s). |
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e. Does not exceed 10 key operational definitions. |
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(1.12)
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a. Defines the term Assumptions and provides citation; lists facts that the student assumes to be true but cannot actually be verified. |
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b. Defines the term Limitations and provides citation; lists potential weaknesses of the study that are not within the control of the researcher. |
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c. Defines the term Delimitations and provides citation; identifies the bounds of the study. |
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(1.13) |
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a. States why the study findings may be of value to businesses. |
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b. States how this study may contribute to effective practice of business (improvement of business practice). |
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c. Identifies how the results might contribute to positive social change. |
27 This area is important in determining Doc Study of the Year Award-justify well.
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Section 1 Foundation of the Study (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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(1.14) |
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A. Literature Review Opening Narrative |
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i. Contains a brief discussion of the content of the literature that includes a critical analysis and synthesis of various sources/content of the literature (journals, reports, and scholarly seminal books, etc.) to convince readers of depth of inquiry. |
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ii. Explains the organization of the review. |
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iii.Explains the strategy for searching the literature. |
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iv. The majority of references should be from peer-reviewed sources. (Suggested 85% of the total sources should be peer-reviewed.) |
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v. The majority of references should be current. (As you consider your references, it is recommended that 85% should be within the past 5 years). |
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B. Application to the Applied Business Problem |
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i. Introduces the purpose of the study. |
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ii. Identifies hypotheses if a quantitative/mixed method study. |
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iii.Contains a critical analysis and synthesis of literature pertaining to the theoretical/conceptual framework the student identified in item #1.10, Theoretical/Conceptual Framework, above29. The student includes a critical analysis with supporting and contrasting theories/conceptual models for the theory in the theoretical/conceptual framework. |
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Section 1 Foundation of the Study (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
28 The average length of substantive literature review is between 30 to 40 pages (25 pages minimum). However, the need for depth and breadth is required. See quantitative example at Appendix F and visit the Writing Center at:
http://writingcenter.waldenu.edu/50.htm for more information on writing the literature review.
29 A key portion of the Review of the Literature must focus on the specific theoretical/conceptual framework you are using in your study. This is a “ key requirement for you to be able to adequately address items 3.2g, Presentation of Findings (quantitative studies) and 3.3c, Presentation of Findings (qualitative studies).
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iv. Contains a critical analysis and synthesis of literature pertaining to the independent variables (quantitative/mixed-method studies) the student identified in item # 4c (Purpose Statement). |
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v. Contains a critical analysis and synthesis of literature pertaining to the dependent variable(s) (quantitative/mixed-method studies) the student identified in item # 4c (Purpose Statement). |
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vi. Discusses measurement of variables (quantitative/mixed-method studies) the student identified in item # 4c (Purpose Statement). |
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vii. Contains a critical analysis and synthesis of literature pertaining to potential themes and phenomena (qualitative studies) the student identified in the Purpose Statement. |
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viii. Compares and contrasts different points of view, and the relationship of the study to previous research and findings (sample size/geographical location variance, etc.). |
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ix. Provides a comprehensive critical analysis and synthesis of the literature. |
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C. Relevancy of the Literature |
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The literature review is well organized. Introduce the purpose of the study. Include hypotheses (if a quantitative/mixed method study) in the opening narrative. |
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D. Literature Review Organization |
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i. Presented in a well-organized manner. |
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ii. Adheres to APA formatting standards. |
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(1.15)
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a. Ends with a Transition Heading that contains a concise summary30 of key points of Section 1. |
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b. Provides an overview introducing Sections 2 and 3. |
30 A concise summary recaps the major elements of the review of the literature and does not introduce new information.
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Section 2 The Project (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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Begins Section 2 with a restatement of the Purpose Statement presented in Section 1. · Note: Copy-and-paste the purpose statement from Section 1 |
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(2.2) Describes the role of the researcher in the data collection process and provides a peer-reviewed or seminal source. Describes any relationship the researcher may have had with the topic, participants, or research area. |
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a. Describes the role of the researcher in the data collection process and provides a peer-reviewed or seminal source. |
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b. Describes any relationship the researcher may have had with the topic, participants, or research area. |
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c. Provides a brief description of the researcher’s role related to ethics and the Belmont Report31 protocol. |
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d. Qualitative studies: Describes how the student will mitigate bias and avoid viewing data through a personal lens/or perspective. |
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e. Qualitative studies with interviews: Briefly describes the rationale for an interview protocol. |
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f. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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a. Describes the eligibility criteria for study participants. |
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b. Discusses strategies for gaining access to participants. |
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c. Identifies strategies for establishing a working relationship with participants. |
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d. The participants’ characteristics must align with the overarching research question. |
31 See Belmont Report at:
http://www.hhs.gov/ohrp/humansubjects/guidance/belmont.html.
32 Select “N/A” and explain why if participants are not used in the study.
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Section 2 The Project (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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e. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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Section 2 The Project (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
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(2.4) Expands on the discussion in Heading 1.5 (Nature of the Study). |
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a. Identifies the use of a specific research method by indicating whether the proposed study is quantitative, qualitative, or mixed methods. |
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b. Justifies the use of the research method over the other research methods. |
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c. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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(2.5) Expands on the discussion in Heading 1.5 (Nature of the Study). |
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a. Identifies the use of a specific research design. |
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b. Justifies the use of the research design over other key designs for the study. |
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c. For qualitative studies, identifies how the student will ensure data saturation. |
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d. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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(2.6) Population and Sampling (Quantitative Only) |
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a. Describes the population from which the sample will come. |
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b. Demonstrates that population aligns with the overarching research question. |
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c. Describes and justifies the sampling method (i.e., probabilistic or nonprobabilistic) and specific subcategory (i.e., simple random or convenience). Addresses the strength and weaknesses associated with the chosen sampling method and subcategory (Appendix C.) |
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d. Justifies sample size via power analysis (see example in |
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e. Cites the source for calculating or the tool used to calculate the sample size. |
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f. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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a. Justifies the number of participants · Describes and justifies the sampling method (e.g., purposeful, snowball, etc.). · Describes and justifies the number of participants. · Identifies how the student will ensure data saturation. |
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b. Demonstrates criteria for selecting participants and interview setting are appropriate to the study (Rich descriptions are encouraged) |
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c. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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(2.8)
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a. Discusses the informed consent process. Includes informed consent form in an appendix and lists in the Table of Contents. |
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b. Discusses participant procedures for withdrawing from the study. |
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c. Describes any incentives for participating. |
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d. Clarifies measures that the student will use to assure that the ethical protection of participants is adequate. |
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e. Refers to agreement documents in the (a) appendices, and (b) Table of Contents. |
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f. Includes statement that the student will store the data securely for 5 years to protect confidentiality of participants. |
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g. Final Doctoral Study includes the Walden IRB approval number. |
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h. Identifies how the student will protect names of individuals or organizations to keep the participants and organizations confidential. |
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i. |
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(2.9)
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Section 2 The Project (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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a. States the name of the instrument(s). |
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b. Identifies name of publisher/developer(s) and year of development (if applicable). |
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c. Discusses concept(s) measured by the instrument(s). |
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d. Includes a detailed description of data that comprise each construct/variable measured by the instrument(s). |
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e. Identifies scale of measurement (i.e., nominal, ordinal, interval, ratio) for each construct/variable measured by the instrument. Please see Scales of Measurement video tutorial at: |
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f. |
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g. Discusses instrument administration (e.g., how long, any special requirements/tools, special instructions, pencil and paper, online, etc.). |
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h. Describes how scores are calculated and what the scores mean; identifies items to be reverse- coded (if applicable). |
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i. Identifies where and/or with what populations the instrument was normed; identifies where and with what populations other researchers have used the instrument(s) for collecting data. |
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j. |
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k. Identifies strategies used to assess validity (e.g., construct validity, concurrent validity, convergent validity, discriminant validity) and reliability (e.g., test- retest reliability, internal consistency, split-half, etc.). |
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l. |
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m. Identifies where in appendices the instrument(s) (or copy of permission to use instrument or purchase is (are) located). Ensures Table of Contents lists appendices. [Copies of the instrument may not be reproduced in an Appendix without written permission.] |
34 Published reliability and validity properties might be found in the test review and in other studies where the instrument was used to collect data.
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Section 2 The Project (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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n. Describes where raw data will be available (appendices, tables, or by request from the researcher). |
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o. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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(2.10)
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a. In addition to identifying the student as the primary data collection instrument, identifies the data collection instrument/process (e.g., informal interview, semistructured interviews, phenomenological in-depth interviews, focus groups, company/archival documents, etc.). |
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b. Clarifies how the student will use the data collection instrument/technique (the process/protocol). |
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c. Identifies how the student will enhance the reliability and validity of the data collection instrument/process (e.g., member checking, transcript review, pilot test, etc.). |
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d. Identifies where in appendices the instrument (e.g., interview protocol, focus group protocol, interview questions, etc.) is (are) located. Ensures Table of Contents lists appendices. |
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e. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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(2.11)
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a. Describes the technique used to collect data such as an online/paper survey, interview, observation, site visit, video recording (think recipe card—step-by- step-process and describe richly. Provides abridged interview protocol ( |
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b. Describes advantages and disadvantages of data collection technique. |
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c. As applicable, describes the process for conducting a pilot study after IRB approval. |
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d. For qualitative studies, identifies how the student will use member checking of the data interpretation or transcript review (if applicable). |
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e. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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Section 2 The Project (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
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a. Describes the systems for keeping track of data, emerging understandings such as research logs, reflective journals, and cataloging/labeling systems. |
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b. Reminds readers all raw data will be stored securely for 5 years. |
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c. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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(2.13)
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a. Restates the research questions and hypotheses from Section 1. |
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b. Describes and defends, in detail, the statistical analyses that the student will conduct (e.g., multiple regression, two-way ANOVA, etc.). |
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c. Describes and defends, in detail, why other statistical analyses are not appropriate. |
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d. Provides explanation of data cleaning and screening procedures as appropriate to the study. |
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e. Provides explanation for addressing missing data. |
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f. |
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g. Identifies the process for testing/assessing the assumptions. |
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h. Identifies appropriate actions to be taken take if the assumptions are violated35. |
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i. |
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j. |
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k. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
35 Bootstrapping can be used as an effective method for addressing violations of assumptions.
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Section 2 The Project (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
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(2.14)
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a. Identifies the appropriate data analysis process for the research design (e.g., one of the four types of triangulation for case study; modified van Kaam, van Maanen, etc. for phenomenology). |
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b. Provides a logical and sequential process for the data analysis. |
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c. Details the student’s conceptual plan or software (e.g., NVivo, Atlasti, Ethnograph, Excel, etc.) for coding, mind-mapping, and identifying themes. |
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d. Identifies how the student will focus on the key themes, correlate the key themes with the literature (including new studies published since writing the proposal) and the conceptual framework. |
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e. It is recommended to support claims and decisions with multiple scholarly peer- reviewed or seminal sources (as appropriate). |
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(2.15) |
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a. Experimental/quasi-experimental designs only: Describes threats to external validity (e.g., testing reactivity, interaction effects of selection and experimental variables, specificity of variables, reactive effects of experimental arrangements, and multiple-treatment interference, as appropriate to the study) and how the student will address the threats to external validity. |
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b. Experimental/quasi-experimental designs only: Describes threats to internal validity (e.g., history, maturation, testing, instrumentation, statistical regression, experimental mortality, and selection-maturation interaction, as appropriate to the study) and how the student will address the threats to internal validity. |
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c. Discusses threats to statistical conclusion validity37 (e.g., factors that affect the alpha/Type I error rate) and how the student will address the threats to statistical conclusion validity. |
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d. Describes the extent to which, and rationale for justifying if, and if so why, research findings can be generalized to larger populations (external validity) and applied to different settings. |
36 Items “a” and “b” pertain to experimental and quasi-experimental designs only. Item “c” pertains to all quantitative designs. Discuss validity as it pertains to the study outcomes. This component is not to address the reliability and validity of the study instruments. The reliability and validity of the study instruments is addressed in item 2.9 (quantitative) and 2.10 (qualitative). Item “d”, external validity, pertains to all quantitative designs.
37 The three factors to be discussed are (a) reliability of the instrument, (b) data assumptions, and (c) sample size.
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Section 2 The Project (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
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e. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
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(2.16) |
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Reliability |
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a. Identifies how the student will address dependability. (i.e., member checking of data interpretation, transcript review, pilot test, etc.). |
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b. It is recommended to support claims and decisions with multiple scholarly peer- reviewed or seminal sources (as appropriate). |
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Validity |
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c. Identifies how the student will ensure credibility (i.e., member checking of the data interpretation, participant transcript review, triangulation, etc.). |
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d. Identifies how the student will address transferability in relation to the reader and future research. |
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e. Identifies how the student will address confirmability. |
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f. Identifies how the student will ensure data saturation. |
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g. It is recommended to support claims and decisions with multiple scholarly peer- reviewed or seminal sources (as appropriate). |
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(2.17)
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a. Ends with a Transition Statement that contains a summary of key points. |
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b. Includes an overview of what the student will cover in Section 3. |
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Proposal Stage. Before IRB approval, the paper is written in future tense and after IRB approval, the paper is changed to past tense. |
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Writing Style. The paper is written in predominantly active voice without slang, euphemisms, or anthropomorphisms. |
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Section 2 The Project (FOR PROPOSAL & DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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Follows APA 6th edition in the text and in the reference list |
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References: Of the total sources cited, a minimum of 85% should be peer reviewed (it is recommended that in business 85% should be within the past 5 years of anticipated completion date). Each source on the References page should match an in-text citation and vice versa |
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Congratulations! This ends the Proposal section. See the Process Checklist located at the Center for Research Quality website (see URL below). http://researchcenter.waldenu.edu/Documents/DBA_Process_Checklist.pdf |
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Section 3 Application for Professional Practice and Implications for Social Change (FOR DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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a. Begins with the purpose of the study. Do not repeat the entire purpose statement. Typically, the first sentence of the purpose statement will suffice. |
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b. |
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a. |
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b. |
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c. |
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d. |
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e. |
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f. |
38 See the following link for further information on descriptive statistics:
http://www.socialresearchmethods.net/kb/statdesc.php
39 See Appendix E for basic formatted descriptive and inferential statistic tables.
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Section 3 Application for Professional Practice and Implications for Social Change (FOR DBA DOCTORAL STUDY DOCUMENTS) Quality Indicators |
Type Met, Not Met, or N/A in Each Cell |
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g. |
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h. |
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i. |
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a. |
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b. Identifies each theme. Analyzes and discusses findings in relation to the themes. |
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c. 41Describes in what ways findings confirm, disconfirm, or extend knowledge in the discipline by comparing the findings with other peer-reviewed studies from the literature review that includes new studies since writing the proposal. |
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d. Ties findings to the conceptual framework |
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e. Ties findings or disputes findings to the existing literature on effective business practice. |
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Provides a detailed discussion on the applicability of the findings with respect to the professional practice of business. This major subsection provides a rich academic argument for why and how the findings are relevant to improved business practice. |
40 It is important to ensure the review of the literature is a critical analysis and synthesis of the theory and variables identified in the study.
41 It is important the student includes a critical analysis and synthesis of the new literature (studies) published since the proposal and correlates the literature with the findings in the study.
42 This is an important area for Doctoral Study of the Year Award.
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Expresses implications in terms of tangible improvements to individuals, communities, organizations, institutions, cultures, or societies as the findings could beneficially affect social change/behaviors. |
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a. Ensures recommendations flow logically from the conclusions and contain steps to useful action. |
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b. States who needs to pay attention to the results. |
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c. Indicates how the results might be disseminated via literature, conferences, training, etc. |
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Lists recommendations for further study related to improved practice in business. Identifies how limitations identified in Section 1.12b, Limitations, can be addressed in future research. |
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Includes a reflection on the researcher’s experience within the DBA Doctoral Study process, in which the researcher discusses possible personal biases or preconceived ideas and values, the possible effects of the researcher on the participants or the situation, and any changes to the researcher’s thinking after completing the study. |
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Closes with a strong concluding statement making the take-home message clear to the reader. |
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a. Consent form(s) attached. (Redact/blackout all personal or identifying data.) |
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b. Organizational permission (Blackout name). |
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c. Sample of Instrument (i.e., survey, interview protocol with interview questions, observation protocol, etc.; copyrighted surveys cannot be included w/o written permissions.) |
43 This is an important area for Doctoral Study of the Year Award.
44 Limitations identified in section 1.12b, as a minimum, are ideal sources for future studies.
Doctor of Business Administration
Research Handbook
Section 1 – Foundation of the Study
Note: This handbook is not in the DBA Doctoral Study Template. Make certain that the proposal and study conform to
DBA Doctoral Study Template
heading sequencing, and formatting with the correct margins and line spacing.
1.1 – Abstract
The abstract must not exceed one page. The abstract text must be double-spaced with no paragraph breaks. The first line must not be indented. Describe the overall research problem being addressed in the first couple of sentences and indicate why it is important (e.g., who would care if the problem were solved). You can include a general introduction of the issue in the first sentence, but you need to move to a clear statement of the research problem. Identify the purpose and theoretical foundations, summarize the key research question(s), and briefly describe the overall research design and data analytic procedures. Identify the key results, themes, one or two conclusions, and recommendations that capture the heart of the research. Conclude with a statement on the implications for positive social change. Here are some form and style tips: (a) limit the abstract to one page; (b) maintain the scholarly language used throughout the doctoral study; (c) keep the abstract concise, accurate, and readable; (d) use correct English; one may use passive voice in the abstract; (e) ensure each sentence adds value to the reader’s understanding of the research; (f) use the full name of any term and if the acronym is used more than once in the abstract include the acronym in parentheses. Do not include references or citations in the abstract. Per APA style, unless at the beginning of a sentence, use numerals in the abstract, and don’t identify the titles of any software. Do not include seriation (i.e., (a), (b), (c), etc.)
1.2 – Background of the Problem
The purpose of the background is to introduce the topic and problem you will address.
Briefly, you want to indicate why the problem deserves new research. More important, the Doctoral Study must address applied research, so you will want to identify the need to study how some business leaders are solving or have solved an applied business problem. The goal of this heading is to encourage readers to continue reading, to generate interest in the study, and provide an initial frame of reference for understanding the entire research framework.
Applied DBA Versus a Speculative/Theoretical PhD
A DBA study is an applied business study linking theory to professional practice.
Students can use the following criteria to ensure that they have a clear DBA business study or a DBA business study rather than a PhD business study. In contrast to a DBA study, a PhD study is a hypothetical/theoretical study that leads to expanding or creating theory rather than solving a business problem.
Qualitative studies. A qualitative study about people’s perceptions on how to address a business problem is hypothetical and is a PhD study. In contrast, a qualitative study is about a strategy that a business leader or manager has implemented /is implementing to solve a business problem or a strategy that a business leader or manager has implemented to solve a business problem is an applied DBA study.
Quantitative studies. A quantitative study that includes one or more variables in which the leader or manager cannot change to solve a business problem is a hypothetical/theoretical PhD study. Whereas, a quantitative study that includes only variables which business leaders or business managers can manipulate or change to solve a business problem is an applied DBA study.
Preparing the Background of the Problem
The Background of the Problem can be effectively accomplished in no more than one page; brevity and clarity are essential. The Review of the Literature will provide a more detailed discussion on the literature pertaining to the topic/problem. Immersing yourself in the literature on your topic/problem is crucial to uncovering a viable business problem. Do not underestimate the importance of the literature in helping identifying a viable business problem.
The research topic is broad in nature; do not narrow the focus too quickly. You want to provide the reader, especially those not familiar with the topic, time to become familiar with the topic. Transition the reader to a more a concise presentation of the specific business topic/problem under study. This component focuses on identifying why the study is important, how the study relates to previous research on the topic/problem, and gives the reader a firm sense of what your study is going to address and why. The Background of the Problem contains information supporting the business problem. Do not describe, explain, justify, etc., the need for the study in the Problem Statement. Provide these critical elements (description, explanation, justification, etc.) in the Background of the Problem component. As such, the Problem Statement can be written effectively in as little as four sentences: (a) hook, (b) anchor (c) general business problem, and (d) specific business problem. Transfer the supporting references in the Background of the Problem to the Problem Statement, but submit in a concise manner. For example, the hook and anchor reference provided in the Background of the Problem should be used in the Problem Statement.
Include a transition statement that leads to problem statement that will provide more specificity regarding the problem identified in the Background or the Problem component. A well-written transition signals a change in content. It tells your reader that they have finished one main unit and are moving to the next, or it tells them that they are moving from a general explanation to a specific example or application. A transition form the background to the Problem Statement is often as brief as one sentence, as follows: The background to the problem has been provided; the focus will now shift to the Problem Statement. Tip: Many potential business topics/problems can be found in the Area for Future Research heading of most peer- reviewed journal articles.
1.3 – Problem Statement
As shown in the following graphic, the Problem Statement must include four specific components the (a) hook, (b) anchor, (c) general business problem, and (d) specific business problem. It is recommended that the Problem Statement be approximately 150 words. More important, ensure the problem statement reflects an applied business problem; avoid Rubric Creep45. You must ensure you map to the rubric requirements. This is the most critical component of the doctoral study and will be highly scrutinized in the review process. Again, the Problem Statement is not to identify causes for the problem, solutions to the problem, or any other superfluous information. A well-written problem statement can be presented in four to five sentences. Please review the training video (see link below) developed by the DBA methodology team to aid in writing your problem statement. The video will help add clarity and save you time. The Problem Statement Video Tutorial can be found at:
http://youtu.be/IYWzCYyrgpo.
45 Rubric creep occurs when the problem statement does not reflect an applied business problem.
DBA students are seeking a degree in business and must ensure the problem statement is business focused. The problem statement must not represent a problem that has a social, psychological, educational, or other discipline specific emphasis. A business problem is something that is a problem for a business from the perspective of the business managers or the industry’s leaders. Therefore, it is important to adopt a management perspective, and not that of social advocates. The perspective must be from the position of the managers and leaders of business who can address the problem.
Avoiding Rubric Creep
To ascertain if a problem addresses a business issue or has Rubric creep/Rubric drift, please consider the following:
· An important indicator that a business related problem is a specific business problem is that the problem statement relates to a key business process that organizational leaders need to address and effectively meet the organization’s mission.
· A business problem relates to one or more critical success factors (CSFs). Business leaders use business processes to function effectively to complete one or more CSF’s needed to carry out their business mission.
· A business problem is one that a business manager/leader can solve.
Conduct a final check of the problem statement by putting the hook, anchor, general business problem, and specific business problem in bullet form and check for alignment among the four bullets. When you can ensure that the problem statement aligns throughout, write in scholarly narrative form (no bullets).
Strategy for Mapping to the Rubric
· Read the rubric requirements for a heading.
· Read what you wrote in the heading.
· Read the rubric requirements for a heading again.
· Read what you wrote in the section and highlight (in the proposal and the rubric) the rubric elements that you addressed in the heading.
· Revise the heading as needed to include the rubric elements that you missed and eliminate superfluous narrative.
· Start the process at the top again until you have mastered the rubric elements in the heading.
Specific Business Problem
The specific business problem is the genesis of one’s study. It is vital that one has a clear and precise specific business problem. One will align the contents of the Research Question and Purpose Statement with the specific business problem.
The qualitative specific business problem. The qualitative specific business problem must be well defined and not contain multiple issues (variables in quantitative studies). The
following graphic depicts how to include the elements needed in a qualitative specific business problem.
The quantitative specific business problem. The quantitative specific business problem must be well defined and contain the key variables. The following graphic depicts how to include the elements needed in a qualitative specific business problem.
Aligning the Specific Business Problem With the Purpose Statement and RQ
Make certain that the specific business problem, Purpose Statement, and Research Question (RQ) align. A good technique to use to enhance the alignment is to put the specific business problem, RQ, and first sentence of the Purpose Statement together on a blank document to ensure that you are using the same words. Notice the suggested order differs from the order the headings appear in the study.
Qualitative alignment example. The graphic below provides an example of alignment among the Specific Business Problem, Research Question, and first sentence of the Purpose Statement using the same key words. Pay attention to the words one uses in identifying the issue that the leader lacks or has in limited supply. The word determines how one can collect data.
· Some business leaders lack understanding… To ascertain what one understands will require a quantitative design.
· Some business leaders lack knowledge… To ascertain a business leader’s knowledge will require a quantitative design.
· Some business leaders lack strategies (or have limited plans, processes, procedures)… To ascertain a business leader’s strategies may involve interviews, focus groups, company archival records and documents, company policies and procedures, company intranet/Internet site, and direct/participant observation (in some cases) to collect data. Usually interviews or focus groups are the primary data collection method.
· Some business leaders lack skills… To ascertain a business leader’s skills will involve direct/participant observation as the primary data collection method.
Quantitative alignment example. Notice how the Specific Business Problem, Research Question, and first sentence of the Purpose Statement use the same key words with the exception that the research question and subsequent first sentence in the purpose statement do not address the business leader—this is a difference between qualitative and quantitative studies. The following is an example of alignment for a quantitative correlational study.
1.4 – Purpose Statement
There is a difference in the rubric requirements for a quantitative versus a qualitative study. The Purpose Statement must include the following components: (a) methodology, (b) design, (c) independent and dependent variables (for quantitative studies only), (d) specific population and justification for using the chosen population, (e) geographical location, and (f) the study’s potential for effecting social change. It is recommended that the Purpose Statement be approximately 200 words. The Purpose Statement is to be a concise statement and must not include detailed design information (sample size, data collection, etc.). Please be sure to map to the rubric. Please review the purpose statement video at: http://youtu.be/pLP4r0mfT9A. This video tutorial will be helpful to you in preparing your Purpose Statement.
Six Elements of the Purpose Statement
As mentioned above, the Purpose Statement consists of six elements. These six elements, and their contents, are:
Methodology. The first element to be presented in the Purpose Statement is the research methodology. The methodology is the overall philosophical assumption the researcher uses for designing and developing the study. In other words, the methodology is a worldview of how knowledge is acquired. The qualitative method is a means for exploring and understanding the meaning individuals or groups ascribe to a business problem. The qualitative method involves researchers using open-ended questions to learn what a business leader is doing or has done to solve a business problem. The quantitative method involves researchers using closed-ended questions to test hypotheses. Mixed-method studies contain a qualitative study methodology and a quantitative study methodology and must meet the requirements of both methodologies.
Mixed-method studies are rarely conducted in the DBA program. You simply need to identify the methodology for or your study in a single sentence. There is no other information required other than this single statement.
Design. The second element to be presented in the Purpose Statement is the research design. While there are numerous designs, the most common qualitative designs seen in DBA doctoral studies are the case study design, miniethnography, focus group, and the phenomenological design. The correlational design is the most common design for quantitative studies. You simply need to identify the design of your study. There is no other information required other than this single statement.
Variables (quantitative study only)46. A variable is any entity that can take on different values. Another definition of a variable is that it is a characteristic or condition that changes or has different values for different individuals or units of analyses (i.e. sample units). More so, variables are the corner stone of quantitative research, where the researcher seeks to explain the relationships among variables or to compare group differences regarding a variable or variables
46 See section 1.6 “Research Questions” for more information on variable requirements.
of interest. Another important distinction for term variable is the distinction between an
independent and dependent variable.
An independent variable is the variable you have control over (experimental designs), what you can choose and manipulate. A dependent variable is also known as a response variable or explained variable. The independent variable is usually what you think will affect the dependent variable. In some cases, you may not be able to manipulate the independent variable. It may be something that is already there and is fixed (i.e. company size), something you would like to evaluate with respect to how it predicts, influences, impacts, or causes a change in the dependent variable (i.e. employee satisfaction).
As it applies to your research, the dependent variable is normally the problematic variable in DBA studies where the researcher it trying to explain what influences, affects, causes or can predict the problem. For example, if the specific business problem is low employee satisfaction then employee satisfaction is the dependent variable. The researcher then selects independent variables that are thought to predict, influence, impact, or cause the dependent variable, in this case, employee satisfaction.
Thus, it is extremely important to identify clearly the independent and dependent variables in the Purpose Statement component of the proposal. Identification of the variables informs other research components such as sample size and type of statistical analysis that is to be conducted. See more on variables at: http://www.socialresearchmethods.net/kb/variable.php
Targeted population. A population is the larger group that you are studying. The population is not to be misconstrued as the sample, or your study’s participants. You will select your sample, or study participants from the larger population. For example, your population might be all small business leaders in New York. You will however, select a subset of small business leaders in New York to serve as your sample or participants. Remember, you are to address the broader population in this component of the Purpose Statement.
In a qualitative ethnographic or case study, you will need to define the population with the scope of the study. For example, if you are conducting a single case study, the population will be people that meet the participant criteria within that organization/company. Likewise, in a multiple case study the population will be the people that meet the participant criteria within the organizations/companies in the study.
Examples for a case study with the following research question: What strategies do department store managers use to motivate their sales associates?
Single case study example. The population will be department store managers in one New England department store who have a strategy to motivate their sales associates.
Multiple case study example. The population will be department store managers in four New England department stores who have a strategy to motivate their sales associates.
Geographical location. The geographical location simply identifies the geographical location of your study’s participants. The participants might be in a particular country, region,
state, or city. Of course, this may vary based upon the purpose of your study. In the decision to identify the geographic location, one must ensure that the confidentiality of the company(ies) and participants. If one is conducting a study in an automotive manufacturing facility and there are only one or two companies in the city or state (i.e. Alabama), one should define the geographic location to avoid the specific sample units being easily identifiable (i.e., southern United States).
Social change. The final element of your Purpose Statement requires you to provide a positive social change statement. Positive social change involves improvement of human or social conditions by promoting the worth, dignity, and development of individuals, communities, organizations, institutions, cultures, or societies. Focus on explaining “WHO” may benefit, and “HOW” the “WHO” may benefit from your study’s findings and recommendations.
Quantitative hypothetical example. The purpose of this quantitative correlation study is to examine the relationship between leadership styles, size of business, and business revenue.
The independent variables are leadership style and size of business size. The dependent variable is business revenue. The targeted population will consist of business leaders of microelectronic companies in the southeast United States. The implications for positive social change include the potential to (provide social change statement).
Note: DBA doctoral studies require the highest level or rigor and scholarship. One focus of rigor and scholarship is that of the number of predictor or independent variables examined in quantitative doctoral studies. Nonexperimental research (i.e. correlation, quasi- experimental, etc.) requires the use of at least two independent or predictor variables.
Qualitative hypothetical example (case study). The purpose of this qualitative multiple case study is to explore the strategies that department store managers use to motivate their sales associates. The targeted population will comprise of department store managers form one of the three department stores in the southeast region of the United States who have implemented strategies to motivate their sales associates. The implication for positive social change includes the potential to (provide social change statement).
Note: In a case study, and often in ethnographic studies, the population is limited to those people meeting the participant criteria in the company or companies being studies. In a phenomenological or narrative study, the population includes all people who meet the participant criteria.
1.5 – Nature of the Study
The Nature of the Study component serves two purposes (a) describing and justifying the methodology (i.e. quantitative, qualitative, mixed-method) and (b) describing and justifying the design (i.e. case study, phenomenological, correlation, sequential explanatory, etc.). Therefore, a well-crafted Nature of the Study can be presented in two paragraphs and not exceed one page.
The first paragraph describes and justifies the methodology and the second paragraph describes and justifies the design. These two components should not be intermingled. A common error in this heading is to restate the purpose, identify variables, analyses, etc. and include other superfluous information. Again, map to the rubric and only include the required content!
Remember that the Nature of the Study succinctly represents your defense of your choice of method and design; therefore, it must have depth. You must demonstrate to the reviewers that you have done the reading and research needed to support your research method and design. That evidence also includes discussing why you did not choose other methods and designs.
Keep this heading deep yet brief. You will have time to expand upon the Nature of the Study
later in the Research Method and Design heading.
Hypothetical Quantitative Example47
I chose a quantitative methodology for this study. Using a quantitative study enables one to identify results that can be used to describe or note numerical changes in numerical characteristics of a population of interest; generalize to other, similar situations; provide explanations of predictions, and explain casual relationships (cite). Thus, the quantitative method is appropriate for this study because the purpose of the study is to analyze numerical data and infer the results to a larger population. A mixed methods study contains the attributes of both quantitative and qualitative methods (cite). The qualitative method is appropriate when the research intent is to explore business processes, how people make sense and meaning, and what their experiences are like (cite). Therefore, the qualitative and qualitative portions of a mixed- method approach are not appropriate for this study.
Specifically, the correlation design is chosen for this study. A correlation researcher examines the relationship between or among two or more variables (cite). The correlation design is appropriate for this study because a key objective for this study is to predict the relationship between a set of predictor variables (leadership style and size of business) and a dependent variable (company revenue). Other designs, such as experimental and quasi-experimental designs are appropriate when the researcher seeks to assess a degree of cause and effect (cite). This principal objective for this study is to identify a predictive model; thus the experimental and quasi-experimental designs are not appropriate.
Hypothetical Qualitative Example
The three research methods include qualitative, quantitative, and mixed methods (cite). I selected the qualitative method to use open-ended questions. Qualitative researchers use open- ended questions to discover what is occurring or has occurred (cite). In contrast, quantitative researchers use closed ended questions to test hypotheses (cite). Mixed methods research includes both a qualitative element and quantitative element (cite). To explore (your topic), I will not be testing hypotheses which is part of a quantitative study or the quantitative portion of a mixed methods study.
47 Note: As you can see, the example clearly starts with topic sentences (red text) that foreshadow what is to be addressed in the paragraph. Notice the quantitative method paragraph does not address the design, as the topic sentence does not suggest the design is the focus of the paragraph. The design is not foreshadowed in the topic sentence. Remember, a topic sentence alerts the reader to the main topic of the paragraph.
I considered four research designs that one could use for a qualitative study on (2-3 words identifying your topic): (a) miniethnography, (b) focus group, (c) narrative, and (d) case study. (Note: Select the designs that you considered and are applicable to an applied qualitative study.) Miniethnography involves… (Briefly discuss miniethnography, 1-sentence defining with a citation, 1-sentence if needed why it is or is not the optimal choice). Business researchers use focus groups to… (Briefly discuss focus groups, 1-sentence defining with a citation, 1-sentence if needed why it is or is not the optimal choice). A narrative design entails… (Briefly discuss narrative designs, 1-sentence defining with a citation, 1-sentence if needed for why it is or is not the optimal choice). Case study researchers… (Briefly discuss case study, 1-sentence defining with a citation, 1-sentence is needed why it is or is not the optimal choice).
1.6 – Research Question (Quantitative Only)
DBA doctoral studies require the highest level or rigor and scholarship. One focus of rigor and scholarship is that of the number of predictor or independent
variables
examined in quantitative doc studies. Non-experimental research (i.e.
correlation
,
quasi-
experimental
, etc.) requires the use of at least two independent or predictor variables. This is due to the “third variable” problem. A third variable also known as a confounding or mediator variable can confound the relationship between the independent and dependent variable. This confounding can lead the researcher to incorrectly interpret the results, leading to an incorrect rejection of the null hypothesis.
As such, all DBA quantitative studies require the examination of at least two predictor, or independent variables. This affects the statistical analysis, as simple bivariate correlations (correlation designs) or one-way ANOVAs cannot be used as inferential statistical tests. Other statistical procedures, such as partial correlation, semipartial correlation, mediation and moderation, and multiple regression analyses, as a minimum must be used for correlation studies. Quasi-experimental, causal comparative, etc., designs must employ statistical analyses (i.e. factorial ANOVAs), as a minimum, which examines more than one independent variable.
Below are appropriate and inappropriate examples of correlation and quasi-experimental research questions. These examples depict predictor/independent variables, which are (a) employee job satisfaction and (b) leadership experience. The dependent variable is company gross revenue.
·
Appropriate Correlation Example (two predictor variables): Does a linear combination of employee job satisfaction and leadership experience significantly predict employee productivity?
·
Inappropriate Correlation Example (only one predictor variable): Does employee job satisfaction significantly predict employee productivity?
·
Appropriate Quasi-experimental Example (two independent variables): Do employee job satisfaction and leadership experience significantly influence employee productivity?
· Inappropriate Quasi-experimental Example (only one independent variable):
Does employee job satisfaction significantly influence employee productivity?
1.7 – Hypotheses (Quantitative/Mixed-Method Only)
Hypotheses
Two major elements in the research design are the hypotheses and the variables used to test them. A hypothesis is a provisional idea whose merit deserves further evaluation. Two hypotheses, the null (H0) and alternative (H1), are to be stated for each research question. Below are appropriate examples of correlation and quasi-experimental/casual comparative null and alternative hypotheses; note how they mirror the research questions identified above in the Quantitative Research Questions heading. These examples depict predictor/independent variables, which are (a) employee job satisfaction and (b) leadership experience. The dependent variable is company gross revenue. The H0 and H1 reflect the appropriate statistical notation and are to be included. See more on hypotheses at:
http://www.socialresearchmethods.net/kb/hypothes.php
Correlation
· Null Hypothesis (H0): The linear combination of employee job satisfaction and leadership experience will not significantly predict employee productivity.
· Alternative Hypothesis (H1): The linear combination of employee job satisfaction and leadership experience will significantly predict employee productivity.
Quasi-experimental
· Null Hypothesis (H0): Employee job satisfaction and leadership experience do not significantly influence employee productivity.
· Alternative Hypothesis (H1): Employee job satisfaction and leadership experience significantly influence employee productivity.
1.8 – Research Question (Qualitative Only)
In a qualitative study, the Research Question uses the same words as in the Specific Business Problem to identify the specific business leader and identify what the leader has limited supply of or is lacking. The following examples demonstrate how to align the research question with the specific business problem.
1.9 – Interview Questions (Qualitative Only)
In qualitative studies, the researcher must first identify the population for the study (business leaders that have solved or are solving the specific business problem) and align the interview questions with the population and the research question. Interview questions must (a) provide answers to the research question, (b) not go beyond the research question (i.e., no demographics if not part of the research question), (c) be in the language (word choice) that the participant will understand, (d) be open-ended questions (no Yes or No answerable questions), and (e) be applied DBA rather than speculative PhD questions (see the example below).
Interview questions should be straightforward and ask what or how the business leader has addressed the research problem. Typically, case study and ethnographic interviews will be semistructured, semiformal, unstructured, or informal. Phenomenological studies use the phenomenological long interview with only one to three questions to have a longer discussion getting in depth data and reaching a state of epoché. Students should critically read about the different interviewing techniques and select the best technique for the study design.
Semistructured and semiformal interviews frequently include six to ten interview questions to allow time for probing questions. The final interview question in a semistructured or informal interview frequently asks the participant to share any additional information for addressing the research question(s): What additional information would you like to share about XYZ? One typically uses an unstructured or informal interview technique when having a more casual discussion often spreading the interview questions out over time during field visits (i.e., during a direct observation or participant observation phase in data collection).
In contrast, the phenomenological long interview typically has one or two interview questions. Although phenomenological interview questions are written as a question, the interview protocol involves creating an in depth discussion (typically 1-2 hours) and reaching a state of epoché. The phenomenological long interview requires more study and preparation as compared to more traditional interviewing techniques used in ethnography and case study designs.
Be cautious not to confuse the interviewing process with the interviewing questions. The concept of semistructured questions or semistructured interview questions does not exist.
Semistructured interviews (semiformal, unstructured, or informal interviews) are a specific interviewing technique/process. All qualitative interview questions are open-ended. However, the interview questions are not semistructured.
Example Research Question
What strategies do department store managers use to motivate their sales associates?
Example Applied DBA Interview Questions
1. What strategies are you using to motivate your sales associates?
2. What method did you find worked best to motivate your sales associates?
3. How did your sales associates respond to your different motivation techniques?
Example Speculative/Theoretical PhD Questions (do not use)
1. What strategies should managers use to motivate sales associates?
2. What method do you think will work best to motivate sales associates?
3. How do you feel your sales associates respond to other motivation techniques?
1.10 – Theoretical/Conceptual Framework
A theoretical (for quantitative studies) or conceptual framework (for qualitative studies) offers a systematic view of a phenomenon. In other words, the framework provides a lens through which to view a phenomenon.
Identifying the Best Theory or Conceptual Model
Make certain that the theory aligns with the research question. Consider the following when searching for a theory or conceptual model for the conceptual framework.
· Critically read peer- reviewed studies related to your topic and identify the theories that the sources found aligned with their studies. After one has read and synthesized numerous peer-reviewed studies related to the topic for the annotated bibliography, one will notice a few theories (or conceptual models) that aligned with several studies.
· Critically read the seminal work on the theories (or conceptual models) that you found in peer-reviewed studies related to your topic.
· Related studies may be about the concept and not the specific industry.
· For example, if one is studying how the family owned wrecking yard leaders succession plan, one could look at studies on leadership training and development in other types of organizations.
· Quantitative. Select the theory or conceptual model that best aligns with the research question and provides an interrelated set of constructs, variables, hypotheses, or propositions that offer an explanation for phenomenon.
· Qualitative. Select the theory or conceptual model that best aligns with the research question.
As you can see, it is important to immerse yourself in the literature pertaining to your conceptual framework to gain a good understanding of the framework. More important, your literature review must include an exhaustive review of the literature pertaining to the conceptual framework you are proposing for your study. This is extremely important, as you will be required to discuss your findings as they confirm, disconfirm, extend, etc., the extant literature on your conceptual framework. You must critically analyze and synthesize the studies where your conceptual framework has been the lens through which the phenomenon has been viewed.
As outlined in the DBA Rubric, you are required to present a brief overview of your theory or conceptual framework in Section one of the proposal. Please note this is not to be a detailed review of your theory or framework. The detailed review is required in the Review of the Literature heading. Here, a model for presenting the theory or framework heading is offered.
You will want to state the name of the theory or identify the conceptual framework, identify the theorist if applicable, list key concepts of the theory or framework, identify any propositions or hypotheses, and identify how the theory or framework applies to your study. Please note there are obvious variations to this model depending upon your particular study and topic. However, the intent is to briefly present the key aspects of your theory and or framework and show how it fits into your study.
Quantitative Example
Burns (1978) developed the transformational leadership theory. Burns used the theory to offer an explanation for leadership based upon the premise that leaders are able to inspire followers to change expectations, perceptions, and motivations to work toward common goals. Burns identified the following key constructs underlying the theory (a) idealized attributes, (b) idealized behaviors, (c) intellectual stimulation, (d) inspirational motivation, and (e) individualized consideration. As applied to this study, the transformational leadership theory holds that I would expect the independent variables (transformational leadership constructs), measured by the Multifaceted Leadership Questionnaire, to predict employee turnover intention because (provide a rationale based upon the logic of the theory and extant literature). The following figure48 is a graphical depiction of the transformational leadership theory as it applies to examining turnover intentions.
48 Graphical models are useful for depicting the theoretical framework in quantitative studies.
Let’s examine the theoretical framework from the perspective of possible lenses through which to view phenomena. Assume the business problem or phenomenon is the failure rate of small businesses, an obvious business concern. There are plethora’s of explanations that can be offered for the failure of small businesses. As the researcher, you have the choice of lens for which to view the problem. For example, you might hypothesize or rationalize that transformational leadership characteristics offer a systematic view for the failure of small businesses. Specifically, you hypothesize or rationalize that a leaders transformational leadership characteristics are influential in the success of small businesses. As such, your study would be grounded in transformational leadership theory or transformational leadership conceptual framework.
Or perhaps, you hypothesize or rationalize that servant leadership characteristics offer a systematic view for the failure of small businesses. Specifically, you hypothesize or rationalize that a leaders servant leadership characteristics are influential in the success of small businesses. As such, your study would be grounded in transformational leadership theory or transformational leadership conceptual framework. Hence, the number of lenses through which a problem or phenomena can be viewed is limitless. Only your imagination stands between you and selecting the theory or conceptual framework that can be used to connect your study to existing knowledge.
Perhaps, one of the most misunderstood aspects of theory is how to apply it in the doctoral study. Researchers utilizing a quantitative study grounded in transformational leadership theory must measure or assess the constructs underlying the theory. The broad constructs of transformational leadership theory are idealized attributes, idealized behaviors, inspirational motivation, stimulation, and idealized consideration.
Therefore, an instrument such as the Multifaceted Leadership Questionnaire (MLQ) is appropriate to measure the underlying constructs of transformational leadership theory. Any instrument not proven to assess transformational leadership cannot be approved for use in a study grounded in transformational leadership theory. If you (inappropriately) used a nonvalidated instrument, you would not be testing the proposed transformational leadership theory, and your
study would not have construct validity. For example, the Servant Leadership Survey (SLS) instrument could not be approved for use in a study grounded in transformational leadership theory, as the SLS was validated for use in measuring constructs underlying servant leadership theory.
Qualitative Example
Example research question. What strategies do department store managers use to motivate their sales associates?
Example conceptual framework. Vroom (1959) developed the expectancy-valence theory, which he later called the expectancy motivation theory (Vroom, 1964). The expectancy motivation theory suggests that employees will exhibit positive performance behaviors when they believe that their work will result in certain rewards (Vroom, 1964). Building upon Vroom’s expectancy motivation theory, Gilbert (1978, 2013) published his behavioral engineering model that provided a motivational foundation for the inputs that can lead to specific employee motives. Gilbert identified three categories covering information, instrumentation, and motivation. Within the manager’s scope of control are data, resources, and incentives. Within the employee’s scope of control are knowledge, capacity, and motives. Gilbert argued that if managers improved the availability of data access, provided the tools and equipment, or incentives to perform, employees would exhibit a change in willingness to participate. Likewise, if employees have a change in knowledge or capacity to perform, employees would exhibit a change in willingness to participate (Gilbert, 1978, 2013). Vroom’s (1964) expectancy motivation theory and Gilbert’s (1978) behavioral engineering model both align with this study exploring the strategies that department store managers use to motivate their sales associates.
1.11 – Operational Definitions
Do not include terms found in a basic academic dictionary (i.e. Webster’s). List only terms than might not be understood by the reader. All definitions should be sourced from professional/scholarly sources and in alphabetical order. Do not include more than 10 key operational definitions. Although one can use a maximum of 10 terms, there may only be a few terms pertinent to the study. Listing a specific term that only one or two sources in the literature review introduce is likely not pertinent to the study and should not be listed in the operational definitions.
1.12 – Assumptions, Limitations, and Delimitations49
Assumptions are facts considered to be true, but which cannot actually be verified by the researcher. Assumptions carry risk and should be treated as such. A mitigation discussion would be appropriate. Identify all assumptions associated with the study. Limitations refer to potential study weaknesses, which cannot be addressed by the researcher. Identify all limitations
49 Review the following resource for more detailed information: Ellis, T. J., & Levy, Y. (2009). Towards a guide for novice researchers on research methodology: Review and proposed methods. Issues in Informing Science and Information Technology, 6, 323-337. Retrieved from http://www.informingscience.org/Journals/IISIT/Overview
associated with the study. Delimitations refer to the bounds or scope of the study. Describe the boundaries and what is in and out of your study’s scope.
1.13 – Significance of the Study
Contribution to Business Practice
Discuss how the findings, conclusions, and recommendations from your study could fill gaps in the understanding and effective practice of business.
Implications for Social Change
Provide a statement of the your study’s potential for effecting positive social change or the improvement of human or social conditions by promoting the worth, dignity, and development of individuals, communities, organizations, institutions, cultures, or societies.
1.14 – Review of the Professional and Academic Literature
The literature review content needs to be a comprehensive and critical analysis and synthesis of the literature related to the theory and/or conceptual model from the Theoretical/Conceptual Framework as well as the existing body of knowledge regarding the research topic. What a literature review should not be is an amalgamation of essays on the topic. The approach to this heading may vary by authors’ specific purpose. For example, if your study is to be grounded in the transformational leadership theoretical or conceptual framework, you will be examining or exploring your phenomenon through a leadership lens. You want to report on extant research that was grounded in the transformational leadership theoretical/conceptual framework. You would want to report on the literature that is as close to your topic/phenomenon as possible. In addition, if you are conducting a quantitative study, you need to include the literature for any other key variables. A basic outline is presented at Appendix A.50
Critical analysis and synthesis of the relevant literature will be an important element of the literature review. The review of the literature is not to be a regurgitation of what you have read. It is also not to teach about a topic; rather, it is to show your mastery of the previous and recent research on your topic and provide a comprehensive up-to-date literature review on your topic. Start with an introductory heading and then report the literature. This should be an exhaustive review of the literature using the chosen theoretical/conceptual framework and consist of the key and recent writings in the field. Repeat this approach if there are any additional theories. In addition, in quantitative studies, there must be a critical analysis and synthesis for each variable.
There are three questions that students typically ask about the literature review: (a) length, (b) organizational structure, and (c) content. The length will depend upon the theoretical foundation related to the topic and scholarly studies related to the theory. Typically, for a doctoral study, a literature review will average 35-40 pages. However, demonstrating a rich and
50 Literature reviews will vary by topic, author, etc. However, Appendix A presents the minimum requirements for a quantitative study.
comprehensive review of the topic is more important than the number of pages in a literature review.
The most common ways that one may organize the literature review are to use a chronological, topical, or combination of chronological and topical structure. The literature review should be a succinct yet in-depth critical analysis of scholarly studies and authoritative seminal work. The literature review should not be a summary of one’s reading or an amalgamation of essays on the topic.
The literature review content needs to be a comprehensive and critical analysis and synthesis of the literature related to the theory and/or conceptual model that one identified in the Theoretical/Conceptual Framework as well as the existing body of knowledge regarding the research topic. Typically one half to two thirds of a good literature review will relate the theory or conceptual models to a critical analysis and synthesis about the topic and problem. One organizational strategy for the literature review is (a) one third discussing the theory or conceptual model (see figure below), (b) one third topical foundation, and (c) one third discussing the topic in relation to the theory.
1.15 – Transition
This heading summarizes the key contents of Section 1. Do not introduce any new material in the summary, but do provide an overview of the primary objectives and contents of Sections 2 and 3.
Section 2 – The Project
2.1 – Purpose Statement
Simply cut-and-paste the Purpose Statement from Section 1.
2.2 – Role of the Researcher
The Role of the Researcher is an important part of your proposal and study. The content that you present in this subheading is important because it demonstrates that a) you have done the research that is required, b) that you understand what your role is in the study design, and 3) you understand the limitations and challenges in this type of role, and how any concerns may be mitigated to enhance the reliability and validity of your work.
One of the most challenging parts to write in this subheading is about the use of a personal lens primarily because novice researchers (like students) assume that they have no bias in their data collection. However, it is important to remember that a participant’s as well as the researcher’s bias/worldview is present in all social research, both intentionally and unintentionally which is why it is important to address strategies to mitigate bias.
To address the concept of a personal lens, remember that in qualitative research, the researcher is the data collection instrument and cannot separate themselves from the research, which brings up special concerns. Remember that the researcher operates among multiple worlds while engaging in research, which include the cultural world of the study participants as well as the world of one’s own perspective. A researcher’s cultural and experiential background will contain biases, values, and ideologies that can affect the interpretation of a study’s findings.
Therefore, researcher bias is a concern because the data can reflect the researcher’s personal bias and concerns. It becomes imperative that the interpretation of the phenomena represent that of participants and not of the researcher. Hearing and understanding the perspective of others may be one of the most difficult dilemmas the researcher must address. The better a researcher is able to recognize his/her personal view of the world and to discern the presence of a personal lens, the better one is able to hear and interpret the behavior and reflections of others.
How you address and mitigate a personal lens/worldview during your data collection and analysis is important and a key component in the Role of the Researcher subheading. It is important that a novice researcher recognizes their own personal role in the study and mitigates any concerns during data collection. Part of your discussion in this subheading should address how this is demonstrated through using an interview protocol, member checking, transcript validation and review, reaching data saturation, enabling sense making, facilitating epoché, careful construction of interview questions, and other strategies to mitigate the use of one’s personal lens during the data collection process of the study.
It would be impossible to remove all bias because you are a human being. Rather, one mitigates bias as best as one can. This is demonstrated via using an interview protocol, member checking, data saturation, and other strategies to mitigate the use of one personal lens during the data collection process of your study. Inadvertently driving participants to predetermined conclusions speaks to the same concepts.
2.3 – Participants
The requirements are straight forward but often missed in the Participants heading.
Consider the explanations in the following table.
|
Rubric Requirement |
Explanation |
|
a. Describes the eligibility criteria for study participants. |
The participants must meet the eligibility requirement within the scope of the population. Consider the research question: What strategies do department store managers use to motivate their sales associates? If one identified the population as department store managers who have worked in the field for 8-years and have a minimum of 5-years supervising sales associates, one would not be necessarily addressing the requirement. The criteria for the example research question would be department store managers who have successful strategies that they are using to motivate sales associates. The department store manager may have been in the field for 20-years or 1-month—the time in position has nothing to do with the study. Likewise, working with the employees does not mean that the department store manager is using a strategy to motivate the sales associates. |
|
b. Discusses strategies for gaining access to participants. |
Explain your plan for gaining access to participants. In a quantitative survey, one may use a professional association membership list or other types of list to access participants via email, phone, etc. For a qualitative study, one may also use professional associations, trade affiliations, etc. for gaining access. One may also be using rosters inside the company(ies) and emailing, calling, or visiting in person for a case study. It is vital that you develop a strategy to determine that participants meet the study criteria before inviting participation. |
|
c. Identifies strategies for establishing a working relationship with participants. |
Once one gains access, one needs to develop a working relationship with the participants. This may be as simple as sending a survey link via email in a quantitative study to how you will cover the informed consent form and set the |
|
stage for a qualitative interview (often referencing the interview protocol). |
|
|
d. The participants must align with the overarching research question. |
This requirement is a reminder that one must have the correct criteria for selecting the participants and that the criteria must align with the research question—nothing else should be included in the criteria. |
|
e. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources (as appropriate). |
During planning the study, one will make several decisions. In this heading, there is a decision for the participant criteria, how one will gain access to the participants, and how one will build a working relationship with the participants. It is recommended to support claims and decisions with multiple scholarly peer-reviewed or seminal sources. Fortunately, you have an annotated bibliography with peer-reviewed studies where others have made similar decisions as well as seminal sources on methodology. Tip: To represent your sources correctly: Write about what you will do in one sentence and synthesize your sources
|
2.4 – Research Method
This heading is an extension of the Nature of the Study. The first paragraph of the Nature of the Study required a description of and justified the methodology. Here you will extend that discussion by providing more information and additional resources. Remember to use multiple sources to support claims and decisions. It is important to have a strong case to support the rationale for research method and design.
2.5 – Research Design
This section is an extension of the Nature of the Study. The second paragraph of the Nature of the Study required a description of and justified the design. Here you will extend that description by providing more information and additional resources. Remember to use multiple sources to support claims and decisions.
Data Saturation in Qualitative Study Designs
A vital prerequisite for a valid qualitative study is having a plan to ensure data saturation.
Data saturation in qualitative research ensures the validity in a qualitative study similar to a statistically valid sample in a quantitative study. See more on data saturation in the Population and Sampling heading below.
How to Use Multiple Sources to Support Claims and Decisions
Specifically stating multiple sources is one way to make it clear to the reviewers that you have mapped to the Rubric. However, what the reviewers are looking for is that students have done the required reading to justify the choice of research design that will best assist collecting data to answer the research question. Rather than list name-date, name-date, name-date repeatedly, one would synthesize the concepts into one cohesive whole supported by sources in a somewhat indirect manner. For example:
Case studies are the preferred strategy researchers employ when asking how or what questions (Amerson, 2011; Andrade, 2009; Yin, 2009). These types of studies identify operational links among events over time (Andrade, 2009; Baxter & Jack, 2008; Yin, 2009). Case studies may be exploratory, explanatory, or descriptive and may involve one organization and location or multiple organizations and locations for a comparative case study (Amerson, 2011; Stake, 1995; Yin, 2009).
In other words, you are supporting your synthesis with multiple sources. Another way to support your design with a source is:
Ethnographic study is unique in that it includes fieldwork where all relevant participants are observed and interviewed informally rather than a specified number as in phenomenology (Fusch, 2001; Wolcott, 2011). Bernard (2012) stated that the number of participants needed for a qualitative study was a number he could not quantify, but that the researcher takes what he can get it.
In other words, you support your synthesis in a more direct way. Note that Bernard’s entire work is not within the text, but, rather, one important statement that he did make is and it supports the chosen research design.
In both examples, the synthesis demonstrated depth of knowledge that is supported by published peer-reviewed work, which is what reviewers want to see in your work. Moreover, it is a demonstration of your scholarly research abilities. Note, you may use the same source to support more than one decision if applicable.
2.6 – Population and Sampling (Quantitative Only)
Population
Start by describing the population from which the sample will be drawn. Include any pertinent demographic variables (e.g., CEO, senior executive, mid-level manager, sales professional, front-line supervisor, etc.). Refer to pg. 29 (Participant Characteristics) of the APA Manual (American Psychological Association, 2010) for other appropriate characteristics when appropriate.
Sampling
The two broad categories of sampling methods are probabilistic sampling (random sampling) and non-probabilistic sampling (non-random sampling)51. Identify and defend your sampling method. You must address the strengths and weaknesses of your chosen sampling method. For example, if you will utilize a stratified random technique defend your reason for doing so. Also note why stratified sampling is more appropriate for your research situation than another sampling technique. You will need to refer to the literature pertaining to sampling techniques.
Describe and defend the sample size. This is where you discuss conducting a power analysis to determine the appropriate sample size. You will present your power analysis in this component. G*Power3 is an excellent power analysis software tool and can be downloaded at:
http://www.gpower.hhu.de/en.html
. You will find a user’s manual and short tutorial at the same website. See
Appendix B for an example power analysis.
Describe the eligibility criteria for inclusion in the study. Discuss any exclusion criteria. Make the eligibility criteria clear, as the results of the study cannot be generalized beyond your targeted population. You need to make it clear as to who can, and who cannot, participate in your study.
2.7 – Population and Sampling (Qualitative Only)
Defining the Population
In this heading, one needs to define the scope of the study. For example, in a phenomenological study, the population will be all the people within the scope of the study (i.e., a specific industry) that meet the participant criteria noted in the participant section 2.3 above. In an ethnographic study or case study, the population would comprise all people that meet the participant criteria in one company for an ethnographic study or single case study and multiple companies for a multiple case study. One should identify the number of companies in a multiple case study. Likewise, one should identify the approximate number of people (that meet the participant criteria) within your study’s population.
Sampling
One must describe and justify the sampling method (census, convenience, criterion, purposeful, quota, snowball, etc.). Once one defines the total population meeting the participant criteria within the scope of the study, one must identify the sample size that has the best opportunity for the researcher to reach data saturation. A large sample size does not guarantee that one will reach data saturation, nor does a small sample size—rather, it is what constitutes the sample size. One must also select a sampling technique that supports the research design.
51 See Appendix B for a typology of sampling strategies.
For example, one may use a census sample for a single or multiple case study with a small population versus a convenience sample in an ethnographic study. A census sample is actually a census, which means that the study participants will include 100% of the population. For example, as depicted in the following graphic, if one identified the scope of a multiple case study to include five companies and the people that meet the participant criteria for the population as the CEOs of the five companies, there would be a census sample if all five of the CEOs participated.
Data Saturation and Sampling
In the Population and Sampling heading (as well as the Research Design and the Validity headings), one must define how one will ensure data saturation. Although data saturation in qualitative research ensures the validity in a qualitative study similar to a statistically valid sample in a quantitative study, there is no direct correlation between the sample size and reaching data saturation. Data saturation in qualitative research is a way to ensure that one obtained accurate and valid data. Using too small of a sample or too large of a sample will not ensure data saturation. One should critically read and obtain a clear understanding of data saturation before writing a qualitative proposal. Fusch and Ness (2015) synthesized the literature to identify some key characteristics of reaching data saturation which include no new data, no new themes, no new coding, and ability to replicate the study (providing one asks the same participants the same questions in the same timeframe). The study design (case study, miniethnography, phenomenological, etc.) will affect when and how one reaches data saturation. One may be conducting interviews only in a phenomenological study, whereas one would use multiple data collection methods in a case study.
Although the DBA leadership requires a minimum of 20-participants in a phenomenological study and although one may use member checking to enhance the richness of the data, one may have to interview many more participants to reach data saturation. In contrast, in a case study using a small census sample and multiple data collection methods, one may reach data saturation with one or a few participants. In qualitative studies, quality (rich data) is more important than quantity (thick data).
2.8 – Ethical Research
Each research study comes with its own set of specific ethical issues. Thus, a rubric cannot address all possible scenarios. Therefore, it will be helpful to review the IRB Application Form before you complete this component to ensure you address any requirements not identified in the rubric or Research Handbook. However, as a minimum, discuss the informed consent process. Include a copy of the informed consent form in an appendix and list the informed
consent form in the Table of Contents. Discuss participant procedures for withdrawing from the study. Describe any applicable incentives. Clarify measures for assuring the ethical protection of participants is adequate. Agreement documents are to be listed in the (a) text of the study, (b) appendices and (c) Table of Contents. Include a statement that data will be maintained in a safe place for 5-years to protect rights of participants. Ensure you indicate that the final doctoral manuscript will include the Walden IRB approval number. Ensure the document does not include names or any other identifiable information of individuals or organizations.
Each participant in your study must give written consent to take part in the data collection phase of the work. Moreover, as a researcher following the protocols of the Belmont Report, you must ensure that your participants have a full understanding of their part in the study. Finally, you must ensure that participants understand that they may withdraw from your study at any time without penalty, and how to withdraw from the study.
It is a good practice to complete the first draft of your IRB application while completing the ethics section as well as Section 2. Consider: (a) writing a sentence about your plan to share a summary of the findings with the study participants, and (b) do not use the term anonymous for qualitative studies if you will be interviewing or knowing whom the participants are. Qualitative researchers can protect the confidentiality but not the anonymity of participants because the researcher will know who the participants are. Depending upon the data collection method, quantitative researchers may be able to protect participants’ anonymity.
2.9 – Data Collection—Instruments (Quantitative)
You will describe each instrument’s purpose, intended populations, scales, scoring process, time needed to complete, etc. This heading will also address the psychometric issues surrounding the instrument, reliability and validity—this is very important. You will need to report the reliability and validity coefficients. Where possible, include the details of the reliability measures employed (e.g. test-retest, equivalent or alternate form, split-half, and internal consistency). Validity should include content validity, criterion-related validity, and construct validity. State briefly what these measures of validity are, and report their Intercorrelation coefficients.
You will need to address any special requirements of the publisher. You will need to gain permission from the test publisher to use some instruments. This can be requested by sending a formal letter or email to the publisher. Alternatively, you may need to complete a training course or require your chair’s signature to acquire the instrument—be sure to include this information if applicable.
2.10 – Data Collection – Instruments (Qualitative)
The requirements are straight forward but often missed in the Participants heading.
Consider the explanations in the following table.
|
Rubric requirement |
Explanation |
|
a. In addition to identifying the student as the primary data collection instrument, identifies the data collection instrument/process (i.e., informal interview, semistructured interviews, phenomenological in-depth interviews, focus groups, company/archival documents, etc.). |
Rubric requirement has two parts and students sometimes miss one of them, which can lead to a revision request. 1. Identifying that you are the primary data collection instrument. 2. Identifying all of the secondary, tertiary, etc. data collection instruments. Although common in ethnographic research, in case studies, students must have a minimum of two data collection methods. |
|
b. Clarifies how the student will use the data collection instrument/technique (the process/protocol). |
Describe how you will use the instrument(s) by providing a brief definition of each instrument and referencing interview or focus group protocols, etc. The focus here should be more on defining and using the instrument. For example, if you are using a specific type of interview, what is the interviewing technique specific to your chosen approach (i.e., unstructured or semistructured interviews). Keep this brief; however, be sure to define the different data collection methods (with scholarly support). In the Data Collection Technique Heading, where you will expand upon the process. |
|
c. Identifies how the student will enhance the reliability and validity of the data collection instrument/process (i.e., member checking, transcript review, pilot test, etc.). |
Clarify how you will enhance the reliability and validity of the instruments such as using an expert panel to validate interview questions, member checking follow up interviews after semistructured interviews, triangulation of multiple data collection methods (during the data analysis as applicable to the research design), etc. |
|
d. Identifies where in appendices the instrument (i.e., interview protocol, focus group protocol, interview questions, etc.) is (are) located. Ensures Table of Contents lists appendices. |
As applicable, include interview protocols, focus group protocols, direct/participant observation protocols in the appendices. |
|
e. Supports every decision with a minimum of three scholarly peer-reviewed or seminal sources. |
During the study plan, one will make several decisions. In this heading there are several decisions to make and support. Each decision such as the following will need scholarly support: · Identifying that you are the primary data collection |
instrument.
· Identifying all of the secondary, tertiary, etc. data collection instruments such as type of interviews, focus groups, company/archival documents, company marketing materials, etc.).
· Identifying how you will use the instruments by providing a brief definition of the instrument and referencing interview or focus group protocols, etc.
· Identifying how you will enhance the reliability and validity of the instruments such as by using member-checking follow up interviews after a semistructured interview.
Tip to represent your sources correctly: Write about what you will do in one sentence and synthesize your sources supporting your decision in a separate sentence. See the following examples:
Academic integrity code of conduct violation (misrepresenting sources) example 1:
I will use semistructured to explore the strategies that department store managers use to motive their sales associates (Johnson & Williams, 2013; Rubin & Rubin, 2012; Smith, 2014). Note that the sources did not discuss the student’s study in their publications and the example is a misrepresentation of the sources.
Correctly supporting a decision example 1. Cite (2014) used semistructured interviews to determine how sales managers motivate sales associates. Likewise, Cite (2013) found that semistructured interviews were a good approach to learn how department store managers motivate sales clerks. Rubin and Rubin (2012) argued that semistructured interviews are a good way for the researcher to focus on the details that address the research question. Therefore, I will use semistructured to explore the strategies that department store managers use to motivate their sales associates. Note: please be sure to synthesize your sources to support your decisions.
Academic integrity code of conduct violation (misrepresenting sources) example 2:
I will be the primary data collection instrument in this study (Denzin, 2014; Marshall & Rossman, 2016; Wolcott, 2005). Note that the sources did not discuss the student’s study in their publications and the example is a misrepresentation of the
sources.
Correctly supporting a decision example 2. I will be the primary data collection instrument in this study. In qualitative research, the researcher is the primary data collection instrument because the researcher hears, sees, and interprets the data (Denzin, 2014; Marshall & Rossman, 2016; Wolcott, 2005). Note: please be sure to synthesize your sources to support your decisions.
2.11 – Data Collection Technique
Do not confuse the purpose of this heading with that for the explanation of procedures. You want to discuss the main approach to collecting your data. It is a good idea to restate the research question and then address the data collection process. Depending upon whether you are using a quantitative or qualitative method, you should discuss and support your decision for collecting the data.
Quantitative Studies
In a quantitative study one would discuss: (a) surveys, (b) structured record reviews to collect data (e.g., sales data, performance records, government databases, etc.), and (d) structured observations. Self-administered questionnaires and structured records are more prevalent with quantitative research. Indicate the process you will use to collect your data. State your rationale for selecting the process (e.g., in terms of strengths and weaknesses, cost, data availability, convenience, etc.).
Qualitative Studies
Describe the process for collecting the data (i.e., interviews, focus groups, direct or participant observations, and review of company/archival documents, performance indicators, sales reports, business plans, etc.) Provide an abridged interview protocol, focus group protocol, observation protocol, etc., and identify the location of the protocols in an appendix.
2.12 – Data Organization Technique (Qualitative Only)
The Data Organization Technique can often be a short paragraph where students address all of the data that they collected in this heading. There are typically two decisions in this section: (a) about how one will securely store the data (electronic and hard copies) and (b) that the data will be destroyed after 5 years.
2.13 – Data Analysis (Quantitative Only)
Data analysis involves discussing the statistical test(s) you will use to answer each research question, and justify the tests’ selection. Indicate the nature of the scale for each
variable (e.g., nominal, ordinal, interval, and ratio). Why is the selected statistical test more appropriate than another? (Hint: The statistical test is usually selected due to the nature of the question and scale of measurement of the variables you defined). Describe how you will deal with discrepant cases (missing data, data that cannot be interpreted, etc.). Identify the software that will be used to analyze the data. Be sure to discuss the data assumptions, how they will be assessed, and how you will address any violations (e.g., using Bootstrapping).
2.14 – Data Analysis (Qualitative Only)
The qualitative data analysis heading is critical for demonstrating doctoral level competence and will help you prepare for Section 3. This heading must be deep yet can be covered in one or two succinct paragraphs. Reviewing the following table’s contents will help you develop and write your data analysis plan.
|
Rubric requirement |
Explanation |
|
a. Identifies the appropriate data analysis process for the research design (i.e., one of the four types of triangulation for case studies; modified van Kaam, van Maanen, etc. for phenomenology). |
Different qualitative research designs require different data analysis processes. Critically read seminal works and other studies using your research design to be able to demonstrate that you are prepared to conduct a data analysis. For example, case study researchers will use methodological triangulation. Ethnographic researchers will likely use methodological triangulation. However ethnographers may also use data triangulation. |
|
b. Provides a logical and sequential process for the data analysis. |
Students must succinctly describe how they will perform the data analysis. Students must use all the data for the analysis. Often students planning case studies or ethnographic studies discuss the data collection instruments and techniques above, but forget everything but the interview data in the data analysis section. Students should begin their data analysis heading by noting the data from the planned collection methods and how they will use the data analysis process (in either order). For a case study, one would start by discussing how one will use methodological triangulation for the information from the different data collection methods. |
|
c. Details the student’s conceptual plan |
Or is the key word in this requirement. Explain the classic data analysis method or qualitative software analysis method (how you will do it). Classic Data Analysis Method For the classic data analysis method, discuss sorting all of the concepts and ideas on separate sheets of paper into categorized piles—be sure to support your decision. Critically analyze the data using a large physical mind map (i.e., stacks, piles, or clusters of concepts and ideas on a wall or large room floor) for the classic data analysis method. Qualitative Software Analysis Method For the qualitative software analysis method, code all of the concepts and ideas (all of the data and not just the interview questions)—be sure to support your decision. Critically analyze the data in a graphical portrayal of categorized and coded concepts and ideas using the qualitative software analysis method. Themes Question the meaning of the reoccurring concepts and ideas to identify the themes. In effect, the compiling phase involves organizing the data in an order, to create a database, while disassembling phases involves dividing the complied data into fragments and labels. The reassembling process involves clustering and categorizing the labels into sequences and groups. The interpretation stage requires creating narratives from the sequences and groups including conclusions. |
|
d. Identifies how the student will focus on the key themes, correlate the key themes with the literature (including new studies published since writing the proposal) and the conceptual framework. |
This should be a one or two sentence plan on how you will correlate the key themes with recent studies and the theory or conceptual models from your conceptual framework. This will help you prepare for the presentation of findings in Section 3. |
|
e. Supports every decision |
Critically reading seminal and authoritative work for data |
|
with a minimum of three scholarly peer-reviewed or seminal sources. |
analysis in your selected research design is vital at this stage of your doctoral journey. You should have ample sources to support your decisions—there are some suggested readings lists in the Bibliography-Suggested Readings Lists |
2.15 – Study Validity (Quantitative Only)
Internal Validity52
Internal validity is the approximate truth about inferences regarding cause-effect or causal relationships. Thus, internal validity is only relevant in studies in which researchers seek to examine causal relationships
(
i.e., experiments or quasi-experimental designs). Internal validity is not relevant in observational (
i.e., correlation designs or descriptive studies, for instance.) However, for studies in which researchers seek to assess the effects of programs or interventions, internal validity is perhaps the primary consideration. In those contexts, you would like to be able to conclude that your program or treatment made a difference — it improved a business process or outcome
Experiments/quasiexperiments.
Experimental and quasi-experimental designs are susceptible to up to 8 threats to internal validity, depending upon the specific design. These eight threats are (a) selection, (b) selection by maturation, (c) statistical regression, (d) mortality, (e) maturation, (f) history, (g) testing, and (h) instrumentation. You need to address each of these threats by briefly mentioning what they are, and, as relevant, the steps you will take in your study to address each of these threats. Again, some of the threats may not be applicable, depending upon your specific design. You can refer to a basic research design textbook to obtain a better understanding of these threats and how to combat them. Be sure to cite your sources. See the following link for further information:
http://www.socialresearchmethods.net/kb/causeeff.php
If you are not conducting an experiment then indicate that this is a nonexperimental design (i.e. correlation) and threats to internal validity are not applicable. However, indicate that threats to statistical conclusion validity are of concern, and then address threats to statistical conclusion validity.
Threats to statistical conclusion validity.
Start by explaining what these threats are.
Threats to statistical conclusion validity are conditions that inflate the Type I error rates, (rejecting the null hypothesis when it is in fact true), and Type II error rates (accepting the null hypothesis when it is false.) The three conditions that you need to cover here are: (a) reliability of the instrument, (b) data assumptions, and (c) sample size.
52 See more on internal validity @
http://www.socialresearchmethods.net/kb/intval.php
Reliability of the instrument. You already reported the reliability properties of your instrument in the Instrumentation heading. However, you need to determine how reliable the instrument is for your specific sample. Here you will indicate you will conduct an internal consistency reliability check of the instrument against your specific sample. The intent is to see how close the reported reliability coefficient (in section 2.9 – Instrumentation) is and your calculated reliability coefficient. State what an acceptable value is (i.e. >.7) and how you will check your instrument’s reliability. There is a procedure (Analyze/Scale/Reliability Analysis) in SPSS that will allow you to compute Cronbach’s alpha, one of several reliability coefficients.
You will report the results of the reliability analysis in Section 3, Presentation of Findings heading. The degree of agreement/disagreement can provide information for your discussion, especially in the event of a nonsignificant result.
Data assumptions53 (varies by statistical test).
You will state what the assumptions are pertaining to your tests and the effects violation of the assumptions can have on your results.
Indicate how you will check these assumptions. Refer to a basic statistics textbook for assumptions regarding various tests. For example, the Green and Salkind text used in the DDBA 8438 course is an excellent resource for identifying assumptions for most basic statistical tests. Pallant (2010)54 is an excellent text for instruction on performing parametric assumption testing. The following Table contains the major assumptions and procedures for testing the assumptions for multiple linear regression and for ANOVA tests.
Table X
Statistical Test, Assumptions, and Procedures for Testing Assumptions
|
Statistical test |
Assumptions |
Testing |
|
Multiple Regression |
||
|
Outliers |
Scatterplot |
|
|
Multicollinearity |
Normal Probability Plot (P- P) of the Regression Standardized Residual |
|
|
Normality |
“ |
|
|
Linearity |
“ |
|
|
Homoscedasticity |
“ |
|
|
Independence of Residuals |
“ |
|
|
ANOVA |
||
|
Normality |
Histograms |
|
|
Equality of Variances |
Levene’s Test of Equality of Variances |
53 Data assumptions vary by statistical test.
54 Pallant, J. (2010). SPSS survivor manual (4th ed.). Berkshire. England: McGraw-Hill.
Sample size. Include a brief explanation of the effects of using too small a sample size could have on your study’s outcomes (refer to any basic statistics textbook). However, you will indicate this threat has been met by conducting a power analysis to ensure you have a sufficient sample size. Be sure to cite your work.
External Validity
External validity refers to the extent the study findings can be generalized to larger populations and applied to different settings. External validity is related to the sampling strategy (identified in Heading 2.6, Population and Sampling). Probability sampling strategies (random sampling) enhances external validity. Conversely, nonprobabilistic sampling strategies hinder external validity. This relationship is to be discussed in this heading.
2.16 – Reliability and Validity (Qualitative Only)
A key difference from quantitative research is the reliability and validity headings. The analogous criteria for qualitative studies are dependability, credibility, transferability, and confirmability. These criteria are not measurable and need to be established using qualitative methods such as member checking [Marshall and Rossman (2016) provide a good definition.] and triangulation (Data triangulation, investigator triangulation, theoretical triangulation, and methodological triangulation). See Norman Denzin’s work on triangulation). Please review more detailed information on qualitative validity at:
http://www.socialresearchmethods.net/kb/qualval.php
Reliability
Reliability refers to how one will address dependability. Some of the ways to enhance the dependability of the study are member checking of data interpretation, transcript review, pilot test, expert validation of the interview questions, interview protocol, focus group protocol, direct or participant observation protocol, etc. Reaching data saturation will help assure the dependability of the findings. See the seminal literature on reliability.
Validity
Qualitative study validity refers to the credibility, transferability, and confirmability of the findings. Reaching data saturation will help assure the credibility, transferability, and confirmability of the findings. Please see seminal work on qualitative validity to ensure that you have a valid study.
Credibility. One can enhance credibility by member checking of the data interpretation, participant transcript review, triangulation, interview protocol, focus group protocol, direct or participant observation protocol, etc. Demonstrating qualitative credibility ensures the reviewers that one is addressing the findings from the perspective of the participants.
Confirmability. One can enhance the confirmability by ensuring that the results can be confirmed or supported by others. Probing during interviews and follow up member checking interviews, questioning from different perspectives, triangulation, etc. are techniques one may use to enhance the confirmability.
Transferability. Be sure to demonstrate how you will enable others to determine the transferability of the findings (i.e., meticulously adhering to the data collection and analysis techniques for the research design, using interview protocol, focus group protocol, direct or participant observation protocol, reaching data saturation, etc.). In contrast to quantitative studies where the researcher generalizes the findings, qualitative researchers do not generalize and do not state that the findings are transferable.
2.17 – Transition and Summary
End with a transaction heading that contains a summary of key points and provides an overview introducing Section 3. Do not include any new information in the summary.
Section 3 –Application to Professional Practice and Implications for Change
3.1 – Introduction
Reacquaint the reader to the purpose of the study. For quantitative studies, simply restating the first two sentences of the Purpose Statement followed by a brief summary of the study findings. For qualitative studies simply restate the first sentence of the purpose statement and briefly summarize the findings.
Quantitative Example
The purpose of this quantitative correlation study was to examine the relationship between employee job satisfaction, employee motivation, and employee turnover intention. The independent variables were employee job satisfaction and employee motivation. The dependent variable was employee turnover intention. The null hypothesis was rejected and the alternative hypothesis was accepted. Employee job satisfaction and employee motivation significantly predicted employee turnover.
Qualitative Example
The purpose of this qualitative multiple case study was to explore the strategies that department store managers used to motivate their sales associates. The data came from manager interviews, manager-employee observations, and company documentation at five department stores in Texas. The findings showed methods that the managers used to motivate their sales employees to provide better customer service and increase sales.
3.2 – Presentation of Findings (Quantitative)
An example of an APA results write-up for a multiple regression analysis is provided. Assumptions vary by statistical test. Therefore, ensure you address the appropriate assumptions for your statistical test.
Quantitative Example
In this subheading, I will discuss testing of the assumptions, present descriptive statistics, present inferential statistic results, provide a theoretical conversation pertaining to the findings, and conclude with a concise summary. I employed Bootstrapping, using 1,000 samples, to address the possible influence of assumption violations. Thus, bootstrapping 95% confidence intervals are presented where appropriate.
Tests of Assumptions
The assumptions of multicollinearity, outliers, normality, linearity, homoscedasticity, and independence of residuals were evaluated. Bootstrapping, using 1,000 samples, enabled combating the influence of assumption violations.
Multicollinearity. Multicollinearity was evaluated by viewing the correlation coefficients among the predictor variables. All bivariate correlations were small to medium (Table X); therefore the violation of the assumption of multicollinearity was not evident. The following table contains the correlation coefficients.
Table X
Correlation Coefficients Among Study Predictor Variables
|
Variable |
Age |
Weight |
Height |
|
Age |
1.00 |
.151 |
-.010 |
|
Weight |
.151 |
1.00 |
.562 |
|
Height |
-.010 |
.562 |
1.00 |
Note. N = 204.
Outliers, normality, linearity, homoscedasticity, and independence of residuals55.
Outliers, normality, linearity, homoscedasticity, and independence of residuals were evaluated by examining the Normal Probability Plot (P-P) of the Regression Standardized Residual (Figure 1) and the scatterplot of the standardized residuals (Figure 2). The examinations indicated there were no major violations of these assumptions. The tendency of the points to lie in a reasonably straight line (Figure 1), diagonal from the bottom left to the top right, provides supportive evidence the assumption of normality has not been grossly violated (Pallant, 2010). The lack of a clear or systematic pattern in the scatterplot of the standardized residuals (Figure 2) supports the tenability of the assumptions being met. However, 1,000 bootstrapping samples were computed to combat any possible influence of assumption violations and 95% confidence intervals based upon the bootstrap samples are reported where appropriate.
55 These are the same assumptions discussed in Section 2; the results of the assumption testing are now discussed. These assumptions differ by statistical test and the appropriate assumptions are to be discussed. Note, your specific discussion might differ. For example, there may be severe data assumption violations in the data you collected. Therefore, you would discuss appropriately.
Figure 1. Normal probability plot (P-P) of the regression standardized residuals.
Figure 2. Scatterplot of the standardized residuals.
Descriptive Statistics
In total, I received 207 surveys. Three records were eliminated due to missing data, resulting in 204 records for the analysis. Table X contains descriptive statistics of the study variables.
Table X
Means and Standard Deviations for Quantitative Study Variables
|
Variable |
M |
SD |
Bootstrapped 95% CI (M)56 |
|
Sleep Index |
26.36 |
10.56 |
[24.80, 27.94] |
|
Age |
43.60 |
12.51 |
[41.90, 45.28] |
|
Weight |
72.34 |
15.21 |
[70.23, 74.51] |
|
Height |
169.12 |
10.00 |
[167.68, 170.44] |
Note: N = 204.
Inferential Results
Standard multiple linear regression,57 α = .05 (two-tailed), was used to examine the efficacy of age, weight, and height in predicting sleep index. The independent variables were age, weight, and height 58. The dependent variable was sleep index 59. The null hypothesis was that age, weight, and height would not significantly predict sleep index. The alternative hypothesis was that age, weight, and height would significantly predict sleep index. Preliminary analyses were conducted to assess whether the assumptions of multicollinearity, outliers, normality, linearity, homoscedasticity, and independence of residuals60 were met; no serious violations were noted (see Tests of Assumptions). The model as a whole was able to significantly predict sleep index, F(3, 200) = 4.778, p < .003, R2 = .06761. The R2 (.067) value indicated that approximately 7% of variations in sleep index is accounted for by the linear combination of the predictor variables (sex, weight, and height). In the final model, age and height were statistically
56 The 95% Bootstrap confidence intervals are produced when the bootstrapping procedure is selected in the SPSS regression process. See regression video tutorial located at:
https://www.youtube.com/watch?v=1ItFMKlPG5k
57 Identify the test and of purpose of the test.
58 Restate the independent variables as presented in the purpose statement and research question; there is to be no deviation.
59 Restate the dependent variables as presented in the purpose statement and research question; there is to be no deviation.
60 Identify the assumptions and state they how were assessed.
61 State whether the model as a whole was able to predict (or not) the dependent variable. Report the appropriate statistics.
significant with age (t= -3.892, p < .01) accounting for a higher contribution to the model than height (t = -2.595, p < .05). Weight did not explain any significant variation in sleep index. The final predictive equation was:
Sleep Index = 70.205 -.148(Age) + .109(Weight) –2.303(Height).
Age. The negative slope for age (-.148) as a predictor of sleep index indicated there was about a .148 decrease in sleep index for each one-point increase in age. In other words, sleep index tends to decrease as age increases. The squared semi-partial coefficient (sr2) 62 that estimated how much variance in sleep index was uniquely predictable from age was .03, indicating that 3% of the variance in sleep index is uniquely accounted for by age, when weight and height are controlled.
Height. The negative slope for height (-2.303) as a predictor of sleep index indicated there was a 2.303 decrease in sleep index for each additional one-unit increase in height, controlling for age and weight. In other words, sleep index tends to decrease as height increases. The squared semi-partial coefficient (sr2) that estimated how much variance in sleep index was uniquely predictable from height was .04, indicating that 4% of the variance in sleep is uniquely accounted for by height, when age and weight are controlled. The following Table depicts the regression summary table.
Table X
62 Derived from the SPSS output.
Regression Analysis Summary for Predictor Variables
|
Variable |
Β63 |
SE Β |
β64 |
t65 |
p66 |
B 95%67 Bootstrap CI |
|
Age |
-.148 |
0.054 |
-.393 |
-3.892 |
<. 01 |
[-.262, -.025] |
|
Weight |
.109 |
3.770 |
-.038 |
0.371 |
.712 |
[-.008, .245] |
|
Height |
-2.303 |
.888 |
-.268 |
-2.595 |
.011 |
[-.442, -.081] |
Note. N= 204.
Analysis summary. The purpose of this study was to examine the efficacy of age, weight, and height in predicting sleep index. I used standard multiple linear regression to examine the ability of age, weight, and height to predict the value of sleep index. Assumptions surrounding multiple regression were assessed with no serious violations noted. The model as a whole was able to significantly predict sleep index, F(3, 200) = 4.778, p < .003, R2 = .067. Both age and height provide useful predictive information about sleep index. The conclusion from this analysis is that age and height are significantly associated with sleep index, even when weight is controlled (e.g. held constant).
Theoretical conversation on findings. 68Describe in what ways findings confirm, disconfirm, or extend knowledge of the theoretical framework and relationship(s) among variables by comparing the findings with other peer-reviewed studies69 from the literature review that includes studies addressed during the proposal stage and new studies since writing the proposal. 70Ties findings or disputes findings to the existing literature on effective business
63
Β values are to be used in the regression equation. These are the unstandardized coefficients in the SPSS output.
64 The beta weights identify which variables contribute more to the model. These are the standardized coefficients in the SPSS output.
65 The test statistic for the hypothesis test for the slope (Β); derived from the SPSS output; used to evaluate the significance of the Β weights, where p ≤ .05 is significant.
66 The test statistic for the hypothesis test for the slope (Β); derived from the SPSS output; used to evaluate the significance of the Β weights, where p ≤ .05 is significant.
67 The 95% Bootstrap confidence intervals are produced when the bootstrapping procedure is selected in the SPSS regression process. See regression video tutorial located at:
https://www.youtube.com/watch?v=1ItFMKlPG5k
68 Rubric item 3.2g
69 This rubric requirement substantiates the requirement to critically analyze, synthesize and “report” the results of the literature (studies) pertaining to the theory and variables (see rubric component 1.14, Review of the Professional and Academic Literature).
70 Rubric item 3.2h
practice. Analyzes and interpret the findings in the context of the theoretical framework, as appropriate. 71Ensures interpretations do not exceed the data, findings, and scope.
3.3 – Presentation of Findings (Qualitative)
There is a common misconception about Section 3. Reporting the results of the study findings is more complicated than it first appears to be. This is because the findings
must be related back to the body of knowledge as well as the conceptual framework. It is not a matter of telling the reader who-said-what-and-when, one must present an in-depth scholarly discussion of how the study findings contribute to the field.
Do not be misled or fail to understand that reporting the findings is not about listing the answers to the interview questions. The answers to the interview questions are your evidence, not the answer to the research question. Moreover, one should never list the interview questions in the presentation of findings.
Remember that the rubric asks about the research question, not the interview questions.
The research question is the overarching question that your study answers.
Also, remember that you are presenting your findings as themes
—major, minor, unexpected, and/or serendipitous that are a result of your data—answers to interview questions, document review, journaling, observation notes, focus group answers, etc. Also, remember that it is a good practice when using a qualitative data analysis software program to include at least one table per theme from NVivo, Atlasti, Ethnograph, or others that illustrates the frequencies.
Finally, when appropriate, remember to integrate member checking.
To sum up: Present the theme, present the evidence from the findings that support the theme (including tables), then support both from the body of knowledge/conceptual framework.
3.4 – Application to Professional Practice
Discuss how business leaders can apply the findings to aid in solving the specific business problem. Do not repeat literature review; rather focus on application. Often researchers can use this heading to help gain access by offering potentially participating company leaders a summary of the findings including suggestions for professional practice.
3.5 – Implications for Social Change
Now that you have analyzed and discussed the findings, suggest potential implications in terms of tangible improvements for individuals, communities, organizations, institutions, cultures, or societies as the findings could catalyze beneficial social change/behaviors.
71 Rubric item 3.2i
3.6 – Recommendations for Action
This is where you can create a win-win for companies and individuals participating in your study. The rubric requires the following: (a) that you ensure the recommendations flow logically from the conclusions and contain steps to useful action, (b) that you state who needs to pay attention to the results (this can help you with a win-win to discuss when gaining access for the study), and (c) that you indicate how the results might be disseminated via literature, conferences, training, etc.
3.7 – Recommendations for Further Research
Discuss areas for future research. A starting point is to identify how the limitations (weaknesses) identified in Heading 1.12, Assumptions, Limitations, Delimitations, can be improved upon in future studies. Follow up this conversation by identifying other research possibilities illuminated while conducting the study. Do not repeat literature; rather provide future researchers (e.g., other DBA students) with potential research agenda for furthering the scholarly conversation pertaining to the business problem.
This is a good section to discuss serendipitous results, unanswered new questions that arose, and a finding that does not seem to align with a theory or conceptual model warranting a recommendation for further research. Often this section can lead to postdoc research.
3.8 – Reflections
Per the rubric, this short heading includes a reflection on the researcher’s experience within the DBA Doctoral Study process in which the researcher discusses possible personal biases or preconceived ideas and values, the possible effects of the researcher on the participants or the situation, and her/his changes in thinking after completing the study.
3.9 – Conclusion
Per the rubric, students should close with a strong concluding statement making the take- home message clear to the reader. This should be a conclusion and not a summary.
3.10 – Appendices/Table of Contents
Ensure all appendices appear in the order they are referenced in the proposal/doctoral
study.
APPENDIX A: WALDEN UNIVERSITY DOCTOR OF BUSINESS ADMINISTRATION PROGRAM VIDEO TITLES AND URL ADDRESSES
|
Title |
URL Address |
||
|
1 |
Walden DBA Rubric and Handbook Video Tutorial |
||
|
2 |
Walden DBA Problem Statement Tutorial |
||
|
3 |
Walden DBA Purpose Statement Tutorial |
||
|
4 |
Walden DBA Theoretical/Conceptual Framework |
||
|
5 |
Scales of Measurement |
||
|
6 |
DDBA Week One Application |
||
|
7 |
DDBA 8438 Week Two Application Video – Part 1 |
||
|
8 |
Week Two Application Video – Part 2 |
||
|
9 |
Part 1: Independent Samples T – Test |
||
|
10 |
Part 2: Independent Samples T – Test |
||
|
11 |
Part 1: Week Five One-way ANOVA |
||
|
12 |
Part 2: Week Five One-way ANOVA |
||
|
13 |
Walden University Doctor of Business Administration Multiple Linear Regression – Part 1 |
||
|
14 |
Walden University Doctor of Business Administration Multiple Linear Regression – Part 2 |
Note: Titles in green are used in DDBA 8438 but can be applicable in the research process.
APPENDIX B: QUANTITATIVE RESEARCH PRIMER: PROBLEM STATEMENT, PURPOSE STATEMENT, RESEARCH QUESTION(S), AND HYPOTHESES
Doctor of Business Administration
Quantitative Research Primer: Problem Statement, Purpose Statement, Research Question, and Hypotheses
Prepared by the DBA Methodology Team: June 2014
DBA doctoral studies require the highest level of rigor and scholarship. One focus of rigor and scholarship is the number of predictor or independent variables72 examined in quantitative doc studies. Nonexperimental research (i.e. correlation73, quasi- experimental74, etc.) requires the use of at least two independent or predictor variables. This is due to the third variable problem. A third variable, also known as a confounding or mediator variable, can confound the relationship between the independent and dependent variable. This compounding effect can lead the researcher to incorrectly interpret the results, leading to an incorrect rejection of the null hypothesis (Type I error).
As such, all DBA quantitative studies require the examination of at least two predictor (correlation studies), or independent (i.e., quasi-experimental, causal comparative, etc. studies) variables. This affects the statistical analysis, as simple bivariate correlations (correlation designs) or one-way ANOVAs cannot be used as inferential statistical tests. Other statistical procedures, such as multiple regression analyses, must be used for correlation studies. Quasi-experimental/causal comparative designs must employ statistical analyses (i.e. factorial ANOVAs), as a minimum capable of examining more than one independent variable. Please be sure to discuss this with your chair!
Below are hypothetical examples of correlation and quasi-experimental research scenarios, which include the Problem Statement, Purpose Statement, Research Question, and Hypotheses. These examples depict two predictor (correlation studies)/independent (quasi-experimental) variables, which are (a) employee job satisfaction and (b) employee motivation. The dependent variable is employee turnover intentions. It may be helpful to use this model as a script and fill in the specifics as they apply to your study. The red underlined text is what you will need to change for your specific study. Footnotes (in red) are included to identify the required rubric elements.
Again, map to the rubric in this component and all components of your doctoral study. The rubric criteria are the basis for judging the quality of your study. Notice how each of the six rubric elements is included in the purpose statement and there is no superfluous information.
Please review the Problem Statement video tutorial at:
http://youtu.be/IYWzCYyrgpo to aid you in preparing the Problem Statement.
Please review the Purpose statement video tutorial at:
http://youtu.be/pLP4r0mfT9A to aid you in preparing the Purpose Statement.
72 Click the hyperlink to be taken to additional information. 73 Click the hyperlink to be taken to additional information. 74 Click the hyperlink to be taken to additional information.
Hypothetical Example (Correlation Design) Problem Statement
Organizations place great emphasis on retention because of the strategic value of intellectual capital and the costs of replacing valued employees (cite)75. Research in this domain is potentially valuable because turnover costs U.S. businesses billions of dollars per year (cite), and practices that promote retention can save even small companies millions of dollars annually (cite)76. The general business problem is that turnover intention has been shown to be among the best predictors of turnover (cite)77. The specific business problem is that some microelectronic business owners do not understand the relationship between job satisfaction, motivation, and employee turnover intentions78.
Purpose Statement
The purpose of this quantitative79 correlation80 study is to examine the relationship between employee job satisfaction, employee motivation, and employee turnover intentions. The independent variables are employee job satisfaction and employee motivation81. The dependent variable is employee turnover intention82. The targeted population will consist of mid-level employees of microelectronic companies83 located in the southeast United States. The implications for positive social change include the potential to better understand the correlates of employee turnover, thus increasing propensity for sustainability of the microelectronic industry 84.
Research Question
What is the relationship between employee job satisfaction, employee motivation, and employee turnover intentions?
Hypotheses
Null Hypothesis (H0): There is no statistically significant relationship between employee job satisfaction, employee motivation, and employee turnover intentions.
75 Hook
76 Anchor
77 General business problem 78 Specific business problem 79 Method
80 Design
81 Independent variables
82 Dependent variable
83 Targeted population
84 Social change statement
Alternative Hypothesis (H1): There is a statistically significant relationship between employee job satisfaction, employee motivation, and employee turnover intentions.
Hypothetical Example (Causal-Comparative Design)
Problem Statement
Organizations place great emphasis on retention because of the strategic value of intellectual capital and the costs of replacing valued employees (cite). Research in this domain is potentially valuable because turnover costs U.S. businesses billions of dollars per year (cite), and practices that promote retention can save even small companies millions of dollars annually (cite). The general business problem is that turnover intention have been shown to have a significant impact on employee turnover (cite). The specific business problem is that some micro-electronic business owners do not understand the impact of job satisfaction, motivation, on employee turnover intentions.
Purpose Statement
The purpose of this quantitative85 correlation86 study is to examine the impact of employee job satisfaction and employee motivation on employee turnover intentions. The independent variables are employee job satisfaction and employee motivation87. The dependent variable is employee turnover intention88. The targeted population will consist of midlevel employees of microelectronic companies89 located in the southeast United States. The implications for positive social change include the potential to provide a better understanding of the correlates of employee turnover, thus increasing propensity for sustainability of the microelectronic industry90.
Research Question
What is the impact of employee job satisfaction and employee motivation on
employee turnover intentions?
Hypotheses
Null Hypothesis (H0): Employee job satisfaction and employee motivation have no significant impact on employee turnover intentions.
Alternative Hypothesis (H1): Employee job satisfaction and employee motivation have a statistically significant impact on employee turnover intentions.
85 Method
86 Design
87 Independent variables
88 Dependent variable
89 Targeted population
90 Social change statement
Research Tips
· Correlation designs use the term relationship
· Causal comparative designs use the terms impact or influence
· Variables are presented in temporal order; that is the independent variables are presented first, followed by the dependent variable
· The word
and
(see bold text in Purpose Statement) separates the predictor variables from the dependent variable in correlation designs
· The word
on
(see bold text in Purpose Statement) separates the independent variables from the dependent variable in experimental/quasi-experimental designs
· The null and alternative hypotheses are almost mirror images of the research question
· The null hypothesis is the hypothesis of no difference; suggesting there will not be a significant result
· The alternative hypothesis is the hypothesis of difference; suggesting there will be a significant result
APPENDIX C: MAJOR QUANTITATIVE DESIGNS
Research design91 is the blueprint that enables the investigator to develop solutions to research problems and guides the researcher in the various stages of the research (Frankfort- Nachmias & Nachmias, 2008). The research design aids the researcher in structuring, analyzing, and interpreting the data (Frankfort-Nachmias & Nachmias, 2008). DeForge (2010) described research design as a plan for guiding researchers in addressing research problems and answering research questions.
Quantitative Methodology and Associated Designs
|
Design |
Characteristics |
|
Experimental |
· Assess causal (cause and effect) relationships between an independent and dependent variable · Defining feature: random assignment to group condition · Manipulation of the independent variable · Strongest in terms of internal validity; greatest confidence in causal inferences · Requires power analysis to determine appropriate sample size · Analyses can include, but are not limited to, (ANOVA, ANCOVA, MANOVA, etc.) |
|
Quasi-experimental |
· Assess causal relationships between an independent and dependent variable. · Defining feature: lack of random assignment to group condition · Manipulation of the independent variable · Weakened ability to make causal inferences · Requires power analysis to determine appropriate sample size |
|
Correlation |
· Assess relationships between independent and dependent variables · Defining feature: does not imply causality · Requires power analysis to determine appropriate sample size · Analyses can include, but are not limited to, (a) multiple regression, (b) logistic regression, and (c) discriminant analysis |
Note. Correlation designs are the most common seen in DBA studies.
91 Review the Research Methods Knowledge Base at:
http://www.socialresearchmethods.net/kb/design.php for more information pertaining to research design.
APPENDIX D: SAMPLING TYPOLOGIES92
|
Non Probabilistic Sampling (Non-Random) |
|
|
Availability (Convenience) |
A nonprobabilistic sampling procedure in which units are selected from the target population based on their availability or convenience of the researcher. |
|
Purposive |
A nonprobabilistic sampling procedure in which units are selected from the target population based on their fit with the purpose of the study and specific inclusion and exclusion criteria. |
|
Quota |
A nonprobabilistic sampling procedure in which the population is divided into mutually exclusive subcategories. Interviewers or other data collectors solicit participation in the study from members of the subcategories until a target number of elements to be sampled from the subcategories have been met. |
|
Snowball |
A nonprobabilistic sampling procedure in which elements are selected from the target population with assistance of
|
|
Probabilistic Sampling (Random) |
|
|
Simple Random Sampling |
A probability sampling procedure that gives every unit in the target population, and each possible sample of a given size, an equal chance of being selected. |
|
Stratified Sampling |
A probability sampling procedure in which the target population is first separated into mutually exclusive, homogeneous segments (strata) and then a simple random sample is selected from each segment (stratum) |
|
Systematic Sampling |
A probability sampling procedure in which a random selection is made of the first unit for the sample, and then subsequent units are selected used a fixed or systematic interval until the desired sample size is reached. |
|
Cluster Sampling |
A nonprobabilistic sampling procedure in which units of the target population are randomly selected in natural
|
92 Adapted from Daniel, J. (2012). Sampling essentials: Practical guidelines for making sampling choices. Los Angeles, CA: SAGE.
APPENDIX E: SAMPLE POWER ANALYSIS
G*Power is a statistical software package quantiative researhcers use to conduct an apriori sample size analysis (Faul, Erdfelder, Buchner, & Lang, 2009)93. A power analysis, using G*Power version 3.1.9 software, was conducted to determine the appropriate sample size for the study. An a priori power analysis, assuming a medium effect size (f 2= .15), α = .05, and 2 predictor variables, identified that a minumum sample size of 68 participants is required to achieve a power of .80. Increasing the sample size to 146 will increase power to .99. Therefore, the researcher will seek between 68 and 146 participants for the study (Figure 1).
Figure 1. Power as a function of sample size.
The use of a medium effect size (f2 = .15) is apporiate for this proposed study. The medium effect size was based on the analysis of X articles where (identify your variable) was the outcome measurement.
93 Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41, 1149-1160. doi:10.3758/brm.41.4.1149
APPENDIX F: SAMPLE QUANTITATIVE LITERATURE REVIEW OUTLINE
Introduction
Provide an introduction containing a discussion of the content of the literature review (including the percentages of total references that are peer reviewed, and the percentage of total references that are published within 5 years of the expected year of CAO approval). Also discuss the organization of the review, and the strategy for searching the literature. The review of the literature will follow in appropriately formatted APA headings. Do not present the literature review in annotated bibliography format (i.e., presenting one study after another.) Rather, provide a critical analysis and synthesis of the literature.
Transformational Leadership Theory94
Introduce the theory. You can present the information provided in Heading 1-4, Theoretical/Conceptual Framework. However, this heading should be expanded, providing the reader with more depth pertaining to the theory. Descriptive information should be included here. The critical analysis and synthesis of the literature follows below.
Main point one.95 Conducting a good literature review involves the reader identifying and separating literature by similar ideas, themes, topics etc. The similar ideas can be presented using appropriate APA L2 headings; use subordinate headings as appropriate. You are not to simply regurgitate the material you have read. The literature presented in each main topic heading must be a critical analysis and synthesis of the empirical observations (research studies) you have reviewed. Critical analysis and synthesis of the literature grounded in your theoretical framework will enable you to meet the requirements in the Presentation of Findings heading.
See the Doctoral Study Rubric for more information.
Main point two. The same information presented in main point one applies for main point two.
Main point three. The same information presented in main point three applies for Main Point C.
Rival Theories/Opponents of the Theoretical/Conceptual Framework
There are always rival theories, that is, rival/alternate lenses for examining a phenomenon. A good literature review comprises an inquiry into the major rival theories. Provide a very brief overview of two to three rival theories and then shift the discussion to one major rival theory. Questions you may consider addressing in this component are:
· What are the strengths and limitations of this theory?
94 APA Level 2 heading.
95 APA Level 3 heading.
· Why did you not choose to examine your problem through this theoretical lens?
· What do opponents (other authorities) in the field identify as the limitations or weakness of this rival theory?
Measurement
A good literature review must address the measurement instruments pertaining to the variables or constructs underlying the theoretical framework. Often times, there is more than one measurement instrument available to measure the same variables or constructs. A review of the measurement instruments will facilitate your identifying appropriate instruments for your theoretical variables/constructs. Addressing, validity and reliability properties of the various instruments is a vital component of this heading. In addition, discussing the various populations for which the instruments were used is vital to addressing the requirements for this component.
For example, a study grounded in transformational leadership theory will undoubtedly uncover a plethora of literature where previous researchers employed the Multifaceted Leadership Questionnaire (MLQ) to measure the transformational leadership constructs. In many cases, you will identify more than one instrument purporting to measure the same variables or constructs. A critical analysis and synthesis will enable you to select the most appropriate instrument to measure the constructs underlying your study. Address the strengths and weaknesses of each instrument. The results of your critical analysis and synthesis will justify the selection of the instrument you propose to use for your study. Remember, many decisions you make in your study (i.e. selecting instruments) are grounded in the extant literature; these decisions are not to be arbitrarily made.
Independent Variable A (variable not underlying the theory)
The study may contain
additional variables96 outside the umbrella of the theoretical framework. Therefore, discussions of these variables are warranted. An informed decision must be made to include variables in a study. As such, variables or constructs examined in a quantitative study are derived from extant literature; they are not arbitrarily selected for inclusion in a study. For example, assume job satisfaction is an independent or predictor variable in your study. If so, this variable must be substantiated from the literature. Therefore, you are to conduct a critical analysis and synthesis pertaining to the literature. This critical analysis and synthesis must support evidence of a relationship between each potential independent variable and the dependent variable in your study, or a variable closely related to the dependent variable in your study. In addition, there might be inconclusive evidence and you are to provide the support for including the independent or predictor variable in your study. Include APA sub headings for each independent and dependent variable.
96 It is important to understand you are not addressing variables underlying the theoretical framework. Here you are addressing any “additional” variables included in the study that are not aligned with the theoretical framework. In essence, there will be justification for every variable measured in the study.
Independent Variable B (variable not underlying the theory)
The same information in Independent Variable A applies for each independent or predictor variable in the study.
Independent Variable C (variable not underlying the theory)
The same information in Independent Variable A applies for each independent or predictor variable in the study.
Dependent Variable
The dependent variable must also be addressed in the literature review. This is normally the problematic variable in the study. Remember you are viewing this problematic variable through the identified theoretical lens. Again, this component is to include a critical analysis and synthesis of the empirical literature pertaining to the dependent variable.
Methodologies
Address they various methodologies (quantitative, qualitative, mixed-method) in the literature through which previous researchers have addressed the dependent variable. A literature review must not solely address the methodology that matches to intended studies design.
Remember, the literature review is to be an exhaustive review of the literature pertaining to a topic.
Summary
End with a transition heading that contains a summary of key points and provides an overview introducing Section 2 and Section 3. Do not include any new information in the summary.
APPENDIX G: SAMPLE APA TABLES
Properly formatted APA tables are critical media for presenting descriptive and inferential statistics results. This appendix provides templates that serve as models for what is required for various types of statistical analyses. The examples are based on guidelines contained in the sixth edition of the Publication Manual of the American Psychological Association97. You can simply cut and paste these tables into the appropriate section of your proposal/doctoral study.98
97 American Psychological Association. (2010). Publication manual of the American Psychological Association. (6th ed.). Washington, DC: Author.
98 Tables will need to be adjusted for your particular analyses. For example, you may need to add/delete additional rows/columns as appropriate.
Basic One Group Descriptive Statistics Table for Quantitative Variables (Example Depicting 3 Variables)
Table X
The Table Title Goes Here and Is Italicized (N = XX)
|
Variable |
n |
M |
M 95% Bootstrap CI |
SD |
SD 95% Bootstrap CI |
|
Variable 1 |
23 |
2.4 |
[1.85, 2.99] |
.24 |
[.11, .64] |
|
Variable 2 |
34 |
2.8 |
[1.56, 3.94] |
.34 |
[.22, .53] |
|
Variable 3 |
34 |
2.9 |
[2.05, 3.35] |
.28 |
[.25, .44] |
Basic Descriptive Statistics Table for Qualitative
(Example Depicting 3 Variables)
Table X
The Table Title Goes Here and Is Italicized (N = XX)
|
Variable |
n |
% |
|
Variable 1 |
32 |
32 |
|
Variable 2 |
34 |
34 |
|
Variable 3 |
34 |
34 |
|
Total |
100 |
100 |
Simultaneous Regression Table (2 Variables)
Table X
The Table Title Goes Here and Is Italicized (N = XX)
|
Variable |
B |
SE Β |
β |
t |
p |
B 95% Bootstrap CI |
|
Variable 1 |
0.00 |
0.00 |
.00 |
.00 |
.00 |
[00.00, 00.00] |
|
Variable 2 |
0.00 |
0.00 |
.00 |
.00 |
.00 |
[00.00, 00.00] |
Note. Type any notes here.
Hierarchical Regression Table (2 Steps)
Table X
The Table Title Goes Here and Is Italicized (N
= XX)
|
Variable |
B |
SE Β |
β |
R2 |
∆R2 |
|
Step 1 |
|||||
|
Variable 1 |
0.00 |
0.00 |
.00 |
.00 |
.00 |
|
Variable 2 |
0.00 |
0.00 |
.00 |
.00 |
.00 |
|
Step 2 |
0.00 |
0.00 |
.00 |
.00 |
.00 |
|
Variable 1 |
0.00 |
0.00 |
.00 |
.00 |
.00 |
|
Variable 2 |
0.00 |
0.00 |
.00 |
.00 |
.00 |
|
Variable 3 |
0.00 |
0.00 |
.00 |
.00 |
.00 |
Note. Type any notes here.
The table above reflects a “Play it Safe99” hierarchical regression table with 2 variables in step one and 3 variables in step 2. You will need to make modifications according to your specific model.
99 The “Play It safe” table is comprehensive and thus would be appropriate if the writer wanted to be as thorough as possible and was not concerned with brevity.
Two-Way ANOVA Table
Table X
The Table Title Goes Here and Is Italicized (N = XX)
|
Source |
df |
F |
η |
p |
|
Between subjects |
||||
|
Variable 1 (A) |
XX |
0.00 |
0.00 |
.00 |
|
Variable 2 (B) |
XX |
0.00 |
0.00 |
.00 |
|
A x B |
XX |
.00 |
||
|
B within-group error |
XX |
.00 |
||
|
Within-subjects |
||||
|
XX |
0.00 |
0.00 |
.00 |
|
|
XX |
0.00 |
0.00 |
.00 |
|
|
XX |
0.00 |
0.00 |
.00 |
Note. Type any notes here.
Correlation Table
Table X
The Table Title Goes Here and Is Italicized (N = XX)
|
Subscale |
1 |
2 |
3 |
4 |
|
Students (n = XX) |
||||
|
1. Variable 1 |
1.0 |
.00 |
.00 |
.00 |
|
2. Variable 2 |
.00 |
1.0 |
.00 |
.00 |
|
3. Variable 3 |
.00 |
.00 |
1.0 |
.00 |
|
4. Variable 4 |
.00 |
.00 |
.00 |
1.0 |
|
Older adults (n = XX) |
||||
|
1. Variable 1 |
1.0 |
.00 |
.00 |
.00 |
|
2. Variable 2 |
.00 |
1.0 |
.00 |
.00 |
|
3. Variable 3 |
.00 |
.00 |
1.0 |
.00 |
|
4. Variable 4 |
.00 |
.00 |
.00 |
1.0 |
Note. Type any notes here.
Logistic Regression Table (6 Predictors)
Table X
The Table Title Goes Here and Is Italicized (N = XX)
|
B |
S.E |
Wald |
df |
p |
Odds Ratio |
95% CI for Odds Ratio |
|
|
Lower |
Upper |
||||||
|
Variable 1 |
|||||||
|
Variable 2 |
|||||||
|
Variable 3 |
|||||||
|
Variable 4 |
|||||||
|
Variable 5 |
|||||||
|
Variable 6 |
|||||||
|
Constant |
APPENDIX H: SAMPLE INTERVIEW PROTOCOL
|
Interview Protocol |
||
|
What you will do |
What you will say—script |
|
|
Introduce the interview and set the stage—often over a meal or coffee |
Script XXXXXXXXXXXXXXXXXXXXX |
|
|
· Watch for non-verbal queues · Paraphrase as needed · Ask follow-up probing questions to get more in depth |
1. Interview question |
|
|
2. Interview question |
||
|
3. Interview question |
||
|
4. Interview question |
||
|
5. Interview question |
||
|
6. Interview question |
||
|
7. Interview question |
||
|
8. Interview question |
||
|
9. Interview question |
||
|
10. Last interview question should be a wrap up question such as: What additional experiences have you had…? |
||
|
Wrap up interview thanking participant |
Script XXXXXXXXXXXXXXXXXXXXX |
|
|
Schedule follow-up member checking interview |
Script XXXXXXXXXXXXXXXXXXXXX |
|
|
Follow–up Member Checking Interview
Graphic by Gene E. Fusch, Ph.D. not needed in proposal or study—just a visual reminder during proposal stage when creating interview protocol. |
||
|
Introduce follow-up interview and set the stage |
Script XXXXXXXXXXXXXXXXXXXXX |
|
Share a copy of the succinct synthesis for each individual question Bring in probing questions related to other information that you may have found— note the information must be related so that you are probing and adhering to the IRB approval. Walk through each question, read the interpretation and ask: Did I miss anything? Or, What would you like to add? |
Script XXXXXXXXXXXXXXXXXXXXX |
|
1. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
|
|
2. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
|
|
3. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
|
|
4. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
|
|
5. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
|
|
6. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
|
|
7. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
|
|
8. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
|
|
9. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
|
|
10. Question and succinct synthesis of the interpretation—perhaps one paragraph or as needed |
BIBLIOGRAPHY: SUGGESTED READINGS LISTS
Please note that these references are an amalgamation of input and suggestions. The purpose is to provide DBA students with additional reading sources to prepare for the doctoral study. Students are responsible for correctly referencing any sources per the APA publication manual (6th ed.). The following Readings lists are in order by the following topics.
· Assumptions, Limitations, and Delimitations
· Case Study Sources
· Case Study Seminal Books
· Data Saturation and Data Collection Sources
· Ethical Considerations/IRB
· Ethnography Sources
· Focus Groups
· Interview Protocol Sources
· Interviews Sources
· Journaling Sources
· Member Checking Sources
· Mixed Methods Research
· Notetaking and Fieldwork
· Phenomenological Sources
· Pilot Studies
· Qualitative Research Foundation
· Qualitative and Quantitative Sources
· Reliability, Validity, Transferability, and Generalizability Sources
· Sampling and Incentives
· Sense-making
· Qualitative Software Analysis Sources
· Triangulation Sources
Assumptions, Limitations, and Delimitations
Assumptions
Abrams, L. S. (2010). Sampling hard to reach populations in qualitative research: The case of incarcerated youth. Qualitative Social Work, 9, 536-550. doi:10.1077/1473325010367821
Applebaum, M. (2012). Phenomenological psychological research as science. Journal of Phenomenological Psychology, 43(1), 36-72. doi:10.1163/156916212×632952
Arghode, V. (2012). Qualitative and quantitative research: Paradigmatic differences.
Global Education Journal, 2012(4), 155-163. Retrieved from http://franklinpublishing.net/globaleducation.html
Bansal, P., & Corley, K. (2011). The coming of age for qualitative research: Embracing the diversity of qualitative methods. Academy of Management Journal, 54, 233- 237. doi:10.5465/AMJ.2011.60262792
Bunniss, S., & Kelly, D. R. (2010). Research paradigms in medical education research.
Qualitative Research in Medical Education, 44, 358-366. doi:10.1111/j.1365- 2923.2009.03611.x
Castellan, C. M. (2010). Quantitative and qualitative research: A view for clarity.
International Journal of Education, 2(2), 1-14. Retrieved from http:// www.macrothink.org/ije
Cunliffe, A. L. (2011). Crafting qualitative research: Morgan and Smircich 30 years on.
Organizational Research Methods, 14, 647-673. doi:10.1177/1094428110373658
Diefenbach, T. (2009). Are case studies more than sophisticated storytelling?
Methodological problems of qualitative empirical research mainly based on semistructured interviews. Quality and Quantity, 43, 875-894. doi:10.1007/s11135-008-9164-0
Draper, A. A., & Swift, J. A. (2011). Qualitative research in nutrition and dietetics: Data collection issues. Journal of Human Nutrition & Dietetics, 24(1), 3-12. doi:10.1111/j.1365-277X.2010.01117.x
Ellis, T. J., & Levy, Y. (2009). Towards a guide for novice researchers on research methodology: Review and proposed methods.
Issues in Informing Science & Information Technology, 323-337. Retrieved from http://informingscience.org/
Fan, X. (2013). “The test is reliable”; “The test is valid”: Language use, unconscious assumptions, and education research practice. The Asia-Pacific Education Researcher, 22, 217-218. doi:10.1007/s40299-012-0036-y
Gallop, S. (2011). Viewpoint: Assumptions. Journal of Behavioral Optometry, 22, 158-
160. Retrieved from http://www.oepf.org/journals
Grant, A. (2014). Troubling ‘lived experience’: A post-structural critique of mental health nursing qualitative research assumptions. Journal of Psychiatric and Mental Health Nursing, 21(6), 544-549 doi:10.1111/jpm.12113
Hodges, N. (2011). Qualitative research: A discussion of frequently articulated qualms (FAQs). Family and Consumer Sciences Research Journal, 40, 90-92. doi:10.1111/j.1552-3934.2011.02091.x
Lips-Wiersma, M., & Mills, A. J. (2013) Understanding the basic assumptions about human nature in workplace spirituality: Beyond the critical versus positive divide. Journal of Management Inquiry, 23(2), 148-161. doi:10.1177/1056492613501227
Kirkwood, A., & Price, L. (2013). Examining some assumptions and limitations of research on the effects of emerging technologies for teaching and learning in higher education. British Journal of Educational Technology, 44, 536-543. doi:10.1111/bjet.12049
Kouchaki, M., Okhuysen, G. A., Waller, M. J., & Tajeddin, G. (2012). The treatment of the relationship between croups and their environments: A review and critical examination of common assumptions in research. Group & Organization Management, 37, 171-203. doi:10.1177/1059601112443850
Marshall, C., & Rossman, G. B. (2016). Designing qualitative research (6th ed.).
Thousand Oaks, CA: Sage.
Martin, K., & Parmar, B. (2012). Assumptions in decision-making scholarship: Implications for business ethics research. Journal of Business Ethics, 105, 289- 306. doi:10.1007/s10551-011-0965-z
Pratt, M. G. (2009). For the lack of a boilerplate: Tips on writing up (and reviewing) qualitative research. Academy of Management Journal, 52, 856-862. doi:10.5465/AMJ.2009.44632557
Rocha Pereira, H. (2012). Rigour in phenomenological research: Reflections of a novice nurse researcher. Nurse Researcher, 19(3), 16-19. Retrieved from http://nurse researcher.rcnpublishing.co.uk
Wahyuni, D. (2012). The research design maze: understanding paradigms, cases, methods and methodologies. Journal of Applied Management Accounting Research, 10(1), 69-80. Retrieved from http://maaw.info/JAMAR.htm
Limitations
Aastrup, J., & Halldorsson, A. (2013). Quality criteria for qualitative inquiries in logistics. European Journal of Operational Research, 144, 321-332. doi:10.1016/S0377- 2217(02)00397-1
Anderson, C. (2010). Presenting and evaluating qualitative research. American Journal of Pharmaceutical Education, 74(8), 1-7. doi:10.5688/aj7408141
Brutus, S., Aguinis, H., & Wassmer, U. (2012). Self-reported limitations and future directions in scholarly reports analysis and recommendations. Journal of Management, 39(1) 48-75. doi:10.1177/0149206312455245
Brutus, S., Gill, H., & Duniewicz, K. (2010). State of science in industrial and organizational psychology: A review of self-reported limitations. Personnel Psychology, 63, 907-936. doi:10.1111/j.1744-6570.2010.01192.x
Bunniss, S., & Kelly, D. R. (2010). Research paradigms in medical education research.
Qualitative Research in Medical Education, 44, 358-366. doi:10.1111/j.1365- 2923.2009.03611.x
Castellan, C. M. (2010). Quantitative and qualitative research: A view for clarity.
International Journal of Education, 2(2), 1-14. Retrieved from http:// www.macrothink.org/ije
Connelly, L. M. (2013). Limitation section. Medsurg Nursing, 22, 325-325, 336.
Retrieved from http://www.medsurgnursing.net/cgi- bin/WebObjects/MSNJournal.woa
Cunliffe, A. L. (2011). Crafting qualitative research: Morgan and Smircich 30 years on.
Organizational Research Methods, 14, 647-673. doi:10.1177/1094428110373658
Diefenbach, T. (2009). Are case studies more than sophisticated storytelling?
Methodological problems of qualitative empirical research mainly based on semistructured interviews. Quality and Quantity, 43, 875-894. doi:10.1007/s11135-008-9164-0
Draper, A. A., & Swift, J. A. (2011). Qualitative research in nutrition and dietetics: Data collection issues. Journal of Human Nutrition & Dietetics, 24(1), 3-12. doi:10.1111/j.1365-277X.2010.01117.x
Ellis, T. J., & Levy, Y. (2009). Towards a guide for novice researchers on research methodology: Review and proposed methods.
Issues in Informing Science & Information Technology, 323-337. Retrieved from http://informingscience.org/
Fan, X. (2013). “The test is reliable”; “The test is valid”: Language use, unconscious assumptions, and education research practice. The Asia-Pacific Education Researcher, 22, 217-218. doi:10.1007/s40299-012-0036-y
Finfgeld-Connett, D. (2010). Generalizability and transferability of meta-synthesis research findings. Journal of Advanced Nursing, 66, 246-254. doi:10.1111/j.1365-2648.2009.05250.x
Gibbs, L., Kealy, M., Willis, K., Green, J., Welch, N., & Daly, J. (2007). What have sampling and data collection got to do with good qualitative research? Australian and New Zealand Journal of Public Health, 31, 540-544. doi:10.1111/j.1753- 6405.2007.00140.x
Hodges, N. (2011). Qualitative research: A discussion of frequently articulated qualms (FAQs). Family and Consumer Sciences Research Journal, 40, 90-92. doi:10.1111/j.1552-3934.2011.02091.x
Houghton, C., Casey, D., Shaw, D., & Murphy, K. (2013). Rigour in qualitative case- study research. Nurse Researcher, 20(4), 12-17. doi:10.7748/nr2013.03.20.4.12.e326
Marshall, C., & Rossman, G. B. (2016). Designing qualitative research (6th ed.).
Thousand Oaks, CA: Sage.
O’Reilly, M., & Parker, N. (2012, May). Unsatisfactory saturation: A critical exploration of the notion of saturated sample sizes in qualitative research. Qualitative Research Journal, 1-8. doi:10.1177/1468794112446106
Polit, D. F., & Beck, C. T. (2010). Generalization in quantitative and qualitative research: Myths and strategies. International Journal of Nursing Studies, 47, 1451-1458. doi:10.1016/j.ijnurstu.2010.06.004
Pratt, M. G. (2009). For the lack of a boilerplate: Tips on writing up (and reviewing) qualitative research. Academy of Management Journal, 52, 856-862. doi:10.5465/AMJ.2009.44632557
Prowse, M., & Camfield, L. (2013). Improving the quality of development assistance: What role for qualitative methods in randomized experiments? Progress in Development Studies, 13(1), 51-61. doi:10.1177/146499341201300104
Rocha Pereira, H. (2012). Rigour in phenomenological research: Reflections of a novice nurse researcher. Nurse Researcher, 19(3), 16-19. Retrieved from http://nurse researcher.rcnpublishing.co.uk
Sabbour, S., Lasi, H., & Tessin, P. (2012). Business intelligence and strategic decision simulation. World Academy of Science, Engineering and Technology, 6, 980-987. Retrieved from http://waset.org/Publications?p=61
Delimitations
Barratt, M., Choi, T. Y., & Li, M. (2011). Qualitative case studies in operations management: Trends, research outcomes, and future research implications. Journal of Operations Management, 29, 329-342. doi:10.1016/j.jom.2010.06.002
Baxter, P., & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report, 13, 544-559. Retrieved from http://www.nova.edu/ssss/QR/QR13-4/baxter
Bunniss, S., & Kelly, D. R. (2010). Research paradigms in medical education research.
Qualitative Research in Medical Education, 44, 358-366. doi:10.1111/j.1365- 2923.2009.03611.x
Castellan, C. M. (2010). Quantitative and qualitative research: A view for clarity.
International Journal of Education, 2(2), 1-14. Retrieved from http:// www.macrothink.org/ije
Cunliffe, A. L. (2011). Crafting qualitative research: Morgan and Smircich 30 years on.
Organizational Research Methods, 14, 647-673. doi:10.1177/1094428110373658
Diefenbach, T. (2009). Are case studies more than sophisticated storytelling?
Methodological problems of qualitative empirical research mainly based on semistructured interviews. Quality and Quantity, 43, 875-894. doi:10.1007/s11135-008-9164-0
Draper, A. A., & Swift, J. A. (2011). Qualitative research in nutrition and dietetics: Data collection issues. Journal of Human Nutrition & Dietetics, 24(1), 3-12. doi:10.1111/j.1365-277X.2010.01117.x
Ellis, T. J., & Levy, Y. (2009). Towards a guide for novice researchers on research methodology: Review and proposed methods.
Issues in Informing Science & Information Technology, 323-337. Retrieved from http://informingscience.org/
Fan, X. (2013). “The test is reliable”; “The test is valid”: Language use, unconscious assumptions, and education research practice. The Asia-Pacific Education Researcher, 22, 217-218. doi:10.1007/s40299-012-0036-y
Marshall, C., & Rossman, G. B. (2016). Designing qualitative research (6th ed.).
Thousand Oaks, CA: Sage.
Hodges, N. (2011). Qualitative research: A discussion of frequently articulated qualms (FAQs). Family and Consumer Sciences Research Journal, 40, 90-92. doi:10.1111/j.1552-3934.2011.02091.x
Nenty, H., & Adedoyin, O. O. (2010). Research orientation and research-related behaviour of graduate education students at University of Botswana.
International Research Journal, 1, 577-585. Retrieved from http://interesjournals.org
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control
it. Annual Review of Psychology, 63, 539-569. doi:10.1146/annurev-psych- 120710-100452
Pratt, M. G. (2009). For the lack of a boilerplate: Tips on writing up (and reviewing) qualitative research. Academy of Management Journal, 52, 856-862. doi:10.5465/AMJ.2009.44632557
Rocha Pereira, H. (2012). Rigour in phenomenological research: Reflections of a novice nurse researcher. Nurse Researcher, 19(3), 16-19. Retrieved from http://nurse researcher.rcnpublishing.co.uk
Scotland, J. (2012). Exploring the philosophical underpinnings of research: Relating ontology and epistemology to the methodology and methods of the scientific, interpretive, and critical research paradigms. English Language Teaching, 5(9), 9-17. doi:10.5539/elt.v5n9p9
Small, M. (2009). How many cases do I need: On science and the logic of case selection in field-based research. Ethnography, 10(1), 5-38. doi:10.1177/1466138108099586
Spitzmüller, J., & Warnke, I. H. (2011). Discourse as a “linguistic object”: Methodical and methodological delimitations. Critical Discourse Studies, 8, 75-94. doi:10.1080/17405904.2011.558680
Case Study Sources
Alfonso, M., Nickelson, L., & Cohen, D. (2012). Farmers’ markets in rural communities: A case study. American Journal of Health Education, 43(3), 143-151. Retrieved from http://www.aahperd.org/aahe/publications/ajhe/
Almutairi, A. F., Gardner, G. E., & McCarthy, A. (2014). Practical guidance for the use of pattern-matching technique in case-study research: A case presentation. Nursing & Health Sciences, 16, 239-244. doi:10.1111/nhs.12096
Amerson, R. (2011). Making a case for the case study method. Journal of Nursing Education, 50, 427-428. doi:10.3928.01484834-20110719-01
Andrade, A. D. (2009). Interpretive research aiming at theory building: Adopting and adapting the case study design. The Qualitative Report, 14(1), 42-60. Retrieved from http://www.nova.edu/ssss/QR/QR14-1/diaz-andrade
Ates, O. (2013). Using case studies for teaching management to computer engineering students. International Journal of Business and Management, 8(5), 72-81. doi:10.5539/ijbm.v8n5p72
Baker, R. G., (2011). The contribution of case study research to knowledge of how to improve the quality of care. British Medical Journal Quality and Safety, 20, 30-35. doi:10.1136/bmjqs.2010.046490
Baxter, P., & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report, 13, 544-559. Retrieved from http://www.nova.edu/ssss/QR/QR13-4/baxter
Beverland, M., & Lindgreen, A. (2010). What makes a good case study? A positivist review of qualitative case research published in Industrial Marketing Management, 1971-2006. Industrial Marketing Management, 39, 56-63. doi:10.1016/j.indmarman.2008.09.005
Boblin, S. L., Ireland, S., Kirkpatrick, H., & Robertson, K. (2013). Using Stakes qualitative case study approach to explore implementation evidence-based practice. Qualitative Health Research, 23, 1267-1275. doi:10.1177/1049732313502128
Breslin, M., & Buchanan, R. (2011). On the case study method of research and teaching in design. Design Issues, 24(1), 36-40. Retrieved from http://www.mitjournals.org
Bucic, T., Robinson, L., & Ramburuth, P. (2010). Effects of leadership style on team learning. Journal of Workplace Learning, 22, 228-248. doi:10.1108/13665621011040680
Butvilas, T., & Zygmantas, J. (2011). An ethnographic case study in educational research. Acta Paedagogica Vilnensia, 27, 33-42. Retrieved from http://www.leidykla.eu/index.php?id=36
Cinneide, B. (2015). The role of effectiveness of case studies: Student performance in case study vs. “theory” examinations. Journal of European Industrial Training, 21(1) 3-13. www.emeraldinsight.com/journal.jeit
Cronin, C. (2014). Using case study research as a rigorous form of inquiry. Nurse Researcher, 21(5), 19-27. doi:10.7748/nr.21.5.19.e1240
Crowe, S., Cresswell, K., Robertson, A., Huby, G., Avery, A., & Sheikh, A. (2011). The case study approach. BMC Medical Research Methodology, 11(1), 1-9. doi:10.1186/1471-2288-11-100
Da Mota Pedrosa, A., Näslund, D., & Jasmand, C. (2012). Logistics case study based research: Towards higher quality. International Journal of Physical Distribution & Logistics Management, 42, 275-295. doi:10.1108/09600031211225963
Dasgupta, M. (2015). Exploring the relevance of case study research. Vision (09722629), 19(2), 147-160. doi:10.1177/0972262915575661
De Massis, A., & Kotlar, J. (2014). The case study method in family business research: Guidelines for qualitative scholarship. Journal of Family Business Strategy, 5(1), 15-29. doi:10.1016/j.jfbs.2014.01.007
Easton, G. (2010). Critical realism in case study research. Industrial Marketing Management, 39(1), 118-128. doi:10.1016/j.indmarman.2008.06.004
Eno, M., & Dammak, A. (2014). Debating the case study dilemma: Controversies and considerations. Veritas: The Academic Journal of St Clements Education Group, 5(3), 1-8. Retrieved from http://stclements.edu/Veritas/VERITAS%20October%202014
Gibbert, M., & Ruigrok, W. (2010). The what and how of case study rigor: Three strategies based on published work. Organizational Research Methods, 13, 710- 737. doi:10.1177/1094428109351319
Harland, T. (2014). Learning about case study methodology to research higher education. Higher Education Research & Development, 1-10. doi:10.1080/07294360.2014.911253
Hietanen, J., Sihvonen, A., Tikkanen, H., & Mattila, P. (2014). Managerial storytelling: How we produce managerial and academic stories in qualitative B2B case study research. Journal of Global Scholars of Marketing, 24. doi:10.1080/21639159.2014.911496
Houghton, C. E., Casey, D., Shaw, D., & Murphy, K. (2010). Ethical challenges in qualitative research: Examples from practice. Nurse Researcher, 18(1), 15-25. Retrieved from http://nurseresearcher.rcnpublishing.co.uk
Hyett, N., Kenny, A., & Dickson-Swift, V. (2014). Methodology or method? A critical review of qualitative case study reports. International Journal of Qualitative, 9. doi:10.3402/qhw.v9.23606
Järvensivu, T., & Törnroos, J. Å. (2010). Case study research with moderate constructionism: Conceptualization and practical illustration. Industrial Marketing Management, 39(1), 100-108. doi:10.1016/j.indmarman.2008.05.005
Ketokivi, M., & Choi, T. (2014). Renaissance of case research as a scientific method.
Journal of Operations Management, 32, 232-240. doi:10.1016/j.jom.2014.03.004
Moll, S. (2012). Navigating political minefields: Partnerships in organizational case study research. Work, 43, 5-12. doi:10.3233/wor-2012-1442
Morse, A. L., & McEvoy, C. D. (2014). Qualitative research in sport management: Case study as a methodological approach. The Qualitative Report, 19, 1-13. Retrieved from
http://www.nova.edu/ssss/QR/QR19/morse17
Murakami, Y. (2013, March). Rethinking a case study method in educational research: A comparative analysis method in qualitative research. Educational Studies in Japan: International Yearbook, (7), 81-96. Retrieved from
http://ci.nii.ac.jp/vol_issue/nels/AA12192695_en.html
Pan, S., & Tan, B. (2011). Demystifying case research: A structured-pragmatic- situational (SPS) approach to conducting case studies. Information and Organization, 21(3), 161-176. doi:10.1016/j.infoandorg.2011.07.001
Petty, N. J., Thomson, O. P., & Stew, G. (2012). Ready for a paradigm shift? Part 2: Introducing qualitative research methodologies and methods. Manual Therapy, 17, 378-384. doi:10.1016/j.math.2012.03.004
Piekkari, R., Plakoyiannaki, E., & Welch, C. (2010). Good’ case research in industrial marketing: Insights from research practice. Industrial Marketing Management, 39, 109-117. doi:10.1016/j.indmarman.2008.04.017
Pratama, A., & Firman, A. (2010). Exploring the use of qualitative research methodology in conducting research in cross cultural management. International Journal of Interdisciplinary Social Sciences, 5, 331-342. Retrieved from http://www.iji.cgpublisher.com
Radley, A., & Chamberlain, K. (2012). The study of the case: Conceptualising case study research. Journal of Community & Applied Social Psychology, 22, 390– 399. doi:10.1002/casp.1106
Ridder, H. (2012). Case study research. Design and methods (book review of Robert Yin). Zeitschrift fur Personalforschung, 26(1), 93-95. Retrieved from http://www.zfp-personalforschung.de/de/
Rodrigues, G. N., Alves, V., Silveira, R., & Laranjeira, L. A. (2012). Dependability analysis in the Ambient Assisted Living Domain: An exploratory case study. Journal of Systems and Software, 85(1), 112-131. doi:10.1016/j.jss.2011.07.037
Sandelowski, M. (2011). “Casing” the research case study. Research in Nursing & Health, 34, 153-159. doi:10.1002/nur.20421
Sangster-Gromley, E. (2013). How case-study research can help to explain implementation of the nurse practitioner role. Nurse Researcher, 20(4), 6-11. doi:10.7748/nr2013.03.20.4.6.e291
Singh, A. S. (2014). Conducting case study research in non-profit organisations.
Qualitative Market Research: An International Journal, 17, 77-84. doi:10.1108/QMR-04-2013-0024
Small, M. (2009). How many cases do I need? On science and the logic of case selection in field-based research. Ethnography, 10(1), 5-38. doi:10.1177/1466138108099586
Snowden, A., & Martin C. R. (2011). Concurrent analysis: Towards generalizable qualitative research. Journal of Clinical Nursing, 20, 2868-2877. doi:10.1111/j.1365-2702.2010.03513.x
Snyder, C. (2012). A case study of a case study: Analysis of a robust qualitative research methodology. The Qualitative Report, 17(26), 1-21. Retrieved from
http://www.nova.edu/ssss/QR/QR17/snyder
Stewart, J. (2012). Multiple-case study methods in governance-related research. Public Management Review, 14(1), 67-82. doi:10.1080/14719037.2011.589618
Street, C. T., & Ward, K. W. (2012). Improving validity and reliability in longitudinal case study timelines. European Journal of Information Systems, 21, 160-175. doi:10.1057/ejis.2011.53
Taylor, R. (2013). Case-study research in context. Nurse Researcher, 20(4), 4-5.
Retrieved from http://www.nursing-standard.co.uk/
Thomas, G. (2011). A typology for the case study in social science following a review of definition, discourse, and structure. Qualitative Inquiry, 17, 511-521. doi:10.1177/1077800411409884
Tight, M. (2010). The curious case of case study: A viewpoint. International Journal of Social Research Methodology, 13, 329-339. doi:10.1080/13645570903187181
Tsang, E. W. (2012, August 26). Case study methodology: Causal explanation, contextualization, and theorizing. Journal of International Management, 19, 195- 202. doi:10.1016/j.intman.2012.08.004
Tsang, E. W. (2014). Case studies and generalization in information systems research: A critical realist perspective. Journal of Strategic Information Systems, 23, 174- 186. doi:10.1016/j.jsis.2013.09.002
Verner, J. M., & Abdullah, L. M. (2012). Exploratory case study research: Outsources project failure. Information and Software Technology, 54, 866-886. doi:10.1016/j.infsof.2011.11.001
Vissak, T. (2010). Recommendations for using case study methods in international business research. The Qualitative Report, 15, 370-388. Retrieved from http://nsuworks.nova.edu/cgi/viewcontent.cgi?article=1156&context=tqr
Vohra, V. (2014). Using the multiple case study design to decipher contextual leadership behaviors in Indian organizations. The Electronic Journal of Business Research Methods, 12, 54-65. Retrieved from http://www.ejbrm.com
Wahyuni, D. (2012). The research design maze: Understanding paradigms, cases, methods and methodologies. Journal of Applied Management Accounting Research, 10(1), 69-80. Retrieved from http://www.cmawebline.org/jamar
Welch, C., Piekkari, R., Plakoyiannaki, E., & Paavilainen-Mäntymäki, E. (2011).
Theorising from case studies: Towards a pluralist future for international business research. Journal of International Business Studies, 42, 740-762. doi:10.1057/jibs.2010.55
Westerman, M. A. (2014). Examining arguments against quantitative research: “Case studies” illustrating the challenge of finding a sound philosophical basis of a human sciences approach to psychology. New Ideas in Psychology, 32, 42-58. doi:10.1016/jnewideapsych.2013.08.002
Whiffin, C. J., Bailey, C., Ellis-Hill, C., & Jarrett, N. (2014). Challenges and solutions during analysis in a longitudinal narrative case study. Nurse Researcher, 21(4), 20-26. Retrieved from http://rcnpublishing.com/journal/nr
White, J., Drew, S., & Hay, T. (2009). Ethnography versus case study: Positioning research and researchers. Qualitative Research Journal, 9(1), 18-27. doi:10.3316/QRJ0901018
Woodside, A. G. (2010). Bridging the chasm between survey and case study research: Research methods for achieving generalization, accuracy, and complexity.
Industrial Marketing Management, 39(1), 64-75. doi:10.1016/j.indmarman.2009.03.017
Yadav, A., Shaver, G. M., & Meckl, P. (2010). Lesson learned: Implementing the case teaching method in a mechanical engineering course. Journal of Engineering Education, 99(1), 149-162. doi:10.1002/j.2168-9830.2010.tb01042.x
Yazan, B. (2015). Three approaches to case study methods in education: Yin, Merriam, and Stake. The Qualitative Report, 20(2), 134-152. Retrieved from http://nsuworks.nova.edu/tqr/vol20/iss2/12
Yin, R. K. (2013, July 10). Validity and generalization in future case study evaluations.
Evaluation, 19, 312-332. doi:10.1177/1356389013497081
Zivkovic, J. (2012). Strengths and weaknesses of business research methodologies: Two disparate case studies. Business Studies Journal, 4(2), 91-99. Retrieved from http://www.alliedacademies.org/public/journals/JournalDetails.aspx?jid=26
Case Study Seminal Books
Stake, R. E. (1995). The art of case study research. Thousand Oaks: Sage.
Yin, R. K. (2012). Applications of case study research (3rd ed.). Thousand Oaks: Sage. Yin, R. K. (2014). Case study research: designs and methods (5th ed.). Thousand
Oaks: Sage.
Data Saturation and Data Collection Sources
Abowitz, D. A., & Toole, T. M. (2010). Mixed methods research: Fundamental issues of design, validity, and reliability in construction research. Journal of Construction Engineering & Management, 136(1), 108-116. doi:10.1061/(ASCE)CO.1943-
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Focus Groups
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Qualitative Research Foundation
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Industrial Marketing Management, 39(1), 64-75. doi:10.1016/j.indmarman.2009.03.017
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Reliability, Validity, Transferability, and Generalizability Sources
Abowitz, D. A., & Toole, T. M. (2010). Mixed methods research: Fundamental issues of design, validity, and reliability in construction research. Journal of Construction Engineering & Management, 136(1), 108-116. doi:10.1061/(ASCE)CO.1943-
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Aust, F., Diedenhofen, B., Ullrich, S., & Musch, J. (2013). Seriousness checks are useful to improve data validity in online research. Behavior Research Methods (Online), 45, 527-35. doi:10.3758/s13428-012-0265-2
Azham, A., & Hamidah, Y. (2011). Quality in qualitative studies: The case of validity, reliability and generalizability. Issues in Social & Environmental Accounting, 5(1/2), 25-64. Retrieved from http://isea.icseard.uns.ac.id
Bekhet, A. K., & Zauszniewski, J. A. (2012). Methodological triangulation: An approach to understanding data. Nurse Researcher, 20(2), 40-43. Retrieved from http://www.nursing-standard.co.uk
Bisman, J. (2010). Postpositivism and accounting research: A personal primer on critical realism. Australasian Accounting Business & Finance Journal, 4(4), 3-25.
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Bleijenbergh, I., Korzilius, H., & Verschuren, P. (2011). Methodological criteria for the internal validity and utility of practice oriented research. Quality and Quantity, 45(1), 145-156. doi:10.1007/s11135-010-9361-5
Bouckenooghe, D., Clercq, D. D., Willem, A., & Buelens, M. (2007). An assessment of validity in entrepreneurship research. The Journal of Entrepreneurship , 16(2), 147-171. doi: 10.1177/097135570701600202
Brahma, S. S. (2009). Assessment of construct validity in management research: A structured guideline. Journal of Management Research, 9, 59-71. Retrieved from http://www.indianjournals.com/ijor.aspz?target=ijor:jmr&type=home
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Brod, M., Tesler, L. E., & Christiansen, T. L. (2009). Qualitative research and content validity: Developing best practices based on science and experience. Quality of Life Research, 18, 1263-1278. doi:10.1007/s11136-009-9540-9
Burchett, H. E., Mayhew, S. H., Lavis, J. N., & Dobrow, M. J. (2013). When can research from one setting be useful in another? Understanding perceptions of the applicability and transferability of research. Health Promotion International, 28, 418-430. doi:10.1093/heapro/das026
Burghardt, G. M., Bartmess-LeVasseur, J. N., Browning, S. A., Morrison, K. E., Stec, C. L., Zachau, C. E., & Freeberg, T. M. (2012). Perspectives – minimizing observer bias in behavioral studies: A review and recommendations. Ethology, 118, 511- 517. doi:10.1111/j.1439-0310.2012.02040.x
Cahoon, M. V., Bowler, J. L., & Bowler, M. C. (2012). A reevaluation of assessment center construct-related validity. International Journal of Business and Management, 7(9), 3-19. doi:10.5539/ijbm.v7n9p3
Chenail, R. J. (2010). Getting specific about qualitative research generalizability.
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Da Mota Pedrosa, A., Näslund, D., & Jasmand, C. (2012). Logistics case study based research: Towards higher quality. International Journal of Physical Distribution & Logistics Management, 42, 275-295. doi:10.1108/09600031211225963
Donatelli, R. E., & Lee, S. J. (2013). How to report reliability in orthodontic research: Part 1. American Journal of Orthodontics and Dentofacial Orthopedics, 144(1), 156-161. doi:10.1016/j.ajodo.2013.03.014
Dressman, M., McCarthey, S., & Prior, P. (2011). Generalizability or a thousand points of light? The promises and dilemmas of qualitative literacy research. Research in the Teaching of English, 45, 349-352. Retrieved from http://www.ncte.org
Drost, E. A. (2011). Validity and reliability in social science research. Education Research and Perspectives, 38(1), 105-124. Retrieved from http://www.education.uwa.edu.au/research/journal
El Hussein, M., Jakubec, S. L., & Osuji, J. (2015). Assessing the FACTS: A mnemonic for teaching and learning the rapid assessment of rigor in qualitative research studies. The Qualitative Report, 20, 1182-1184. Retrieved from http://nsuworks.nova.edu/tqr/vol20/iss8/3
Elo, S., Kaariainen, M., Kanste, O., Polkki, T., Utriainen, K., & Kyngas, H. (2014, January-March). Qualitative content analysis: A focus on trustworthiness. SAGE Open, 1-10. doi:10.1177/2158244014522633
Feldt, R. C., & Koch, C. (2011). Reliability and construct validity of the college student stress scale. Psychological Reports, 108, 660-666. doi:10.2466/02.08.13.16.PRO.108.2.660-666
Gheondea-Eladi, A. (2014). Is qualitative research generalizable? Journal of Community Positive Practices, 14(3), 114-124. Retrieved from http://jppc.ro/?lang=en
Gibbert, M., & Ruigrok, W. (2010). The what and how of case study rigor: Three strategies based on published work. Organizational Research Methods, 13, 710- 737. doi:10.1177/1094428109351319
Gibbert, M., Ruigrok, W., & Wicki, B. (2008). What passes as a rigorous case study?
Strategic Management Journal, 29, 1465-1474. Retrieved from http://smj.strategicmanagement.net/
Golafshani, N. (2003). Understanding reliability and validity in qualitative research. The Qualitative Report, 8, 597-607. Retrieved from http://www.nova.edu/ssss/QR/QR8-4/golafshani
Green, L. W., & Glasgow, R. E. (2006). Evaluating the relevance, generalization, and applicability of research: Issues in external validation and translation methodology. Evaluation & the Health Professions, 29(1), 126-153. doi:10:1177/0163278705284445
Hodges, N. (2011). Qualitative research: A discussion of frequently articulated qualms (FAQs). Family and Consumer Sciences Research Journal, 40, 90-92. doi:10.1111/j.1552-3934.2011.02091.x
Holloway, I., Brown, L., & Shipway, R. (2010). Meaning not measurement: Using ethnography to bring a deeper understanding to the participant experience of festivals and events. International Journal of Event and Festival Management, 1(1), 74-85. doi:10.1108/17852951011029315
Houghton, C., Casey, D., Shaw, D., & Murphy, K. (2013). Rigour in qualitative case- study research. Nurse Researcher, 20(4), 12-17. doi:10.7748/nr2013.03.20.4.12.e326
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Ihantola, E. M, & Kihn, L. A. (2011). Threats to validity and reliability in mixed methods accounting research. Qualitative Research in Accounting and Management, 8(1), 39-58. doi:10:1108/11766091111124694
Jensen, H. I., Ammentorp, J., Erlandsen, M., & Ording, H. (2012). End of life practices in Danish ICUs: Development and validation of a questionnaire. BMC Anesthesiology, 12(1), 16-22. doi:10.1186/1471-2253-12-16
Kane, M. (2012). All validity is construct validity. Or is it? Measurement, 10(1/2), 66-70. doi:10.1080/15366367.2012.681977
Kelemen, M., & Rumens, N. (2012). Pragmatism and heterodoxy in organization research: Going beyond the quantitative/qualitative divide. International Journal of Organizational Analysis, 20, 5-12. doi:10.1108/19348831211215704
Kihn, L. & Ihantola, E. (2015). Approaches to validation and evaluation in qualitative studies of management accounting. Qualitative Research in Accounting & Management, 12(3), 230-255. doi:10.1109/QRAM-03-2013-0012
Kornbluh, M. (2015). Combatting challenges to establishing trustworthiness in qualitative research. Qualitative Research in Psychology, 12, 397-414. doi:10.1080/14780887.2015.1021941
Krippendorff, K. (2011). Agreement and information in the reliability of coding.
Communications Methods & Measures, 5(2), 93-112. doi:10.1080/19312458.2011568376
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Lasch, K. E., Marquis, P., Vigneux, M., Abetz, L., Arnould, B., Bayliss, M., Crawford, B., & Rosa, K. (2010). PRO development: Rigorous qualitative research as the crucial foundation. Quality of Life Research, 19, 1087-1096. doi:10.1007/s11136- 010-9677-6
Molina-Azorin, J. F. (2011). The use and added value of mixed methods in management research. Journal of Mixed Methods Research, 5(1), 7-24. doi:10.1177/1558689810384490
Morse, J. M., Barrett, M., Mayan, M., Olson, K., & Spiers, J. (2002). Verification strategies for establishing reliability and validity in qualitative research.
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Nakkeeran, N., & Zodpey, S. P. (2012). Qualitative research in applied situations: Strategies to ensure rigor and validity. Indian Journal of Public Health, 56(1), 4- 11. doi:10.10.4103/0019-557X.96949
Noble, H., & Smith, J. (2015). Issues of validity and reliability in qualitative research.
Evidence-Based Nursing, 18(2), 34-35. doi:10.1136/eb-2015-102054
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Pearson, M., & Coomber, R. (2010). The challenge of external validity in policy-relevant systematic reviews: A case study from the field of substance misuse. Addiction, 105(1), 136-145. doi:10.1111/j.1360-0443.2009.02713.x
Polit, D. F., & Beck, C. T. (2010). Generalization in quantitative and qualitative research: Myths and strategies. International Journal of Nursing Studies, 47, 1451-1458. doi:10.1016/j.ijnurstu.2010.06.004
Rennie, D. L. (2012). Qualitative research as methodical hermeneutics. Psychological Methods, 17, 385-398. Retrieved from http://www.psycnet.apa.org
Riege, A. M. (2003). Validity and reliability tests in case study research: A literature review with “hands-on” applications for each research phase. Qualitative Market Research: An International Journal, 6(2), 75-86. doi:10.1108/13522750310470055
Rocha Pereira, H. (2012). Rigour in phenomenological research: Reflections of a novice nurse researcher. Nurse Researcher, 19(3), 16-19. Retrieved from http://nurse researcher.rcnpublishing.co.uk
Roe, B. E., & Just, D. R. (2009). Internal and external validity in economics research: Tradeoffs between experiments, field experiments, natural experiments, and field data. American Journal of Agricultural Economics, 91, 1266-1271. doi:10.1111/j.14678276.2009.01295.x.
Rossiter, J. R. (2008). Content validity of measures of abstract constructs in management and organizational research. British Journal of Management, 19, 380-388. doi:10.1111/j.1467-8551.2008.00587.x
Shadish, W. R. (2011). The truth about validity. New Directions for Evaluation, 2011(130), 107-117. doi:10.1002/ev.369
Slater, S., & Yani-de-Soriano, M. (2010). Researching consumers in multicultural societies: Emerging methodological issues. Journal of Marketing Management, 26, 1143-1160. doi:10.1080/0267257X.2010.509581
Slone, D. J. (2009). Visualizing qualitative information. The Qualitative Report, 14, 489-
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Soter, A. O., Connors, S. P., & Rudge, L. (2012). Use of coding manual when providing a meta-interpretation of internal-validity mechanisms and demographic data used in qualitative research. Journal of Ethnographic and Qualitative Research, 17(6), 69-80. doi:10.24584593467.567945
Steckler, A., & McLeroy, K.R. (2008). The importance of external validity. American Journal of Public Health, 98(1), 9-10. doi:10.2105/AJP.2007.126847
Stone-Romero, E., & Rosopa, P. J. (2010). Research design options for testing mediation models and their implications for facets of validity. Journal of Managerial Psychology, 25, 697-712. doi:10.1108/02683941011075256
Street, C. T., & Ward, K. W. (2012). Improving validity and reliability in longitudinal case study timelines. European Journal of Information Systems, 21(2), 160-175. doi:10.1057/ejis.2011.53
Thomas, E., & Magilvy, J. K. (2011). Qualitative rigor or research validity in qualitative research. Journal for Specialists in Pediatric Nursing, 16(2), 151-155. doi:10.1111/j.1744-6155.2011.00283.x
Tiira, K., & Lohi, H. (2014). Reliability and validity of a questionnaire survey in canine anxiety research. Applied Animal Behavior Science, 155, 82-92. doi:10.1016/j.applanim.2014.03.007
Tomasik, T. (2010). Reliability and validity of the Delphi method in guideline development for family physicians. Quality in Primary Care, 18, 317-326. Retrieved from http://www.ingentaconnect.com
Woolcock, M. (2013). Using case studies to explore the external validity of ‘complex’ development interventions. Evaluation, 19, 229-248. doi:10.1177/1356389013495210
Yildirim, K. (2010). Raising the quality in qualitative research. Ilkogretim Online, 9(1), 79-92. Retrieved from
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Yin, R. K. (2013, July 10). Validity and generalization in future case study evaluations.
Evaluation, 19, 312-332. doi:10.1177/1356389013497081
Yu, C., Jannasch-Pennell, A., & DiGangi, S. (2011). Compatibility between text mining and qualitative research in the perspectives of grounded theory content analysis, and reliability. The Qualitative Report, 16, 730-744. Retrieved from http://www.nova.edu/ssss/QR/QR16-3/yu
Sampling and Incentives
Abrams, L. S. (2010). Sampling hard to reach populations in qualitative research: The case of incarcerated youth. Qualitative Social Work, 9, 536-550. doi:10.1077/1473325010367821
Acharya, A. S., Prakash, A., Saxena, P., & Nigam, A. (2013). Sampling: Why and how of it? Indian Journal of Medical Specialties, 4(2), 330-333. doi:10.7713/ijms.2013.0032
Anderson, R. B., & Hartzler, B. M. (2014. Belief bias in the perception of sample size adequacy. Thinking & Reasoning, 20, 297-314. doi:10.1080/13546783.2013.787121
Angelos, P. (2013). Ethical issues of participant recruitment in surgical clinical trials.
Annals of Surgical Oncology, 20, 3184-3187. doi:10.1245/s10434-013-3178-0
Ardern, C. I., Nie, J. X., Perez, D. F., Radhu, N., & Ritvo, P. (2013). Impact of participant incentives and direct and snowball sampling on survey response rate in an ethnically diverse community: Results from a pilot study of physical activity and the built environment. Journal of Immigrant and Minority Health, 15(1), 207-214. doi:10.1007/s10903-011-9525-y
Baltar, F., & Brunet, I. (2012). Social research 2.0: Virtual snowball sampling method using facebook. Internet Research, 22, 57-74. doi:10.1108/10662241211199960
Brewis, J. (2014). The ethics of researching friends: On convenience sampling in qualitative management and organization studies. Journal of British Management, 25, 849-862. doi:10.1111/1467-8551.12064
Burmeister, E., & Aitken, L. M. (2012). Sample size: How many is enough? Australian Critical Care, 25, 271-274. doi:10.1016/j.aucc.2012.07.002
Cader, H. A., & Leatherman, J. C. (2011). Small business survival and sample selection bias. Small Business Economics, 37, 155-165. doi:10.1007/s11187-009-9240-4
Carlsen, B., & Glenton, C. (2011). What about N? A methodological study of sample size reporting in focus group studies. BMC Medical Research Methodology, 11(1), 26-35. doi:10.1186/1471-2288-11-26
Cleary, M., Horsfall, J., & Hayter, M. (2014). Data collection and sampling in qualitative research: Does size matter? Journal of Advanced Nursing, 70, 473-475. doi:10.1111/jan.12163
Cohen, N., & Arieli, T. (2011). Field research in conflict environments: Methodological challenges and snowball sampling. Journal of Peace Research, 48, 423-435. doi:10.1177/0022343311405698
Dworkin, S. L. (2012). Sample size policy for qualitative studies using in-depth interviews. Archives of Sexual Behavior, 41, 1319-1320. doi:10.1007/s105080120016-6
Emerson, R. W. (2015). Convenience sampling, random sampling, and snowball sampling: How does sampling affect the validity of research? Journal of Visual Impairment & Blindness, 109(2), 164-168. Retrieved from http://http://www.afb.org/jvib/jvib_main.asp
Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs, principles and practices. Health Services Research, 48, 2134- 2156. doi:10.1111/1475-6773.12117
Francis, J. J., Johnston, M., Robertson, C., Glidewell, L., Entwistle, V. Eccles, M. P., & Grimshaw, J. M. (2010). What is an adequate sample size? Operationalizing data saturation for theory-based interview studies. Psychology and Health, 25, 1229- 1245. doi:10.1080/08870440903194015
Fugard, A., & Potts, H. (2015). Supporting thinking on sample sizes for thematic analysis: A quantitative tool. International Journal of Social Research Methodology, 18, 669-684. doi:10.1080/13645579.2015.1005453
Gibbs, L., Kealy, M., Willis, K., Green, J., Welch, N., & Daly, J. (2007). What have sampling and data collection got to do with good qualitative research? Australian and New Zealand Journal of Public Health, 31, 540-544. doi:10.1111/j.1753- 6405.2007.00140.x
Gillet, J., Cartwright, E., & Van Vugt, M. (2011). Selfish or servant leadership?
Evolutionary predictions on leadership personalities in coordination games. Personality and Individual Differences, 51, 231-236. doi:10.1016/j.paid.2010.06.003
Griffith, D. A. (2013). Establishing qualitative geographic sample size in the presence of spatial autocorrelation. Annals of the Association of American Geographers, 103, 1107-1122. doi:10.1080/00045608.2013.776884
Guyll, M., Spoth, R., & Redmond, C. (2003). The effects of incentives and research requirements on participation rates for a community-based preventive intervention research study. Journal of Primary Prevention, 24.doi:10.1023/A:1025023600517
Handcock, M. S., & Gile, K. J. (2011). Comment: On the concept of snowball sampling.
Sociological Methodology, 41, 367-371. doi:10.1111/j.1467-9531.2011.01243.x
Hanson, J., Balmer, D., & Giardino, A. (2011). Qualitative research methods for medical educators. Academic Pediatrics, 11, 375-386. doi:10.1016/j.acap.2011.05.001
Harsh, S. (2011). Purposeful sampling in qualitative research synthesis. Qualitative Research Journal, 11, 63-75. doi:10.3316/QRJ1102063
Head, E. (2009). The ethics and implications of paying participants in qualitative research. International Journal of Social Research Methodology, 12, 335-344. doi:10.1080/13645570802246724
Hochwarter, W. (2014). On the merits of student‐recruited sampling: Opinions a decade in the making. Journal of Occupational and Organizational Psychology, 87(1), 27- 33. doi:10.1111/joop.12043
Hodges, N. (2011). Qualitative research: A discussion of frequently articulated qualms (FAQs). Family and Consumer Sciences Research Journal, 40, 90-92. doi:10.1111/j.1552-3934.2011.02091.x
Hyat, M. J. (2013). Understanding sample size determination in nursing research.
Western Journal of Nursing Research, 35, 943-956. doi:10.1177/0193945913482052
Jawale, K. V. (2012). Methods of sampling design in the legal research: Advantages and disadvantages. Online International Interdisciplinary Research Journal, 2(6), 183-190. Retrieved from http://www.oiirj.org/oiirj/?page_id=924
Jessiman, W. (2013). ‘To be honest, I haven’t even thought about it’ – recruitment in small-scale, qualitative research in primary care. Nurse Researcher, 21(2), 18- 23. doi:10.7748/nr2013.11.21.2.18.e226
Kadam, P., & Bhalerao, S. (2010). Sample size calculation. International Journal of Ayurveda Research, 1(1), 55-57. doi:10.4103/0974-7788.59946
Klotz, A. C., Da Motta Veiga, S. P., Buckley, M. R., & Gavin, M. B. (2013). The role of trustworthiness in recruitment and selection: A review and guide for future research. Journal of Organizational Behavior, 34(Suppl 1), S104-S119. doi:10.1002/job.1891
Larson, A. J., & Sachau, D. A. (2009). Effects of incentives and the Big Five personality dimensions on internet panelists’ ratings. International Journal of Market Research, 51, 687-706. Retrieved from http://www.ijmr.com
Marshall, B., Cardon, P., Poddar, A., & Fontenot, R. (2013). Does sample size matter in qualitative research? A review of qualitative interview in is research. Journal of Computer Information Systems, 54(1), 11-22. Retrieved from http://www.iacis.org/jcis/jcis.php
Mason, M. (2010, September). Sample size and saturation in PhD studies using qualitative interviews. Forum: Qualitative Social Research, 11(3). Retrieved from http://www.qualitative-research.net/index.php/fqs/article/view/1428/3027
McQuarrie, E. F., & McIntyre, S. H. (2014). What can you project from small sample qualitative research? Marketing Insights, 26(2), 34-39. Retrieved from https://www.ama.org/publications/MarketingInsights/Pages/what-can-you-project- from-small-sample-qualitative-research-mi-march-april.aspx
Michaelidou, N., & Dibb, S. (2006). Using email questionnaires for research: Good practice in tackling non-response. Journal of Targeting, Measurement & Analysis for Marketing, 14, 289-296. doi:10.1057/palgrave.jt.5740189
Molenberghs, G., Kenward, M., Aerts, M., Verbeke, G., Tsiatis, A., Davidian, M., & Rizopoulos, D. (2014). On random sample size, ignorability, ancillarity, completeness, separability, and degeneracy: Sequential trials, random sample sizes, and missing data. Statistical Methods in Medical Research, 23, 11-41. doi:10.1177/0962280212445801
Monroe, M. C., & Adams, D. C. (2012). Increasing response rates to web-based surveys. Journal of Extension, 50(6), 6-7. Retrieved from http://www.joe.org/joe/2012december/tt7.php
Namageyo-Funa, A., Rimando, M., Brace, A. M., Christiana, R.W., Fowles, T. L., Davis,
T. L., Martinez, L. M., & Sealy, D. A. (2014). Recruitment in qualitative public health research: Lessons learned during dissertation sample recruitment. The Qualitative Report, 19(1), 1-17. Retrieved http://www.nova.edu/ssss/QR/QR19/namageyo-funa1
Nolen, A., & Talbert, T. (2011). Qualitative assertions as prescriptive statements.
Educational Psychology Review, 23, 263-271. doi:10.1007/s10648-011-9159-6
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Sensemaking
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Qualitative Software Analysis Sources
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Triangulation Sources
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March 2016
DBA RESEARCH HANDBOOK
SECTION 1: FOUNDATION OF THE STUDY
Inspirational Motivation
Turnover Intention
Intellectual Stimulation
Idealized Behavior
Idealized Attributes
Moral Integrity
SECTION 2: THE PROJECT
SECTION 3: APPLICATION TO PROFESSIONAL PRACTICE AND IMPLICATIONS FOR CHANGE
Literature Review (Due in 2 days)/peer-reviewed sources.zip
peer-reviewed sources/Application of principles of supply chain management to the pharmaceutical good transportation practices.pdf
Application of principles of supply
chain management to the
pharmaceutical good
transportation practices
Nirmal Kumar
Department of Management Studies, Sikkim Manipal Institute of Technology,
Majhitar, India, and
Ajeya Jha
Sikkim Manipal Institute of Technology, Majhitar, India
Abstract
Purpose – Pharmaceuticals supply chain management (SCM) requires special expertise to transport the
medicinal products because of weird features of their demand, supply and sensitivity towards quality. The
purpose of this study is to establish the linkage of pharmaceutical quality system requirements with the SCM
principles. The study enables the collaborative approach of technical, transport, logistics and supply chain
teams within the pharmaceutical industry.
Design/methodology/approach – The methodology followed for this study is literature review and
survey. The study is supplemented with data obtained through the structured questionnaire.
Findings – Through this study, an exclusive perspective for pharmaceutical good transportation practice
(GTP) has been propagated in alignment with seven principles of SCM by Anderson. This study offers
guidance to pharmaceutical industry for transportation of products by conceptualizing basic supply chain
features such as segmentation, customization of requirement, market signals, differentiation, technology
orientation and channel spanning performance.
Research limitations/implications – Here is limited information available about the transportation
failures in the pharmaceutical industry. Application of supply chain principles to pharmaceutical
transportation is sometimes affected by technical knowledge bias of the researcher.
Practical implications – The study has successfully expounded the practical aspects of pharmaceutical
GTP for supply chain professionals.
Social implications – The study facilitates the patients and pharmaceutical consumers to get quality
products in a timely manner across the globe.
Originality/value – The application of SCM principles to the pharmaceutical GTP is the result of novel
research and has not been studied earlier.
Keywords Good distribution practices, Good transportation practices, Pharmaceutical complaint,
Pharmaceutical quality, Pharmaceutical supply chain quality
Paper type Conceptual paper
1. Introduction
The supply chain operation commencing from the drugs’ manufacturers is under the
scanner of drug regulatory agencies to make sure that drugs are safely delivered to the end-
users. Pharmaceutical industry has obligation to follow specialized and stringent system
prescribed by the drugs regulatory agency. The good manufacturing practice (GMP) and
good distribution practice (GDP) are the most popular systems to manage their operations.
IJPHM
13,3
306
Received 13 September 2017
Revised 17 September 2018
Accepted 10 April 2019
International Journal of
Pharmaceutical and Healthcare
Marketing
Vol. 13 No. 3, 2019
pp. 306-330
© EmeraldPublishingLimited
1750-6123
DOI 10.1108/IJPHM-09-2017-0048
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1750-6123.htm
In addition to these two, the term GXP is commonly used for various subsystems to denote
some good practice in the pharmaceutical industry, wherein G stands for good, P for practice
and X for any aspect in the pharmaceutical industry. The acronyms based on GXP have
been endorsed by various national drug regulatory agencies including that from the USA,
the UK and Europe. Pharmaceutical international convention system (PICS, 2007) issued a
guidance paper on good practices for computerized systems in regulated “GXP”
environments that asserts the recognition of terms like core philosophy GMP which stands
for good manufacturing practice in the pharmaceutical industry, GDP for good distribution
practice, GLP for good laboratory practice, etc. (PICS, 2007).
Transportation is a process of moving active substances between two locations without
storing them for an unwarranted duration of time (EUR-Lex, 2015). The review of good
practices during pharmaceutical transportation highlights the need of developing a
systematic approach through good transportation practice (GTP) (Kumar and Jha, 2017)
(Figure 1).
The pharmaceuticals industry is very sensitive towards quality requirement in all
operations to protect the goods throughout the product lifecycle. Abnormal temperature
variations during transportation can seriously peril the integrity of prudent products. In
addition, the transportation should be free from the scope of pilferages, theft and other
malpractices. To maintain feasible and consistent supply chain in a global context, careful
consideration must, therefore, be there to handle transportation and quality agreement
during the planning of import and export.
World’s Top Exports (WTEx) in a strategic study estimated that about half of total
drugs and medicines exports of be from four nations Germany, Switzerland, Belgium, the
USA and the UK to rest of the world. It is therefore in view of product mobility during sales,
the transportation business shall be on the rise during coming years (Daniel Workman,
2018). Moreover, many drug manufacturing plants are situated in tropical zones of Asia,
where sea, air and rail connectivity infrastructures are intricate, thus posing enormous
challenges for transportation. Based on Global Cold Chain Report published by IQPC/Cold
Chain IQ, a dramatic growth has been anticipated for the cold-chain logistics market in 2017
with increases of 57 per cent in emerging markets, 46 per cent in Asia, 21 per cent in Europe
and 18 per cent in North America (Hallie Forcinio, 2014). IMS observed estimate that the
Figure 1.
Graphical
representation of
pharmaceutical
operations
Transportation
Dispensaries &
Retail Outlets
Pharmaceutical
Manufacturing Plant
Warehouse
Good
transportation
practices
307
losses associated with temperature excursions in healthcare come to $35bn of which $1bn in
wasted logistics costs (IMS, 2014).
One US-based logistics firm Cargosense (2015) has estimated that nearly 20 per cent of
cold chain products are damaged because of uneven temperature conditions. Further, the
losses across the industry comparatively appear as:
� 25 per cent of vaccines degraded because of incorrect shipping; and
� 30 per cent of pharmaceuticals destroyed because of logistics issues.
1.1 Supply chain management versus good transportation practice
The supply chain management (SCM) can be described as design, planning, execution,
control and monitoring of supply chain activities with the objective of creating net value,
building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply
with demand and measuring performance globally (APICS, 2016). ISPE has described
pharmaceutical supply chain as the management of product supply from raw material
sourcing to manufacturing through formulation, packaging and distribution to the patient.
A key requirement is the safe and reliable supply of quality medicines through a supply
chain which is responsive to true demand and understands the voice of the customer (ISPE
Conference, 2012). World Health Organization (WHO) issued technical report to describe the
good storage practice for storing of pharmaceutical products and materials up to their point
of use (WHO, 2003). The purpose of this guidance paper is to describe the extraordinary
measures considered appropriate for the storage and transportation of pharmaceuticals
(EMA, 2010). However, the guidance to achieve the desired standards of quality during
transportation and logistics operation have not been detailed out in existing literature
(Table I).
The transportation and shipment are the important aspects of pharmaceutical
entrepreneurship, but there is hardly a systematic quality approach which governs and
monitors the pharmaceutical product transit.
1.2 Review of regulatory guidance papers
A comparative review of the guidance papers from drug regulatory agencies providing
insights of pharmaceutical GDP reveals that there is lack of insight on pharmaceutical SCM
(Table II).
The European Commission has spearheaded the initiative to create a common approach
for GMP systems followed in countries like Australia, Canada, Israel, Japan, New Zealand,
Switzerland and the USA (EMA, 2017). There is growing cooperation between regulatory
agencies of various countries towards the exchange of information pertaining to GMP status
(FDA, 2018). However, there is an enhanced need of mutual recognition of concept relating to
the pharmaceutical distribution and transportation system.
1.3 Gap in existing pieces of literature
Several types of research have been carried out to discuss the GXP in the pharmaceutical
industry, which contributes towards business goal by establishing the quality benchmark in
different facets. The drug regulatory and/or nodal agencies have issued various guidance
papers, wherein the term GXP has been coined for various quality management systems,
such as following:
� GMP: Good manufacturing practice;
� GDP: Good distribution practice; and
� GLP: Good laboratory practice.
IJPHM
13,3
308
However, there is lack of standard regulatory guidance dedicated to GTP in the
pharmaceutical industry. The GTP can be deliberated to highlight the advantage to protect
the medicinal quality during distribution operation (Kumar and Jha, 2017). Some researchers
observed that still there is a dearth of studies on pharmaceutical supply chain because of the
complexity of inherent requirement (Singh et al., 2016). GDP describes a variety of practices
focusing on drugs storage but has stayed away from an in-depth focus on transportation
aspects of SCM. In existing studies, the transportation is perceived more from supply chain
perspective rather than quality management angle giving rise to numerous business
implications because of product rejections. The risk of freezing or overheating because of
temperature excursions during transportation and the effects on the products also pose the
concern to pharmaceutical product quality (Collin, 2003). There is a noticeable gap in
existing literature related to the quality system for manufacturing and distribution (Kumar
and Jha, 2016). This study has been envisaged to strengthen the concept of GTP to
supplement the quality system approach during transportation planning and
implementation throughout the supply chain operation. Noteworthy “The Seven Principles
of Supply Chain Management” by David Anderson has not been applied in GTP by any
author.
Table I.
Overview of ‘SCM’
vis-à-vis ‘GTP’
Supply chain management (SCM) Good transportation practice (GTP)
Objective
This encompasses the management starting from
procurement of raw material, work in progress
inventory and end-user of finished goods
This is a system for ensuring that products are
consistently transported and controlled according to
quality standards
Genesis
The idiom “supply chain management” was first
coined by consultant Keith Oliver in talk for the
Financial Times in the early 80s (Laseter and Oliver,
2003)
PIC/S has used the acronym ‘GxP’ in the document
with an expectation that document will be of
assistance to all ‘Good Practice’ Inspectors
responsible for inspecting applications in the
regulated pharmaceutical sector (PICS, 2007).
One or a combination of GCP, GMP, GLP, GDP –
often used for everything of interest for the
Regulatory Bodies. ‘X’, one of: Clinical,
Manufacturing, Laboratory, Distribution (ISPE,
2018).
Drug regulator from the UK, MHRA inspectorate
has referred GXP as good practices across all areas
(MHRA, 2015).
European medicines agency, EMA has referred GXP
Inspections within the Centralized Procedure
(EMEA, 2013)
Relevance
This is a common management practice relevant to
all industry
This is relevant to drugs, pharmaceutical and food
industry only
Policy and priorities:
The policy and priorities are laid down by supply
chain managers under consultation of finance
department managers
The policy and priorities are laid down by quality
managers under consultation with regulatory
department managers
Focus
Revenue-oriented business accomplishment
approach
Quality oriented regulatory compliant approach
Good
transportation
practices
309
2. Method
The study is based on a mixed approach which emphasizes a holistic view of qualitative
analysis and quantitative analysis. The review of articles and regulatory guidance papers
on pharmaceutical good distribution were considered under the study purview. The
materials from search engine Google have been collected by using the keywords like
pharmaceutical transportation, distribution practices and pharmaceutical SCM. The
pertinent information has been drawn from literature and regulatory guidance according to
exclusion principle. The irrelevant information has been omitted as per consent of both
authors.
To supplement the exploratory study outcome, the data obtained from the survey on the
Likert scale were considered for drawing comparison of adherence of practice during
manufacturing and that during transportation to draw a corollary between GMP vis-a-vis
GTP. The survey was conducted among pharmaceutical professionals engaged in
manufacturing and distribution of products in regulated pharmaceutical markets like the
USA, the UK and European countries.
Table II.
Drug regulatory
guidance for
distribution
Country/
region Drugs regulatory agency Reference guidance paper
United
States of
America
United States Food and Drugs
Administration (USFDA)
Federal Food, Drug and Cosmetics Act, 1938
(FFDCA, 1938)
USP-Monograph 1083, Good Distribution Practices-
Supply Chain Integrity (USP, 2014)
United States Pharmacopeia (USP) has an intention
to ensure that drug products (medicines) reach the
end-user (practitioners and patient/ consumers) with
quality intact
Federal Drug Supply Chain and Security Act, 2015
(FDSCS, 2015)
United
Kingdom
Medicines and Healthcare Products
Regulatory Agency (MHRA)
Rules and Guidance for Pharmaceutical
Manufacturers and Distributors (MHRA, 2017)
Europe European Medicines Agency (EMA) Guidelines on Good Distribution Practice of
Medicinal Products for Human Use. Has also issued a
concept Paper on Storage Conditions during
Transport (EMA, 2013)
India Central Drugs Standard Control
Organization (CDSCO)
Guidelines on Good Distribution Practice for
Pharmaceutical Products giving a glimpse of
transportation (CDSCO, 2013)
Canada Health Canada Guidelines for Temperature Control of Drug
Products during Storage and Transportation (Health
Canada, 2011)
Australia Therapeutic Goods Administration
(TGA)
Australian code of good wholesaling practice for
medicines in Schedules 2, 3, 4 and 8 (TGA, 2011)
China Ministry of Health of the People’s
Republic of China
Good Supply Practice for Pharmaceutical Products
Nigeria National Agency for Food and Drug
Administration and Control
(NAFDAC)
Good Distribution Practice for Pharmaceutical
Products (NAFDAC, 2016) describes the drugs
distribution provisions including one section on
transportation and products in transit
WHO-
affiliated
nations
World Health Organization Technical Report Series 961, Model guidance for the
storage and transport of time- and temperature-
sensitive pharmaceutical products (WHO, 2011)
IJPHM
13,3
310
3. Data
3.1 Data collection
The survey participants comprised the pharmaceutical professionals, who are engaged in
manufacturing, distribution, handling or case analysis related to complaints of
pharmaceutical products.
Because of the technical nature and complexity of the subject, the eligibility of survey
participants has been decided with an approach to avoid error and bias. The participants
have minimum qualification in pharmacy, science and management or their combination
with by substantial experience. The professionals who participated in survey have essential
working experience with leading pharmaceutical organizations with major regulatory
approval from USFDA, EUGMP, MHRA, ANVISA, TGA and WHO. There is a provision of
mutual recognition among regulatory agencies of various countries about compliance (FDA,
2018). Thus, the regional borders are not significant so far basic GXP concepts are concerned
(Table III).
The participants served pharmaceutical industry as executive or superior roles; hence,
they possess understanding of global pharmaceutical context and regulatory aspirations
across the world.
A total 207 professionals working in leading pharmaceutical organizations were
contacted for collecting the data, of which 190 valid responses were received. The
respondents whosoever denied participation in the survey had expressed the apprehension of
disclosure of identity of their employing organization. However, the respondents participated
in survey process in the individual capacity and they do not represent organizational
affiliations, thereby endorsing their opinion free from any conflict of interest and bias.
The survey has been conducted among senior executives handling GXP affairs in 20
leading global pharmaceutical companies to ascertain high reliability of data. The
distribution of result has been considered 50 per cent. As the measurement of data has an
objective to compare the participants agreeing against the disagreeing population, there is
less scope of misinterpretation of results. On an average, each of these companies has less
than 750 professionals responsible for GXP issues, specific to the distribution and
transportation operations. Thus, a population of 15,000 has been considered appropriate for
the survey study. At a confidence level of 95 per cent, the sample size of 190 has a
probability of error 7.06 per cent, which is acceptable for this study design. The above
sample size of the survey has been found valid at the confidence level of 95 per cent. The
results for participants “agreeing and strongly agreeing” shall provide the result in favor of
the proposed application of supply chain principles in pharmaceutical GTP. The sum of
percentages of population falling in categories of “Agree and Strongly Agreed” have been
compared with data for “Disagree and Strongly Disagree” to assess the controls during
manufacturing and that during drugs distribution.
3.2 Data analysis
3.2.1 Paired t-test. There are the same set of data available for comparison between the
controls during manufacturing and transportation practices; Type 1 has been applied for t-
test. The two-tailed P value was found less than 0.0001. A p-value < 0.05 has been
considered significant.
3.2.2 Null hypothesis. The data were subjected to two-tailed t-test and the null hypothesis
was postulated.
H0: m = 0; that is, any differences in the approach adopted during manufacturing and
that during distribution to prevent spurious drug in a market is because of chance.
Good
transportation
practices
311
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is
an
ad
eq
ua
te
un
de
rs
ta
nd
in
g
am
on
g
tr
an
sp
or
t
pe
rs
on
ne
lt
ha
t
se
a
m
od
e
of
tr
an
sp
or
ta
ti
on
m
ay
po
se
ri
sk
be
ca
us
e
of
m
oi
st
ur
e
pe
rm
ea
bi
lit
y
th
ro
ug
h
pa
ck
un
de
r
st
re
ss
ed
hu
m
id
it
y
ex
po
su
re
38
P
ri
nc
ip
le
3:
L
is
te
n
to
m
ar
ke
ts
ig
na
ls
an
d
al
ig
n
de
m
an
d
pl
an
ni
ng
ac
co
rd
in
gl
y
ac
ro
ss
th
e
su
pp
ly
ch
ai
n,
en
su
ri
ng
co
ns
is
te
nt
fo
re
ca
st
s
an
d
op
ti
m
al
re
so
ur
ce
al
lo
ca
ti
on
7
T
he
re
is
ad
eq
ua
te
kn
ow
le
dg
e
ab
ou
tt
he
re
gu
la
to
ry
co
ns
tr
ai
nt
s
in
sp
ec
ifi
c
co
un
tr
y
an
d
ba
n
of
ce
rt
ai
n
fo
rm
ul
at
io
n,
w
hi
ch
co
ul
d
ha
ve
an
im
pa
ct
on
tr
an
sp
or
ta
ti
on
st
ra
te
gi
es
76
T
he
re
is
ad
eq
ua
te
kn
ow
le
dg
e
ab
ou
t
th
e
re
gu
la
to
ry
co
ns
tr
ai
nt
s
in
sp
ec
ifi
c
co
un
tr
y
an
d
ba
n
of
a
fo
rm
ul
at
io
n,
w
hi
ch
co
ul
d
ha
ve
an
im
pa
ct
on
tr
an
sp
or
ta
ti
on
st
ra
te
gi
es
21
8
E
ff
ec
ti
ve
an
d
pr
io
r
co
m
m
un
ic
at
io
n
ab
ou
t
th
e
re
gu
la
to
ry
ap
pr
ov
al
st
at
us
of
th
e
pr
od
uc
t
is
re
ce
iv
ed
be
fo
re
m
ar
ke
ti
ng
86
E
ff
ec
ti
ve
an
d
pr
io
r
co
m
m
un
ic
at
io
n
ab
ou
t
th
e
re
gu
la
to
ry
ap
pr
ov
al
st
at
us
of
th
e
pr
od
uc
t
is
re
ce
iv
ed
be
fo
re
m
ar
ke
ti
ng
52
(c
on
ti
nu
ed
)
Table III.
Comparison of
practice of adherence
IJPHM
13,3
312
Se
ri
al
nu
m
be
r
A
dh
er
en
ce
to
pr
ac
ti
ce
du
ri
ng
m
an
uf
ac
tu
ri
ng
A
dh
er
en
ce
to
pr
ac
ti
ce
du
ri
ng
tr
an
sp
or
ta
ti
on
C
on
tr
ol
s
du
ri
ng
m
an
uf
ac
tu
ri
ng
op
er
at
io
ns
%
po
pu
la
ti
on
ag
re
ed
C
on
tr
ol
s
du
ri
ng
di
st
ri
bu
ti
on
op
er
at
io
ns
%
po
pu
la
ti
on
ag
re
ed
la
un
ch
in
th
e
ne
xt
tw
o
ye
ar
s
to
fa
ci
lit
at
e
th
e
tr
an
sp
or
ta
ti
on
in
th
e
ne
w
co
un
tr
y
la
un
ch
in
th
e
ne
xt
tw
o
ye
ar
s
to
fa
ci
lit
at
e
th
e
tr
an
sp
or
ta
ti
on
in
th
e
ne
w
co
un
tr
y
P
ri
nc
ip
le
4:
D
if
fe
re
nt
ia
te
pr
od
uc
tc
lo
se
r
to
th
e
cu
st
om
er
an
d
sp
ee
d
co
nv
er
si
on
ac
ro
ss
th
e
su
pp
ly
ch
ai
n
9
T
he
re
is
a
fa
ir
am
ou
nt
of
un
de
rs
ta
nd
in
g
ab
ou
tr
eg
ul
at
or
y
re
qu
ir
em
en
t
am
on
g
pl
an
t
pe
rs
on
ne
lt
ha
t
pa
ck
ag
in
g
co
nfi
gu
ra
ti
on
fo
r
w
ra
pp
in
g
of
ph
ar
m
ac
eu
ti
ca
lp
ro
du
ct
s
sh
ou
ld
be
du
ly
sy
nc
hr
on
iz
ed
w
it
h
ve
hi
cl
e
ar
ra
ng
em
en
ts
as
pe
r
re
gu
la
to
ry
no
rm
s
in
cu
st
om
er
’s
co
un
tr
y;
ot
he
rw
is
e,
th
e
co
ns
ig
nm
en
t
sh
al
lb
e
re
tu
rn
ed
84
T
he
re
is
a
fa
ir
am
ou
nt
of
un
de
rs
ta
nd
in
g
ab
ou
tr
eg
ul
at
or
y
re
qu
ir
em
en
t
am
on
g
su
pp
ly
ch
ai
n
pe
rs
on
ne
lt
ha
t
pa
ck
ag
in
g
co
nfi
gu
ra
ti
on
fo
r
w
ra
pp
in
g
of
ph
ar
m
ac
eu
ti
ca
lp
ro
du
ct
s
sh
ou
ld
be
du
ly
sy
nc
hr
on
iz
ed
w
it
h
ve
hi
cl
e
ar
ra
ng
em
en
ts
as
pe
r
re
gu
la
to
ry
no
rm
s
in
cu
st
om
er
’s
co
un
tr
y;
ot
he
rw
is
e,
th
e
co
ns
ig
nm
en
t
sh
al
lb
e
re
tu
rn
ed
51
10
M
an
uf
ac
tu
ri
ng
pl
an
t’
s
qu
al
it
y
as
su
ra
nc
e
pe
rs
on
ne
lh
av
e
th
e
te
ch
ni
ca
lu
nd
er
st
an
di
ng
of
th
e
m
ic
ro
bi
al
ri
sk
be
ca
us
e
of
th
e
us
ag
e
of
ho
se
pi
pe
s
ki
nd
of
tr
an
sf
er
ai
ds
us
ed
fo
r
un
lo
ad
in
g
of
ac
ti
ve
ph
ar
m
ac
eu
ti
ca
li
ng
re
di
en
ts
fr
om
si
lo
tr
uc
ks
at
cu
st
om
er
’s
en
d
87
T
ra
ns
po
rt
pe
rs
on
ne
lh
as
te
ch
ni
ca
lu
nd
er
st
an
di
ng
of
th
e
m
ic
ro
bi
al
ri
sk
be
ca
us
e
of
th
e
us
ag
e
of
ho
se
pi
pe
s
ki
nd
of
tr
an
sf
er
ai
ds
us
ed
fo
r
un
lo
ad
in
g
of
ac
ti
ve
ph
ar
m
ac
eu
ti
ca
l
in
gr
ed
ie
nt
s
fr
om
si
lo
tr
uc
ks
at
cu
st
om
er
’s
en
d
62
11
T
he
re
is
an
ef
fe
ct
iv
e
co
m
m
un
ic
at
io
n
av
ai
la
bl
e
w
it
hi
n
m
an
uf
ac
tu
ri
ng
pl
an
t
to
en
su
re
th
at
pr
od
uc
ts
ar
e
di
ff
er
en
ti
at
ed
ba
se
d
on
th
ei
r
th
er
ap
eu
ti
c
pr
op
er
ti
es
,
fa
ci
lit
at
in
g
th
e
m
od
e
of
tr
an
sp
or
ta
ti
on
88
T
he
re
is
an
ef
fe
ct
iv
e
co
m
m
un
ic
at
io
n
av
ai
la
bl
e
fo
r
tr
an
sp
or
te
rs
an
d
lo
gi
st
ic
s
pe
rs
on
ne
lt
o
en
su
re
th
at
pr
od
uc
ts
ar
e
di
ff
er
en
ti
at
ed
ba
se
d
on
th
ei
r
th
er
ap
eu
ti
c
pr
op
er
ti
es
,
fa
ci
lit
at
in
g
th
e
m
od
e
of
tr
an
sp
or
ta
ti
on
56
P
ri
nc
ip
le
5:
M
an
ag
e
so
ur
ce
s
of
su
pp
ly
st
ra
te
gi
ca
lly
to
re
du
ce
th
e
to
ta
lc
os
to
f
ow
ni
ng
m
at
er
ia
ls
an
d
se
rv
ic
es
12
T
he
co
ld
ch
ai
n
ph
ar
m
ac
eu
ti
ca
lp
ro
du
ct
s
sh
al
ll
os
e
it
s
th
er
ap
eu
ti
c
pr
op
er
ty
if
ex
po
se
d
to
ro
om
te
m
pe
ra
tu
re
87
T
he
co
ld
ch
ai
n
ph
ar
m
ac
eu
ti
ca
lp
ro
du
ct
s
sh
al
ll
os
e
it
s
th
er
ap
eu
ti
c
pr
op
er
ty
if
ex
po
se
d
to
ro
om
te
m
pe
ra
tu
re
51
13
D
ur
in
g
re
ce
ip
t
of
ra
w
m
at
er
ia
ls
lik
e
ac
ti
ve
ph
ar
m
ac
eu
ti
ca
l
in
gr
ed
ie
nt
s,
te
m
pe
ra
tu
re
ex
cu
rs
io
ns
ob
se
rv
ed
in
tr
an
sp
or
t
da
ta
sh
al
lb
e
co
ns
id
er
ed
as
no
n-
co
nf
or
m
an
ce
ha
vi
ng
th
e
po
te
nt
ia
lo
fb
at
ch
re
je
ct
io
n
82
D
ur
in
g
re
ce
ip
t
of
ra
w
m
at
er
ia
ls
lik
e
ac
ti
ve
ph
ar
m
ac
eu
ti
ca
l
in
gr
ed
ie
nt
s,
te
m
pe
ra
tu
re
ex
cu
rs
io
ns
ob
se
rv
ed
in
tr
an
sp
or
t
da
ta
sh
al
lb
e
co
ns
id
er
ed
as
no
n-
co
nf
or
m
an
ce
ha
vi
ng
th
e
po
te
nt
ia
lo
fb
at
ch
re
je
ct
io
n
32
(c
on
ti
nu
ed
)
Table III.
Good
transportation
practices
313
Se
ri
al
nu
m
be
r
A
dh
er
en
ce
to
pr
ac
ti
ce
du
ri
ng
m
an
uf
ac
tu
ri
ng
A
dh
er
en
ce
to
pr
ac
ti
ce
du
ri
ng
tr
an
sp
or
ta
ti
on
C
on
tr
ol
s
du
ri
ng
m
an
uf
ac
tu
ri
ng
op
er
at
io
ns
%
po
pu
la
ti
on
ag
re
ed
C
on
tr
ol
s
du
ri
ng
di
st
ri
bu
ti
on
op
er
at
io
ns
%
po
pu
la
ti
on
ag
re
ed
14
T
he
pr
ov
is
io
n
of
pe
ri
od
ic
ev
al
ua
ti
on
(a
ud
it
/i
ns
pe
ct
io
n)
an
d
ap
pr
ov
al
of
co
nt
ra
ct
or
an
d
su
bc
on
tr
ac
to
rs
ar
e
di
lig
en
tl
y
fo
llo
w
ed
at
th
e
pl
an
t
le
ve
l
89
T
he
pr
ov
is
io
n
of
pe
ri
od
ic
ev
al
ua
ti
on
(c
ap
ac
it
y/
co
m
pe
te
nc
y)
an
d
ap
pr
ov
al
of
co
nt
ra
ct
or
an
d
su
bc
on
tr
ac
to
rs
ar
e
di
lig
en
tl
y
fo
llo
w
ed
at
su
pp
ly
ch
ai
n
le
ve
l
48
P
ri
nc
ip
le
6:
D
ev
el
op
a
su
pp
ly
ch
ai
n-
w
id
e
te
ch
no
lo
gy
st
ra
te
gy
th
at
su
pp
or
ts
m
ul
ti
pl
e
le
ve
ls
of
de
ci
si
on
-m
ak
in
g
an
d
gi
ve
s
a
cl
ea
r
vi
ew
of
th
e
fl
ow
of
pr
od
uc
ts
,s
er
vi
ce
s
an
d
in
fo
rm
at
io
n
15
T
he
re
is
te
ch
no
lo
gy
-b
as
ed
co
m
m
un
ic
at
io
n
av
ai
la
bl
e
at
pl
an
t
le
ve
lr
eg
ar
di
ng
pr
od
uc
t
re
ca
ll,
w
hi
ch
ha
s
st
at
ut
or
y
ti
m
e
lim
it
of
30
da
ys
in
se
ve
ra
lc
ou
nt
ri
es
91
T
he
re
is
te
ch
no
lo
gy
-b
as
ed
co
m
m
un
ic
at
io
n
av
ai
la
bl
e
at
lo
gi
st
ic
s
an
d
tr
an
sp
or
t
le
ve
lr
eg
ar
di
ng
pr
od
uc
t
re
ca
ll,
w
hi
ch
ha
s
st
at
ut
or
y
ti
m
e
lim
it
of
30
da
ys
in
se
ve
ra
lc
ou
nt
ri
es
81
16
T
he
te
ch
no
lo
gy
st
ra
te
gy
sh
ou
ld
co
ve
r
th
e
in
te
gr
at
ed
as
pe
ct
s
th
ro
ug
ho
ut
th
e
su
pp
ly
ne
tw
or
k
fo
r
de
ci
si
on
-m
ak
in
g
in
an
ef
fe
ct
iv
e
m
an
ne
r
87
T
he
y
sh
ou
ld
ex
te
nd
th
e
te
ch
no
lo
gy
st
ra
te
gy
th
ro
ug
ho
ut
th
e
su
pp
ly
ne
tw
or
k
to
in
te
gr
at
e
th
e
de
ci
si
on
-m
ak
in
g
in
a
tr
an
sp
ar
en
t
m
an
ne
r
51
17
D
ev
ia
ti
on
fr
om
co
nt
ro
lle
d
ro
ut
e
fo
r
tr
an
sp
or
ta
ti
on
sh
al
l
vi
ol
at
e
th
e
no
rm
s
of
tr
an
sp
or
t
va
lid
at
io
n
st
ra
te
gy
an
d
ca
n
ca
us
e
re
je
ct
io
n
of
pr
od
uc
ts
on
qu
al
it
y
gr
ou
nd
,e
ve
n
th
ou
gh
oc
cu
pa
nc
y
of
tr
an
sp
or
t
ve
hi
cl
e
is
an
ef
fe
ct
iv
e
to
ol
to
en
ha
nc
e
pr
ofi
ta
bi
lit
y
77
D
ev
ia
ti
on
fr
om
co
nt
ro
lle
d
ro
ut
e
fo
r
tr
an
sp
or
ta
ti
on
sh
al
l
vi
ol
at
e
th
e
no
rm
s
of
tr
an
sp
or
t
va
lid
at
io
n
st
ra
te
gy
an
d
ca
n
ca
us
e
re
je
ct
io
n
of
pr
od
uc
ts
on
qu
al
it
y
gr
ou
nd
,e
ve
n
th
ou
gh
oc
cu
pa
nc
y
of
tr
an
sp
or
tv
eh
ic
le
is
an
ef
fe
ct
iv
e
to
ol
to
en
ha
nc
e
pr
ofi
ta
bi
lit
y
51
P
ri
nc
ip
le
7:
A
do
pt
ch
an
ne
l-s
pa
nn
in
g
pe
rf
or
m
an
ce
m
ea
su
re
s
to
ga
ug
e
co
lle
ct
iv
e
su
cc
es
s
in
re
ac
hi
ng
th
e
en
d-
us
er
ef
fe
ct
iv
el
y
an
d
ef
fi
ci
en
tly
18
T
he
re
ar
e
es
ta
bl
is
he
d
ke
y
pe
rf
or
m
an
ce
m
ea
su
re
s
of
op
er
at
io
n
(e
.g
.m
ar
ke
tr
ec
al
ld
at
a,
ba
tc
h
re
je
ct
io
ns
,e
tc
.)
to
ga
ug
e
co
lle
ct
iv
e
su
cc
es
s
in
sa
ti
sf
yi
ng
th
e
ne
ed
fo
r
en
d-
us
er
ef
fe
ct
iv
el
y
an
d
ef
fi
ci
en
tl
y
68
T
he
re
ar
e
es
ta
bl
is
he
d
ke
y
pe
rf
or
m
an
ce
m
ea
su
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s
of
tr
an
sp
or
ta
ti
on
(e
.g
.c
os
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o
ga
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co
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ct
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su
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sa
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sf
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th
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ne
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fo
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d-
us
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ef
fe
ct
iv
el
y
an
d
ef
fi
ci
en
tl
y
34
(c
on
ti
nu
ed
)
Table III.
IJPHM
13,3
314
Se
ri
al
nu
m
be
r
A
dh
er
en
ce
to
pr
ac
ti
ce
du
ri
ng
m
an
uf
ac
tu
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A
dh
er
en
ce
to
pr
ac
ti
ce
du
ri
ng
tr
an
sp
or
ta
ti
on
C
on
tr
ol
s
du
ri
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m
an
uf
ac
tu
ri
ng
op
er
at
io
ns
%
po
pu
la
ti
on
ag
re
ed
C
on
tr
ol
s
du
ri
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di
st
ri
bu
ti
on
op
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at
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ns
%
po
pu
la
ti
on
ag
re
ed
19
In
ph
ar
m
ac
eu
ti
ca
lb
us
in
es
s,
th
er
e
is
a
st
an
da
rd
op
er
at
in
g
pr
oc
ed
ur
e
to
m
ea
su
re
th
e
pe
rf
or
m
an
ce
w
it
h
he
lp
of
qu
al
it
y
m
et
ri
cs
lik
e
cu
st
om
er
co
m
pl
ai
nt
s
an
d
ba
tc
h
re
je
ct
io
ns
fr
om
th
e
m
ar
ke
t
79
In
ph
ar
m
ac
eu
ti
ca
lb
us
in
es
s,
th
er
e
is
a
st
an
da
rd
op
er
at
in
g
pr
oc
ed
ur
e
to
m
ea
su
re
th
e
pe
rf
or
m
an
ce
th
ro
ug
h
th
e
in
di
ce
s
lik
e
th
e
nu
m
be
r
of
ba
tc
h
da
m
ag
es
du
ri
ng
tr
an
sp
or
ta
ti
on
39
20
T
he
re
vi
ew
of
te
m
pe
ra
tu
re
da
ta
lo
gg
er
s
tr
an
sp
or
te
d
al
on
g
w
it
h
pr
od
uc
t
ba
tc
h
is
en
su
re
d
by
co
m
pe
te
nt
ba
tc
h
re
le
as
in
g
au
th
or
it
y
an
d
an
y
pi
tf
al
ls
in
th
e
ai
r
ca
rg
o
or
se
a
tr
av
el
m
od
e
le
ad
fi
na
lly
to
th
e
m
on
et
ar
y
lo
ss
be
ca
us
e
of
ba
tc
h
re
je
ct
io
n
79
T
he
re
vi
ew
of
te
m
pe
ra
tu
re
da
ta
lo
gg
er
s
tr
an
sp
or
te
d
al
on
g
w
it
h
pr
od
uc
t
ba
tc
h
is
en
su
re
d
by
co
m
pe
te
nt
su
pp
ly
ch
ai
n
pe
rs
on
ne
la
nd
an
y
pi
tf
al
ls
in
th
e
ai
r
ca
rg
o
or
se
a
tr
av
el
m
od
e
le
ad
fi
na
lly
to
th
e
m
on
et
ar
y
lo
ss
be
ca
us
e
of
ba
tc
h
re
je
ct
io
n
61
Table III.
Good
transportation
practices
315
3.3.3 Inference from data analysis. As tobs > tcrit, we reject the null hypothesis and conclude
with 95 per cent confidence that there is the difference in adherence of principles of SCM
within manufacturing plant and that during transportation practices is not solely because of
chance. There is the clear inference drawn that control activities within manufacturing plant
are better than the control exercised during transportation operations which have the
potential to impact the overall drug quality.
4. Discussion
The integrated logistics for SCM requires a strategic objective to transport goods between
suppliers, manufacturing or distribution locations, warehousing facilities and all involved
intermediate points of the supply chain (Collin PF, 2003). The researchers expressed hope
that US Food and Drug Administration (FDA) would reinforce the principles of GDP to
make a logical progress in the extended regions (Jeff Clark, 2014).
According to FreightWatch International (2016), the pharmaceutical pilfering accounted
for 9 per cent of all recorded cargo theft incidents in Italy in a year. This is nine times of the
average number (1 per cent) recorded in the whole region of Europe, Middle East and Africa
(EMEA). A few research studies found that there are different approaches to address the
criminal threats (Ekwall, et al., 2016). For the different countermeasures to be effective, it
needs to be implemented with a holistic viewpoint. Ray Goff (2012) has observed that if the
changing nature of the shipping lane, if not monitored, then this can affect the temperature
of the product (Ray Goff, 2012). This is an important aspect affecting the quality of
pharmaceutical products. IMS Health estimates that the Compound Annual Growth Rate
(CAGR) for global pharmaceutical sales of over $1bn from 2014 to 2019 will be
approximately 5 per cent. Thus, the number of losses incurred in total dollars will continue
to rise in a similar fashion (IMS, 2014).
The fact sheet issued by Interpol mentioned a significant increase in the manufacture,
trade and distribution of counterfeit, diverted, stolen and illicit medicines and medical
devices (Interpol, 2012).
Official Journal of European Union (2015) has also clarified that active substances should
be stored under the conditions specified by the manufacturer, for example, controlled
temperature and humidity when necessary, and in such a manner to prevent contamination
and/or mix up (EUR-Lex, 2015).
With the implementation of GDP in the European Union, it is inevitable that the FDA will
strengthen GDP as well. This is one solid foundation for securing the “identity, strength,
quality and purity” of all pharmaceutical products as defined under US federal law
described under Part 211 of US Code of federal regulation.
The Chinese Minister released Good Supply Practice for Pharmaceutical Products
guidance on behalf of People’s Republic of China which is a set of basic rules for drug
distribution management and quality control, during drug purchase, storage, sales,
transportation and other links so as to guarantee the quality of drugs (Chen Zhu, 2013).
The international trade statistics highlights the fact that pharmaceuticals recorded the
second-highest average growth rates for exports (11 per cent) between 1995 and 2014 (WTO,
2015). With the growing pharmaceutical trades, the transportation shall increase
simultaneously. Hence, the transportation quality system needed to be customized in line with
the specific requirement of drug regulatory agencies and aspirations of customers and patients.
This general information chapter of United States Pharmacopeia (USP) describes good
storage and distribution practices to ensure that drug products (medicines) reach the end-
user (practitioners and patient consumers) with quality intact.
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The general chapters of USP have described issues like Good Storage and Shipping
Practices. The principles laid down in USP are relevant to all pharmaceutical organizations
and persons involved in any facet of the storage and distribution of all drug products,
including importers and exporters of record, third-party logistics providers, freight
forwarders and consolidators, mail distributors, etc. (USP, 2014).
The drug products must be transported in a manner that ensures the products will be
maintained within an acceptable temperature range as defined in the approved label and the
conditions supported by stability data (Health Canada, 2011). Temperature excursions
beyond the respective labelled storage conditions for brief periods may be acceptable based
on backed up with stability data wherein rationale exists to demonstrate that product
quality is not affected.
The temperature excursions during transport are not unusual events and transportation
is one of the least trustworthy pharmaceutical processes (Claude Ammann, 2013). It has
been observed that enhanced understanding of pharmaceutical SCM shall help to embark
upon the challenges of intricacy because of market growth and regulatory requirements
(Ebel et al., 2013). The information on local transportation access, laws, customs and politics
are the imperative factors to properly function in the targeted country and is vital for
insightful supply chain considerations (Baines, 2013). These enable the supply chain
managers to tackle the situation in view of recent disease patterns and requirements in
addition to their current products range (Susan Thaul, 2013). Thus, the good transportation
is an essential element of the quality management system for the pharmaceutical
entrepreneur that shall be envisaged with SCM just like hands and glove relationship.
5. Results
The magnitude of the gap in practices of product distribution can be understood from the
fact that US Congress has addressed pharmaceutical supply chain security several times
over the past hundred years (Susan Thaul, 2013). US Congressional Research Service (CRS)
apprehended that chain is probably vulnerable, and in case of the supply chain integrity is
broken, a pharmacist may provide a counterfeit product dangerous swapped item. CRS
further adds that even though current federal law and actions are in place, the opportunities
for drug security violations on the way of supply chain continue to exist. The end-user
might also have been provided mishandled pharmaceutical products that are substandard
or is expired. In addition to the potential harm to patients, these security breaches can affect
a manufacturer’s goodwill and pecuniary status. The system GTP is the set of activities
involved in the transportation of pharmaceutical products that are followed product release
from manufacturer’s site to distribute them to drug retailers in line with principles of SCM.
5.1 Setting up a direction for resolution
Based on literature gap and the analysis of hypothesis study results (H1 = 0), it is found that
there is a need for evolution of framework for SCM in pharmaceutical GTP. The framework
model shall enable the stakeholders to streamline the transportation practices to prevent:
� Impact on quality of pharmaceutical products because of adverse weather conditions.
GTP is vital for all drug products, other than for cold chain pharmaceutical products.
Storage conditions for cold chain require the temperature between 2 and 8°C. Drugs
quality deterioration depends upon the storage temperature, which can be estimated
through stability and freeze-thaw studies. The vaccines are prone to improper
handling during transportation, hence require the special approach.
Good
transportation
practices
317
� Anti-counterfeiting during supply chain network is a growing menace (Swaminath,
2008). Through effective transportation control, the scope of counterfeiting can be
effectively reduced.
It was found that there is hardly any literature available for managing pharmaceutical
product transportation through the SCM-based approach. In spite of the growing
pharmaceutical transportation, the guidance paper from drug regulatory agencies could not
elaborate the practical aspect of the quality system that shall help transportation and
logistics personnel in making their policy conforming to quality goal.
5.2 Application of principles of supply chain management in ‘pharmaceutical good
transportation practices’
The key issues have been observed in pharmaceutical SCM include the cost to poor quality
of transportation resulting in rejections, product security and the trade-free zone borders
(Figure 2). In line with philosophy given by Anderson highlighting the seven principles of
the supply chain, the concept of pharmaceutical GTP has been revisited (Anderson David L,
et al., 1997).
5.2.1 Principle 1: the product profile as per segment customer’s needs and special charac-
teristics of pharmaceutical products. To cater the customer’s needs of particular segment,
there is requirement of in-depth knowledge of products handling, storage and expiration.
Based on product knowledge of segment, the technical agreement should clearly spell out
the service needs. The customers can be segmented based on the service needs of distinct
groups (Figure 3).
The GTP provision should be capable to ensure that pharmaceutical product range is
divided into market segments on the basis of product characteristics and sensitivity criteria
because of specific storage requirements, such as:
� normal product that can be stored in ambient environment conditions;
� cold chain products that require storage conditions between 2 and 8°C;
� injectable products that require special handling precautions; and
� biological products and vaccines that require storage under refrigerated conditions.
Figure 2.
A perspective of
principles of supply
chain management
Management
of Pharma
Transportation
CUSTOMER’S
NEEDS
Product sensi�vity
PRODUCT CLOSER
TO THE
CUSTOMER
Connec�vity
LOGISTICS
NETWORK
Mode of
distribu�on
DEMAND –
PLANNING
Market fluctua�ons
OUTSOURCE
STRATEGICALLY
TECHNOLOGY
BASED STRATEGY
CHANNEL-
PERFORMANCE
Market complaint
1
5
4
32
76
IJPHM
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Database of impact on quality of pharmaceutical products because of adverse weather
conditions shall be the important asset. Vaccines have the tendency to naturally biodegrade
over time and storage outside the specified temperature limit, including that during
transport, may speed up the loss of potency, which cannot be reversed. While segmenting
the customer’s need, it must be remembered that a variety of quality issues come up during
transportation of pharmaceutical products. This quality risk may result into a business loss
and damage to goodwill of organizations, such as:
� Product mix-up during transportation.
Strip of a product with 1 mg strength could mix up with that of 2 mg tablets because of
resemblance in product package appearance:
� Deterioration of product quality.
During the course of replenishment of shipment, the products are sometimes kept out of
container and port warehouse, thereby posing quality risk to them (Carli Derifield, 2016).
The responsible pharmaceutical organization should make the standard operating
procedure available to each person handling cold chain products throughout storage and
distribution operations:
� Discoloration of formulation.
Because of exposure to temperature, the color of suspension may change and discoloration
can be noticed, which shall be a non-conformance to the specified color of product:
� Microbial contaminations.
The microbial contamination because of pilferage or sun specified storage shall cause
adverse drug reaction and that may be fatal in nature:
� Label mutilation.
The labels of pharmaceutical products have great importance because of its text content;
hence, mutilation in any form during the course of transportation is an undesired action:
� Loss of product integrity.
Figure 3.
Considerations based
on product
characteristics
NORMAL
PRODUCTS
COLD
CHAIN
INJECTABLE
VACCINES
WAREHOUSEW
Refrigerated Van
Wider choice
Careful handling
Manufacturing Site
Good
transportation
practices
319
Because of mishandling, the tablets or capsule units may break through cutline (also called
score line) and few active particles can fall down.
Temperature monitoring and recording devices such as data logger should be installed
within containers used to transport the pharmaceutical products. There should be auto-
indicators in such measuring devices to alert concerned persons in case of excursion beyond
specified environmental conditions (Claude Ammann, 2013).
5.2.2 Principle 2: Align the supply chain network in line with transport validation
requirement. Cargo vans, containers, airplane, railway and ships are popular modes for the
transportation of pharmaceutical products. As pharmaceutical sector has unique business
requirement because of the perishable characteristics, there is growing need to customize the
logistics network to avoid the impact on product quality and maximize the business output
(Figure 4). The mode of distribution should be designed in line with following:
� Customer’s technical inputs about products shelf life, stability and storage
conditions during transit should be considered.
� Delivery compliance to meet the market demand, service requirements and
profitability of customer segments shall prevent market rejection and pharmaceutical
product recall because of product older than expiration period.
Transport validation data for a transit route with specific set of logistics should be
considered as a baseline for pharmaceutical distribution operations (GMP News, 2014). The
transport validation should be clearly defined to support multiple levels of quality assurance
and gives a clear view of the flow of products, services and information.
In view of the security requirement against the potential of theft during transport, the
sealed security of pharmaceutical product containers are very important. Recently, the
cases of theft of pharmaceuticals during transport in Europe are on the rise (Ekwall
et al., 2016). As a part of GTP, the transportation along the SCM network must be
Figure 4.
Transport
validation – a
prerequisite to decide
the route of transport
P
ha
rm
ac
eu
tic
al
M
an
uf
ac
tu
ri
ng
P
la
nt
Central
Warehouse
Regional
Warehouse Distributor
Pharmacy
Drug Retailer
Ship Yard Warehouse Pharmacy
Airport yard
Warehouse Pharmacy
Warehouse Pharmacy
Na�onal Transit Network
Cu
st
o
m
er
s
a
n
d
P
a�
en
ts
TRANSPORTATION VALIDATION ROUTE -3
TRANSPORTATION VALIDATION ROUTE -2
TRANSPORTATION VALIDATION ROUTE -1
IJPHM
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320
validated to have consistent distribution operation. Validation is a process to collect the
documentary evidence that a process consistently produces result meeting pre-
determined criteria. The transport validation refers to the evidence for demonstrating
the validity of transportation chain, when operated within established parameters, can
perform effectively and consistently deliver the pharmaceutical product meeting its pre-
determined criteria and quality parameters during transit from factory premises to the
destination (PICS, 2007).
The transport validation report should be chosen for the most critical path of the
distribution network following:
� scope of the distribution network;
� responsibility of validation team member;
� validation acceptance criteria;
� environment monitoring instrument details;
� detailed procedure;
� result outcome recording;
� deviations, if any;
� report approval by quality unit of product manufacturer; and
� validation report conclusion and recommendations.
Refrigerated containers (also called reefer container) should be mapped before use and
calibrated temperature monitoring devices should be installed. If temperature excursions
out of specified temperature conditions are observed, then the associated quality risk
leading to financial losses must be analyzed.
5.2.3 Principle 3: Perceiving the right signal of particular pharmaceutical demand as a
baseline for planning of transportation need. The supply and demand pattern for the
pharmaceutical industry works differently than a normal trend. This is because the
pharmaceutical industry functions in a dissimilar way than others. Pharmaceutical products
are always in demand and any shortages in medicine supply give rise to the sale of falsified
and counterfeit drugs (Ossola, 2015).
Interpol fact sheet (2014) finds a total increase in increase in the manufacture, trade and
distribution of falsified, diverted, stolen and illicit medicines. In some areas of Asia, Africa
and Latin America, falsified medical products can form around one-third of the market
(Interpol, 2012). Catching and evaluating the right signal of pharmaceutical demand in
advance timing for the planning of transportation need may prove the business worth.
Based on market demand, the mode of transportation can be decided, for example, the
planning of transportation of medicines to flood-affected zone through aircraft may enhance
company image because of delivery compliance on time. There is need to understand
the market signal to forecast the demand for particular product in a region with help of
suitable tools like:
� outbreak because of natural calamity or because of specific reason;
� disease pattern; and
� regulatory compliance strategies.
The alignment of demand with planning across all the nodes of supply chain shall help to
plan optimal resource allocation (Figure 5).
Good
transportation
practices
321
5.2.4 Principle 4: Differentiate pharmaceutical repackaging requirement close to
customer. World Health Organization (WHO) regularly updates the disease outbreak news
in its fact sheets, which can be the useful source of information to pharmaceutical industry
in extracting the manufacturing plan or repackaging operation near to a region where
particular medicine has to be distributed (Figure 6).
Although the supply chain’s logistics cell of pharmaceutical industry would find it
difficult to put it forward in decision-making regarding the location of warehouse or
repackaging, it is worth to calculate the return on investment to further take logical decision
to reduce transportations. A few cases as follows have been recommended for reference:
� Under the purview of WHO’s disease-specific recommendations, it is accepted that
requirements for calcium might vary from culture to culture for dietary, genetic, lifestyle
and geographical reasons (WHO, 2014). In another report by Food and Agriculture
Organizations (FAO, 2004), it is also found that calcium intake of people in the USA and
Canada is above 1,000 mg, whereas that in the far East country is close to 300 mg. To
avoid transit cost, it shall be a wise decision for an interpreter to set up a manufacturing
plant for calcium rich food supplement close to the USA and Canada (WHO, 2016).
Figure 5.
Optimization of
demand and
availability of
transport options
Transport
availability
Available
stocks of
medicines
Supply
Demand
P*
Q*
Transport
constraint
Q s
PF
Shortage of medicine
shall augment counterfeit business
Q d
D*
Figure 6.
Differentiate
pharmaceutical
repackaging
requirement
Drug
Manufacturer-2
Repackaging
and Logis�cs
Support Centre
Calcium based
medicines are
consump�on is
high in USA &
Canada
Anemia is
prevalent in
Asian countries
A high number of
pa�ents HIV are
in Africa
Drug
Manufacturer-3
Drug
Manufacturer-1
Drug
Manufacturer-4
IJPHM
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322
� In view of the rampant cases of anemia in Asia Pacific region, the iron-based
pharmaceutical manufacturing and warehousing facility should locate in that region
only to reduce the cost and implications of long route transportation (WHO, 2014).
� The AIDS medicines are on demand in African countries; hence, centers for
repackaging of HIV medicines should be established near that region to avoid the
transportation load (WHO, 2016).
Knowledge of local transportation access, laws, customs and politics is also very important
to properly assess the feasibility of setting up operations in the targeted country and is
critical for understanding supply chain considerations (Susan Thaul, 2013).
5.2.5 Principle 5: Outsourcing the supply strategically. This biggest challenge of
pharmaceutical SCM is control of the counterfeit and falsified drugs infiltrating during the
distribution process. The pharmaceutical industry should outsource the supply strategically
to reduce the total cost of transportation and distribution. A study at MIT Centre for
Transportation and Logistics that the two factors of outsourcing strategy primarily decide
the dependence. This dependence can acquire two forms of design and execution (Andrea
and Dana Meyer, 2002) (Figure 7).
Technical competency of transporters across the network is important to ensure that
special pharmaceutical products would be handled appropriately, such as psychotropic and
narcotic products require special licenses. A pharmaceutical organization aspirant of
outsourcing the logistics, require a partner with following characteristics:
� technologically expert in designing and execution of new systems on an
international arena; and
� capable to illustrate the return of computable value to in company.
Thus, the pharmaceutical company may develop the knowledge to design a transport cycle,
with mode of transportation. In full outsourcing, the company would be dependent on both
design and manufacturing. The approved list of subcontractors and transporters should be
made on the basis of their technical capabilities. Technical design expertise shall include the
knowledge of paramount permissible storage time during transit and shipment should be
established on the basis of scientific aspects, with following considerations:
Figure 7.
Outsource decision to
be taken based on
strength and
weakness
STRONG
TRANSPORTATION
DESIGN EXPERTISE
&
STRONG
TRANSPORTATION
EXPERTISE
WEAK
TRANSPORTATION
DESIGN EXPERTISE
&
WEAK
TRANSPORTATION
EXPERTISE
TR
AN
SP
O
RT
P
LA
N
E
XE
CU
TI
O
N
E
XP
ER
TI
SE
TRANSPORT PLAN DESIGN EXPERTISE
Good
transportation
practices
323
� means of transportation;
� length of transit;
� prescribed storage condition;
� packaging and container arrangements;
� scientific stability study results; and
� freeze-thaw data.
There should be standard operating procedures for managing the transportation of
pharmaceutical products. Due considerations should be there for the characteristics of the
pharmaceutical products that shall have the significant impact on product quality.
Environment-controlled vehicles are used to transport the pharmaceutical products. The
temperature mapping should be carried out according to the guidelines laid down by WHO
(2011) that entails following phases:
� preapproved scope, objective and execution plan;
� realization of execution plan; and
� report approval and recommendations.
5.2.6 Principle 6: Extend the technology strategy throughout the supply network to integrate
the decision-making in a transparent manner. Pharmaceutical entrepreneurs should make
use of technology-based software systems that shall send the electronic message to haulers,
reduce freight costs by utilizing most favorable option, shipment. The use of software-based
transportation management system, e-auction and contract bidding to choose logistics sub-
contractors for pharmaceutical products can be helpful to transportation strategy (Dan
Gilmore, 2007). A global manufacturer of measurement instruments refers to the challenge
of international logistics, the different regulations of the countries concerned require
sophisticated serialization solution, as pharmaceutical products are manufactured, supplied
to market and put on sale by a multiple of parties before the product finally reaches to the
customer (Ludasi et al., 2018). A compassionate technological strategy should be present to
assist the supply chain operation to facilitate the decision-making process (Figure 8).
It is envisaged that as a part of pharmaceutical GTP, following aspects should be
harmonized appropriately:
� automated transportation management system to correctly represent the location of
products with date and timings;
� e-auctions and online contracts bidding to hire the transportation and logistics
solutions;
� serialization process for verifiable “Track and Trace”; and
� automated shipper loading and unloading system to avoid manual intervention.
Serialization technique is one of the latest improvements in pharmaceutical SCM. The
unique identifier with the randomized serial number and tamper-evident packaging is a
helpful tool to tackle the menace of counterfeit and falsified drugs prevailing in the market
through infiltration during drugs distribution.
5.2.7 Principle 7: Embrace a channel spanning key performance measures to gauge col-
lective success in reaching the end-user effectively and efficiently. A pharmaceutical
organization should establish key performance indicators of each span of transit to estimate
the collective success in the arrival of products to the end-user effectively and efficiently. An
IJPHM
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324
approach to aggregate the loss and gain of each span of transportation shall be used to
collect and analyze the financial success.
The causes of financial losses on the following account must be considered through
channel straddling performance measures:
� shipment theft during transit or misplaced because of wrong address tracking
number;
� consignment destroyed because of product inventory crossed the expiration period; and
� temperature excursion caused the product quality deterioration.
Total losses during transportation should be estimated through the sum total of individual
losses during each channel of entire transportation span (Figure 9).
Indicators like market complaint data, product recall cases and regulatory actions on
account of above must be analyzed and tracked for improvement in reaching the medicinal
products to retailers and pharmacies.
5.3 Implementation strategy – Approval of standard operating procedure and awareness
The major part of pharmaceutical business operation is handled through the standard
operating procedure (SOP) because of periodic inspection by drug regulatory and
enforcement agencies. There is the institutionalized provision in the pharmaceutical
industry to implement GMP at manufacturing plant level. Furthermore, there is a need to
enhance the system implementation approach up to transportation operation. The essential
content of such procedure detailing out the GTP should be critically reviewed by the cross-
functional team comprising experts from the supply chain, transportation and logistics and
quality assurance.
Figure 8.
Technology based
control and
communications
AUTOMATED
TRANSPORTATION
MANAGEMENT
Harmonized
documenta�on
Communica�on
and updates
ONLINE BIDDING
FOR
TRANSPORTERS
Online-contract
bidding
Structured
agreement
SERIALIZATION
PROCESS
Track and trace
Reconcilia�on at
appropriate level
AUTOMATED
SHIPPER HANDLING
SYSTEM
Recogni�on of
label and box
pelle�za�on
Loading and
unloading to
transport
EXTEND THE TECHNOLOGY STRATEGY THROUGHOUT SUPPLY NETWORK
TECHNOLOGY BACKED UP DRUG REGULATORY CONTROLS
FINGER PRINT
TECHNIQUES FOR GENUINELY CHECK
Te
ch
ni
ca
l C
om
pe
te
nc
y
of
t
ra
ns
po
rt
er
s
A
ut
o
co
nt
ro
ls
a
nd
r
ev
ie
w
Good
transportation
practices
325
The content of SOP on GTP should be designed to address all seven principles of SCM with
seamless alignment with technical requirement laid down in regulatory guidelines for
current GMP with an appropriate focus as follows:
� The product profile as per segment customer’s needs regarding superior quality
and handling characteristics.
� The transport validation requirement should be plugged in with the impact of
length and mode of transportation on potential of quality deteriorations. The supply
chain personnel and logistics operators should bear and refer ‘List of Time and
temperature sensitive pharmaceutical product’ (TTSPP).
� Electronic mode of communication and control for planning and arranging resource
for pharmaceutical demand should be used as a baseline for the planning of
transportation need.
� Logical protocol is needed to differentiate pharmaceutical repackaging requirement
close to the customer to handle replenishment of products during transportation.
� Methodology, strategy and impact because of outsourced activities of transportation
should be logically dealt out to enhance understanding among all concerned. The
drivers of vehicles should be able to produce identity through appropriate
documentation to demonstrate that they are the authorized custodian of pharmaceutical
products who are aware of quantity and storage conditions of products.
� Procedure for communication, calculation and forecasting should be established
based on latest technology and elaborated throughout the supply network to include
the appropriate personnel having significant relation with transportation operations.
Dispatch and delivery of pharmaceutical products should be undertaken only after
acquiring valid delivery order describing full name and quantity of products. The
batch number on invoice and order should exactly match with that on labels.
� The updated transport channel layouts should be depicted in clear terms with cross-
reference with modalities across the supply chain span. The provision should exist
to give assurance of the trustworthiness throughout the transportation span.
Figure 9.
Overall performance
depends upon
individual component
contribution
FI
N
A
N
CI
A
L
LO
SS
ES
D
U
RI
N
G
TR
A
N
SP
O
RT
AT
IO
N
MODE OF TRANSPORTATION
3 Transit
through
aircra�
1 Loading to
first vehicle
2 Transit
through ship
4 Transit to
end point
through van
5 Unloading
from van to
end point
ESTABLISH ‘KEY
PERFORMANCE
INDICATORS’
DURING INDIVIDUAL
TRANSPORT MODES
IJPHM
13,3
326
The provision for identification of directly employed and contracted delivery personnel
should be available (TGA, 2010). Training should be imparted against GTP to the
supervisors and responsible transport personnel. Drivers of transport van carrying drugs
products should be trained for handling the data loggers during transit.
6. Conclusion
The existing pharmaceutical world adheres to the system approach at manufacturing plant
level with high degree of dedication, whereas there is an enhanced requirement to focus on
elements of GTP. To maintain the consistent quality product during transportation of
pharmaceutical products, there is a need of alignment of principles of the supply chain in
good transportation in the broader interest of corporate officials and consumers. The
pharmaceutical industry should embed the SCM principles in pharmaceutical GTP for
maximum business output. SOPs should be in place for cold chain medicines across the
supply chain network during the logistics and transportation operations.
7. Recommendation
To ensure the safe distribution of pharmaceutical products from manufacturing plant to the
retailer, each organization must define and document the “Good Transportation Practices”.
This philosophy deserves the equal importance as other GXP practices, like GMP, GLP and
GDP, etc. The pharmaceutical industry is recommended to align the principle of SCM with
good transportation practice and vice-a-versa. Further, it is recommended to carry out a
separate study with an objective to integrate the systems of pharmaceutical manufacturing
and distribution. The best practices in pharmaceutical transportation can become the
strength of pharmaceutical business to ensure business growth by maintaining seamless
quality system throughout the transportation process, if sincerely aligned with principles of
SCM.
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No. 11, pp. 28-32.
About the authors
Nirmal Kumar has Master’s degree in three disciplines from premier Indian institutions, Delhi
University, Birla Institute of Technology and Science, Pilani and Sikkim Manipal University. He is
also ASQ-Certified Supplier Quality Professional. He has more than 21 years of industrial work
experience in various quality functions of pharmaceutical organizations of India and Malaysia.
Kumar has thorough exposure to manage the USFDA-, MHRA- and EU-certified pharmaceutical
industry in various leadership roles of quality function. There are 12 of review papers published in
various international journals to credit his authorship. Nirmal Kumar is the corresponding author
and can be contacted at: [email protected]
Professor (Dr) Ajeya Jha has Master’s degree in two streams Pharmacy and Business Management
followed by PhD. He is a Professor and Head in the Department of Management Studies at Sikkim
Manipal Institute of Technology (SMIT), a constituent college of Maniapl Group of Education.
Professor Jha is also a Trainer, Academician, Researcher, Consultant and Administrator. There are
about 26 review and research papers published in various international journals to credit his
authorship. He has authored of four books.
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
Or contact us for further details: [email protected]
IJPHM
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- Application of principles of supply chain management to the pharmaceutical good transportation practices
- 1. Introduction
- 1.1 Supply chain management versus good transportation practice
- 1.2 Review of regulatory guidance papers
- 1.3 Gap in existing pieces of literature
- 2. Method
- 3. Data
- 3.1 Data collection
- 3.2 Data analysis
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- 5. Results
- 5.1 Setting up a direction for resolution
- 5.2 Application of principles of supply chain management in ‘pharmaceutical good transportation practices’
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- 6. Conclusion
- 7. Recommendation
- References
peer-reviewed sources/Complaints addressed by regulatory authorities in drug advertising targeted.pdf
Contents lists available at ScienceDirect
Research in Social and Administrative Pharmacy
journal homepage: www.elsevier.com/locate/rsap
Complaints addressed by regulatory authorities in drug advertising targeted
at consumers: Cases across three, different countries
Seung Yeon Songa, Ji Hyei Leeb, Seong Chul Kimb, Jin-Woo Choib, Jongwoo Baeb,
EunYoung Kima,b,∗
a Department of Health, Social and Clinical Pharmacy, Chung-Ang University College of Pharmacy, Seoul, South Korea
b The Graduate School of Pharmaceutical Industry Management, Chung-Ang University, Seoul, South Korea
A B S T R A C T
Background: Misleading advertisements can affect behavior of both consumers
and prescribers and may lead to inappropriate use of medications.
Objective: To analyze the complaints upheld by regulatory authorities in the United Kingdom, Canada, and Australia regarding pharmaceutical advertising directed at
consumers.
Methods: Complaints addressed between January 2014 and June 2017 were retrieved from the websites of regulatory authorities. Complaints addressed by self-
regulatory bodies were not included due to the poor availability of data.
Results: Sixty complaints, 374 complaints, and 223 complaints from the United Kingdom, Canada, and Australia, respectively, were analyzed. In the United Kingdom,
the most frequent type of violation was advertising of prescription drugs (70.5%); most of these violations involved botulinum toxin. In Canada, advertising on online
media was more likely to be associated with prescription drugs than that on traditional media (P < 0.001). In Australia, advertising of prescription drugs accounted
for less than 10% of complaints, but all were associated with online media.
Conclusions: In countries where direct-to-consumer advertising of prescription drugs is prohibited, regulatory authorities may need to devise further strategies to
safeguard the public as this is an unresolved issue and is predicted to become more problematic with the increased use of online media.
Introduction
A large proportion of the literature regarding pharmaceutical ad-
vertising has focused on direct-to-consumer advertising (DTCA) of
prescription drugs, with most studies based in the United States (US).
However, the US and New Zealand are the only two developed coun-
tries known to allow DTCA. In countries where such act is prohibited,
studies have often focused on the effectiveness of banning DTCA or the
promotion of prescription drugs targeting healthcare professionals.1–7
Many studies have analyzed DTCA violations in prescription medicine
using US Food and Drug Administration (FDA) letters.8–14 However,
few studies have analyzed complaints addressed by the United Kingdom
(UK) Prescription Medicines Code of Practice Authority (PMCPA); this
body only handles complaints related to prescription drugs.4,5 Thus, to
our knowledge, no studies have analyzed complaints on pharmaceutical
advertising targeted at consumers, which can be applied to countries in
which DTCA of prescription drugs is prohibited.
In the UK, Canada, and Australia, pharmaceutical advertising is
predominantly regulated through industry self-regulation with the
statutory function of a government regulatory authority (Fig. 1).
Although they take different forms, all three countries have procedures
in place for both the self-regulation of complaints where industry codes
are breached and the regulatory handling of complaints where the law
is contravened. Further, in all three countries, complaints found justi-
fied by the authority as in breach of the law, are published online for
public access. This study aims to analyze the complaints upheld by
government regulatory authorities on drug advertising targeted at
consumers that have been made available publicly. In addition, as the
use of digital advertising in the pharmaceutical industry is increasing,
the study aims to assess the differences between upheld complaints in
traditional and online media as this may allow the identification of
areas in which regulations require reinforcement to adapt to the rapidly
changing environment of advertising.
Methods
All complaints addressed between June 1, 2014, and June 30, 2017,
were first retrieved from the respective websites of the Medicines and
Healthcare products Regulatory Agency (MHRA; https://www.gov.uk/
government/collections/advertising-investigations-by-mhra), Health
https://doi.org/10.1016/j.sapharm.2018.12.001
Received 26 June 2018; Received in revised form 29 November 2018; Accepted 4 December 2018
∗ Corresponding author. Department of Health, Social and Clinical Pharmacy, Chung-Ang University College of Pharmacy, The Graduate School of Pharmaceutical
Industry Management, Chung-Ang University, 84 Heukseok-Ro, Dangjak-gu, Seoul, 06974, South Korea.
E-mail address: [email protected] (E. Kim).
Research in Social and Administrative Pharmacy 15 (2019) 1274–1279
1551-7411/ © 2018 Published by Elsevier Inc.
T
Canada (https://www.canada.ca/en/health-canada/services/drugs-
health-products/regulatory-requirements-advertising/health-product-
advertising-complaints.html), and the Complaints Resolution Panel
(CRP; http://www.tgacrp.com.au/complaint-register/). For inclusion
in the study, the complaints were required to: i) involve advertising
targeted at consumers, and ii) be found justified by the authority. Thus,
complaints on advertisements involving cosmetic products, such as
sunscreens, and medical devices, those targeting healthcare profes-
sionals, and those found not justified were excluded. Two independent
reviewers extracted the data on product type, advertiser, advertising
medium, complaint type, and action upon determination. Any dis-
agreements were resolved through discussion with a third reviewer.
Data analysis
Complaint types between traditional and online media were com-
pared after excluding complaints routed through multiple media or
unspecified media by using Pearson’s chi-square analyses or Fisher’s
exact tests, as appropriate. All tests for statistical significance were two-
tailed, with the threshold set at 0.05. All analyses were performed using
SPSS software version 23.0.
Results
The details of the inclusion of complaints for analysis are shown in
Fig. 2. After applying inclusion and exclusion criteria, 60, 374, and 223
complaints were included from the UK, Canada, and Australia, re-
spectively. The characteristics of the drug advertising complaints are
summarized in Table 1. In the UK, drug advertising complaints were
mostly related to prescription drugs; in Canada, they were mostly re-
lated to OTC medicines. There were no complaints related to pre-
scription drugs among those handled by CRP, and most were related to
natural herbal medicines. Non-medical clinics, such as cosmetic, health,
or beauty clinics, were the main subject of drug advertising complaints
in the UK and Canada, while in Australia, manufacturers, pharmaceu-
tical companies, or distributors were the main subject of complaints. In
all three countries, the Internet was the most common advertising
medium associated with complaints.
The complaints grouped into the main categories for comparison are
shown in Table 2. A detailed table of the complaint types per country
can be accessed in Appendix A. The complaints in the UK were mostly
related to the advertising of prescription drugs. Of the 43 upheld
complaints regarding the DTCA of prescription medicines, 35 (81.4%)
were related to botulinum toxin products. The advertising medium was
not specified for all complaints involving the advertising of botulinum
toxin products. The sites of violations for other prescription medica-
tions were mostly esthetic centers or salons. Among the upheld com-
plaints pertaining to the contents of advertisements, “unsubstantiated
claims” (13.3%) were the most frequent type of violation. In Canada,
“prohibited DTCA” (37.2%) was the most common type of complaint,
followed by “unsubstantiated claims” (36.4%). The prescription drugs
involved were primarily Botox (64.7%) and human chorionic gonado-
trophin (21.6%). In Australia, only 6.3% of complaints was associated
with “prohibited DTCA,” specifically “reference to Schedule 3, 4, or 8
products.” In Australia, medicines are classified into Schedules ac-
cording to the level of regulatory control over the availability of the
medicine. Schedule 3 is Pharmacist Only Medicine, which refers to
medicines that require a pharmacist’s advice, and a pharmacist must be
involved in the sale. Schedule 4 is Prescription-Only Medicine, and
Schedule 8 refers to Controlled Drugs, which includes substances with a
high potential for abuse and addiction.
Approximately one fifth of the upheld complaints in Canada in-
volved “serious health claims,” regarding “prohibited advertising to the
general public as a treatment or cure for any Schedule A disease”
(19.0%; Appendix A). Schedule A diseases are listed in the in the Food
and Drugs Act, and include diseases such as acute anxiety, asthma,
cancer, and diabetes, which should not be referenced in labeling and
advertising the product to the general public. There is a similar provi-
sion in Australia, “reference to serious diseases” (64.6%; Appendix A),
where the list of serious diseases is defined under the Therapeutic
Goods Advertising Code (TGAC). Other “serious health claims” included
“encouragement for self-diagnosing or inappropriately treating poten-
tially serious diseases” (30.9%; Appendix A) and “encouragement for
inappropriate or excessive use” (11.2%; Appendix A).
In Australia, over 90% of the upheld complaints were associated
with “unsubstantiated claims” (94.2%). The second most frequent main
category of complaints was “information provision” (66.4%), with the
most common complaint type being “omission of required information”
(56.5%; Appendix A). Under the TGAC, advertisements should contain:
(a) the trade name of the goods; (b) a reference to the approved/per-
mitted indication(s) for the use of the goods; and (c) where applicable, a
list of ingredients or the following statement prominently displayed or
communicated: “ALWAYS READ THE LABEL.” Among other complaint
types, “promotion outside the terms of registration” (43.0%) was
common, followed by “implied endorsement” (30.0%) by a health
professional or government agency. The main category of “other” in-
cluded “testimonials” (9.4%; Appendix A), “unapproved advertisement
or approval number not presented prominently” (8.1%; Appendix A),
and “offer of samples” (1.8%; Appendix A).
A comparison of types of drug advertising complaints between
Fig. 1. Regulatory authorities and self-reg-
ulatory bodies in A) the UK, B) Canada, and C)
Australia.
Abbreviations: Rx, prescription; MHRA,
Medicines and Healthcare products Regulatory
Agency; PAGB, Proprietary Association of Great
Britain; CAP, Committee of Advertising Practice;
ASA, Advertising Standards Authority; ABPI,
Association of the British Pharmaceutical
Industry; PMCPA, Prescription Medicines Code
of Practice Authority; ASC, Advertising
Standards Canada; PAAB, Pharmaceutical
Advertising Advisory Board; TGA, Therapeutic
Goods Administration; ASMI, Australian Self-
Medication Industry.
Note. Italic text indicates self-regulatory bodies
of the advertising industry, whereas Roman text
indicates self-regulatory bodies of pharmaceu-
tical industry.
S.Y. Song et al. Research in Social and Administrative Pharmacy 15 (2019) 1274–1279
1275
traditional and online media is shown in Table 3. In the UK, owing to
the low number of complaints involved, a statistical comparison be-
tween upheld complaints in traditional and online media was not
possible. In Canada, online media were more likely to involve “adver-
tising of a prescription drug beyond brand name, price, and quantity”
(P < 0.001). In Australia, online media were more likely to involve
“comparative claims” (P = 0.019), “promotion of an unregistered in-
dication” (P = 0.003), “implied endorsement by a health professional
or government agency” (P = 0.025), “scientific information not pre-
sented in a manner that is accurate, balanced, and not misleading”
(P = 0.007), “reference to serious diseases” (P < 0.001), and “en-
couragement for self-diagnosing or inappropriately treating potentially
serious diseases” (P = 0.017).
Actions requested from the advertisers upon decision of the com-
plaints are summarized in Table 4. In the UK and Canada, the majority
of action resulting from upheld complaints was correction of adver-
tisements (81.7% and 72.7%, respectively). In contrast, the actions
requested in Australia were primarily withdrawal of advertisements
(98.2%), closely followed by correction of advertisements (95.5%).
Discussion
This study is the first to analyze complaints addressed by govern-
ment regulatory authorities in regard to pharmaceutical advertising
targeted at consumers in the UK, Canada, and Australia. Prohibited
DTCA was the most common type of upheld complaint, and these
complaints primarily involved botulinum toxin. Owing to their close
proximity to countries that allow DTCA, Canadian and Australian re-
sidents are more likely than residents of other countries to be exposed
Fig. 2. Flow diagram of case selection. Note: In Canada, only the complaints addressed by Health Canada are publicly available.
Table 1
Characteristics of drug advertising complaints.
UK (N = 60) Canada
(N = 374)
Australia
(N = 223)
Product type a
Prescription medicine 45 (78.7%) 139 (37.2%) 0 (0%)
OTC medicine 4 (6.7%) 221 (59.1%) 14 (6.3%)
Natural herbal medicine 7 (11.7%) 27 (7.2%) 209 (93.7%)
Unlicensed medicine 5 (8.3%) 14 (3.7%) 0 (0%)
Complaint source
Monitoring by regulatory
authority
4 (6.7%) 52 (13.9%) 0 (0%)
Consumer 2 (3.3%) 176 (47.1%) 1 (0.4%)
Pharmaceutical company 7 (11.7%) 128 (34.2%) 4 (1.8%)
Healthcare professional 3 (5%) 0 (0%) 4 (1.8%)
Referral from other bodies 0 (0%) 18 (4.8%) 1 (0.4%)
Anonymous/unspecified 44 (73.3%) 0 (0%) 213 (95.5%)
Advertiser a
Manufacturer/pharmaceutical
company/distributer
17 (27.9%) 159 (42.5%) 196 (87.9%)
Non-medical clinic 35 (57.4%) 98 (26.2%) 0 (0%)
Medical service provider 3 (6.6%) 38 (10.2%) 0 (0%)
Pharmacy 3 (4.9%) 3 (0.8%) 12 (5.4%)
Vitamin, supplement, and
health food supplier
1 (1.6%) 24 (6.4%) 12 (5.4%)
Publisher/broadcaster 0 (0%) 15 (4%) 13 (5.8%)
Online retailer 0 (0%) 11 (2.9%) 8 (3.6%)
Other 1 (1.6%) 26 (4.3%) 4 (1.8%)
Advertising medium a
Internet 13 (23%) 309 (82.6%) 209 (93.7%)
Print 4 (6.6%) 18 (4.8%) 11 (4.9%)
TV/Radio 7 (11.5%) 79 (21.1%) 26 (11.7%)
Display 1 (1.6%) 5 (1.3%) 2 (0.9%)
In person 0 (0%) 13 (3.5%) 0 (0%)
Other/unspecified 35 (57.4%) 4 (1.1%) 0 (0%)
Note. The high number of “other/unspecified” advertising medium in the UK
was due to all complaints (n = 35) involving the advertising of botulinum toxin
products not specifying the advertising medium involved.
a Owing to the multiple products, advertisers, and media involved, percen-
tage values may not add to 100%.
Table 2
Main categories of complaints upheld in the UK, Canada, and Australia.
Main category UK (N = 60) Canada
(N = 374)
Australia
(N = 223)
Unsubstantiated claims 8 (13.3%) 136 (36.4%) 210 (94.2%)
Comparative claims 1 (1.7%) 1 (0.3%) 66 (29.6%)
Prohibited DTCA 43 (71.7%) 139 (37.2%) 14 (6.3%)
Advertising of an unlicensed
medicine
3 (5.0%) 94 (25.1%) 0 (0.0%)
Promotion outside the terms
of registration
4 (6.7%) 0 (0.0%) 96 (43.0%)
Implied endorsement 1 (1.7%) 1 (0.3%) 67 (30.0%)
Information provision 1 (1.7%) 4 (1.1%) 148 (66.4%)
Unbalanced presentation of
safety
0 (0.0%) 1 (0.3%) 42 (18.8%)
Serious health claims 0 (0.0%) 72 (19.3%) 147 (65.9%)
Other 0 (0.0%) 39 (10.4%) 41 (18.4%)
Note. Owing to multiple upheld complaints per investigation, percentage values
may not add to 100%.
S.Y. Song et al. Research in Social and Administrative Pharmacy 15 (2019) 1274–1279
1276
to DTCA.15,16 In addition, the ability to safeguard the public from DTCA
of prescription medicine is often threatened through trade agreements.
For example, the Australia-US Free Trade Agreement in 2005 sought to
legalize DTCA via the internet. Fortunately, this was prevented by the
addition of the phrase, “as is permitted to be disseminated under the
Party’s laws, regulations and procedures.”17 Later, such attempts at
legalization were again made in the Trans-Pacific Partnership Agree-
ment, which was prevented through a similar use of language. Thus, the
government regulatory authorities in countries that prohibit DTCA of
prescription medicines are often challenged by various issues.
Other than prohibited DTCA, the number of complaints addressed
by the MHRA was small. The low number of complaints received by the
MHRA may be an outcome of effective self-regulation as the MHRA is
only required to investigate a complaint that has not been dealt with by
the self-regulatory body in a satisfactory or timely manner.18 In con-
trast, it may be a reflection of public tendency to complain to the Ad-
vertising Standards Authority (ASA) instead of the MHRA.19 In support
of this, only 3.3% of complaints addressed by the UK were from con-
sumers. In both Canada and Australia, advertisements in online media
were more likely to involve DTCA of prescription drugs. The global
reach of the internet makes it harder to regulate DTCA. Despite legal
prohibition, DTCA is occurring in various forms online.3,20 Methods of
online advertising are numerous, from social media to company or
Table 3
Comparison of upheld complaints between traditional and online media.
UK Traditional media Online media P-valuea
N = 11 N = 15
Unsubstantiated claims Unsubstantiated claims of efficacy 5 (45.5%) 3 (26.7%) N/A
Comparative claims Comparative claims 1 (9.1%) 0 (0%) N/A
Prohibited DTCA Advertising of a prescription medicine 2 (18.2%) 6 (40%) N/A
Advertising of an unlicensed medicine Advertising of an unlicensed medicine 1 (9.1%) 2 (13.3%) N/A
Promotion outside the terms of registration Promotion outside the terms of registration 1 (9.1%) 3 (20%) N/A
Implied endorsement Recommendation by scientists or healthcare professionals 1 (9.1%) 0 (0%) N/A
Information provision Failure to include an invitation to read the label or leaflet 1 (9.1%) 0 (0%) N/A
Canada N = 63 N = 260
Unsubstantiated claims Unauthorized claims 31 (49.2%) 78 (30%) 0.004
Therapeutic claims for cosmetic-like products 3 (4.8%) 12 (4.6%) 1.000
Comparative claims Comparative claims 0 (0%) 1 (0.4%)
Prohibited DTCA Advertising of a prescription drug beyond brand name, price, and quantity 8 (12.7%) 124 (47.7%) < 0.001
Advertising of an unlicensed medicine Unauthorized products 20 (31.7%) 47 (18.1%) 0.016
Prohibited advertising of a new drug 20 (31.7%) 47 (18.1%) 0.006
Implied endorsement Implied endorsement of the product by Health Canada 0 (0%) 1 (0.4%) N/A
Information provision Missing product information 0 (0%) 2 (0.8%) N/A
Unbalanced presentation of safety Lack of adequate safety warnings 0 (0%) 1 (0.4%) N/A
Serious health claims Unauthorized serious health claims 0 (0%) 1 (0.4%)
Prohibited advertising to the general public as a treatment or cure for any Schedule A
disease
17 (27%) 36 (13.8%) 0.012
Other False, misleading, or deceptive advertising – Unspecified 6 (9.5%) 31 (11.9%) 0.592
Australia N = 27 N = 180
Unsubstantiated claims Overstatement of efficacy 22 (81.5%) 166 (92.2%) 0.081
Misleading claims 22 (81.5%) 164 (91.1%) 0.163
Comparative claims Comparative claims 3 (11.1%) 60 (33.3%) 0.019
Prohibited DTCA Reference to Schedule 3, 4, or 8 products 0 (0%) 13 (7.2%) N/A
Promotion outside the terms of registration Promotion of an unregistered indication 5 (18.5%) 88 (48.9%) 0.003
Implied endorsement Implied endorsement by a health professional or government agency 3 (11.1%) 58 (32.2%) 0.025
Information provision Omission of required information 12 (44.4%) 109 (60.6%) 0.113
Scientific information not presented in a manner that is accurate, balanced, and not
misleading.
3 (11.1%) 67 (37.2%) 0.007
Unbalanced presentation of safety Overstatement of safety 4 (14.8%) 35 (19.4%) 0.566
Serious health claims Reference to serious diseases 8 (29.6%) 127 (70.6%) < 0.001
Encouragement for self-diagnosing or inappropriately treating potentially serious
diseases
3 (11.1%) 61 (33.9%) 0.017
Encouragement for inappropriate or excessive use 1 (3.7%) 23 (12.8%) 0.328
Other Testimonials 1 (3.7%) 19 (10.6%) 0.482
Unapproved advertisement or approval number not presented prominently 16 (59.3%) 1 (0.6%) < 0.001
Offer of samples 0 (0%) 4 (2.2%) N/A
Note. Owing to multiple upheld complaints per investigation, percentage values may not add to 100%. Complaints with unspecified media and complaints involving
both online and traditional media were excluded from the analysis.
a Pearson’s chi-square or Fisher’s exact test.
Table 4
Action requested upon decision of complaint.
Country and action requested n (%)
UK N = 60
Correction of advertisements 49 (81.7%)
Withdrawal of advertisements 7 (11.7%)
Advice provided 3 (5%)
Unspecified 1 (1.7%)
Canada N = 374
Correction of advertisements 272 (72.7%)
Stop sale and advertising of unlicensed product 64 (17.1%)
No follow-up required 6 (1.6%)
Unspecified 30 (8%)
Australia N = 223
Correction of advertisements 213 (95.5%)
Withdrawal of advertisements 219 (98.2%)
Publication of retraction 50 (22.4%)
S.Y. Song et al. Research in Social and Administrative Pharmacy 15 (2019) 1274–1279
1277
product websites, which render monitoring difficult. Many pharma-
ceutical companies are transitioning from traditional to online media
and are attracted by their lower costs and broader audience access. This
transition poses many regulatory challenges for authorities.21 In sup-
port, our analysis of complaints showed that online media were more
likely to be associated with complaints about the content of adver-
tisements, such as references to serious diseases and misleading in-
formation.
Although the best methods for the regulation of online advertising
of pharmaceuticals remain unclear, the provision of specific guidelines
to which pharmaceutical companies can adhere to could be a possible
option. However, previous experience in the US has shown that issu-
ance of detailed guidelines for online advertising may actually cause
more problems and even promote the use of online media.21 Mandatory
preclearance of materials may be another option. Currently, none of the
three countries require preclearance of materials intended for online
media. However, the large number of complaints regarding advertise-
ments on specified media, which require mandatory preclearance in
Australia, suggest that preclearance may not be the most effective
method for regulation, considering the time and resources required for
such preclearance. Another possibility could be the imposition of much
higher fines and the public disclosure of violations to deter pharma-
ceutical companies from conducting unlawful marketing.22 Our ana-
lysis shows that most actions imposed for upheld complaints were mild,
with the correction of advertisements arising as the principal actions in
the UK and Canada. Even in cases in which some companies were
subject to the same complaint on multiple occasions and where some
clinics were involved in multiple complaints involving prohibited
DTCA, no further actions were taken. Although by law, contravention of
the act or regulations can lead to a fine or imprisonment (or both), such
actions appear to be rarely pursued. In Australia, many cases resulted in
referral to the Secretary for resolution due to ongoing non-compliance.
The CRP comprises both government and non-government members
and thus, compliance power is limited. For such reasons, the Australian
system is undergoing reform, and from July 1, 2018, the Therapeutic
Goods Administration (TGA) is the sole responsible body for handling
all complaints about pharmaceutical advertising targeted at con-
sumers.23 Such a change is expected to simplify the process and im-
prove the effectiveness of handling complaints. Other advertising re-
forms, which the TGA plans to implement in 2018, include removing
preclearance and applying broader and more enhanced enforcement.
The outcomes of such reforms are expected to be highly informative for
all, including researchers and policy makers.
Limitations
The limitations of this study mainly arise from the lack of detailed
information on complaints, which precludes further analyses. Secondly,
the complaints included in this study may not represent all violations
that occur in advertising directed at consumers, as those addressed by
self-regulatory bodies are not included. However, such inclusion of
cases was not possible due to the poor availability of data as inter-
company complaints are often resolved informally and not made public.
In addition, the analyzed complaints are more likely to involve orga-
nizations other than pharmaceutical companies, such as private clinics,
where industry self-regulation would not apply. Additionally, com-
plaints related to DTCA are handled differently by the three countries.
Thus, the differences in the characteristics of complaints, as well as the
frequencies of complaint types in each country, especially those re-
garding DTCA, may be a simple reflection of differences in the reg-
ulatory systems. Although our analysis of complaints handled by gov-
ernment regulatory authorities is likely to be an underestimation of
violations associated with pharmaceutical advertising targeted at con-
sumers, the authors believe that this study provides a valuable overview
of common issues faced in countries where DTCA of prescription drugs
is prohibited.
Conclusions
In conclusion, this study is the first to analyze complaints upheld by
government regulatory authorities regarding advertising directed to the
public in countries where DTCA of prescription drugs is prohibited.
Through the comparison of the types of violations that occurred in
advertising on traditional and online media, it was found that the
complaints regarding advertisements on online media are more likely to
involve prohibited DTCA. Given the rapidly changing advertising en-
vironment and the rise in digital advertising, the study findings provide
an overview of common types of violations occurring in pharmaceutical
advertising targeted at consumers and can offer a basis for devising
policies to strengthen regulations and to ensure public safety.
Declarations of interest
None.
Funding
This research was supported by a grant (17172MFDS159) from
Ministry of Food and Drug Safety in 2017. The funding source had no
involvement in study design; in the collection, analysis and inter-
pretation of data; in the writing of the report; nor in the decision to
submit the article for publication.
Acknowledgments
None.
Appendix A. Frequency of complaint types in each main category in the UK, Canada and Australia
Main Category UK (N = 60) Canada (N = 374) Australia (N = 223)
Complaint type n (%) Complaint type n (%) Complaint type n (%)
Unsubstantiated cl-
aims
Unsubstantiated claims of
efficacy
8
(13.3%)
Unauthorized claims 129
(34.5%)
Overstatement of efficacy 204
(91.5%)
Therapeutic claims for cosmetic-like products 20
(5.3%)
Misleading claims 203
(91.0%)
Comparative claims Comparative claims 1 (1.7%) Comparative claims 1 (0.3%) Comparative claims 68
(30.5%)
Prohibited DTCA Advertising of a prescription
medicine
43
(71.7%)
Advertising of a prescription drug beyond
brand name, price, and quantity
139
(37.2%)
Reference to Schedule 3, 4, or 8 products 14
(6.3%)
Advertising of an u-
nlicensed medi-
cine
Advertising of an unlicensed
medicine
3 (5.0%) Unauthorized products 89
(23.8%)
Prohibited advertising of a new drug 5 (1.3%)
S.Y. Song et al. Research in Social and Administrative Pharmacy 15 (2019) 1274–1279
1278
Promotion outside t-
he terms of re-
gistration
Promotion outside the terms
of registration
4 (6.7%) Promotion of an unregistered indication 96
(43.0%)
Implied endorsement Recommendation by scien-
tists or healthcare profes-
sionals
1 (1.7%) Implied endorsement of the product by Health
Canada
1 (0.3%) Implied endorsement by a health profes-
sional or government agency
67
(30.0%)
Information provi-
sion
Failure to include an invita-
tion to read the label or
leaflet
1 (1.7%) Missing product information 3 (0.8%) Omission of required information 126
(56.5%)
Scientific information not presented in a
manner that is accurate, balanced, and not
misleading.
75
(33.6%)
Unbalanced presen-
tation of safety
Lack of adequate safety warnings 1 (0.3%) Overstatement of safety 42
(18.8%)
Serious health clai-
ms
Unauthorized serious health claims 1 (0.3%) Reference to serious diseases 144
(64.6%)
Prohibited advertising to the general public as
a treatment or cure for any Schedule A disease
71
(19.0%)
Encouragement for self-diagnosing or inap-
propriately treating potentially serious dis-
eases
69
(30.9%)
Encouragement for inappropriate or exces-
sive use
25
(11.2%)
Other False, misleading, or deceptive advertising –
Unspecified
39
(10.4%)
Testimonials 21
(9.4%)
Unapproved advertisement or approval
number not presented prominently
18
(8.1%)
Offer of samples 4(1.8%)
Note. Due to multiple upheld complaints per investigation, percent values may not add to 100%.
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S.Y. Song et al. Research in Social and Administrative Pharmacy 15 (2019) 1274–1279
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- Complaints addressed by regulatory authorities in drug advertising targeted at consumers: Cases across three, different countries
- Introduction
- Methods
- Data analysis
- Results
- Discussion
- Limitations
- Conclusions
- Declarations of interest
- Funding
- Acknowledgments
- Frequency of complaint types in each main category in the UK, Canada and Australia
- References
peer-reviewed sources/Investigation the Relationship Between Supply Chain Management.pdf
International Business Research; Vol. 13, No. 2; 2020
ISSN 1913-9004 E-ISSN 1913-9012
Published by Canadian Center of Science and Education
74
Investigation the Relationship Between Supply Chain Management
Activities and Operational Performance: Testing the Mediating Role
of Strategic Agility
A Practical Study on the Pharmaceutical Companies
Majd Mohammad Omoush
1
1
Business Administration Department, Business Faculty, Tafila Technical University, Tafila, Jordan
Correspondence: Dr. Majd Mohammad Omoush Faculty, Tafila Technical University, Tafila, Jordan, P. O. Box
179, Tafila 66110, Jordan.
Received: December 12, 2019 Accepted: January 13, 2020 Online Published: January 17, 2020
doi:10.5539/ibr.v13n2p74 URL: https://doi.org/10.5539/ibr.v13n2p74
Abstract
This study has been conducted to investigate the relationship between the supply chain management (SCM)
activities and operational performance through testing the mediating factor strategic agility in (16)
pharmaceutical companies listed on Amman stock exchange in Jordan Which is considered one of the most
important industrial sectors, where the nature of the work and the problems faced in the performance of supply
chain were identified the reasons for the delay of the logistical orders of raw materials they need from suppliers,
and found that there is a missing link between partners and is the proportion of obtaining the necessary
information from suppliers to complete operations Streamlined and easy production. In terms of identifying the
activities of supply chain management as the most important factors supporting the best practices of SCM in
pharmaceutical companies (i.e. Alliances with suppliers, Customer Relation Management, Logistic, flow
Information and knowledge sharing). The study population consisted of all the executives and directors of
departments, sections and employee specialized in SCM in pharmaceutical companies, and a simple random
sample was chosen from pharmaceutical companies to conduct a field survey using a tool, a questionnaire, of
which 150 were distributed and 139 were retrieved. In addition, a number of statistical techniques have been
used for data analysis; such as statistical analysis package for Social Sciences (SPSS) and AMOS, which
depends on Structure Equation Modeling approach because of the presence one variable, as well as for the
reason of examining the importance of the track. Based on the results of the statistical analysis, it was concluded
that there is an impact of the independent variable managing the supply chain on operational performance, but in
terms of the intermediate variable, the results showed that the relationship is partial in terms of the strategic
agility variable through Path Analysis.
Keywords: supply chain management activates, alliances with suppliers, customer relationship management,
logistic, information and knowledge sharing, operational performance, pharmaceutical companies
1. Introduction
Within this current era of globalization, the advancement in the technology, and the rapid changes in the
environment surrounding the business organizations, supply chains have become an important phenomenon help
the organization in achieving its objectives, and also helps it to look towards exploiting the external opportunities,
whether locally regionally, or globally, as a result of relationships connecting the partners, suppliers, and the
customers inside the chain. This will provide it with power factor Customer Retention and to keep strong
relationships with the suppliers for specific demands at times of high demand, so to satisfy their expectations.
Organizations become looking for the global competition, since the challenges related to receive the product and
the service should be timely available, at the right place and less cost, the issue made the organizations to start
considering that un-sufficient to develop and improve the efficacy inside the organization.
So, supply chain management strategy became successful in linking the partners together and interesting in
transporting the materials from the supply sources to deliver the products to the customers, to facilitate
information flow through the supply chain parties (Beamon, 2000).Successfully supply chain management one
of the strategic challenges facing the business organizations, success of this idea or the practices depends on the
http://ibr.ccsenet.org International Business Research Vol. 13, No. 2; 2020
75
supply parties integration, which means the suppliers, manufacturers and the customers, for these parties to
achieve goals such as growth & financial objectives, especially at the long term (Beamon, 2000).Most of the
studies and the researches that had addressed this confirm the need for persuasion that of the supply chain
requires the need for achieving integration coordination, cooperation, and exchange of information between the
chain‟s parties (Mentzer, 2001).
(SCM) is one of the most important trends leading to compete with the requirements of the organizations‟
competitive power, since they compete in frame of competitive between some organizations, and the ability of
these chains for continuous rapid response within the changes in the business environment (Taylor, 2004).(SCM)
is considered one of the important functions that should be undertaken effectively and in competence in all
business (Gbadeyan, Boachie-Mensah, Osemene, 2017).By looking at the basic goals of SCM, it can be easily
noted that all above effects related to customers service. Some of the advantages include: (1) Reducing the
demand‟s time, (2) Assuring reliability, quality and flexibility in the delivery, (3) The optimal level of the
supplies inside the supply chain as a whole (4) Reducing the total costs of the goods flow (Dtugoz, 2010).
This study aims to find out the relationship between SCM activities and the operational performance through a
mediating variable which is the strategic agility. Since it is noticed the absence of previous researches that have
addressed this variable, since the researcher has felt from the present reality of the supply chain and the
production in the pharmaceutical factories in Jordan which is considered one of the most important industrial
sectors, getting acknowledge with the nature of the work and the problems encountered in performance of the
supply chain, the most important that they have problem in finding out reasons for the delay in the logistic
demands for the raw materials they need from the suppliers, also found out that there is a missing chain between
the partners represents in the percentage of receiving the needed information from the suppliers to compete the
production processes with ease and harmony.
Depending on a number of previous studies regarding the problems facing the organizations in the supply chain,
it become clear that there are a number of problems, the most important, time of delivery, flexibility, and
response, information sharing, and the relationships linked with supply chain, perceiving the concept
organizational agility as a mediating variable between SCM activities and achieving the operational performance.
Strategic agility importance includes the ability to adapt with the environmental changes in a continuous way
and the rapid response to the changing markets, response to the customers, flexible up-dates of the products in
accordance with the organizations‟ strategies and goals.
2. Literature Review
2.1 Concept of Supply Chain Management
A supply chain refers to the organization‟s providers and distributors of goods, within their factories and
warehouses that handle various tasks such as procurement, inventory control, production, distribution, and
delivery (Stadtler & Kilger, 2008).Essentially, as (Kandagatla,2005) states, a supply chain is a sequence of
shared operations and associations between Common Processors, and it entails all aspects of getting raw
materials, turning them into finished products, and delivering them to the final customer.
These processes need not occur at a single company. In fact, a supply chain “consists of two or more companies
connected” via the flow of resources, information, and finances, as (Stadtler, 2008) put it. The connected
companies serve each other by dividing the tasks of producing parts and components, producing finished
products, processing logistics services, and distributing to the final customer. Thus, several companies, with
differing functions and purposes, must collaborate in order for the supply chain to operate fluidly (Chance, 2010).
From another perspective, these associated companies may be seen as a processing chain, or a network of
companies connecting their upstream and downstream operations and activities, for the central purpose of
delivering value to the end consumer (Santos, 2006).
With that in mind, supply chain management (SCM) serve the business functions of producing enhanced
performance and optimal supply chain decisions in a given organization, internally and externally (Rotimi et al.,
2017). It may be seen as assimilating the supplier‟s crucial business procedures in service of the final user, so as
to provide added value through products, services, and information to all beneficiaries involved (Lambert,
García‐Dastugue&Croxton2005).
2.2 Supply Chain Management Activities
In exploring the various scopes of SCM activities, the researcher found much scientific research that describes
the multiplicity and diversity of these activity dimensions; which may result from combining theoretical and
practical applications in the supply chain. These dimensions may involve the establishment of partnerships with
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76
suppliers, and the deliberate application of outsourcing, informational interactions, and pressure cycle times
(Alvarado and Kotzab, 2001). They concern the practices of quality assurance, procurement, and customer
relationship building, which may be convened using a common inter-organizational pivot system―a system that
may, among other things, involve the disposal of excess inventory through postponements. Put simply, the
scopes of SCM comprise a set of activities carried out by an organization in order to augment the efficiency and
efficacy of its supply chain management practices (Alvarado & Kotzab, 2001; Li, Ragu-Nathan, Ragu-Nathan,
Rao & Subba, 2006).
2.2.1 Alliances with Suppliers
It was noted, towards the end of last century, that organizations which maintained successful partnerships with
suppliers tended to increase their competitive advantage (Vencataya, Seebaluk & Doorga, 2016). Such supply
chain partnerships are tactical unions and collaborations between two or more businesses in a supply chain,
which aim to facilitate their shared efforts in such activities as research, product development, manufacturing,
marketing, sales, and distribution. This type of partnership is one of the most prevalent hybrid organizational
forms in SCM (Agus & Hassan, 2008).
(Fawcett, Magnan& McCarter, 2008) conducted a study where they asked managers to specify the extent to
which certain practices may contribute to value creation through SC partnerships, in order to understand how
businesses are attempting to overcome the obstacles to partnership success. The researchers found that SC
relationships may need a modicum of SC simplification, which can be accomplished upstream by supply base
rationalization (Fawcett, Magnan, & McCarter, 2008).Inter-organizational diversity may present in a variety of
forms among partners, a factor which may affect the performance of their alliance, positively and negatively.
Thus, an ideal alliance, exhibiting true collaborative success, requires the concurrent search for partners with
different characteristics on certain scopes, and similar characteristics on other scopes (Sayuti, 2011).
2.2.2 Customer Relationship Management (CRM)
Soliman (2011) affirms that in a majority of worldwide projects, CRM systems are presently one of the most
important targets, and they could further improve in applicability and beneficiary awareness if they were easy to
use and carry out. In CRM, the strategy is a customer-focused one designed to attract, preserve, and expand a
company‟s base. These systems establish and build on the bonds and relationships with external parties, such as
end customers (Soliman, 2011). One type of CRM, the operational CRM, provides a unique source of
information about customers, deals with the creation of information, and supports sales, marketing, and customer
service (Laketaet., al, 2015).It is more and more necessary, in the current competitive business landscape, to
enact strategies to deliberately attract and keep customers. A key factor of a company‟s success in this is
customer value, wherein customers will choose goods or services that they perceive as contributing the most
value (Rahiminik & Ashamsadini, 2014).If the CRM system in an active company functions well, the results
would be sustainable and timely customer segmentation. That segmentation can only be fully exploited for
certain objectives if the system contains current, detailed data―such as the interest of the product portfolio, the
capacities of the business, and so on (Pohludka & Štverková, 2019). A CRM may come to form as results of a
company‟s decisions regarding the inception of relational activities, as targeted towards specific groups of
customers, or individual customers, with whom the company wishes to engage in a cooperative or collaborative
relationship (Parvatiyar & Jagdish, 2001).
2.2.3 Logistics
The challenge now is to determine how to successfully carry out SCM, with this distinction made by the premier
logistics professional organization in mind (Lambert, Cooper & Pagh, 1998).
The facets of outsourcing and hiring of agents are directly related to their impacts on the logistics of
organizations and their transportation activities (Kherbacha & Mocan, 2016). It may be helpful, then, to view
SCM is a network, with many directly and indirectly linked factions, involved in a comprehensive effort to
request, source, purchase, and administer logistics processes (Kherbacha&Mocan,2016).
To have any effect on the end consumer, the true value of the logistic service, as well as of the presented good or
service, must be distinguished by the supply chain. The typical client‟s product expectations are ever climbing, in
contrast to their dwindling loyalty to any specific company, so it is essential to construct logistics system deeply
engrained in all aspects of the supply chain. It should dynamically adjust to the effects of market analysis, which
is constantly assessed for the desires of the different, relevant consumer populations (Długosz, 2010).
2.2.4 Information and Knowledge Sharing
Knowledge management (KM) refers to how well verifiable and effective information flows across the supply
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chain (Mentzer, 2001, Yu et al. 2001, Li, Ragu-Nathan, Ragu-Nathan, Rao & Subba, 2006). To better utilize KM,
it is crucial to understand what it offers to the supply chain, and its roots in how the industrial landscape
ultimately moved from intensive data processing operations to being comprised of knowledge-based
organizations (Liew & Talalayevsky 2008).It is also helpful, here, to understand that the supply chain may be
perceived as an fundamentally intricate and dynamic system of flows― where information and knowledge flow
drive material and capital flow (Del Rosarioet al., 2013).
To add some distinction, a supply chain in which knowledge is shared is actually a progression of the
information-based supply chain. This is because knowledge is considered a more valuable, more practically
advantageous type of information, in the lexicon of organizations (Rashed, Azeem & Halim, 2010). That being
said, it is the precision, timeliness, suitability, and trustworthiness of information exchanged throughout the
supply chain that determines the quality of that information (Li, Ragu-Nathan, Ragu-Nathan, Rao & Subba,
2006). the incorporation of information in a supply chain may also bring substantial advantages specific to
manufacturing sector. These may include the ability to cut costs intelligently, a decrease of uncertainties,
increased organizational efficacy, improved services, building and solidification of social bonds, earlier problem
discovery, faster responses, reduced cycle time from order to delivery market, an ability to decrease inventory
due to efficient inventory management, and so on. Of course, it has to be said that some obstacles may arise to
information distribution, which necessitates having contingency plans to overcome them (Lotfi, Mukhtar, Sahran,
&Zadeh, 2013). Specialized data is in sub group of the data that is found inside the data storage which is usually
directed toward a specific line or specific work-team or it is used for a specific goal to achieve knowledge
sharing (Rahahleh, & Omoush, 2020).
2.3 Strategic Agility
Companies have come to pursue, more and more, the development of unique approaches for business
development in all its phases (Macclever, Anna &Boahen, 2017).To that effect, the approach of agile
management, where agility and time needs reductions are the main elements, may be used to provide speedy
responses to changes in demand, or to customers’ ever-changing needs. Agile supply chains strategies are most
effective when dealing with differentiated products in circumstances of changing demand. When the total lead
time is quite limited, this strategy may be found to be the least demanding to execute (Długosz, 2010). Deliberate
and planned agility may, therefore, be considered a special type of dynamic organizational competence (Arbussa,
Bikfalvi, & Marquès, 2017).
Doz & Kosonen (2010) defined strategic agility as the ability to dynamically adapt or restructure an organization
and its strategies, wherein the shifting professional environment and changing customer tendencies accounted for
continuously, without deserting the business’s vision. Building on that, (Ojha,2008) described it as the capacity
to perceive and take advantage of environmental opportunities, which involves efficient, short-term and
long-term planning for anticipated organizational changes. It may also be seen as the ability to make crucial
decisions in limited time, as would be expected for typical markets and strategic circumstances (Brannen & Doz,
2012).
Sull & Bryant (2006) described strategic agility as a relative concept, representing an organization‟s capacity to
exploit opportunities in a more-timely fashion than its competitors, and to conquer crises more successfully than
competitors with weaker capabilities. It has been clarified by (Sull, 2009) as recognizing and seizing
opportunities faster than competitors. Here, the emphasis is placed on strategic sensitivity, or the ability to be
open and sensitive, and to anticipate needs and opportunities, by sorting through available information and
maintaining relationships with a variety of individuals and organizations (Kosonen and Doz, 2008).This also
integrates the concept of response speed, which refers to the degree to which an organization can take immediate
action at a certain point, such the ideal opportunity to introduce a new product (Abu Radi, 2013).
Beltrame (2008), on the other hand, placed a greater focus on the practice of change, and described strategic
agility as a process of adjusting an organization‟s strategic orientation to developments and changes in its
environment. He saw the growing perception is that an organization as agile if it can continuously maximize
strength and flexibility, thereby giving itself access to more options to deliver what is necessary― at the right
time and place for clients. Correspondingly, organizations are reacting to this increasing desire for flexibility, in
an ever more diverse organizational environment, by incorporating it as a key aspect of their strategies
(Macclever, Anna & Boahen, 2017). (Long, 2000) believes that an organization‟s core capabilities, in
conjunction to its judicious application of knowledge, are the combination needed to attain desired speed for
strategic agility. In the absence of knowledge, it will not be able to pursue its opportunities, and will instead
misuse them.
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2.4 Operational Performances
Operational performance refers to an organization‟s level of functioning, as weighed against typical benchmarks
of efficacy, productivity, and environment accountability― including waste reduction and regulatory
acquiescence, for example. This performance may be improved by including the consumer on pertinent matters
like quality and material flows, resulting in faster and more precise delivery of results. This CRM dimension
must be given suitable significance when coming up with SCM strategies (Vencataya, Seebaluk & Doorga, 2016).
Slack, Chamber Johnston (2004) quantified five distinct points to operational performance Costs the ability to
manufacture or provide at low cost and quality: the ability to manufacture or provide according to requirements,
without defects and speed: the ability to respond quickly to customer requests, and thus provide short time
periods also reliability: the ability to deliver goods and services as was promised to customers 5. Flexibility: The
capacity to vary procedures, in presence of changing circumstances. (Jensen and Sage, 2000), in the same vein,
identified many measurement goals for evaluating the performance of operations. These goals included
Cost-effectiveness, strategic positioning, sufficiency, utility, deliverability and feasibility, consistency, reliability,
accuracy, frequency, reasonableness, timeliness, response, known functions, and safety. It can be seen that
flexibility is a key factor, which many researchers see as increasing the efficacy of operational performance.
(Vanichchinchai,2014) argues that many organizations use flexibility, or their operational ability to successfully
adapt to environmental changes and address requirements, to achieve a level of competitive advantage. Russell
&Taylor (2004) noted that flexibility has become an important competitive weapon because it leads to quicker,
more substantial production and delivery of new products in response to customer needs.
3. Framework and Research Hypotheses
3.1 Research Model
Based on the literature review, the researcher is going to discuss the propose model impact of SCM activities on
operational performance. To reproduce more accurate analysis between SCM activities and operational
performance, the purpose of Strategic agility is mediated as important section in SCM In Industrial Companies.
Figure 1. the Study Model
3.2 Research Hypothesis
The First Main Hypothesis:
H01: There is No relationship between SCM activities (Alliances with suppliers, Customer Relationship
Management, Logistic, Information and knowledge sharing) and operational performance (at 0.05 levels).
From This Main Hypothesis the Following Sub-Hypotheses.
H01-1: There is No relationship between SCM activities (Alliances with suppliers) and operational performance
(at 0.05 level).
H01-2: There is No relationship between SCM activities (Customer Relationship Management) and operational
performance (at 0.05 level).
H01-3: There is No relationship between SCM activities (Logistic) and operational performance (at 0.05 level).
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H04-2: Strategic Agility (SA) does not mediate the relationship between Information – Knowledge Sharing(IKS)
and operational performance (OP) at 0.05 level.
The Second Main Hypothesis:
H02: Strategic Agility (SA) does not mediate the relationship between SCM activities and operational
performance (OP) at 0.05 level.
H01-2: Strategic Agility (SA) does not mediate the relationship between Alliance with Support (AWS) and
operational performance (OP) at 0.05 level
H02-2: Strategic Agility (SA) does not mediate the relationship between Customer Relation Management (CEM)
and operational performance (OP) at 0.05 level.
H03-2: Strategic Agility (SA) does not mediate the relationship between Logistic and operational performance
(OP) at 0.05 level.
H04-2: Strategic Agility (SA) does not mediate the relationship between Information – Knowledge Sharing(IKS)
and operational performance (OP) at 0.05 level.
4. Research Methodology
The study methodology describes the methods used to test the conceptual framework in an experimental manner
and thus provides a method for answering the research problem and research questions. In this research the
descriptive research describes the data and characteristics of what is being studied. The idea behind this type of
research is to study frequencies, averages, and other statistical calculations. Describing the phenomena for area
will be studied as well. To test the proposed theoretical model, the (22) AMOS program is used. An important
feature of the structural the equation model method used is not only the flexibility of its role in the interaction
between theory and data, but also its ability to bridge the gap between theoretical and empirical knowledge to
obtain a perfect conception of the world (Fornell & Larcker, 1981). This type of analysis enables the formation
of modeling based on both apparent and underlying variables, which is an important characteristic of
well-assumed model, since most formulations represent an unnoticeable abstraction rather than experimental and
concrete phenomena. Moreover, in modeling the structural equation, measurement errors, multi-group
comparisons and variables with multiple indicators are taken into account. This type of Analysis enables
modeling to be modeled based on both apparent and latent variables. Moreover, when formulating the structural
equation, measurement, multi-group comparisons, and variables with multiple indices are taken into account.
4.1 The Population and Sample of the Study
The study population consisted of all Jordanian companies „pharmaceutical companies listed on the Amman
stock exchange in Jordan it was (16), The sampling element and analysis was all the executives and directors of
departments, sections and employee specialized in SCM in pharmaceutical companies. To Select the sample of
the study, the researcher employs a simple random sample representing Composed of 150 members were
distributed questionnaires to the sample were retrieved 139 questionnaires, which is supposed to collect data for
statistical analysis for each company.
Table (1) presents the characteristics of study sample.
Table 1. Describing the Sample’s Personal and Demographic Variables
Variable Category Counts %
Gender
Males 59 42.4
Females 80 57.6
Total 139 100
Job
1 22 15.8
2 33 23.7
3 49 35.3
4 21 15.1
5 12 8.6
6 2 1.4
Total 139 100
Department
1 44 31.7
2 27 19.4
3 7 5.0
4 14 10.1
5 22 15.8
6 25 18.0
Total 139 100
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Experience
1 16 11.5
2 75 54.0
3 32 23.0
4 3 2.2
5 13 9.4
Total 139 100
Position
1 10 7.2
2 39 28.1
3 27 19.4
4 63 45.3
Total 139 100
4.2 Study Instrument
The questionnaire in this study which is prepared by researcher in based on literature review and a pilot test
before distributing the questionnaire contains a cover letter and a general definition that explained the purposes
of the survey and its perceived importance embedded in the questionnaire. In addition, the questionnaire is
divided into four major sections (See Appendix A). The first section is devoted to identify the sample
characteristics, including the characteristics of the respondents (gender, job position, department, and
Experience).The second section of the questionnaire includes five-point Likert scale from 1 (strongly disagree)
to 5 (strongly agree) to identify the purpose of research includes 4 items for every factor in part one and
SCMincludes 4 items in every factor in part two the mediating factor strategic agility and finally 4 questions
about the operational performance includes 4 items.) Saunders et al., 2007) indicates rating questions most
frequently use the Likert-style rating scale.
4.3 Confirmatory Factor Analysis (CFA)
Confirmatory factor analysis (CFA) was performed using AMOS version 22 software. It provides both the
standardized and unstandardized loading for each item on its proposed (latent) variable. The software provides an
advantage that it gives an indication for the goodness of fit for the overall data variables being used in the model.
The provided indicators are numerous. The researcher will use the most common indicators (five) that most studies
rely on to decide the goodness of model fit, chi square test (χ
2
), the (χ
2
/df), comparative fit index CFI, the goodness
of fit index GFI and the root mean square error approximate RMESA. Each of these indicators has a reference
value, which reflects good model fitting. In general, the chi square test is the inferential test that uses probability to
accept or reject the goodness of fit; the desire situation is that the probability of chi square test is > 0.05 suggesting
no statistical differences between the real (actual measured model) and the theoretical one. One major negative
aspect of chi square is that it is sensitive to the sample size (i.e. its affected and varied largely among different
sample sizes) accordingly rarely that a researcher obtains a suitable desired chi square value (i.e. p>0.05). In the
same context the RMSEA indicator refers to the average of squared errors, so as less the value as the desired
situation is met, typically a value less than 0.08 is considered to be good indicator, (the ideal situation is to equal
0.00). Both the CFI and GFI indicators ranges between (0 -1) so a value of 0.90 or higher suggest good fitting.
Concerning the χ
2
/df indicator, it is considered good indicator if the obtained value was (< 3)
The results pertaining the independent variable (SCMA), the dependent variable (OP) and the mediator variable
(SA) are provided in the following tables.
Table 2. Convergent Validity and Reliability analysis Results Composite (CR) And Cronbach Alpha (CA) Using
Confirmatory Factor Analysis (CFA)
Factor Code
Factor
loadings
AVE CR Cronbach alpha
Alliance with suppliers (AWS)
IV 1.1 0.749
0.546 0.868 0.810
IV 1.2 0.648
IV 1.3 0.837
IV 1.4 0.711
CRM
IV 2.1 0.637
0.513 0.832 0.710
IV 2.3 0.745
IV 3.1 0.638
IV 2.4 0.826
Logistic
IV 3.11 0.751
0.521 0.872 0.804 IV 3.2 0.822
IV 3.3 0.754
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IV 3.4 0.529
Information -Knowledge sharing(IKS)
IV 4.1 0.656
0.508 0.857 0.814
IV 4.2 0.823
IV 4.3 0.751
IV 4.4 0.603
Strategic agility (SA)
MV 4.1 0.839
0.542 0.860 0.864
MV 4.2 0.613
MV 4.3 0.727
MV 4.4 0.748
Operational Performance (OP)
DV 4.1 0.668
0.515 0.861 0.871
DV 4.2 0.876
DV 4.3 0.698
DV 4.4 0.598
Table (2) presents the results items loadings reflect the concept of convergent validity using the technique of
CFA (confirmatory factor analysis). Inspecting the results provided by table (2) it can be seen that the minimum
loading was assigned to the item coded (IV 3.4) in the logistic factor which was (0.529) so this value was above
the minimum required (0.50) suggesting reasonable convergent validity for each factor. As a result, the
convergent validity is considered satisfied the table presents the values of an important indicator for the factors
validity (AVE) it represents the amount of variance among the items of the factor, this indicator values must be >
0.50 as a good indication of the factor validity. Inspecting the provided values, we can see that the minimum
value was (0.508) for the Information – Knowledge sharing (IKS). So, the results tell that the validity of the
factors has been satisfied.
The table also indicates the results of both the composite and Cronbach alpha reliabilities. Inspecting the
provided values (CR) it can be seen that the minimum value obtained was (0.832) for CRM items factor, while
the minimum value obtained using the (CA) was (0.710) for CRM items factor. The reliability mentioned values
reflect satisfactory reliability values (> 0.70) so a conclusion of a high reliability could be considered.
Table 3. Model fitting indicators
χ2 p χ2/df GFI CFI RMSEA
Indicators 3.16 0.674 0.633 0.98 0.99 0.010
critical values 0.00 1.00 3.00 (0.90 – 1.00) (0.90 – 1.00) (0.00 – 0.08)
According to the results provided in table (3) the chi square value (3.16) is considered to be not statistically
significant as the related probability value (0.674) was > 0.05 suggesting no significant differences. The value
ofχ
2
/df indicator was (0.633), the value of the goodness of fit index GFI was (0.98) and the value of the
comparative index CFI was (0.99) suggest a very good and acceptable values as they were above the critical
(0.90). Finally, the RMSEA value was (0.010) suggesting a good and acceptable fitting as the value was < 0.08.
The mentioned indices suggest good model fitting.
4.4 Discriminate Validity
Table 4. Discriminate Validity Results
FACTORS AWS CRM Logistic IKS Strategic agility
AWS 0.739
CRM .447** 0.716
Logistic .484** .485** 0.722
IKS .496** .484** .481** 0.713
Strategic agility .609** .615** .721** .670** 0.736
Table (4) indicates the discriminate validity results. This type of validity assumes that the variable correlate with
an acceptable degree (generally < 0.70). According to results included the greatest correlation value between
Logistic and the mediator variable (Strategic agility) was (0.721). Such value may be considered to be accepted
as these two variables are strongly correlate in real despite that the importance of each as a separate variable.
Another important measure for discriminate validity is the square root of the (AVE) presented in bold and
diagonally. With this measure its assumed that its value will be greater than the other correlations included by the
other variables. Obviously, the mentioned values satisfy this criterion; accordingly, the discriminate validity is
considered to be met.
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4.5 Statistical Analysis and Hypothesis Testing.
Table 5. Means, Standard Deviations and Relative Importance Index RI
No. Factors M SD RI % Level
1 Alliance with Suppliers (AWS) 4.09 0.53 81.80 High
2 CRM 4.23 0.57 84.60 High
3 Logistic 3.93 0.65 78.60 High
4 Information – Knowledge sharing (IKS) 3.78 0.59 75.60 High
5 SCMA activities 4.01 0.46 80.20 High
6 Strategic agility (SA) 4.05 0.47 81.00 High
7 Operational performance (OP) 4.13 0.48 82.60 High
Note. Means description (1 – 2.33 low, 2.34 – 3.67 moderate, 3.68 – 5 high)
Table (5) indicates the values of means and standard deviation and relative importance index RI (expressed in
percentage), for the study variables (factors).The results tell that all the variables had been reported “high”
according to the sample‟s opinions. Concerning the sub factors of (SCMA) it was noticed that CRM was the
highest sub factor rated (4.23) and that the (IKS) was minimal sub factor that was rated (3.78) .The Strategic agility
(SA) was rated by a mean of (4.05) and the that the operational performance was assessed by the sample by a mean
of (4.13).
Table 6. Means and Standard Deviations for the Items in each Dimension
DIMENSION ITEMS MEAN SD
Alliance with suppliers
a1 4.06 0.74
a2 4.04 0.89
a3 3.97 0.85
a4 4.29 0.63
CRM
b1 4.17 0.83
b2 4.35 0.70
b3 4.26 0.71
b4 4.16 0.85
Logistic
c1 4.03 0.77
c2 3.96 0.78
c3 3.94 0.84
c4 3.81 0.87
Information – Knowledge
sharing
d1 3.81 0.81
d2 3.94 0.81
d3 3.77 0.73
d4 3.59 0.89
Strategic agility
M1 4.14 0.59
M2 4.18 0.70
M3 3.99 0.72
M4 3.89 0.62
Operational Performance
Y1 4.23 0.63
Y2 4.37 0.65
Y3 4.01 0.70
Y4 3.89 0.60
4.5.1 Hypothesis Testing
The hypotheses related to the impact of the independent variable on the dependent variable
Table 7. Standardized Total Effects
Hypotheses Impact Direction β prob
H01 SCM (IV) —> OP 0.991 ***
H01-1 AWS —> OP 0.643 ***
H01-2 CRM —> OP 0.613 ***
H01-3 Logistic —> OP 0.585 ***
H1-4 IKS —> OP 0.598 ***
Note. Indicate that the probe value is < 0.001***
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Model 2. results using structured equations model
1- Results of Testing the Main Hypothesis:
H01: There is No relationship between SCM activities (Alliances with suppliers, Customer Relationship
Management, Logistic, Information and knowledge sharing) and operational performance (at 0.05 levels).
Based on the results provided by table (6) the impact value of the SCM activities on the operational performance
(OP) was expressed by the standardized beta coefficient (0.991) this impact value was considered to be
statistically significant as the related probability value was < 0.05 (actually< 0.001).Consequently, the null
hypothesis represented by the main one is rejected concluding that SCM activities affects (OP).
2- Results of testing the sub hypothesis:
H01-1: There is No relationship between SCM activities(Alliances with suppliers)and operational performance(at
0.05 level).
Based on the results provided by table (6) the impact value of the Alliances with suppliers (AWS) on the
operational performance (OP) was expressed by the standardized beta coefficient (0.643) this impact value was
considered to be statistically significant as the related probability value was < 0.05 (actually < 0.001).
Consequently, the null hypothesis represented by the main one is rejected concluding that the Alliances with
suppliers (AWS) affect (OP).
H01-2: There is No relationship between SCM activities (Customer Relationship Management) and operational
performance (at 0.05 level).
Based on to the results provided by table (6) the impact value of the Customer Relationship Management (CRM)
on the operational performance (OP) was expressed by the standardized beta coefficient (0.613) this impact
value was considered to be statistically significant as the related probability value was < 0.05 (actually < 0.001).
Consequently, the null hypothesis represented by the main one is rejected concluding that Customer Relationship
Management affects (OP)
H01-3: There is No relationship between SCM activities (Logistic) and operational performance (at 0.05 level).
Based on the results provided by table (6) the impact value of Logistic on the operational performance (OP) was
expressed by the standardized beta coefficient (0.585) this impact value was considered to be statistically
significant as the related probability value was < 0.05 (actually < 0.001).
Consequently, the null hypothesis represented by the main one is rejected concluding that Logistic affects (OP).
H01-4: There is No relationship between SCM activities (Information and knowledge sharing)and operational
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performance (at 0.05 level).
Based on the results provided by table (6) the impact value of the Information and knowledge sharing (IKS) on
the operational performance (OP) was expressed by the standardized beta coefficient (0.598) this impact value
was considered to be statistically significant as the related probability value was < 0.05 (actually < 0.001).
Consequently, the null hypothesis represented by the main one is rejected concluding that Information and
knowledge sharing (IKS) affects (OP).
The hypotheses related to the mediator variable strategic agility (SA) effect on the relationship between the
independent variable (SCM) on the dependent variable (OP).
Results of testing the second main hypothesis
Table 8. Standardized Direct Effects for the Relations between the Independent Factors and Mediator
Relation direction
Direct Effects
β p
SCMA (IV) —> (SA) 0.863 ***
AWS —> (SA) 0.537 ***
CRM —> (SA) 0.510 ***
Logistic —> (SA) 0.522 ***
IKS —> (SA) 0.529 ***
SA (MV) —> (OP) 0.212 ***
Note. Indicate that the prob value is < 0.001***))
Table 9. Standardized Direct, Indirect and Total Effects, With the Confidence Interval for the Models Mediated
Relations
Relation
direction
Direct
Effects
Indirect
effects
Total
effect
VAF
(%)
β p value CI.L CI.U
SCMA (IV) —> (OP) 0.808 *** 0.183 0.088 0.311 0.991 22.65
AWS —> (OP) 0.529 *** 0.114 0.240 0.467 0.643 21.55
CRM —> (OP) 0.505 *** 0.108 0.274 0.493 0.613 21.39
Logistic —> (OP) 0.474 *** 0.111 0.274 0.456 0.585 23.42
IKS —> (OP) 0.486 *** 0.112 0.230 0.431 0.598 23.05
Note. (VAF < 20 no mediation, between 20 to< 80 partial mediation and 80 + full mediation)
H02: Strategic Agility (SA) does not mediate the relationship between SCM activities and operational
performance (OP) at 0.05 level.
Based on the results provided by table (8) the indirect effect of strategic agility on the relationship between
supply chain management SCM activities and operational performance (OP) was estimated by (0.183) this value
was considered to be statistically significant as the biased corrected confidence interval limits did not include
“zero”. (The lower bound of the interval 0.088 was > 0.00). The table also provides the direct impact value of the
independent variable on the dependent variable this value was (0.808) so the total effect was (0.991). The
mediation that appeared is considered to be partially affecting the relationship between the independent and
dependent variables because the relationship significance was the same prior and with the presence of the
mediator. In the same context the VAF (variance accounted for) value (22.65 %) which reflects the percentage of
the indirect effect to the total effect indicate that the mediation numerically is considered to be partially too. once
the impact signs of the two paths of mediator were the same (positive); the effect is called complementary
partial.
Consequently, the null hypothesis represented by the main one is rejected concluding that strategic agility (SA)
mediates the relationship between SCM activities affects (OP) at 0.05.
2- Results of testing the second sub main hypothesis:
H01-2: Strategic Agility (SA) does not mediate the relationship between Alliance with Support (AWS) and
operational performance (OP) at 0.05 level.
Based on the results provided by table (8) the indirect effect of strategic agility on the relationship between
Alliance with Support (AWS) and operational performance (OP) was estimated by (0.114) this value was
considered to be statistically significant as the biased corrected confidence interval limits did not include “zero”.
(The lower bound of the interval 0.240 was > 0.00). The table also provides the direct impact value of the
independent variable on the dependent variable this value was (0.529) so the total effect was (0.643). The
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85
mediation that appeared is considered to be partially affecting the relationship between the independent and
dependent variables because the relationship significance was the same prior and with the presence of the
mediator. In the same context the VAF (variance accounted for) value (21.55 %) which reflects the percentage of
the indirect effect to the total effect indicate that the mediation numerically is considered to be partially too. once
the impact signs of the two paths of mediator were the same (positive); the effect is called complementary
partial.
Consequently, the null hypothesis represented by the first sub main hypothesis is rejected concluding that
Strategic Agility (SA) mediates (partially)the relationship between Alliance with Support (AWS) and operational
performance (OP) at 0.05.
H02-2: Strategic Agility (SA) does not mediate the relationship between Customer Relation Management (CEM)
and operational performance (OP) at 0.05 level.
Based on the results provided by table (8) the indirect effect of strategic agility on the relationship between
Customer Relation Management (CEM) and operational performance (OP) was estimated by (0.108) this value
was considered to be statistically significant as the biased corrected confidence interval limits did not include
“zero”. (The lower bound of the interval 0.274 was > 0.00). The table also provides the direct impact value of the
independent variable on the dependent variable this value was (0.505) so the total effect was (0.613). The
mediation that appeared is considered to be partially affecting the relationship between the independent and
dependent variables because the relationship significance was the same prior and with the presence of the
mediator. In the same context the VAF (variance accounted for) value (21.39 %) which reflects the percentage of
the indirect effect to the total effect indicate that the mediation numerically is considered to be partially too. once
the impact signs of the two paths of mediator were the same (positive); the effect is called complementary
partial.
Consequently, the null hypothesis represented by the second sub main hypothesis is rejected concluding that
strategic agility (SA) mediates (partially) the relationship between Customer Relation Management (CEM) and
operational performance (OP) at 0.05.
H03-2: Strategic Agility (SA) does not mediate the relationship between Logistic and operational performance
(OP) at 0.05 level.
Based on the results provided by table (8) the indirect effect of strategic agility on the relationship between
Logistic and operational performance (OP) was estimated by (0.111) this value was considered to be statistically
significant as the biased corrected confidence interval limits did not include “zero”. (The lower bound of the
interval 0.274 was > 0.00). The table also provides the direct impact value of the independent variable on the
dependent variable this value was (0.474) so the total effect was (0.585). The mediation that appeared is
considered to be partially affecting the relationship between the independent and dependent variables because the
relationship significance was the same prior and with the presence of the mediator. In the same context the VAF
(variance accounted for) value (23.42 %) which reflects the percentage of the indirect effect to the total effect
indicate that the mediation numerically is considered to be partially too. once the impact signs of the two paths
of mediator were the same (positive);the effect is called complementary partial.
Consequently, the null hypothesis represented by the third sub main hypothesis is rejected concluding that
strategic Agility mediates (partially) the relationship between logistic and (OP) at 0.05.
H04-2: Strategic Agility (SA) does not mediate the relationship between Information – Knowledge Sharing(IKS)
and operational performance (OP) at 0.05 level. based on the results provided by table () the indirect effect of
strategic agility on the relationship between Information – Knowledge Sharing(IKS) and operational performance
(OP) was estimated by (0.112) this value was considered to be statistically significant as the biased corrected
confidence interval limits did not include “zero”. (The lower bound of the interval 0.230 was > 0.00). The table
also provides the direct impact value of the independent variable on the dependent variable this value was (0.486)
so the total effect was (0.598). The mediation that appeared is considered to be partially affecting the relationship
between the independent and dependent variables because the relationship significance was the same prior and
with the presence of the mediator. In the same context the VAF (variance accounted for) value (23.05 %) which
reflects the percentage of the indirect effect to the total effect indicate that the mediation numerically is
considered to be partially too. once the impact signs of the two paths of mediator were the same (positive); the
effect is called complementary partial.Consequently, the null hypothesis represented by the fourth sub main
hypothesis is rejected concluding that strategic Agility mediates (partially) the relationship between Information
– Knowledge Sharing (IKS) and operational performance (OP) at 0.05.
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86
5. Conclusion
Based on literature review the Strategic agility aims to make companies respond to the changes that occur around
them in the external environment, and keep pace with that by leaving the traditional routine practices that do not
achieve the goals of the institution quickly, efficiently and quality required, which makes them slow performance
in an era characterized by rapid and continuous change, and replaced by practices and mechanisms. A new
business that makes the organization faster in performance – more flexible – towards achieving the desired goals
effectively in the era of competition and aims to make the business respond quickly to the changes that take
place around it in the external environment, and keep pace with that by leaving the traditional routine practices
that do not achieve the goals of the institution as quickly Efficiency and required quality, which makes its
performance slow in an era characterized by rapid and continuous change, and its replacement by a new practice
and mechanisms of work that make the institution faster in performance – more flexible – towards achieving the
desired goals effectively in the era of competitiveness. At below reflect the Statistical results from practical
implication from Pharmaceutical Companies.
1. The null hypothesis represented by the main one is rejected concluding that the alliances with suppliers
(AWS) Affect (Op).
2. The null hypothesis represented by the main one is rejected concluding that customer relationship
management affects (OP).
3. The null hypothesis represented by the main one is rejected concluding that logistic affects (OP).
4. The null hypothesis represented by the main one is rejected concluding that information and knowledge.
Sharing (IKS) affects (OP).
5. The null hypothesis represented by the main one is rejected concluding that strategic agility (SA) mediates
the relationship between SCM activities affects (OP).
6. The null hypothesis represented by the first sub main hypothesis is rejected concluding that strategic agility
(SA)mediates (Partially) the relationship between alliance with support (AWS) and operational performance
(OP).
7. The null hypothesis represented by the second sub main hypothesis is rejected concluding that strategic
agility (SA) mediates (Partially) the relationship between customer relation management (CEM) and
operational performance (OP).
8. The null hypothesis represented by the third sub main hypothesis is rejected concluding that strategic agility
mediates (Partially) the relationship between logistic and (OP).
9. The null hypothesis represented by the fourth sub main hypothesis is rejected concluding that strategic
agility mediates(Partially) the relationship between Information – Knowledge Sharing (IKS) and Operational
Performance (OP).
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Appendix 1. Questionnaire
No. The clause Strongly
Agree
Agree Neutral Disagree Strongly
Disagree
Alliances with Suppliers
1. The company confirms communication openness with the
basic suppliers.
2. The company deals with its suppliers based on the
partnership.
3. The company work to engage the basic suppliers in
process of developing its products and services.
4. The company’s strategy depends on building good
relationship with the basic suppliers.
Customer Relationship Management
5. Customer satisfaction is a good which the company seeks
for.
6. In the company there is a specialized division for the
customer’s service.
7. In the company deals with the customers notes and
complaints in an appropriate way.
8. The company keeps complete database about the
customers.
Logistics
9. Does the company responds to the orders from time of
receiving the order and during its transportation and till
handling the bill and receiving the financial merits.
10. Is there a system in the company for accuracy and
complete orders- the absence of returned orders?
11. Logistics management in the company includes planning,
scheduling the production and monitoring them.
12. Logistic management includes all planning and
implementation levels (The Executive and Tactical
Strategy)
Flow Information and Knowledge Sharing
13. The company possesses electronic system to speed-up the
information exchange internally.
14. The company uses the electronic networks for exchanging
information with the customers.
15. The company uses the electronic networks to exchange
information with the suppliers.
16. The company shares the knowledge’s and the information
with the suppliers in building its plans.
Operational Performance
17. The company has the ability to respond to the changes in
the products qualities and the outputs according to
environment change.
18. The company continues in updating the promotion means
and method for its products.
19. The company keeps the minimum limit of the stock to
enable it to work in case of delay in the raw materials and
to reduce cost per-piece .
20. The company cares about delivering the urgent demands
quickly with high quality.
Strategic Agility
21. Distribution flexibility or the ability to provide
widespread access to products.
22. The company adjusts its strategy to felt with the changing
conditions and the surrounding environment.
23. The company’s management possesses the flexibility in
redistributing the resources and benefit from them.
24. The company provides ease of reach to the information
concerning the customers and the workers alike.
Copyrights
Copyright for this article is retained by the author(s), with first publication rights granted to the journal.
This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution
license (http://creativecommons.org/licenses/by/4.0/).
peer-reviewed sources/Service Quality and Customer Satisfaction.pdf
International Journal of
Environmental Research
and Public Health
Article
Service Quality and Customer Satisfaction in
Pharmaceutical Logistics: An Analysis Based on Kano
Model and Importance-Satisfaction Model
Mu-Chen Chen 1,*, Chia-Lin Hsu 2 and Li-Hung Lee 3
1 Department of Transportation and Logistics Management, National Chiao Tung University,
Taipei 100, Taiwan
2 Department of International Business Administration, Chinese Culture University, Taipei 11114, Taiwan;
[email protected]
3 Department of Transportation and Logistics Management, National Chiao Tung University,
Taipei 100, Taiwan; [email protected]
* Correspondence: [email protected]
Received: 30 September 2019; Accepted: 21 October 2019; Published: 24 October 2019
����������
�������
Abstract: The implementation of National Health Insurance in Taiwan has affected the medical
industry by significantly depleting the supply chain’s profits. Service providers in the medical industry
must meet the dual-service expectation of serving as medical manufacturers with upper reaches and
as suppliers in the downstream marketing channel. As a result, service providers must anticipate
customer requirements, offer new service items that align with customer demands and improve
the quality of existing services. This study aims to examine consumer perspectives about service
satisfaction in the domestic medical industry using Kano’s two-dimensional model. In addition,
it employs the importance-satisfaction model to determine service items that need improvement.
The empirical findings show that consumer perceptions about service quality attributes vary and
thus, service items may be categorized differently in Kano’s model. Further, the reliability of service
quality significantly affects customer satisfaction. Thus, service providers can gain a competitive
edge and maintain their market position by offering high value added and critical quality attributes.
Finally, analyzing customer attitudes toward new service items for indifference quality will help
service providers determine effective tactics in a competitive market. In general, service providers
should assign higher priority to items that customers consider in need of improvement.
Keywords: pharmaceutical logistics; Kano model; service quality; customer satisfaction
1. Introduction
Since the implementation of National Health Insurance, the revenue and expenditure situation of
the health insurance industry has been at a continual loss. Further, the Health Insurance Bureau has
made several efforts to control the wastage of medical resources effectively and has adopted a series of
policy measures to curb the growth of medical expenses, reduce problems related to healthcare finance
and decrease drug prices. Measures, such as per-case payment, compensation-based payment, the total
budget system and reasonable outpatient volume have significantly impacted medical institutions,
resulting in a gradual decline in their revenue. Medical institutions initially demanded the use of the
open-source method to expand business volume, although the total budget system and the mandate
for reasonable outpatient volume were implemented. As a result, medical institutions were required
to strengthen cost control using business management methods and reconsider the circulation of
medical material.
Int. J. Environ. Res. Public Health 2019, 16, 4091; doi:10.3390/ijerph16214091 www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2019, 16, 4091 2 of 23
In a hospital’s cost structure, personnel costs account for the highest proportion, followed
by material cost and hospital purchases. From an operational perspective, medical institutions
must (1) function in an open, fair and equitable bidding environment to obtain reasonable low-cost
pharmaceutical materials; (2) reduce storage space to increase inventory turnover and expand
space for medical services and (3) implement the automated collection of order lists to reduce
in-hospital distribution frequency and zero inventory management through the systematic and
effective management of inventory and order quantities. Hospitals have to consider ways to reduce
expenses incurred for the various aspects of medical treatments. The industry explored, for example,
the integration of logistics, which resulted in the outsourcing of pharmaceutical logistics for medical
materials. The rapid and convenient distribution of logistics services is expected to promote the medical
industry through a combination of logistics, information management and automated connection.
This reduces unnecessary costs, creates additional profits, forms a general business model, decreases
operating costs and meets the demand for limited diversified drugs and medical material, thereby
enhancing the overall logistics performance of the medical industry supply chain.
The distribution channels of the pharmaceutical industry are relatively closed compared to
those of other industries. Most pharmaceutical manufacturers engage with logistics or distribution
companies that commission non-professional drugs, which offer poor logistics and distribution quality.
Pharmaceutical logistics must meet the special needs of hospitals, clinics, pharmacies and homecare
treatments, which include storage conditions as well as temperature and humidity control. In a
distribution environment, it is increasingly important to maintain stability in medicine quality during
inventory management and circulation.
Upstream domestic and foreign pharmaceutical manufacturers are constantly striving to survive
this highly competitive industry with a large-scale medical supplies market. To reduce the overall
inventory costs and accurately forecast market demand, manufacturers outsource logistics to
professional third-party pharmaceutical logistics companies. In doing so, they seek cost, strategy and
quality alternatives to reduce logistics costs, improve industry focus, enhance market competitiveness
and eventually, earn higher profits.
Pharmaceutical logistics operators must meet the dual-service expectation of functioning as
upstream pharmaceutical manufacturers and downstream marketers of medical products. To
achieve the loyalty of customers and pharmaceutical companies and to gain market advantages,
pharmaceutical logistics service providers must continually improve their service quality while
accounting for input costs. However, once the quality improvement has reached a certain level,
additional investments are unlikely to produce the same profits. Thus, it is important to examine how
pharmaceutical logistics operators can better understand consumer needs over those of competitors and
upstream pharmaceutical companies to provide services that satisfy consumer demand and improve
service quality.
Improving service quality is a key competitive factor in a service-oriented business model. In their
PZB (i.e., the abbreviation of Parasuraman, Zeithaml & Berry) model, Parasuraman et al. (1988) stated
that quality is a measure of customer perception and is based on consumers’ subjective judgment [1].
That is, in addition to a company’s objective identification, service quality must be accounted for as
the customers’ subjective identification to improve service level. Moreover, customers must be able
to recognize the service quality so that service providers can determine if the improvements meet
customer needs. In this customer-oriented era, convenience has gradually gained attention. The key
focus of customer convenience is improving service standards, which, in turn, will be the basis for
added customer support. Similarly, service convenience is an important aspect of logistics services.
Numerous industries and the service industry, in particular, are increasingly prioritizing customer
satisfaction. Customer satisfaction is achieved by evoking feelings of loyalty and satisfaction in
a customer. Service providers can gain customer attention by identifying customer interests from
an empathy perspective and by offering products and services that resolve customer problems,
thus creating a level of intimacy between the consumer and the service. Cognitive assessments
Int. J. Environ. Res. Public Health 2019, 16, 4091 3 of 23
conducted from a customer viewpoint suggest that convenient services are designed through continuous
improvement aimed at achieving consumer attention and satisfaction.
To achieve consumer satisfaction, it is critical to first examine the customers’ opinions of service
quality, understand related characteristics or dimensions to measure service and product quality,
and strengthen quality factors that are of concern to customers. The most appropriate approach for
achieving customer satisfaction is improving service quality. In addition to optimizing the use of limited
resources, promptly responding to changing customer needs is critical to improve service quality and
achieve customer satisfaction. This also plays an important role in enhancing industry competitiveness.
Adopting a narrow view of quality facets is unlikely to translate into a true understanding of the
consumers’ quality perception. A one-dimensional quality view of customer satisfaction with products
and services considers service quality to be a linear factor. To address the cognitive shortcomings of
the one-dimensional quality view, Kano proposes a two-dimension model that states that satisfaction
is achieved when certain quality requirements have been met, whereas the failure to do so leads to
dissatisfaction [2]. The two-dimensional quality model evaluates customer satisfaction and its source
on the basis of five quality factors: performance, basic, excitement, indifference and reverse.
Using the domestic pharmaceutical logistics industry as an example and the hospital industry as
the research object, this study examines service quality and consumer satisfaction in the pharmaceutical
logistics industry using the PZB model and Berry et al.’s definition of service convenience [3]. Further, it
explores the key factors motivating the pharmaceutical industry to outsource services to major logistics
providers in the domestic pharmaceutical industry. A key finding is that customers are attracted to
services whose quality is aligned with their requirements.
2. Literature Review and Hypothesis Development
2.1. Pharmaceutical Logistics
Pharmaceutical logistics include the operations and activities such as warehousing, inventory
management and transportation for pharmaceuticals. Many pharmaceutical products and medical
devices are temperature sensitive and they need to be in a temperature-controlled environment.
According to MarketWatch’s report, pharmaceuticals cold-chain logistics is defined as “an uninterrupted
series of refrigerated supply chain activities including refrigerated storage and transportation from their production
point to destination of consumption [4].” In recent years, the healthcare service industry has paid much
attention on implementing logistics and supply chain management practice and strategy [5]. Logistics
management is one of the critical enablers for successful services in the healthcare industry. As people
expect efficient healthcare services, excellent pharmaceutical logistics are essential [6]. Several previous
studies have indicated that healthcare organizations can substantially benefit from successful logistics
management [7]. However, Landry et al. indicated that a hospital spends a sizable budget on logistics
operations and if healthcare professionals need to spend too much time on logistics operations, the
delivery of care is influenced [7].
Based on a report of Allied Market Research, Katare and Sonpimple indicated that transportation
of temperature-controlled pharmaceutical products and medical devices has expanded substantially in
the healthcare logistics industry [8]. Another report by Grand View Research, Inc., revealed that the
market of global pharmaceutical logistics is sizeable, amounting to USD (i.e., United States Dollar)
76.4 billion in 2018. Furthermore, the demand for pharmaceutical logistics has risen substantially due
to the requirement of supply chain reliability and the need to reduce distribution costs [9]. As medical
products have unusual demand and supply and they are quality sensitive, special knowledge is entailed
in the transportation operation [10]. Kumar and Jha indicated that maintaining stable temperature
during transportation can avoid damage to medical products, and careful transportation management
is also needed to avoid theft and mismanagement [10]. Summarizing the abovementioned reports
and previous research, the demand for and market of pharmaceutical logistics have been increasing,
and temperature control and management are essential for maintaining the quality of pharmaceutical
Int. J. Environ. Res. Public Health 2019, 16, 4091 4 of 23
products and medical devices. By using the analytical network process (ANP), Kritchanchai et al. found
that the strategies related to inventory management and information and technology management are
most essential to enhancing healthcare logistics performance [5].
2.2. Service Quality, Service Convenience, and Customer Satisfaction
Anderson and Sullivan argued that service quality is a pre-requisite of customer satisfaction [11].
Customer satisfaction depends on the performance of products and services and whether this
performance is consistent with consumer expectations. Satisfaction is generally defined as the feeling
of happiness customers experience from using products or services and it differs from expected
performance. Understanding consumer satisfaction with service quality expectations and perceptions
can serve as a basis to improve service quality, increase consumer repurchase, and enhance consumers’
willingness to recommend the service to others.
Early research focuses on resources expended by consumers to use a purchased good or service.
Etgar, for example, defined convenience as a reduction in the non-monetary cost attributes of goods [12].
Brown stated that convenience is the extent of time and effort invested by a consumer to use a service
and not the classification of product characteristics or attributes [13]. Berry et al. highlighted the lack
of a conceptual framework for service convenience in which time and energy are important aspects
and accordingly, listed various types of service convenience [3]. Their service convenience model
classified convenience into decision-making, access, transaction, benefit and post-benefit convenience.
Decision-making convenience is the time and effort consumers spend on deciding how to obtain a
desired service. Access convenience is the time and energy invested in accessing a service. Transaction
convenience is the amount of time and energy needed to conduct a transaction. Benefit convenience
is defined as the time and energy needed to experience the core features of the service. Finally,
post-benefit convenience is determined by the time and energy a consumer must invest in contacting a
company following service usage.
The amount of time and effort needed to obtain a desired service reduces when consumers can
easily understand product information and trust the professional ability and attitude of the service
staff. This highlights both service and decision-making convenience. However, if business hours
are considered inconvenient to the customer (e.g., customer service staff is difficult to contact) or
if service providers cannot meet customer demands, the extent of time and energy needed from a
customer increase. Both service and access convenience are exemplified in this case. When service
personnel promptly serve customers and complete service transactions on a timely basis, customers’
invested energy and time reduces, suggesting both service and transaction convenience. These
findings are in line with the PZB model. This study focuses on post-benefit and access convenience,
not decision-making, transaction, and benefit convenience proposed by the PZB model, to measure
customer satisfaction and service quality in the pharmaceutical logistics industry.
2.3. Kano Model
As per the one-dimensional quality model, customer satisfaction is achieved when certain quality
requirements are sufficiently met, whereas the failure to do so results in dissatisfaction. However, not
all quality factors can be characterized from such a one-dimensional perspective. Although different
from the traditional one-dimensional model, the two-dimensional quality model suggests that not all
quality factors lead to satisfaction and some may even result in dissatisfaction. Kano’s model draws on
the proposal by psychologist, Herzberg, to use the motivator-hygiene theory aimed at job satisfaction
and Dr. Ishikawa’s concept of backward quality that focuses on quality improvements. Kano et al.
renamed these to attractive quality and must-be quality in their two-dimensional quality model [2].
The model uses the abscissa to denote the quality elements and ordinates to represent the degree
of customer satisfaction. Kano further classified quality into attractive, one-dimensional, must-be,
indifferent quality, and reverse quality.
Int. J. Environ. Res. Public Health 2019, 16, 4091 5 of 23
Customers are satisfied when services have attractive quality, a desired quality whose absence
leads to dissatisfaction. Even a small number of related quality elements significantly improves
customer satisfaction, which can be further enhanced if the customers were not expecting these
elements. In the one-dimensional quality model, customer satisfaction is determined by the availability
of quality factors, where the higher the degree of quality, the greater the customer satisfaction. This
suggests a linear relationship between customer satisfaction and factor supply. For instance, consumer
satisfaction is not affected by the availability of must-be quality factors. However, their absence could
cause severe customer dissatisfaction. Kano also defined quality factors from the viewpoint of expected
quality, that is, consumers expect quality factors, and thus, they become basic characteristics of products
and services. Notably, irrespective of the extent of quality factors provided, the curve is unlikely
to exceed the horizontal axis. The indifferent quality factors do not influence customer satisfaction,
while reverse quality factors could lead to customer dissatisfaction and thus, their absence is preferred.
Kano’s two-dimensional quality model defined quality factors influencing customer satisfaction, and
the findings can be used as a reference to develop and improve products and services [14]. In other
words, companies must meet all basic quality requirements to achieve customer satisfaction and gain a
competitive advantage to attract new customers [15].
2.4. Importance-Satisfaction (IS) Model
Yang examined the relationship between the importance assigned by customers to quality factors
and customer satisfaction and found that both indicators contribute to an organization’s quality
improvement and decision making [16]. When assessing the overall quality, customers respond to
quality factors they consider important [16,17] and a company plays an important role in this evaluation.
The projects with high quality but low satisfaction should be subject to quality improvement [16]. The
importance-satisfaction (IS) model denotes the importance assigned to quality factors on the horizontal
axis and the degree of satisfaction derived from quality factors on the vertical axis. Each quality factor
is scored and the average or median of the importance assigned to quality factors lie in the center,
creating four quadrants: excellent, to be improved, surplus, and careless. The quality elements located
in the excellent quadrant are considered important by customers and lead to customer satisfaction.
Thus, companies aiming to retain their customers must strive for high performance in this area. The
elements in the to-be-improved area are critical but not as good as expected. Companies should work
toward offering such elements or immediately improving existing factors. Customers do not prioritize
quality elements in the surplus area. Thus, a company wanting to reduce costs can decrease the supply
of such elements without negatively affecting customer satisfaction. Finally, the elements in the careless
area are assigned low priority or considered unimportant. Companies can ignore such quality factors
because they do not affect overall customer satisfaction.
2.5. Hypotheses Development
Kano’s model further divided quality into five dimensions on the basis of the importance
assigned by consumers to quality factors and customer satisfaction: attractive, one-dimensional,
must-be, indifferent and reverse quality [2]. The model defined customer satisfaction in line with
these dimensions and the findings can serve as a reference for product or service development and
improvement [14]. Some researchers (e.g., [18–20]) confirmed that customer perceptions about quality
elements tend to differ and use Kano’s model to classify quality elements accordingly. In line with this
approach, this study proposes the following hypothesis.
Hypothesis 1 (H1): The characteristics of quality elements for pharmaceutical logistics services differ in the
Kano model.
Businesses tend to focus on continuous improvements to their products and services. Numerous
business firms employ customer satisfaction as an index to evaluate service performance as satisfied
Int. J. Environ. Res. Public Health 2019, 16, 4091 6 of 23
customers are more likely to repurchase and buy other products and services offered by the same
firm [21]. Some studies confirmed that quality elements are determinants of customer satisfaction [19,22].
Kano et al. suggested that attractive and one-dimensional quality elements increase customer
satisfaction, whereas the lack of one-dimensional and must-be quality elements results in customer
dissatisfaction [2]. Matzler and Hinterhuber identified the elements that significantly influence
customer satisfaction [14]. Accordingly, this study proposes the following hypothesis.
Hypothesis 2 (H2): Customer satisfaction is positively correlated with customers’ positive perceptions of
attractive, one-dimensional, and must-be quality elements.
Medical institutions have varying characteristics, and thus, their response to quality attributes of
pharmaceutical logistics services tends to differ. Studies (e.g., [18–20]) confirmed that these varying
characteristics result in quality elements being differently classified in the Kano model. This study,
therefore, presents the following hypothesis.
Hypothesis 3 (H3): Medical institutions with different characteristics have varying views about the quality
elements of medical logistics services.
3. Methodology
3.1. Sample and Data Collection
The participants of this study are teaching and non-teaching hospitals that function under the
Ministry of Health and Welfare, Executive Yuan. A total of 475 questionnaires were distributed for
convenience sampling. Of these, 104 questionnaires were returned, indicating a response rate of 22%.
Table 1 presents the sample’s demographics.
Table 1. Demographic statistics.
Characteristics Frequency Percentage (%)
Area North 30 28.85
Middle 33 31.73
South 35 33.65
Other 6 5.77
Gender Male 31 29.81
Female 73 70.19
Age ≥24 3 2.88
25–34 41 39.42
35–49 47 45.19
50–64 11 10.58
≤65 2 1.92
Int. J. Environ. Res. Public Health 2019, 16, 4091 7 of 23
Table 1. Cont.
Characteristics Frequency Percentage (%)
Education level High school or below 8 7.69
College 92 88.46
Graduate school or above 4 3.85
Seniority ≤3 19 18.27
4–6 23 22.12
7–10 28 26.92
11–15 13 12.50
≥16 21 20.19
Using pharmaceutical
logistics time
≤3 34 32.69
4–6 29 27.88
7–10 25 24.04
11–15 9 8.65
≥16 7 6.73
The most frequently
used pharmaceutical
logistics type
Professional pharmaceutical
logistics
69 66.35
General logistics 17 16.34
Both 18 17.31
3.2. Questionnaire Design
The questionnaire was designed on the basis of the SERVQUAL (i.e., the abbreviation of service
quality) scale developed by Parasuraman et al. [1] and the two dimensions of benefit and post-benefit
convenience proposed by Berry et al. [3].
This study also employed Kano’s model to classify quality elements into attractive,
one-dimensional, must-be, indifferent and reverse [2]. The questionnaire contains both functional
(positive) and dysfunctional (negative) questions for each service element. The former is for customer
responses to service elements and the latter documents responses to services that are not delivered.
For example, “How would you feel if the delivery staff wore neat and tidy clothing?” is a functional
question and “How would you feel if the delivery staff did not wear neat and tidy clothing?” is
a dysfunctional question. The respondents’ replies were then subject to the quality classifications
proposed in the Kano model.
Drawing on Matzler and Hinterhuber [14], the questionnaire offers five response options to classify
service elements: “I like it,” “It must be that way,” “I am neutral,” “I don’t mind” and “I dislike it.”
The service elements were classified into Kano element types on the basis of their scores. Referencing
previous studies [18–20], the questionnaire also documents basic information such as information on
companies and respondents. The options offer a reasonable level of clarity to the present investigation
on pharmaceutical logistics services. Prior to formally administering the questionnaire, a pre-test was
conducted with five users of logistics services for the healthcare cold chain. The questionnaire was
modified according to the pre-test results.
The questionnaire comprises three parts: respondents’ demographics, functional and dysfunctional
questions, and the importance of and satisfaction with pharmaceutical logistics services. A five-point
Likert scale was used to measure the importance assigned to (1 is “very unimportant” and 5 is “very
important”) and satisfaction derived from (1 is “very unsatisfied” and 5 “very satisfied”) the services
offered by pharmaceutical logistics service providers.
Int. J. Environ. Res. Public Health 2019, 16, 4091 8 of 23
4. Analysis and Results
4.1. Reliability and Validity Analysis
The reliability of each construct measured by the coefficient of Cronbach’s alpha exceeds 0.7, which
is consistently high across all constructs. Cronbach’s alpha for all dimensions—tangibility, reliability,
responsiveness, assurance, empathy, benefit convenience and post-benefit convenience—range between
0.781 and 0.968. This indicates that the constructs for these scales have high reliability. To gain insight
on the relationships among these constructs, the two conditions of convergent validity and discriminant
validity must be fitted.
The convergent validity test shows that the factor loadings for all measures of the underlying
constructs exceed 0.5 (0.521–0.930). This confirms that the composite reliabilities of all constructs
exceed the 0.7 cut-off value (0.78–0.86) recommended by Fornell and Larcker [23]. The average variance
extracted from each construct exceeds 0.5 (0.53–0.67), indicating convergent validity [23]. In sum,
the proposed constructs of the extended model are adequate as per the results of the convergent
validity test.
Next, a discriminant validity test was conducted to assess the degree to which the constructs
differ. If the items in a construct are more strongly correlated with each other than with the items
measuring other constructs, the evaluation is considered to have discriminant validity. Table 2 presents
the squared inter-correlations among the study constructs. In particular, it shows that the shared
variance among the constructs does not exceed the square root of average variance explained. These
results confirm discriminant validity.
Table 2. Discriminant validity analysis.
Tan Rel Res Ass Emp BC PBC
Tan 0.692
Rel 0.385 0.856
Res 0.395 0.333 0.683
Ass 0.405 0.276 0.522 0.767
Emp 0.395 0.478 0.625 0.453 0.667
BC 0.277 0.396 0.450 0.270 0.534 0.710
PBC 0.388 0.276 0.602 0.388 0.547 0.541 0.695
Notes: Tan: Tangibility; Rel: Reliability; Res: Responsiveness; Ass: Assurance; Emp: Empathy; BC: Benefit
convenience; PBC: Post-benefit convenience; All correlations are significant at the 0.05 level. The diagonals represent
the square root of average variance extracted.
4.2. Kano Model Results
4.2.1. Kano Model Results for Respondents
Table 3 shows the 38 quality factors in this study. Specifically, four quality factors were classified
under one-dimension quality, 23 quality factors were classified under must-be quality, 12 quality factors
were classified under indifferent quality.
Int. J. Environ. Res. Public Health 2019, 16, 4091 9 of 23
Table 3. Categorization of quality elements listed by respondents (%).
Elements AQ MBQ ODQ IDQ RQ IVQ
Categorization
of Quality
Elements
1 The clothing of delivery staff is neat and tidy 6.7 47.1 26 19.2 0 1 MBQ
2
Logistics company has good word-of-mouth,
reputation, and popularity
9.6 40.4 32.7 16.3 1 0 MBQ
3
Logistics center has advanced physical
equipment (e.g., warehouses, pickup
systems, shelves)
11.5 40.4 16.3 30.8 1 0 MBQ
4
Processes including order content (items and
quantities) bill of lading documents are
correctly executed
3.8 47.1 39.4 8.7 0 1 MBQ
5
Processes for batch numbers and validity
period management are strictly implemented;
i.e., drugs with a validity period of less than 6
months are not shipped
1.0 48.1 46.2 2.9 1.9 0 MBQ
6
The rate and extent of damage received
are disclosed/low
1.0 50.0 43.3 4.8 1 0 MBQ
7
Logistics equipment and distribution vehicles
meet the temperature requirements of drugs
1.9 51.0 37.5 8.7 1 0 MBQ
8 Goods are delivered on time to customers 1.0 59.6 34.6 3.8 1 0 MBQ
9
The order (i.e., item and quantity) delivery
rate is accurate
0.0 58.7 34.6 6.7 0 0 MBQ
10
Customer enquiries are answered within the
promised period
5.8 43.3 38.5 11.5 1 0 MBQ
11
Return and exchange processes are prompt
and appropriate
4.8 47.1 39.4 5.8 1 1.9 MBQ
12
Urgent orders are accepted and processed
with timely delivery
5.8 40.4 43.3 10.6 0 0 ODQ
13 There is a limit on the minimum order amount 19.2 23.1 26.9 26.9 1 2.9 ODQ/IDQ
14
Customers are notified of product shipment
one day prior
19.2 12.5 10.6 51.9 2.9 2.9 IDQ
15
Single-window customer service staff
provides professional and satisfactory answers
17.3 29.8 21.2 29.8 1 1 MBQ/IDQ
16
Deliveries are completed every other day after
receiving the order
14.4 27.9 34.6 21.2 1.9 0 ODQ
17
Service personnel (i.e., order and delivery
personnel) quickly address delivery errors
4.8 54.8 32.7 5.8 1.9 0 MBQ
18 Customers are notified of delayed shipment 3.8 51.9 36.5 3.8 1.9 1.9 MBQ
19
Service personnel (i.e., order and delivery
personnel) have professional training and
certain degree of understanding about drugs
25 26 8.7 38.5 1.9 0 IDQ
20
Service staff (i.e., order and delivery staff) are
kind and courteous
5.8 51.9 35.6 5.8 1 0 MBQ
21
Customized logistics processing and
packaging services are available
20.2 26.9 15.4 35.6 1 1 IDQ
22
Deliveries are made as per time specified
by customers
12.5 38.5 33.7 13.5 1.9 0 MBQ
23
Customers are notified of
out-of-stock products
4.8 49.0 34.6 6.7 2.9 1.9 MBQ
24 There is no limit on order time 18.3 18.3 24.0 36.5 2.9 0 IDQ
25
Customers can place online orders using the
electronic platform/Online orders are accepted
22.1 17.3 10.6 47.1 1.9 1 IDQ
26
Delivery services are available on weekends
and holidays
19.2 16.3 13.5 47.1 2.9 1 IDQ
27 There are channels for customer complaints 2.9 53.8 26 14.4 2.9 0 MBQ
28
Inventory location or shelf service is
designated as per customer needs
9.6 36.5 30.8 21.2 1 1 MBQ
Int. J. Environ. Res. Public Health 2019, 16, 4091 10 of 23
Table 3. Cont.
Elements AQ MBQ ODQ IDQ RQ IVQ
Categorization
of Quality
Elements
29
Information technology (RFID and barcode)
offers information on drug history and
temperature control
16.3 24 37.5 28.8 2.9 0 ODQ
30
Customers are notified of product packaging
changes in advance
1.9 56.7 29.8 9.6 1.9 0 MBQ
31
Batch number and validity period
requirements specified by the customer
are met
5.8 39.4 25 28.8 1 0 MBQ
32
Customers receive order-processing
status online
21.2 26 18.3 32.7 1 1 IDQ
33 Out-of-stock orders are promptly processed 1.9 50.0 39.4 4.8 1 2.9 MBQ
34
Customer complaints are immediately
addressed and resolved
1.9 55.8 32.7 5.8 1.9 1.9 MBQ
35
Shipment of damaged goods or incorrect
invoices and bills of voucher are
promptly corrected
1.9 51.9 36.5 6.7 1 1.9 MBQ
36
Information on materials related to healthcare
medicines and procurement advice
are provided
23.1 21.2 17.3 36.5 1 1 IDQ
37
Services such as medical waste recycling,
waste disposal, and autoclaving are available
23.1 18.3 16.3 39.4 1.9 1 IDQ
38 Escrow inventory services are provided 16.3 10.6 10.6 56.7 3.8 1.9 IDQ
Notes: AQ, attractive quality; MBQ, must-by quality; ODQ, one-dimension quality; IDQ, indifferent quality; RQ,
reverse quality; IVQ, invalid quality. The bold stands for the majority.
This study employed the Matzler and Hinterhuber’s [14] two-dimensional classification method
to classify the items listed by the respondents under the five quality types. For example, the number
of respondents who classify “cleanliness of distribution staff’s clothing” as a must-be quality is the
highest (47.1%), followed by those who considered it a one-dimensional quality (26%), indifference
quality (19.2%), attractive quality (6.7%) and invalid quality (1%). Therefore, “The clothing of the
delivery staff is neat and tidy” is a must-be quality.
Evidently, opinions about quality factors differed by customer, and thus, this study adopted a
statistical relative majority approach. The results reveal a significant difference in consumer opinions
for two items: “There is a limit on the minimum order amount” and “Single-window customer service
staff provides professional and satisfactory answers.” The classification of dimensional quality can,
therefore, be confusing. Nevertheless, these difficulties do not extend to management and decision
making [16].
The abovementioned results confirm that the variations in customers’ prioritization of quality
factors in the pharmaceutical logistics services and that quality factors are differently classified in the
Kano model. This supports Hypothesis 1 that the quality elements of pharmaceutical logistics services
differ in quality characteristics classified in the Kano model.
4.2.2. Categorization of Quality Elements Specified by Teaching and Non-Teaching Hospitals
This subsection focuses on understanding whether Kano’s two-dimensional quality categorization
can be applied to quality the items mentioned by teaching and non-teaching hospitals (Table 4).
There are significant differences in teaching and non-teaching hospitals’ views regarding five items:
“Customer enquiries are answered within the promised period,” “Return and exchange processes
are prompt and appropriate,” “Service personnel promptly addresses delivery errors,” “Out-of-stock
orders are promptly processed” and “Customer complaints are immediately addressed and properly
resolved.”
Int. J. Environ. Res. Public Health 2019, 16, 4091 11 of 23
Table 4. Categorization of quality elements by teaching hospital and non-teaching hospitals.
Items Teaching Non-Teaching p-Value
1 The clothing of delivery staff is neat and tidy MBQ MBQ –
2
Logistics company has good word-of-mouth,
reputation, and popularity
ODQ MBQ –
3
Logistics center has advanced physical
equipment (e.g., warehouses, pickup
systems, shelves)
MBQ/IDQ MBQ –
4
Processes including order content (items and
quantities) bill of lading documents are
correctly executed
MBQ MBQ/ODQ –
5
Processes for batch numbers and validity period
management are strictly implemented; i.e., drugs
with a validity period of less than 6 months are
not shipped
MBQ MBQ –
6
The rate and extent of damage received are
disclosed/low
MBQ ODQ –
7
Logistics equipment and distribution vehicles
meet the temperature requirements of drugs
MBQ MBQ –
8 Goods are delivered on time to customers MBQ MBQ –
9
The order (i.e., item and quantity) delivery rate
is accurate
MBQ MBQ –
10
Customer enquiries are answered within the
promised period
ODQ MBQ *
11
Return and exchange processes are prompt
and appropriate
ODQ MBQ *
12
Urgent orders are accepted and processed with
timely delivery
ODQ MBQ –
13 There is a limit on the minimum order amount ODQ IDQ –
14
Customers are notified of product shipment one
day prior
IDQ IDQ –
15
Single-window customer service staff provides
professional and satisfactory answers
ODQ/IDQ MBQ –
16
Deliveries are completed every other day after
receiving the order
ODQ ODQ –
17
Service personnel (i.e., order and delivery
personnel) quickly address delivery errors
ODQ MBQ *
18 Customers are notified of delayed shipment ODQ MBQ –
19
Service personnel (i.e., order and delivery
personnel) have professional training and certain
degree of understanding about drugs
IDQ IDQ –
20
Service staff (i.e., order and delivery staff) are
kind and courteous
MBQ MBQ –
21
Customized logistics processing and packaging
services are available
IDQ IDQ –
22
Deliveries are made as per time specified
by customers
MBQ MBQ –
23 Customers are notified of out-of-stock products MBQ MBQ –
24 There is no limit on order time ODQ IDQ –
25
Customers can place online orders using the
electronic platform/Online orders are accepted
IDQ IDQ –
26
Delivery services are available on weekends
and holidays
IDQ IDQ –
Int. J. Environ. Res. Public Health 2019, 16, 4091 12 of 23
Table 4. Cont.
Items Teaching Non-Teaching p-Value
27 There are channels for customer complaints MBQ MBQ –
28
Inventory location or shelf service is designated
as per customer needs
MBQ MBQ –
29
Information technology (RFID and barcode)
offers information on drug history and
temperature control
IDQ ODQ –
30
Customers are notified of product packaging
changes in advance
MBQ MBQ –
31
Batch number and validity period requirements
specified by the customer are met
MBQ MBQ –
32 Customers receive order-processing status online IDQ IDQ –
33 Out-of-stock orders are promptly processed ODQ MBQ *
34
Customer complaints are immediately addressed
and resolved
MBQ MBQ *
35
Shipment of damaged goods or incorrect invoices
and bills of voucher are promptly corrected
MBQ/ODQ MBQ –
36
Information on materials related to healthcare
medicines and procurement advice are provided
IDQ IDQ –
37
Services such as medical waste recycling, waste
disposal, and autoclaving are available
IDQ IDQ –
38 Escrow inventory services are provided IDQ IDQ –
Note: * p < 0.1; – means non-significant.
4.2.3. Categorization of Quality Elements Listed by Logistics Service Providers
Table 5 lists quality elements mentioned by logistics service providers. This subsection determines
if Kano’s two-dimensional quality classification can be applied to the quality items provided by
service providers. The quality items related to pharmaceutical logistics companies most frequently
contacted by customers are professional pharmaceutical logistics, general logistics, or both (Table 5).
The results reveal significant differences among “Customer enquiries are answered within the promised
period,” “Single-window customer service staff provides professional and satisfactory answers” and
“Out-of-stock orders are quickly processed.” In sum, the respondents’ views of quality factors do
not significantly differ on the basis of various hospital characteristics. Therefore, Hypothesis 3—that
is, the quality of medical logistics services differs by the characteristics of medical institutions—is
not supported.
Table 5. Categorization of quality elements by logistics service providers.
Items Professional General Both p-Value
1 The clothing of delivery staff is neat and tidy MBQ MBQ MBQ –
2
Logistics company has good word-of-mouth,
reputation, and popularity
MBQ MBQ MBQ –
3
Logistics center has advanced physical
equipment (e.g., warehouses, pickup
systems, shelves)
MBQ MBQ/IDQ MBQ –
4
Processes including order content (items and
quantities) bill of lading documents are
correctly executed
MBQ MBQ MBQ –
Int. J. Environ. Res. Public Health 2019, 16, 4091 13 of 23
Table 5. Cont.
Items Professional General Both p-Value
5
Processes for batch numbers and validity
period management are strictly implemented;
i.e., drugs with a validity period of less than 6
months are not shipped
MBQ MBQ ODQ –
6
The rate and extent of damage received are
disclosed/low
ODQ MBQ MBQ –
7
Logistics equipment and distribution vehicles
meet the temperature requirements of drugs
MBQ MBQ MBQ –
8 Goods are delivered on time to customers MBQ MBQ MBQ –
9
The order (i.e., item and quantity) delivery
rate is accurate
MBQ MBQ ODQ –
10
Customer enquiries are answered within the
promised period
MBQ MBQ ODQ *
11
Return and exchange processes are prompt
and appropriate
MBQ MBQ ODQ –
12
Urgent orders are accepted and processed
with timely delivery
MBQ MBQ/ODQ ODQ –
13
There is a limit on the minimum
order amount
IDQ ODQ MBQ/ODQ/IDQ –
14
Customers are notified of product shipment
one day prior
IDQ ODQ IDQ –
15
Single-window customer service staff
provides professional and
satisfactory answers
MBQ IDQ ODQ/IDQ *
16
Deliveries are completed every other day
after receiving the order
ODQ IDQ ODQ –
17
Service personnel (i.e., order and delivery
personnel) quickly address delivery errors
MBQ MBQ MBQ –
18 Customers are notified of delayed shipment MBQ MBQ MBQ –
19
Service personnel (i.e., order and delivery
personnel) have professional training and
certain degree of understanding about drugs
IDQ IDQ IDQ –
20
Service staff (i.e., order and delivery staff) are
kind and courteous
MBQ MBQ MBQ –
21
Customized logistics processing and
packaging services are available
IDQ MBQ MBQ –
22
Deliveries are made as per time specified
by customers
ODQ MBQ MBQ –
23
Customers are notified of
out-of-stock products
MBQ MBQ MBQ –
24 There is no limit on order time IDQ IDQ ODQ –
25
Customers can place online orders using the
electronic platform/Online orders
are accepted
IDQ IDQ IDQ –
26
Delivery services are available on weekends
and holidays
IDQ IDQ IDQ –
27 There are channels for customer complaints MBQ MBQ MBQ –
28
Inventory location or shelf service is
designated as per customer needs
MBQ MBQ/ODQ MBQ –
29
Information technology (RFID and barcode)
offers information on drug history and
temperature control
ODQ IDQ ODQ –
Int. J. Environ. Res. Public Health 2019, 16, 4091 14 of 23
Table 5. Cont.
Items Professional General Both p-Value
30
Customers are notified of product packaging
changes in advance
MBQ MBQ MBQ –
31
Batch number and validity period
requirements specified by the customer
are met
MBQ MBQ MBQ –
32
Customers receive order-processing
status online
IDQ IDQ MBQ/AQ –
33 Out-of-stock orders are promptly processed MBQ MBQ ODQ *
34
Customer complaints are immediately
addressed and resolved
MBQ MBQ MBQ –
35
Shipment of damaged goods or incorrect
invoices and bills of voucher are
promptly corrected
MBQ MBQ MBQ –
36
Information on materials related to
healthcare medicines and procurement
advice are provided
IDQ MBQ/AQ IDQ –
37
Services such as medical waste recycling,
waste disposal, and autoclaving are available
IDQ IDQ MBQ/ODQ/IDQ –
38 Escrow inventory services are provided IDQ IDQ IDQ –
Note: * p < 0.1; – means non-significant.
4.3. Importance-Satisfaction Model (IS Model)
Customers assess the overall quality on the basis of quality factors they consider important [16,17].
The importance-satisfaction (IS) model can be further divided into four quadrants: excellent, to be
improved, surplus and careless.
4.3.1. Excellent
The quality elements that fall in the excellent quadrant are considered important by customers,
and thus, service providers must focus on offering these features to achieve customer satisfaction.
The following items are located in the excellent area: “Logistics company has good word-of-mouth,
reputation, and popularity,” “Order content (i.e., items and quantities), bill of lading documents, and
correctness of processing,” “Processes for batch numbers and validity period management are strictly
implemented; e.g., drugs with a validity period of less than 6 months are not shipped,” “The rate and
extent of damage received are disclosed/low,” “Logistics equipment and distribution vehicles meet
the temperature requirements of drugs,” “Goods are promptly delivered to customers,” “Order (e.g.,
item and quantity) delivery accuracy rate,” “Customer enquiries are answered within the promised
period,” “Return and exchange processes are prompt and appropriate,” “Urgent orders are accepted
and processed with timely delivery,” “Single-window customer service staff provides professional
and satisfactory answers,” “Service personnel (i.e., order and delivery personnel) promptly addresses
delivery errors,” “Service staff (i.e., order and delivery staff) is kind and courteous,” “Customers are
notified of product packaging changes in advance,” “Customer complaints are immediately addressed
and properly resolved” and “Shipment of damaged goods or incorrect invoices and bills of voucher
are promptly corrected.”
4.3.2. To Be Improved
The to-be-improved area denotes the items important to customers but not as good as expected. The
following elements fall under this category: “Customers are notified of shipment delays,” “Customers
are notified of out-of-stock products” and “Out-of-stock orders are promptly processed.”
Int. J. Environ. Res. Public Health 2019, 16, 4091 15 of 23
4.3.3. Surplus
The items that fall within the surplus area are not prioritized by customers, and thus, companies
attempting to reduce costs can decrease the supply of such items without negatively affecting customer
satisfaction. The following items are located in the surplus area: “The clothing of delivery staff is neat
and tidy,” “Logistics center has advanced physical equipment (e.g., warehouses, pickup systems, and
shelves),” “Deliveries are completed every other day after receiving the order,” “Deliveries are made
as per time specified by customers,” “Designated inventory location or shelf service are provided as
per customer needs” and “Batch number and validity period requirements specified by the customer
are met.”
4.3.4. Careless
Customers consider the elements that fall in the careless area unimportant, and thus, companies
are not required to prioritize the quality of these elements. The following items are located in the
careless area: “There is a limit on minimum order amounts,” “Customers are notified of item shipment
one day prior,” “Service personnel (i.e., order and delivery personnel) have received professional
training and a certain degree of understanding about drugs,” “Customized logistics processing and
packaging services are available,” “There is no limit on order time,” “Customers can place online
orders using the electronic platform/Online orders are accepted,” “Delivery services are available
on weekends and holidays,” “Customers can lodge complaints through their customer complaints
channel,” “Customers receive order processing status online,” “Information on materials related to
healthcare medicine and procurement advice are provided,” “Services such as medical waste recycling,
waste disposal, and autoclaving are available” and “Services for escrow inventory are provided.”
4.4. Summary of Two-Dimensional Quality Elements
Table 6 summarizes the quality elements for pharmaceutical logistics services using Kano’s
two-dimensional quality model. The table includes the importance and satisfaction scores as well as
attribute classifications under the Kano and IS models. A noteworthy observation is that the quality
elements for pharmaceutical logistics services do not report varying attribute classifications under the
Kano model.
Table 6. Summary of quality elements for pharmaceutical logistics services.
Items
Importance
(Avg.)
Satisfaction
(Avg.)
Kano’ Attribute
Classification
IS Model
1
The clothing of delivery staff is
neat and tidy
3.95 3.94 MBQ Surplus
2
Logistics company has good
word-of-mouth, reputation,
and popularity
4.12 4.06 MBQ Excellent
3
Logistics center has advanced
physical equipment (e.g.,
warehouses, pickup
systems, shelves)
3.93 3.84 MBQ Surplus
4
Processes including order content
(items and quantities) bill of
lading documents are
correctly executed
4.40 4.14 MBQ Excellent
5
Processes for batch numbers and
validity period management are
strictly implemented; i.e., drugs
with a validity period of less than
6 months are not shipped
4.52 3.96 MBQ Excellent
Int. J. Environ. Res. Public Health 2019, 16, 4091 16 of 23
Table 6. Cont.
Items
Importance
(Avg.)
Satisfaction
(Avg.)
Kano’ Attribute
Classification
IS Model
6
The rate and extent of damage
received are disclosed/low
4.50 4.16 MBQ Excellent
7
Logistics equipment and
distribution vehicles meet the
temperature requirements
of drugs
4.41 4.12 MBQ Excellent
8
Goods are delivered on time
to customers
4.52 4.08 MBQ Excellent
9
The order (i.e., item and quantity)
delivery rate is accurate
4.56 4.18 MBQ Excellent
10
Customer enquiries are answered
within the promised period
4.26 3.86 MBQ Excellent
11
Return and exchange processes
are prompt and appropriate
4.35 3.72 MBQ Excellent
12
Urgent orders are accepted and
processed with timely delivery
4.40 4.00 ODQ Excellent
13
There is a limit on the minimum
order amount
3.53 3.33 ODQ/IDQ Care-free
14
Customers are notified of product
shipment one day prior
3.25 3.28 IDQ Care-free
15
Single-window customer service
staff provides professional and
satisfactory answers
4.06 3.81 MBQ/IDQ Excellent
16
Deliveries are completed every
other day after receiving the order
4.01 3.89 ODQ Surplus
17
Service personnel (i.e., order and
delivery personnel) quickly
address delivery errors
4.25 3.92 MBQ Excellent
18
Customers are notified of
delayed shipment
4.34 3.41 MBQ
To be
improved
19
Service personnel (i.e., order and
delivery personnel) have
professional training and certain
degree of understanding
about drugs
3.66 3.56 IDQ Care-free
20
Service staff (i.e., order and
delivery staff) are kind
and courteous
4.24 4.25 MBQ Excellent
21
Customized logistics processing
and packaging services
are available
3.51 3.48 IDQ Care-free
22
Deliveries are made as per time
specified by customers
3.99 3.80 MBQ Surplus
23
Customers are notified of
out-of-stock products
4.36 3.41 MBQ
To be
improved
24 There is no limit on order time 3.72 3.43 IDQ Care-free
Int. J. Environ. Res. Public Health 2019, 16, 4091 17 of 23
Table 6. Cont.
Items
Importance
(Avg.)
Satisfaction
(Avg.)
Kano’ Attribute
Classification
IS Model
25
Customers can place online orders
using the electronic
platform/Online orders
are accepted
3.54 3.38 IDQ Care-free
26
Delivery services are available on
weekends and holidays
3.48 3.38 IDQ Care-free
27
There are channels for
customer complaints
3.96 3.65 MBQ Care-free
28
Inventory location or shelf service
is designated as per
customer needs
3.93 3.84 MBQ Surplus
29
Information technology (RFID
and barcode) offers information
on drug history and
temperature control
3.81 3.47 ODQ Care-free
30
Customers are notified of product
packaging changes in advance
4.26 3.95 MBQ Excellent
31
Batch number and validity period
requirements specified by the
customer are met
4.01 3.75 MBQ Surplus
32
Customers receive
order-processing status online
3.57 3.38 IDQ Care-free
33
Out-of-stock orders are
promptly processed
4.25 3.50 MBQ
To be
improved
34
Customer complaints are
immediately addressed
and resolved
4.21 3.73 MBQ Excellent
35
Shipment of damaged goods or
incorrect invoices and bills of
voucher are promptly corrected
4.33 3.86 MBQ Excellent
36
Information on materials related
to healthcare medicines and
procurement advice are provided
3.61 3.37 IDQ Care-free
37
Services such as medical waste
recycling, waste disposal, and
autoclaving are available
3.53 3.21 IDQ Care-free
38
Escrow inventory services
are provided
3.24 3.16 IDQ Care-free
Note: The bold stands for the above average.
5. Discussion
This study examined medical institutions’ views of service quality for the domestic pharmaceutical
logistics industry using Kano’s two-dimensional model and the IS model. The objective was to determine
the service quality elements that attract customers to pharmaceutical logistics services and that meet
medical institutions’ needs. The hypotheses test results indicate that pharmaceutical logistics services
have varying quality characteristics. The two-dimensional quality classification must be positively
correlated with satisfaction derived from the quality factor. Further, there is no significant difference in
the classification of quality elements listed by medical institutions with varying characteristics.
5.1. Kano Model Results
The results of Kano’s two-dimensional quality highlight that of the 38 quality items, none are
classified under attractive or reverse quality, four items are categorized under one-dimensional quality,
Int. J. Environ. Res. Public Health 2019, 16, 4091 18 of 23
24 items fall under must-be quality, and 12 are considered non-differential qualities. A majority of the
quality items are classified as must-be quality, indifference quality, or both.
Most of the items classified as must-be quality are services currently offered by the pharmaceutical
logistics industry. For example, the following items are deemed basic characteristics of pharmaceutical
logistics services: “Items of order content (i.e., items and quantities), bill of lading documents,
and correctness of processing,” “Processes for batch numbers and validity period management are
strictly implemented; e.g., drugs with a validity period of less than 6 months are not shipped,”
“Logistics equipment and distribution vehicles meet the temperature requirements of drugs,” ‘Goods
are delivered to customers on time,” “Order (i.e., item and quantity) delivery accuracy rate” and
“Customer complaints are immediately addressed and properly resolved,” These factors do not enhance
customer satisfaction. However, their absence could lead to customer dissatisfaction [2]. Both the
tangible and reliable items of pharmaceutical logistics services are classified under must-be quality.
In other words, service personnel and equipment for pharmaceutical logistics should aim to provide
promised services correctly and reliably to meet the basic requirements of medical institutions.
The following items are classified as indifferent elements: “Customers are notified of item shipment
one day prior,” “Service personnel (i.e., order and delivery personnel) have received professional
training and a certain degree of understanding about drugs,” “Delivery services are available on
weekends and holidays,” “Customers are provided order-processing status online,” “Services such
as medical waste recycling, waste disposal, and autoclaving are available” and “Escrow inventory
services are provided.” While the lack of these quality items does not affect customer satisfaction with
pharmaceutical logistics providers, these factors may become attractive qualities. Thus, companies
should consider providing such quality elements (e.g., “There is a limit on the minimum order amount”)
as a strategic tool to attract customers in the future.
In sum, an important strategic implication offered by the findings of Kano’s two-dimensional
quality model is that pharmaceutical logistics operators should provide attractive qualities to attract
future customers and gain a competitive advantage. At the same time, these factors must satisfy the
criteria of must-be quality and one-dimension quality so that service companies can gain a competitive
advantage of their competitors.
IS Analysis Results
The IS model analysis categorizes the following items under the excellent area: “Customer
complaints are immediately addressed and properly resolved,” “Urgent orders are accepted and
processed with timely delivery” and “Processes for batch numbers and validity period management
are strictly implemented; e.g., drugs with a validity period of less than 6 months are not shipped.”
In other words, service providers in the pharmaceutical logistics industry must continuously and
adequately provide these services to achieve customer satisfaction.
The following items are located in the to-be-improved area: “Out-of-stock orders are promptly
processed,” “Customers are notified of delayed shipment” and “Customers are notified of out-of-stock
products.” Service providers in the pharmaceutical logistics must immediately and aggressively
improve these items to ensure customer satisfaction.
The following items fall in the surplus area: “Deliveries are completed every other day after
receiving the order,” “Logistics center has advanced physical equipment (e.g., warehouses, pickup
systems, and shelves)” and “Batch number and validity period requirements specified by the customer
are met.” Customers do not prioritize these services, and the satisfaction obtained from the availability
of these services is above average. Thus, companies attempting to reduce costs can direct their resources
toward service items other than these without significantly impacting customer satisfaction.
Finally, the following items fall in the careless quadrant: “Delivery services are available on
weekends and holidays,” “Customers are notified of item shipment one day prior,” “Customers are
provided with order-processing status online,” “Customers can place orders online using the electronic
platform/Online orders are accepted” and “Escrow inventory services are provided.” These items are
Int. J. Environ. Res. Public Health 2019, 16, 4091 19 of 23
less valued by customers, and thus, their contribution to customer satisfaction is limited. Therefore,
companies do not need to spend much time and resources on these items and may even consider
excluding these items to reduce costs.
5.2. Satisfaction Analysis for Different Service Providers
Table 7 shows that the following items fall in the excellent quadrant: “ Processes for batch numbers
and validity period management are strictly implemented; e.g., drugs with a validity period of less
than 6 months are not shipped,” “Single-window customer service staff provide professional and
satisfactory answers,” “Deliveries are completed every other day after receiving the orders” and “Batch
number and validity period requirements specified by the customer are met.” This finding indicates
that customers prefer professional pharmaceutical logistics services. Further, the following items
are located in the to-be-improved quadrant: “Customer enquiries are answered within the promised
period,” “Return and exchange processes are prompt and appropriate” and “Customer complaints are
immediately addressed and properly resolved.” Customers are satisfied with these items, but a small
proportion believes they are not as good as expected. The item “Inventory location or shelf service is
determined as per customer needs” is located in the surplus quadrant for professional pharmaceutical
logistics services. However, this item is in the to-be-improved quadrant for general pharmaceutical
logistics services. In other words, customers are satisfied with these services and at the same time,
companies may consider excluding them to reduce costs. Similarly, “Deliveries are made as per time
specified by customers” is located in the surplus area for general pharmaceutical logistics services, but
it is in the excellent quadrant for professional pharmaceutical logistics services.
Table 7. IS analysis of different pharmaceutical logistics service providers.
Items Professional General Both
1 The clothing of delivery staff is neat and tidy Surplus Excellent Surplus
2
Logistics company has good word-of-mouth,
reputation, and popularity
Excellent Excellent Excellent
3
Logistics center has advanced physical
equipment (e.g., warehouses, pickup systems,
shelves)
Surplus Surplus Surplus
4
Processes including order content (items and
quantities) bill of lading documents are correctly
executed
Excellent Excellent Excellent
5
Processes for batch numbers and validity period
management are strictly implemented; i.e., drugs
with a validity period of less than 6 months are
not shipped
Excellent To be improved Excellent
6
The rate and extent of damage received are
disclosed/low
Excellent Excellent Excellent
7
Logistics equipment and distribution vehicles
meet the temperature requirements of drugs
Excellent Excellent Excellent
8 Goods are delivered on time to customers Excellent Excellent Excellent
9
The order (i.e., item and quantity) delivery rate is
accurate
Excellent Excellent Excellent
10
Customer enquiries are answered within the
promised period
Excellent Excellent To be improved
Int. J. Environ. Res. Public Health 2019, 16, 4091 20 of 23
Table 7. Cont.
Items Professional General Both
11
Return and exchange processes are prompt and
appropriate
Excellent Excellent To be improved
12
Urgent orders are accepted and processed with
timely delivery
Excellent Excellent Excellent
13 There is a limit on the minimum order amount Care-free Care-free Care-free
14
Customers are notified of product shipment one
day prior
Care-free Care-free Care-free
15
Single-window customer service staff provides
professional and satisfactory answers
Excellent Care-free Surplus
16
Deliveries are completed every other day after
receiving the order
Excellent Care-free Surplus
17
Service personnel (i.e., order and delivery
personnel) quickly address delivery errors
Excellent Excellent Excellent
18 Customers are notified of delayed shipment To be improved To be improved To be improved
19
Service personnel (i.e., order and delivery
personnel) have professional training and certain
degree of understanding about drugs
Care-free Care-free Care-free
20
Service staff (i.e., order and delivery staff) are
kind and courteous
Excellent Excellent Excellent
21
Customized logistics processing and packaging
services are available
Care-free Care-free Care-free
22
Deliveries are made as per time specified by
customers
Surplus Surplus Excellent
23 Customers are notified of out-of-stock products To be improved To be improved To be improved
24 There is no limit on order time Care-free Care-free Care-free
25
Customers can place online orders using the
electronic platform/Online orders are accepted
Care-free Care-free Care-free
26
Delivery services are available on weekends and
holidays
Care-free Care-free Care-free
27 There are channels for customer complaints Care-free Care-free Care-free
28
Inventory location or shelf service is designated
as per customer needs
Surplus To be improved Surplus
29
Information technology (RFID and barcode)
offers information on drug history and
temperature control
Care-free Care-free Care-free
30
Customers are notified of product packaging
changes in advance
Excellent Excellent Excellent
31
Batch number and validity period requirements
specified by the customer are met
Excellent Surplus Care-free
32 Customers receive order-processing status online Care-free Care-free Care-free
33 Out-of-stock orders are promptly processed To be improved To be improved To be improved
34
Customer complaints are immediately addressed
and resolved
Excellent Excellent To be improved
35
Shipment of damaged goods or incorrect invoices
and bills of voucher are promptly corrected
Excellent Excellent Excellent
36
Information on materials related to healthcare
medicines and procurement advice are provided
Care-free Care-free Care-free
37
Services such as medical waste recycling, waste
disposal, and autoclaving are available
Care-free Care-free Care-free
38 Escrow inventory services are provided Care-free Care-free Care-free
5.3. Research Limitations and Suggestions for Future Research
While this study was designed to be extended, certain areas remain that need to be addressed
in future research. First, this study focuses on users of pharmaceutical logistics services in Taiwan
Int. J. Environ. Res. Public Health 2019, 16, 4091 21 of 23
using a questionnaire survey and thus, it does not account for customer needs in other countries.
Researchers may consider surveying pharmaceutical logistics service providers in other countries to
understand issues related to new services and to improve the generalizability of the results. Second,
the questionnaire is mainly designed for downstream customers, such as medical institutions, and does
not consider the views of upstream customers, including drug manufacturers. The research subjects
are medical institutions, including pharmacies, clinics and homecare. Thus, there is scope to further
explore the quality of services provided in the domestic pharmaceutical logistics industry. Finally, this
study adopts a closed questionnaire method to explore customer perceptions of service quality in the
pharmaceutical logistics industry. The omission of certain factors may have weakened the explanatory
power. Future research could conduct theoretical analyses and in-depth interviews to examine other
factors affecting service quality to supplement and revise the scale of pharmaceutical logistics services.
6. Implications
6.1. Managerial Implications of Kano’s Two-Dimensional Quality Model
This study adopted Kano’s two-dimensional quality model and a questionnaire survey to examine
customers’ perceptions about service items and accordingly, classify the service items under various
quality factors. These findings can serve as a reference for service providers in the pharmaceutical
logistics industry working toward improving their services.
6.1.1. Offer all Elements Classified under Must-Be Quality
Service items generally classified as must-be quality are those considered basic services by
customers. Therefore, while the presence of these may not increase customer satisfaction, their absence
could result in customer dissatisfaction [2]. The present empirical results suggest that tangibility and
reliability are key attributes contributing to must-be quality. In the present context, this means medical
institutions will demand high service standards, such as compliance with rules and regulations for the
circulation of medicines. Certain related items that are classified as must-be quality are “The clothing
of delivery staff is neat and tidy,” “Logistics equipment and distribution vehicles meet the temperature
requirement of drugs,” “Order content (i.e., items and quantities), bill of lading documents, and
correctness of processing” and “Processes for batch numbers and validity period management are
strictly implemented, e.g., drugs with a validity period of less than 6 months are not shipped.” This
means wearing clean clothing during drug circulation, satisfying drug temperature requirements and
strictly monitoring batch numbers and expiration dates are some of the quality control measures that
should be adopted by the pharmaceutical logistics service industry.
6.1.2. Strengthen Provisions of One-Dimensional Quality Elements
The availability of one-dimensional quality items positively contributes to customer satisfaction.
A higher number of one-dimensional quality items will result in greater customer satisfaction, whereas
the lack of these items will lead to customer dissatisfaction [2]. For example, “Urgent orders are
accepted and processed with timely delivery” is considered an essential service. Given the generally
urgent demand for medicines, pharmaceutical logistics service providers must ensure prompt delivery,
improve the efficiency of logistical operations, and decrease service delivery time, all of which could
contribute to higher customer satisfaction.
6.1.3. Focus on Providing Services and Products with Attractive Quality
The need to provide products and services with attractive qualities could motivate the industry
to actively innovate. Offering products and services with sufficient attractive quality are likely to
enhance customer satisfaction [17]. However, the empirical results of this study highlight that no item
is classified under attractive quality, indicating that the current medical logistics industry is not highly
innovative. Therefore, if the pharmaceutical logistics industry is committed to providing services with
Int. J. Environ. Res. Public Health 2019, 16, 4091 22 of 23
attractive qualities, it must explore reverse logistics services that are based on customer needs and
differentiated strategies to gain a competitive advantage over competitors.
7. Conclusions
This study examined critical quality factors that influence customer satisfaction using Kano’s
two-dimensional model and the IS model. In doing so, it also shed light on factors that are inadequate
and need strengthening. The empirical findings offer key managerial implications for service providers
of the pharmaceuticals logistics industry to improve their services by, for example, exploring innovative
service content that accounts for customer needs. First, most service items cited by medical institutions
can be classified under one-dimensional or must-be quality. Thus, medical logistics service providers
should strengthen the integrity of their core services. Next, the items such as “Customers are notified
of delayed shipment” and “Out-of-stock orders are promptly processed” fall in the to-be-improved
quadrant. This means customers consider these aspects important, but they do not meet customer
expectations. Companies should focus on improving the quality of such services. Finally, in addition
to offering services in prestigious areas, professional pharmaceutical logistics offer better and different
services than those provided by general logistics service providers. For example, professional
pharmaceutical logistics operators ensure the strict enforcement of batch and expiration management
processes, have well-trained customer service staff, offer prompt delivery once the order is received and
deliver products and services as per the customers’ batch number and drug validity period. In other
words, professional logistics service providers differ from general ones in management and timeliness.
When the quality of services is high, customers tend to classify the items under one-dimensional quality
or must-be quality because customers generally take these items for granted. By contrast, items that
unavailable are classified as attractive or indifference quality. However, no item has been classified as
attractive quality and the market segmentation is likely to differ by attributes prioritized by customers.
Author Contributions: Conceptualization, M.-C.C.; data curation, L.-H.L.; formal analysis, M.-C.C., C.-L.H.
and L.-H.L.; investigation, C.-L.H.; methodology, M.-C.C., C.-L.H. and L.-H.L.; project administration, M.-C.C.;
supervision, M.-C.C.; validation, C.-L.H. and L.-H.L.; writing—original draft, C.-L.H. and L.-H.L.; writing—review
& editing, M.-C.C.
Funding: Ministry of Science and Technology, Taiwan, R.O.C.: MOST 107-2221-E-009-110-MY3.
Acknowledgments: The authors gratefully acknowledge support from the Ministry of Science and Technology,
Taiwan, R.O.C. (Grant number MOST 107-2221-E-009-110-MY3).
Conflicts of Interest: The authors declare no conflicts of interest.
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23. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement
error. J. Mark. Res. 1981, 18, 39–50. [CrossRef]
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
- Introduction
- Literature Review and Hypothesis Development
- Pharmaceutical Logistics
- Service Quality, Service Convenience, and Customer Satisfaction
- Kano Model
- Importance-Satisfaction (IS) Model
- Hypotheses Development
- Methodology
- Sample and Data Collection
- Questionnaire Design
- Analysis and Results
- Reliability and Validity Analysis
- Kano Model Results
- Kano Model Results for Respondents
- Categorization of Quality Elements Specified by Teaching and Non-Teaching Hospitals
- Categorization of Quality Elements Listed by Logistics Service Providers
- Importance-Satisfaction Model (IS Model)
- Excellent
- To Be Improved
- Surplus
- Careless
- Summary of Two-Dimensional Quality Elements
- Discussion
- Kano Model Results
- Satisfaction Analysis for Different Service Providers
- Research Limitations and Suggestions for Future Research
- Implications
- Managerial Implications of Kano’s Two-Dimensional Quality Model
- Offer all Elements Classified under Must-Be Quality
- Strengthen Provisions of One-Dimensional Quality Elements
- Focus on Providing Services and Products with Attractive Quality
- Conclusions
- References
peer-reviewed sources/The role of competitive strategy in the performance impact of exploitation and exploration.pdf
University of Southern Denmark
The role of competitive strategy in the performance impact of exploitation and exploration
quality management practices
Castillo-Apraiz, Julen; Richter, Nicole Franziska; Matey de Antonio, Jesus; Gudergan,
Siegfried P.
Published in:
European Business Review
DOI:
10.1108/EBR-09-2019-0182
Publication date:
2020
Document version:
Accepted manuscript
Citation for pulished version (APA):
Castillo-Apraiz, J., Richter, N. F., Matey de Antonio, J., & Gudergan, S. P. (2020). The role of competitive
strategy in the performance impact of exploitation and exploration quality management practices. European
Business Review, 33(1), 127-153. [33]. https://doi.org/10.1108/EBR-09-2019-0182
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Download date: 30. Jan. 2022
The role of competitive strategy in the performance impact of exploitation
and exploration quality management practices
Julen Castillo-Apraiz1*
Nicole Franziska Richter2
Jesus Matey de Antonio3
Siegfried Gudergan4
1*Corresponding author: Julen Castillo-Apraiz, Economía Financiera II (Economía de la Empresa y
Comercialización), Facultad de Ciencias Económicas y Empresariales, Universidad del País
Vasco/Euskal Herriko Unibertsitatea UPV/EHU, Barrio Sarriena s/n Leioa Bizkaia 48940 Spain,
Phone: +34 94 60 13 62 9, Email: [email protected]
2Nicole Franziska Richter, University of Southern Denmark, Department of Marketing and
Management, Campusvej 55, 5230 Odense, Denmark, Phone: +45 65 50 24 36, Email:
[email protected]
3Jesus Matey de Antonio, Economía Financiera II (Economía de la Empresa y Comercialización),
Facultad de Ciencias Económicas y Empresariales, Universidad del País Vasco/Euskal Herriko
Unibertsitatea UPV/EHU, Barrio Sarriena s/n Leioa Bizkaia 48940 Spain, Phone: +34 94 60 13 87 0,
Email: [email protected]
4Siegfried Gudergan, Waikato Management School, University of Waikato; Private Bag 3105,
Hamilton, 3240, New Zealand; Email: [email protected]
This is a pdf of the accepted manuscript. The manuscript was accepted in
European Business Review (March, 3, 2020); the assigned DOI is: 10.1108/EBR-09-
2019-0182.
Acknowledgements: We appreciate the financial support received from the Fundación Emilio
Soldevilla para la Investigación y el Desarrollo en Economía de la Empresa (FESIDE) foundation and
the Unidad de Formación e Investigación en Dirección Empresarial y Gobernanza Territorial y Social
(UFI 11/51) research and training unit.
1
The role of competitive strategy in the performance impact of exploitation
and exploration quality management practices
Abstract
Purpose: We advance understanding about quality management (QM) practices by clarifying
how competitive strategy conditions the impacts of exploitative and explorative QM practices
on performance.
Design/methodology/approach: We apply partial least squares structural equation modeling
(PLS-SEM) to data from a sample of German pharmaceutical firms.
Findings: The results show that the impact of exploitative and explorative QM practices on
firm performance is contingent on the competitive strategy pursued. Explorative QM
practices are significantly more relevant for firms following a differentiation strategy,
whereas exploitative QM practices are significantly more relevant for cost leaders.
Furthermore, for strategically ambidextrous firms that follow simultaneously a cost and a
differentiation focus, the interplay of the two QM practices matters.
Originality/Value: This paper contributes to understanding about which kind of management
practices, exploitative and/or explorative, have greater performance impacts under certain
competitive strategy conditions.
Keywords: quality management, exploitative, explorative, competitive strategy,
pharmaceutical industry, contingency.
2
The role of competitive strategy in the performance impact of exploitation
and exploration quality management practices
1. INTRODUCTION
Better understanding whether quality management (QM) affects firm performance has
characterized much research since the dawn of the 20th century (Hendricks and Singhal,
1997). While early research raised doubts on a positive performance effect of QM and
criticized that the field lacks methodological rigor (Dow et al., 1999), more current research
offers support for a positive impact of QM on different performance measures, when QM is
considered as an aggregate concept (for an overview see Kaynak, 2003; Ebrahimi and
Sadeghi, 2013; Nair, 2006). Yet, QM encapsulates three constituting principles—doing things
right, striving for improvement, and fulfilling customer needs (Dean and Bowen, 1994)—that
can involve a multitude of specific QM practices (e.g., Zhang et al., 2012; Ebrahimi and
Sadeghi, 2013); Ebrahimi and Sadeghi (2013) identified more than 200 QM practices.
Recent works stress the importance of developing a better understanding of which
specific practices are most effective under which conditions (e.g., Zhang et al., 2014b). Thus,
albeit the progress that has been made in prior research, not only do we still lack an in-depth
understanding of the impact of certain QM practices on performance but, as past studies
suggest that certain factors condition the impact of QM on performance (Jinhui Wu et al.,
2011; Nair, 2006; Saad and Siha, 2000), it is also important to clarify the role of such factors.
Specifically, as some authors (e.g., Herzallah et al., 2014; Herzallah et al., 2017) stress the
role of a firm’s competitive strategy in understanding the performance impact of QM, this
paper aims to close this gap by answering the question of how a firm’s competitive strategy
conditions the relationship between certain QM practices and firm performance.
We address this research question by extending the work of (Herzallah et al., 2017).
Specifically, we argue that the performance impact of a firm’s QM practices is based on
3
failure reduction and conditioned by its competitive strategy. We consider both financial and
market performance (Das et al., 2000; Zhang and Xia, 2013). Furthermore, in synthesizing
prior works, we apply a categorization of process and customer related QM practices that
accounts for a focus on explorative versus exploitative QM (March, 1991; Sitkin et al., 1994;
Li et al., 2008; Lavie et al., 2010; Bocanet and Ponsiglione, 2012). Exploitative QM focuses
on better leveraging existing resources to reduce costs and increase efficiency as the means to
improve performance (Sitkin et al., 1994; Reed et al., 2000; Zhang et al., 2014b). Explorative
QM emphasizes innovation or pursuing novel solutions and learning about new alternatives
which enhance revenues as the means to strengthen performance (March, 1991; Lavie et al.,
2010; Zhang et al., 2014b). Adopting this categorization allows clarifying the strategic
performance implications of QM practices, and studying relevant contextual conditions
under which different QM practices are effective (Lawrence and Lorsch, 1967; Miller, 1987);
the idea being that different contexts under which firms operate require different practices
(Zhang et al., 2014b).
We put forward that the performance effects of exploitative and explorative QM
practices are contingent on the fit with the firm’s strategic focus (Fuentes Fuentes et al.,
2006; Zatzick et al., 2012; Yunis et al., 2013). Specifically, we focus on a firm’s competitive
strategy as a dominant driver of competitive advantage (Miller, 1996; Porter, 1996). We
argue that QM practices are mechanisms that characterize how a firm operates, and
emphasize that the firm’s competitive strategy is the choice of an external positioning which
sets the firm’s overall direction and affects its management practices. In other words, we put
forward that strategic positioning characterizes a firm’s condition within QM practices occur.
Hence, we suggest a conceptualization in which a firm’s QM practices have direct effects on
its performance and in which these performance effects are contingent on the firm’s
competitive strategy. We develop a set of hypotheses that suggest that explorative QM
4
practices are a more relevant determinant of performance for differentiators, whereas
exploitative QM practices are more relevant for cost leaders (Kim and Huh, 2015), and that a
combination of both represents best practice for hybrids that combine in their competitive
strategy differentiation and cost leadership. We test the hypotheses using partial least squares
structural equation modeling (PLS-SEM) on data from a sample of German pharmaceutical
firms. This industry is of specific relevance to this study given the number of firms, the
mandatory use of QM practices therein (Haleem et al., 2015; Marinkovic et al., 2016;
Mehralian et al., 2016; Narayana et al., 2012), and heterogeneity in terms of strategic focus
(Garbe and Richter, 2009; Spitz, 2003).
This paper provides two chief contributions: First, we provide an in-depth
understanding of the effects of exploitative and explorative QM practices on (financial and
market) performance. Second, we advance our understanding of how a firm’s competitive
strategy conditions the performance impacts of QM practices. Specifically, following Porter’s
classification, we outline implications for firms in selecting the right mix of exploitative or
explorative QM in consideration of their competitive strategic focus. In doing so we answer
calls to further clarify understanding about the use of explorative and exploitative QM within
the context of a firm’s competitive strategy (Kim and Huh, 2015; Herzallah et al., 2017).
Specifically, following Porter’s (1980; 1985) classification, we distinguish between
differentiators, cost leaders and hybrid firms, and we accordingly outline implications for
firms in selecting the right mix of exploitative or explorative QM practices in consideration
of their competitive strategic focus.
2. LITERATURE REVIEW AND RESEARCH HYPOTHESES
2.1. Past Research on the impact of QM practices on performance
We reviewed Ebrahimi and Sadeghi (2013)’s work to identify studies referring to financial
and market performance as well as to process and customer-related QM practices (Ebrahimi
5
and Sadeghi, 2013, Table 2). In regards to the latter, most studies bundle several individual
QM elements into overarching factors (Kaynak and Hartley, 2008, 2005; Demirbag et al.,
2006; Martínez-Costa et al., 2008) with the aim distinguish between different facets of QM,
such as ‘customer focus’ (Adam et al., 1997; Fuentes-Fuentes et al., 2004), and ‘process
management’ or ‘process improvement’ (Wilson and Collier, 2000; Kaynak, 2003). In
aggregating QM practices at a higher level, other studies focus, for example, on total quality
management (TQM) (Agus, 2001). These studies mostly analyze the direct relationships of
QM practices on performance. Although there are some inconsistencies, especially in regards
to nonsignificant effects (for process-related items on performance, see Gadenne and Sharma,
2009; Koc, 2011), the majority of studies finds that QM has a positive effect on performance
(e.g., Kaynak, 2003; Demirbag et al., 2006; Kaynak and Hartley, 2008), which is also
confirmed by Nair (2006) who meta-analyzed 23 studies. While he concludes that customer
focus and process management are both positively correlated with financial (and aggregate)
performance (Nair, 2006), he also called for further research to examine moderating effects
or contingencies in the QM and performance relationship.
Very few studies take contingencies of the QM and performance relationship into
consideration (e.g., Adam et al., 1997; Brah et al., 2000; Das et al., 2000; Wang et al., 2012).
Fuentes Fuentes et al. (2006) analyze the impact of customer focus and process management
on financial performance contingent on business strategy (here cost leadership and
differentiation). Their results show that the profitability impact generated by QM practices
depends on how these fit with the strategic focus of the firm. Firms pursuing a differentiation
strategy generate better financial performance, if emphasizing customer focused practices.
For firms following a cost leadership strategy, they show that those practices that related to
continuous improvement help achieve better financial performance; yet they do not find a
significant contingency of the process management and performance relationship on cost
6
leadership strategy (Fuentes Fuentes et al., 2006). Douglas and Judge (2001) analyze the
impact of TQM encompassing seven QM practices (among them customer-focused practices)
on financial performance, contingent on organizational structural control and exploration.
Structural control comprises stabilization, standardization, and a focus on reliability of
outcomes. Structural exploration comprises creativity, openness and flexibility to new ideas.
They postulate that the QM and performance relationship will be stronger for organizations
focusing on control as well as for organizations focusing on exploration in their structure.
They find empirical support for the moderating impact of organizational structure as
hypothesized with respect to financial performance. Moreover, they find that these two
structures appear to work synergistically (Douglas and Judge, 2001).
Due to the surprisingly low attention to contingencies in prior QM research, we still
do not fully understand how to tailor “…QM practices to fit the organization’s situational
context…[although] this can help avoid implementation failure and improve performance”
(Zhang et al., 2014a, p. 81). In line with prior works, we distinguish explorative and
exploitative QM practices (Su and Linderman, 2016; Zhang et al., 2012). These theoretically
substantiated categories of QM practices provide the foundation on which to assess whether a
firm’s strategic focus conditions their performance impact.
While we refer to competitive strategy as a contingency factor, there is another stream
of research that considers competitive strategy as a mediator in the relationship between QM
practices and performance (Herzallah et al., 2014; Herzallah et al., 2017). Specifically,
Herzallah et al. (2017) examine to what extent a firm’s competitive strategy mediates the
relationship between ambidextrous QM and performance. They argue that ambidextrous QM
practices positively affect both a firm’s cost leadership strategy and its differentiation strategy
which then have an impact on performance. They promote the notion that exploitative and
explorative QM practices should be considered jointly (see Yalcinkaya et al., 2007) and that
7
firms should perform explorative and exploitative QM simultaneously; avoiding emphasis on
one at the expense of the other. They also indicate that certain combinations of QM practices
“best suit” each of the competitive strategies. Based on creating subsample of firms with a
particular competitive strategy focus (following Chandrasekaran et al., 2012), they examine
descriptive statistics to suggest that firms with a high focus on cost leadership strategy more
commonly balance explorative and exploitative QM practices. They also suggest that firms
with a high focus on differentiation generally develop higher levels of both QM practices
(Herzallah et al., 2017). We build on these suggestions to answer our research question,
namely how a firm’s competitive strategy conditions the relationship between certain QM
practices and firm performance. Hence, we seek to advance understanding about which QM
practices contribute to a firm’s performance contingent on its competitive strategy.
2.2. Hypotheses on the impact of exploitative and explorative QM practices on performance
Drawing on contingency theory, we suggest that the degree to which firms can profit from a
focus on either exploitative or explorative QM practices depends on the strategic focus of the
firm. We consider the classification of competitive strategies drawing on Porter’s (1980;
1985) framework. This builds on the well-known structure-conduct-performance paradigm
(Bain, 1956), meaning that a firm’s competitive strategy does not follow the firm’s internal
business practices but is tailored to the industry structure (e.g., competition, demand) in
which it operates. Consequently, we examine exploitative and explorative QM practices’
direct impact on performance. Furthermore, to understand whether ambidextrous QM
matters, we examine the direct impact of the interplay between exploitative and explorative
QM practices; capturing their interaction. In addition, we consider competitive strategy (i.e.
differentiation, cost leadership and the simultaneous pursuit of differentiation and cost
leadership elements) as a contextual factor. We argue that competitive strategies condition (or
8
moderate) the performance impact of certain QM practices. Figure 1 presents our conceptual
model.
– Insert Figure 1 about here –
Building on March (1991) we refer to exploitative and explorative QM practices as
failure reduction processes that improve performance. We reason that exploitative QM
practices that focus on better leveraging a firm’s existing resources reduce internal failure by
identifying all processes, products, and materials that do not fully meet quality requirements.
Exploitative QM practices concern all internal activities prior to the sales process of the final
product. For instance, better leveraging resources in a firm’s operations can include
controlling and improving the efficiency of existing processes (Zhang et al., 2014b), thereby
reducing scrap and rework issues and accordingly lowering internal failure (Prajogo and
Sohal, 2006, 2001) and costs (Reed et al., 1996; Reed et al., 2000). Hence, by better
exploiting existing resources, costs are reduced, firms are more efficient, and therefore
performance increases (also in the short-term; Lavie et al., 2010). From a product or sales
perspective, better exploiting resources relates to improving the reliability of existing
products and the quality of existing customer relationships (Sitkin et al., 1994; Zhang et al.,
2014b), which can be achieved through customer involvement, customer focus and customer
orientation (Zakuan et al., 2010). This reduces external failure; reflected in improved
customer satisfaction, increased revenues and strengthened performance (Desphandé et al.,
1993; Narver and Slater, 1990). Several studies substantiate and show that there is a positive
relationship between exploitative QM practices and performance (Sitkin et al., 1994; Piao,
2014; Yang and Li, 2011; Zhang et al., 2014b). We will follow this logic and hypothesize a
positive relationship between exploitative QM practices and performance due to reduced
internal and external failure:
9
Hypothesis 1: There is a positive association between exploitative QM practices and
performance.
Explorative QM practices focus on exploring the unknown, identifying and pursuing
novel solutions. They involve variation, risk taking, experimentation, discovery and
innovation, among others (March, 1991). Firms are thought to become more competitive by
exploring new alternatives and therewith by innovating (Posen and Levinthal, 2012; Zhang et
al., 2014b). From an operations perspective, this translates into innovative manufacturing and
supply chain processes which reduce internal failure in the long-term. For instance, firms
operating in industries such as the pharmaceutical industry are obligated to implement
approaches which would improve effectiveness and efficiency in operations (Friedli et al.,
2010). From a product or sales perspective, this translates into new/innovative products that
aim to reduce external failure in the long-term. Either way, novelty is the key to gaining
competitive advantage and enhancing performance from this perspective (Piao, 2014; Zhang
et al., 2014b; Sitkin et al., 1994). Even if such returns from exploration are risky and remote
(Lavie et al., 2010), firms benefit from engaging in explorative practices for responding
adequately to environmental changes to maintain competitiveness in the long-run (Kim and
Huh, 2015); especially in dynamic environments, i.e. when the amount of change is high and
very unpredictable (Jansen et al., 2006), which is the case in, for instance, high-tech
industries and the pharmaceutical industry (Li and Liu, 2014). We hypothesize a positive
relationship between explorative QM practices and performance due to reduced internal and
external failure:
Hypothesis 2: There is a positive association between explorative QM practices and
performance.
Even if there is a tension between exploitative and explorative QM practices (Sohani
and Singh, 2017), both categories of practices are not mutually exclusive; that is, firms can
10
deploy both (Gupta et al., 2006). In fact, prior works suggest that exploitation and exploration
should be considered jointly: exploitative activities provide financial flows that underpin
explorative activities, while explorative practices provide assets and capabilities for the
renewal of exploitative practices (e.g., Yalcinkaya et al., 2007; Garcia et al., 2003). As
acknowledged by Lavie et al. (2010) and Rothaermel and Alexandre (2009), exploration and
exploitation should not be viewed as a choice between discrete options, but rather
combinations of the two or the appropriate balance between the two can benefit performance
(see also Cegarra-Navarro et al., 2018). This logic underpins the ambidexterity perspective;
arguing that ambidexterity has a positive impact on performance, which does not receive
unambiguous empirical support, however (Herhausen, 2016; Raisch and Birkinshaw, 2008;
Wei et al., 2014; Chandrasekaran et al., 2012). We will argue later that some firms can profit
more from attributing attention to both QM practices than others when outlining our
contingency hypotheses. Still, we posit that, at the core, the interplay between both
exploitative and explorative QM practices has a positive impact on a firm’s performance and
longevity (Kim and Huh, 2015; Piao, 2014; Herzallah et al., 2017), and put forward the
following hypothesis:
Hypothesis 3: There is a positive association between the interplay of explorative and
exploitative QM practices and performance.
2.3. Hypotheses on the conditional effects of competitive strategy focus
Lacking clear focus might involve the risk of getting “disoriented” (Aghajari and Amat
Senin, 2014) and can involve high efforts and costs. A manager of a Standard & Poor’s 500
company stated that “It’s crazy to tell people they should be focused on becoming more
efficient while at the same time you want them to explore untapped growth potential. This is
making me nuts” (Rae, 2007).
11
Because firms have limited resources, the degree to which they can profit from a
focus on either exploitative or explorative QM practices depends on contextual factors (Das
et al., 2000; Sousa and Voss, 2001; Zatzick et al., 2012). Any investment in exploitative
activities by firms may limit their ability to also invest in explorative activities (Oshri et al.,
2005). Hence, it is important to understand the contextual factors, which characterize the
contexts in which either of the QM practices is most effective. Indeed, several authors
suggest that consideration of contextual factors can likely explain the differences in
relationships found between QM practices and performance (Powell, 1995; Dow et al., 1999;
Sousa and Voss, 2001). Hence, we apply a contingency theoretic argument to capture the
impact of contextual conditions under which certain QM practices are more or less effective
(Sousa and Voss, 2001, 2008). Contingency theory posits that performance is dependent on
the fit between firm’s internal features and contextual factors (Lawrence and Lorsch, 1967;
Miller, 1987). One of the contextual factors of relevance to QM research is the strategic
context (Sousa and Voss, 2008).
Exploitative and explorative QM practices are expected to function differently under
different competitive strategies (Kim and Huh, 2015). With some exceptions – see for
instance the analysis of different contextual factors in Sila (2007), studies support the
existence of strategy context effects, which condition the relationships between QM practices
and performance (Fuentes Fuentes et al., 2006; Moreno-Luzón and Peris, 1998; Auh and
Menguc, 2005; Yunis et al., 2013; Zatzick et al., 2012). These contextual effects are based on
the assumption that there needs to be an alignment between strategy and organizational
activities (Miller, 1996; Porter, 1996). In leaning on Porter’s (1980; 1985) widely accepted
competitive strategy framework, we consider differentiation and cost leadership as strategic
foci that affect a firm’s competitive advantage and constitute a relevant contextual condition
within which QM practices occur. As we will outline below, efficiency-oriented business
12
strategies (i.e., cost leadership) are related to exploitation and differentiation-oriented
business strategies to exploration. Notwithstanding Porter’s early arguments concerning the
incompatibility between these two strategic foci, other works develop the idea of benefitting
from the simultaneous pursuit of both strategic foci (Hill, 1988; Murray, 1988; Raisch and
Birkinshaw, 2008). Thus, in addition to differentiators and cost leaders, we consider a
combination of both (hybrids) as a strategic focus that deserves attention. Hence, we also
integrate strategically ambidextrous, hybrid firms that show high levels of both, cost
leadership and differentiation strategies.
A differentiation strategy is characterized by providing products that create a
competitive advantage through increasing the perceived value of the product in customers’
minds. This is achieved through more uniqueness in products or processes at the external
interface with customers. Therewith, it focuses on aspects which are congruent with
explorative QM practices (Phillips et al., 1983). Differentiators benefit more from
innovations especially in products, but also from business processes that increase the
responsiveness to customer preferences (see also Zatzick et al., 2012; Prajogo and Sohal,
2001). Continuously engaging in innovating customer focused processes and providing
products that better fit customers’ needs is key to the success of a differentiation strategy as it
reduces external failure (Prajogo and Sohal, 2006). Explorative QM practices reduce the risk
of obsolescence associated with existing technologies and products and therewith reduce the
risk of external failure (Sitkin et al., 1994; Kim and Huh, 2015). Hence, we hypothesize that
explorative QM practices are particularly suitable to reduce external failure in the context of a
differentiation strategy and should therefore provide a relatively better means to increasing
the financial and market performance of differentiators.
Hypothesis 4a: The positive association between explorative QM practices and
performance is stronger for differentiators than for cost leaders.
13
Hypothesis 4b: The positive association between explorative QM practices and
performance is stronger for differentiators than for hybrids.
On the other hand, we argue that exploitative QM practices are significantly more
relevant for the performance outcome of cost leaders. Firms focus on improving processes to
make them more efficient when their primary competitive strategy is to pursue cost
leadership (Prajogo and Sohal, 2001, 2006; Ruiz Ortega, 2010). Improving the quality of
operations and processes contributes to reducing internal failure (reflected in for instance
reduced scrap ad rework). Furthermore, improving the reliability of products contributes to
reducing external failure (reflected in reduced customer complaints, which positively affects
customer satisfaction and, in turn, a firm’s competitiveness). These mechanisms contribute to
gaining a cost-based advantage that is the ultimate objective of a cost leadership strategy
(Reed et al., 1996). Hence, we hypothesize that exploitative QM practices are congruent and
fit with a cost leadership strategy and, therefore, should provide a relatively better means to
increasing the financial and market performance of cost leaders.
Hypothesis 5a: The positive association between exploitative QM practices and
performance is stronger for cost leaders than for differentiators.
Hypothesis 5b: The positive association between exploitative QM practices and
performance is stronger for cost leaders than for hybrids.
For strategically ambidextrous firms (hybrids) that pursue both differentiation and
cost leadership (Aspara et al., 2011), we assume that drawing on both explorative and
exploitative QM practices is relevant to increasing performance (Raisch and Birkinshaw,
2008). Strategically ambidextrous firms are less vulnerable to changes (Claver-Cortés et al.,
2012) but they need to reduce costs while investing in customer focused QM practices such
as product innovation. This would imply avoiding internal failure by focusing on better
exploiting existing resources. At the same time this would imply allocating other resources to
14
take risks by exploring new alternatives which would allow firms to respond adequately to
environmental changes and to avoid external failure (Raisch and Birkinshaw, 2008). In this
sense, a combination between both QM practices is positively related to the performance of
hybrids (He and Wong, 2004; Lavie et al., 2010).
Hypothesis 6a: For strategically ambidextrous firms (hybrids), the positive
association between the simultaneous interplay of explorative and exploitative QM
practices and performance is stronger than for differentiators.
Hypothesis 6b: For strategically ambidextrous firms (hybrids), the positive
association between the simultaneous interplay of explorative and exploitative QM
practices and performance is stronger than for cost leaders.
3. RESEARCH METHODOLOGY
3.1. Sample and data collection
To test our hypotheses, we draw on a sample of 200 German pharmaceutical firms (to
identify pharmaceutical firms, we referred to the standard industry classification (SIC) codes
and selected those firms with SIC code 2834: Pharmaceutical; an approach that has been
applied in similar settings, see Kim and Park (2013)). We focus on firms within the German
pharmaceutical industry for several reasons: The use of QM practices is mandatory in this
industry (Drew, 1998; Mehralian et al., 2016). Moreover, the German pharmaceutical
industry is particularly strong, both in terms of number of competitors and their performance
(Destatis, 2018), is one of the largest industries in Germany in terms of revenues according to
the German Federal Ministry of Economic Affairs and Energy, and importantly has a
substantial number of firms. Known as the “world’s pharmacy”, Germany is home to
Europe’s largest – and the world’s fourth largest – pharmaceuticals market (Destatis, 2018).
Moreover, the industry is also sufficiently heterogeneous in terms of the competitive strategy
focus that firms have (Garbe and Richter, 2009; Spitz, 2003) such that it offers a good mix of
15
firms with either of the three competitive strategy foci that we study. Having an industry and
country focus likewise has advantages: It avoids that differences in industry characteristics
affect the conditional performance impacts of QM practices. Likewise, we eliminate the
effect of differences in country characteristics.
By conducting a survey and collecting data from financial reports, we gathered
primary and secondary data on these firms. The survey used a stratified proportional data
collection procedure on a sampling frame covering 928 firms provided by Dun and
Bradstreet. The sample is stratified by federal state, turnover, and firm size (measured by the
total number of employees). In mid 2014, we conducted computer-assisted telephone
interviews with CEOs to collect data and obtained valid responses from 200 different firms.
Comparing this to the number of qualified contacts (n = 597) corresponded to a response rate
of 33.5%, which is acceptable especially when considering the one-time contact and specific
target of CEOs (Manfreda et al., 2008). In addition to the survey, we gathered the following
information from (financial) reports provided by an official publication of the German
government (the Bundesanzeiger, www.bundesanzeiger.de): the share of equity, the total
number of employees, the value of total assets, and firm age.
3.2. Analyses
To test our hypotheses, we used PLS-SEM employing the SmartPLS 3 software (Ringle et
al., 2015). The PLS-SEM method allows to establish and estimate a path model with latent
variables (Hair et al., 2019; Hair et al., 2014). The strength of the estimated relationships
depicts the main sources of impact to explain a key target construct of interest (Hair et al.,
2012). Due to the early phase of theorizing on the impact of exploitative and explorative QM
practices on performance (Richter et al., 2016a; Rigdon, 2016), we opted for using PLS-SEM
(rather than another structural equation modelling method, such as covariance-based SEM) as
the most suitable method for extending existing theory in management research (Richter et
16
al., 2016b; Svensson, 2015) which our study is about. Furthermore, we regarded PLS-SEM
advantageous over covariance-based SEM and also over using a combination of first
generation methods such as factor- and regression analyses as it allows to assess multi-group
analyses even for smaller subgroups, does not require normality of data and allows the
assessment of predictive relevance and power (Hair et al., 2019); all aspects that are
applicable to our study.
The analyses involved two key steps (see Figure 2). First, we evaluated a base model
to examine the performance effect of exploitative and explorative QM practices in the total
sample and to understand its predictive relevance. Second, we assessed the impact of the
strategic focus as a contextual factor in QM using multi-group analyses on this base model
(Hair et al., 2017; Sarstedt et al., 2011). Hence, we performed subgroup analyses with
reference to the competitive strategy pursued by the firms (i.e., one analysis for
differentiators, one for cost leaders and one for firms pursuing a hybrid strategy). In turn, this
enables testing of the relevance of the three types of QM practice constellations conditional
on each strategy focus.
– Insert Figure 2 about here –
3.3. Measures
The latent variables in our model require specific items in each measurement model.
Following Diamantopoulos et al. (2012), the dependent and independent research variables
are measured by means of multiple items on 5-point Likert scales, ranking from 1 (“much
below the average”) to 5 (“much above the average”). Following Presser et al. (2004) and
Guest et al. (2006), the questionnaire has been validated by pre-tests with managers from
different companies not included in the final sample. This pre-test ensures the validity of
items used for each construct and the understandability of the questions related to each item.
17
We selected three (reflective) items related to income, revenue and market share to
measure performance based on CEO’s evaluations (Brah et al., 2000; Demirbag et al., 2006;
Douglas and Judge, 2001; Yusuf et al., 2007). To measure exploitative and explorative QM
practices, we created our own scale by adapting the customer and process related practices
emphasized in previously used scales. We concluded with three items for each of the two
constructs for the sake of not increasing questionnaire length, which is of particular
importance as we sought responses from CEOs. Exploitative QM practices are measured
using three (reflective) items related to being in close contact with customers on quality
issues, monitoring of processes regarding quality control, and investing efforts in research
and control practices on production in order to fully exploit these processes (Ahire and
Dreyfus, 2000; Brah et al., 2000; Choi and Eboch, 1998; Demirbag et al., 2006; Douglas and
Judge, 2001; Forza and Filippini, 1998; Gadenne and Sharma, 2009; Lakhal et al., 2006;
Merino-Díaz De Cerio, 2003; Molina et al., 2007; Sharma, 2006). Explorative QM practices
are measured using three (reflective) items related to the exploration of new products, efforts
to continually improve products as well as an item related to the exploration of new
production processes (Arauz et al., 2009; Fuentes Fuentes et al., 2006; Fuentes-Fuentes et al.,
2004; Merino-Díaz De Cerio, 2003). In addition, when looking into exploitative and
explorative QM practices individually, we also created an interaction term of the two
constructs, as we assume that it is the simultaneous interplay of these two QM practices that
matters for firms pursuing both, cost leadership and differentiation strategy aspects. This
interaction term is formed using the two-stage approach (Hair et al., 2017). Applying a
method commonly used in relevant previous studies (Atuahene-Gima, 2005; He and Wong,
2004), we computed a multiplicative interaction of exploitative and explorative QM practices
to indicate the firm’s overall exploration-exploitation ambidexterity in QM. This reflects the
nonsubstitutable and interdependent nature of exploitative and explorative QM practices.
18
Furthermore, we used information gathered from financial reports to include the following
common control variables into the analysis that are known to have an effect on performance
(Goerzen and Beamish, 2003; Coad et al., 2018; Ketokivi and Schroeder, 2004; Garbe and
Richter, 2009): firm size, measured by the total assets and number of employees (both
logarithmized), the share of equity as a single item and the firm’s age as a single-item.
Finally, following Porter’s (1980; 1985) classification, we sort firms into
differentiators and cost leaders. Additionally, we identify strategically ambidextrous firms,
namely hybrids, given the growing interest in hybridization (Salavou, 2015). For grouping
purposes, we use a dummy coding of factor scores representing differentiation or cost
leadership (i.e. firms with an above the average score on differentiation and a below the
average score on cost leadership were coded as differentiators and vice versa). To
operationalize differentiation strategy, we have drawn on several items from previously used
scales (Acquaah and Yasai-Ardekani, 2008; Gabrielsson et al., 2016; Santos-Vijande et al.,
2012) that reflect this construct best. Specifically, the items used to operationalize
differentiation strategy are a focus on specialized products, offering unique and distinct
products, serving high-priced market segments and having a strong reputation in the industry
(see Appendix A). Similarly, to operationalize cost leadership strategy we draw on items used
previously by several authors (Acquaah and Yasai-Ardekani, 2008; Pertusa-Ortega et al.,
2010). Specifically, the items used to operationalize cost leadership are a strong effort to
achieve the lowest cost per unit, focusing on pricing below competitors and serving low-
priced market segments (see Appendix A). Hybrids are firms that simultaneously performed
above average on both sets of characteristics.
This approach allowed to extract groups of data as differentiators (n = 57 firms), cost
leaders (n = 67 firms), and hybrids (n = 51 firms). The sample sizes available for the multi-
group analyses (i.e., 57, 67 and 51 responses) are appropriate in light of the low complexity
19
of the model used (Chin, 2010; Hair et al., 2011). Power analyses (Hair et al., 2017) as well
as the inverse square root and gamma-exponential methods (Kock and Hadaya, 2016) to
determine the minimum sample size needed in PLS-SEM support this notion.
4. RESULTS
4.1. Measurement models
We first evaluated the reliability and validity of measurement models, before starting to
interpret structural relationships (Chin, 2010; Hair et al., 2017). All reflective measures (see
Appendix B.1) meet the quality criteria defined (Chin, 2010; Hair et al., 2017): Outer
loadings (>0.7), indicator reliability (>0.5), average variance extracted (>0.5) and composite
reliability (>0.7) correspond to the threshold values for evaluating reliability given in the
literature. In addition, all measures meet the heterotrait-monotrait (HTMT) discriminant
validity assessment criterion (Henseler et al., 2015; see Appendix B.2).
The following steps were undertaken to account for common method bias: First,
survey items related to the dependent and the independent variables were separated within the
survey and randomized within blocks to reduce a potential bias from their sequencing.
Second, secondary data from financial reports was introduced to the analysis to reduce
common method biases (Podsakoff et al., 2003). Third, we assessed the potential influence of
common method bias post-hoc by using Harman’s single factor test (Podsakoff and Organ,
1986) suggesting that there is no “general factor” in the data. Hence, common method bias
likely is not a serious problem in our study.
As we conducted a multi-group analysis, we also tested for measurement invariance
using the measurement invariance of composite models (MICOM) approach (Henseler et al.,
2016; Schlägel and Sarstedt, 2016). We used identical indicators for the measurement models
within the groups, an identical data treatment and identical algorithm settings for all
subgroups. In consequence, we have established configural invariance. Moreover, the results
20
of a permutation test for equal weights between groups show that we have established
compositional invariance. Performing a permutation test for equal composite means and
variances, we find that we do not have full measurement invariance, yet we have partial
measurement invariance. This is sufficient for being able to compare the standardized
coefficients across our subgroups of differentiators, cost leaders and hybrids.
4.2. Base model results
Table 1 provides an overview of the results for the base model. In addition to the path
coefficients, it provides the R² values and some further quality criteria (namely the variance
inflation factors, which are all below common thresholds, effect sizes and the Q2 value based
on the blindfolding procedure).
– Insert Table 1 about here –
In the total sample, exploitative QM practices are positively and significantly related
to performance (0.297; p = 0.000). Therefore, Hypothesis 1 is supported. Explorative QM
practices are positively, yet not significantly related to performance (0.113; p = 0.124). Thus,
Hypothesis 2 is not supported in the total sample. Hypothesis 3 suggests a positive
relationship between the interplay of exploitative and explorative QM practices with
performance. In the total sample, we find a nonsignificant path coefficient around zero
(0.009; p = 0.883), which does not support Hypothesis 3. Overall, the model explains a good
share of variance in performance, namely 25.3% and has predictive relevance and power.
Predictive relevance and power was assessed by means of the blindfolding procedure (Q2 =
0.18) (Hair et al., 2019) and by means of PLSpredict (Shmueli et al., 2019) which analyzes
the out-of-sample explanatory power of the model. Focusing on our key target construct
performance, we find positive Q2 values for the three indicators of the performance construct
(Q2market share = 0.021, Q2revenue = 0.053, and Q2net income = 0.000). Since prediction errors are
highly symmetrically distributed, we compared the root mean squared error (RMSE) value of
21
PLS with the lineal regression model (LM) value for each indicator and find that PLS-SEM
yields lower prediction errors than the naïve LM benchmark (namely 0.977 < 0.986 for
market share; 1.013 < 1.023 for revenue; 1.047 < 1.064 for net income) (Hair et al., 2019;
Shmueli et al., 2019).
4.3. Results of moderation analyses
Tables 2 and 3 provide an overview of the results generated by means of our multi-group
analyses. More specifically, Table 2 provides the path coefficients and the corresponding p-
values and R2-values for the subgroups of firms which either pursue a differentiation, cost
leadership or both of these orientations in a hybrid strategy. Table 3 shows differences in path
coefficients between the groups as well as the p-values indicating whether the differences
between path coefficients are significant or not.
– Insert Table 2 about here –
– Insert Table 3 about here –
Hypothesis 4a and Hypothesis 4b suggest that the positive association between
explorative QM practices and performance is stronger for differentiators as compared to for
cost leaders and hybrids, respectively. Our results show that explorative QM practices are the
most important (and a significant) determinant of performance among firms pursuing a
differentiation strategy (0.382; p = 0.021). Furthermore, comparing differentiators to cost
leaders, the path coefficients for the association between explorative QM practices and
performance differ by a value of 0.337, which is significant (p < 0.05). Hence, Hypothesis 4a
is supported. Comparing differentiators to hybrids, there is a notable difference in path
coefficients (i.e., 0.272) that, however, is not statistically significant. Therefore, Hypothesis
4b is not supported.
Hypothesis 5a denotes that the positive association between exploitative QM practices
and performance is stronger for cost leaders as compared to for differentiators. The results
22
show that exploitative QM practices are the most important determinant of performance for
firms following a cost leadership strategy (0.321; p < 0.01). Moreover, comparing cost
leaders with differentiators, the path coefficients for the association between exploitative QM
practices and performance differ by a value of 0.431, which is significant (p < 0.05). Hence,
Hypothesis 5a is supported. Comparing cost leaders with hybrids, the path coefficients for the
association between exploitative QM practices and performance differ by 0.159 in the
assumed direction but this difference is not significant. Hence, Hypothesis 5 is not supported.
Hypothesis 6a and 6b imply that for strategically ambidextrous firms (i.e., hybrids),
the simultaneous use of both explorative and exploitative QM practices is of stronger
importance as compared to firms opting for one of the competitive strategies. Both QM
practices are assumed to interact and this interaction is assumed to positively affect
performance more strongly as compared to firms purely concentrating on either cost
leadership or differentiation. For hybrid firms, both exploitative and explorative QM seem to
be important to performance with path coefficients of 0.133 for explorative QM practices and
0.162 for exploitative QM practices. The highest value is moreover found for the interaction
of these practices (0.219). Yet, none of these coefficients shows significance. However,
comparing the path coefficients to the ones of differentiators and of cost leaders, there are
significant differences between the groups: The relevance of the interaction between
exploitative and explorative QM practices is significantly higher for hybrid firms, both when
compared to differentiators (difference in path coefficients: 0.482) and to cost leaders
(difference in path coefficients: 0.284). Hence, Hypotheses 6a and 6b are (partially)
supported. To sum up, our moderation analyses reveal differences among differentiators and
cost leaders. However, the results for hybrid firms are not as conclusive, which may be
explained by the idiosyncrasies of hybrid firms.
5. DISCUSSION
23
5.1. Implications for theory
This study makes several contributions to theory: First, we build on recent suggestions to
distinguish exploitative and explorative QM practices (Zhang et al., 2014a) and therewith
provide valuable insights that advance the literature on exploration and exploitation from a
QM perspective (Posen and Levinthal, 2012). Second, using this classification, we contribute
to the discussion about whether the performance impact of QM practices is best understood
by considering QM practices holistically or not (Kaynak, 2003). Third, by studying the
performance impact of QM practices conditionally on a firm’s competitive strategy focus, we
contribute to closing a gap in the research landscape about the contingent impact of QM
practices (Nair, 2006). Fourth, we add clarity to the conceptual associations between
competitive strategy and QM practices and advance this emerging stream of research
(Herzallah et al., 2017).
More precisely, the first contribution that this paper provides concerns our
understanding of the performance impacts of two different types of QM practices:
exploitative and explorative QM practices. When examining their performance impacts
without consideration of a firm’s strategic focus, we find that only exploitative QM practices
increase performance; which is in line with the findings in Zhang et al. (2014a), this
substantiates the relevance of exploitative QM in dynamic environments. Eliminating scrap
and rework issues by means of controlling and improving the efficiency of existing
operational processes is advantageous and increases performance (Reed et al., 1996).
Furthermore, investing in QM practices to improve the reliability of existing products and the
quality of existing customer relationships likewise has beneficial performance effects
(Fuentes Fuentes et al., 2006; Reed et al., 1996). Explorative QM practices, in contrast, do
not appear to affect performance. However, as our results from subsequent analyses indicate
that explorative QM practices matter for firms that pursue a differentiation strategy, seeking
24
to understand the performance impact of QM practices without accounting the context within
which they used may be less useful. Hence, it is important to consider the use of QM
practices given the competitive strategy focus that firms have. Only firms pursuing a
differentiation strategy are advised to engage in explorative QM practices which contradicts
arguments or findings of a general positive impact of explorative QM practices on
performance (Hendricks and Singhal, 1997).
Second, the simultaneous pursuit of both practices does not necessarily contribute to
increasing performance. This finding is in contrast to views that for QM practices to enhance
performance they always must be considered holistically and combined (He and Wong, 2004;
Kaynak and Hartley, 2005). Hence, our findings do not support the notion that for QM
practices to improve performance they need to function as a whole rather than through its
constituent elements. In fact, the simultaneous use of both, exploitative and explorative QM
practices in general rather seems to involve the risk of disorientation (Aghajari and Amat
Senin, 2014) and does not inevitably contribute to performance. The significant efforts and
costs needed for pursuing both practices simultaneously are only fruitful if combined with a
hybrid competitive strategy focus as we will discuss later.
Third, as research remains inconclusive in regards to the role of context factors that
may condition the performance impact of QM practices (Nair, 2006), we contribute to filling
this gap in the research landscape. Our results show that exploitative QM practices are of
particular relevance for cost leaders, while explorative QM practices are advantageous for
firms pursuing a differentiation strategy. Strategically hybrid firms benefit from the
simultaneous pursuit of both QM practices to increase their performance. Precisely, for
strategically ambidextrous firms (even when the separate QM-performance effects are not
significant) the simultaneous use of QM practices, when assessing their interaction, is
stronger as compared to differentiators. This supports the current efforts (Sousa and Voss,
25
2001) and calls in research (Dow et al., 1999; Nair, 2006; Sousa and Voss, 2008; Herzallah et
al., 2017) to account for the context within which QM practices are used to affect
performance, as our findings substantiate that the performance impact of QM practices is
conditional on a firm’s competitive strategy focus. Hence, this present study is among the few
studies testing contingencies, such as regional differences (Adam et al., 1997), competitive
scope and intensity (Das et al., 2000), similarly market turbulence, competitive intensity and
technological turbulence (Wang et al., 2012), and experience with TQM (Brah et al., 2000)
and introduce a stronger competitive strategy focus to the QM literature.
Finally, building on recent thinking by Herzallah et al. (2017), we adapt and further
develop their work and explain how a firm’s competitive strategy focus (i.e., drawing on
Porter’s classification of competitive strategy foci) conditions the performance impacts of
QM practices. We reason that QM practices do not determine how a firm develops its
strategy. Instead, we argue that the direct impacts of a firm’s QM practices on performance
are conditioned by the competitive strategy that it pursues (i.e., differentiation, cost
leadership, hybrid). That is, beyond arguing that the performance impacts of exploitative and
explorative QM practices are moderated by the firm’s competitive strategy focus, in addition
we also more explicitly examine: a) their combined performance impact by incorporating the
interaction effect of the two QM practices. This allows assessing both, the individual effects
of exploitative and explorative QM practices, as well as the effect that a combination of the
two practices has, on performance (Herhausen, 2016) advancing recent conceptualizations
(Herzallah et al., 2017); and b) we explicitly account for firms that have a hybrid strategic
focus in which both differentiation and cost leadership are pursued. We encourage authors to
further discuss and amend these two different conceptualizations opened up in the QM
literature.
26
5.2. Implications for management
Firms within the pharmaceutical industry are characterized by high pressures for
integration due to high fixed costs such as R&D (i.e., cost leadership) and high pressures for
responsiveness due to high regulation in different environments (i.e. differentiation). Thus,
pharmaceutical firms can presumably benefit from a hybrid competitive strategy focus that
involves elements of both cost leadership and differentiation (Fortanier et al., 2007). Looking
at the performance levels reached by different firms in our sample, this seems to be supported
as hybrids show the highest performance ratings, followed by differentiators and then (with a
below average performance) cost leaders. Yet, for all strategic foci pursued, managers need to
understand which QM practices enhance performance given the competitive strategy pursued.
Hence, while a firm’s competitive strategy focus will need to align with industry pressures,
QM practices need to fit with the pursued strategic focus to be effective.
Our results confirm a positive association between exploitative QM practices and
performance. While this is a more generic recommendation, it holds especially true for firms
pursuing a cost leadership strategy. They will more than other firms profit from exploiting
operations (e.g., by controlling and improving the efficiency of existing operational
processes) and product related QM practices (e.g., by investing into improving the reliability
of existing products and the quality of existing customer relationships). This is different for
explorative QM practices. In light of constrained budgets, only firms pursuing a
differentiation strategy are advised to invest into innovative manufacturing and supply chain
processes as well as in new/innovative products for customers. For these firms, novelty both
in operations and products is key to gain competitive advantage and enhance performance
(this corresponds to the findings in Fuentes Fuentes et al. (2006)). Finally, the rather high
efforts and costs needed for pursuing both QM practices simultaneously are only fruitful if
combined with a hybrid competitive strategy focus. Hybrid firms can increase their
27
performance by focusing simultaneously on both types of QM practices. This is interesting in
light of the findings of Douglas and Judge (2001) which provide evidence of a positive
contingency effect of the QM and performance relationship for firms fostering both structural
control and structural exploration, i.e. in firms working synergistically with both types of
structure.
5.3. Limitations and directions for further research
As with any empirical research, our study is not without limitations regarding the construct
measurement and the sample. With regards to the constructs focused on, we analyzed an
overall performance construct covering three facets (namely the growth of revenue, net
income and market share). Distinguishing between short- and long-term performance or cost-
and revenue-related performance might be fruitful for future research, as well. We argue that
this is fruitful, as, for instance, the effect of explorative QM practices on performance may
take a longer time horizon – than the one considered in this study – to unfold or to be
measurable in empirical settings which may have impacted our results. Furthermore, future
studies may want to expand on the measurement of explorative and exploitative QM practices
and, in addition to the process and product foci, may want to add further aspects, such as a
team or training focus. Second, the only contextual factor focused on in this study is a firm’s
competitive strategy focus; in this sense, further research could examine whether other kinds
of firm-specific or environmental factors condition the performance impact of certain QM
practices (e.g., Auh and Menguc, 2005; Sitkin et al., 1994). Caution should be exercised
however, because including too many contextual factors may limit generalizability of the
findings and comparisons with other studies (Sousa and Voss, 2008). With regards to the
sample, we studied German pharmaceutical firms. Hence, there might be institutional aspects
that condition our results such that results could differ across countries and/or industries.
28
Further research could also be conducted in different industries and countries with a
view to assess whether the main findings can be replicated. In this regard, future research
might investigate how institutional factors affect the performance impact of QM practices.
Thus, linking the results with the new institutional economy is an interesting way to expand
the research reported here. Moreover, analyzing the results in a longitudinal framework
would allow better understanding whether the temporal sequencing of QM practices matters
(as often called for in the field, e.g., see Fynes and Voss, 2002). Finally, we consider mixed
methods approaches in which quantitative analyses are combined with in-depth qualitative
findings a fruitful avenue to enrich more generalizable findings with a deeper exploration of
specific firm contexts.
6. CONCLUSION
We advocate consideration of two crucial perspectives into understanding the performance
impact of QM practices. First, rather than viewing QM as a unidimensional, holistic concept,
we distinguish exploitative QM practices from explorative ones and substantiate that
evaluating the separate performance impacts as well as their combined one is important.
Second, we demonstrate that to fully understand the performance impact of QM practices
they need to be studied conditional on the context within which they function. We show that
aligning QM practices within the competitive strategy focus that a firm pursues is important
to benefit from certain QM practices.
The findings of our study are valuable to managers as they provide clear guidance on
when to use which kind of QM practices (i.e., exploitative QM practices, explorative QM
practices, or both). In using effective QM practices, managers should be aware of the
different effects QM practices have conditional on the competitive strategy focus a firm has
chosen.
29
Figure 1. Conceptual model
30
Figure 2. Analysis approach to hypotheses testing
31
Table 1. PLS-SEM analysis: Base model
Relationship Path coefficient p-value VIF f²
Exploitative QM practices → Perf 0.297*** 0.000 1.646 0.072
Explorative QM practices → Perf 0.113 0.124 1.390 0.012
Exploitative x Explorative → Perf 0.009 0.883 1.105 0.000
Firm size → Perf 0.204** 0.010 1.397 0.040
Firm age → Perf -0.063 0.428 1.009 0.005
Share of equity → Perf 0.021 0.638 1.004 0.001
R² 0.253
Q² 0.180
Note: * p < 0.1; ** p < 0.05; *** p < 0.01. Perf = performance.
Table 2. PLS-SEM analysis: Contextualized model – group results
Relationship
Differentiators Cost Leaders Hybrids
Path
coefficient
p-value
Path
coefficient
p-value
Path
coefficient
p-value
Exploitative QM practices → Perf -0.110 0.596 0.321* 0.005 0.162 0.302
Explorative QM practices → Perf 0.382** 0.021 0.044 0.770 0.133 0.394
Exploitative x Explorative → Perf -0.263 0.253 -0.065 0.581 0.219 0.194
Firm size → Perf 0.135 0.416 0.177 0.203 0.254 0.246
Firm age → Perf 0.105 0.355 0.050 0.797 -0.341*** 0.002
Share of equity → Perf -0.108 0.527 0.066 0.427 -0.166 0.183
R² 0.239 0.206 0.384
Note: * p < 0.1; ** p < 0.05; *** p < 0.01. Perf = performance. For the differences in the PLS-MGA,
additionally: * p > .9; ** p > .95; *** p > .99. Significant probability levels for the delta in path coefficients
depend on the directionality of the effect.
Table 3. PLS-MGA: Contextualized model – group differences
Relationship
Cost Leaders –
Differentiators
Cost Leaders –
Hybrids
Differentiators –
Hybrids
Δ Path
coefficients
p-value
Δ Path
coefficients
p-value
Δ Path
coefficients
p-value
Exploitative QM practices → Perf 0.431** 0.038 0.159 0.194 0.272 0.857
Explorative QM practices → Perf 0.337* 0.940 0.089 0.663 0.248 0.130
Exploitative x Explorative → Perf 0.198 0.215 0.284* 0.913 0.482** 0.950
Firm size → Perf 0.042 0.428 0.077 0.667 0.118 0.710
Firm age → Perf 0.054 0.577 0.392** 0.044 0.446*** 0.005
Share of equity → Perf 0.174 0.178 0.232* 0.058 0.058 0.389
Note: * p < 0.1; ** p < 0.05; *** p < 0.01. Perf = performance. For the differences in the PLS-MGA,
additionally: * p > .9; ** p > .95; *** p > .99. Significant probability levels for the delta in path coefficients
depend on the directionality of the effect.
32
Appendix A. Research Constructs and Items
Construct Definition Items References
Differen-
tiation
Strategy
A differentiation strategy is
characterized by providing unique
products that create a competitive
advantage by increasing the perceived
value of the product in customers’
minds. By focusing on specialized
products, emphasizing products or
services for high priced market
segments and building and improving
brand reputation, firms are able to
achieve a competitive advantage over
their rivals (Acquaah and Yasai-
Ardekani, 2008).
Focus on
specialized
products
Offering unique
products
Serving high-
priced market
segments
Reputation in
industry
(See also Gabrielsson et al., 2016;
Powers and Hahn, 2004; Qi et al.,
2011; Santos-Vijande et al., 2012)
Cost
leadership
strategy
Following a cost leadership strategy
would imply lowering costs and
focusing on low-priced market
segments. Thus, by pricing below
competitors, firms can compete in
prices, which would contribute to
gaining a competitive advantage (Ruiz-
Ortega and García-Villaverde, 2008).
Lowest cost per
unit
Pricing below
competitors
Low-priced market
segments
(See also Acquaah and Yasai-
Ardekani, 2008; Amoako-Gyampah
and Acquaah, 2008; Pelham and
Wilson, 1996; Pertusa-Ortega et al.,
2010; Qi et al., 2011)
Firm
performance
Performance is divided into financial
performance operationalized with
indicators such as growth in revenues
and net-income/profits. Furthermore
from a non-financial (and more long-
term) perspective performance is
operationalized with indicators such as
market shares (Venkatraman and
Ramanujam, 1986; Roth and Morrison,
1990).
Revenue growth
Net income growth
Market share
growth
(See also Brah et al., 2000;
Demirbag et al., 2006; Douglas and
Judge, 2001; Yusuf et al., 2007)
Exploitative
QM
practices
Exploitative QM practices aim to
control, yet also to improve existing
processes. From a customer
perspective, they comprise the
identification and assessment of
customer needs or the development of a
better understanding of customer
expectations (Zhang et al., 2012).
Strict quality
control
Process orientated
R&D
Extensive customer
contact/ service
(See also Ahire and Dreyfus, 2000;
Brah et al., 2000; Choi and Eboch,
1998; Demirbag et al., 2006;
Douglas and Judge, 2001; Forza and
Filippini, 1998; Gadenne and
Sharma, 2009; Lakhal et al., 2006;
Merino-Díaz De Cerio, 2003;
Molina et al., 2007; Sharma, 2006)
Explorative
QM
practices
Explorative QM practices refer to
variation, discovery, and innovation
activities. They comprise the
improvement of processes and products
(Zhang et al., 2012).
Innovation in
manufacturing
process
New product
development
Develop and refine
established
products
(See also Arauz et al., 2009;
Fuentes Fuentes et al., 2006;
Fuentes-Fuentes et al., 2004;
Merino-Díaz De Cerio, 2003)
33
Appendix B1. Measures
Construct
(Source)
Items Loading
Item
reliability
AVE
Composite
reliability (α)
HTMT- (BcA-)
confidence interval
includes 1
Performance
(Survey)
Revenue growth
Net income growth
Market share growth
0.90
0.85
0.92
0.81
0.72
0.85
0.79
0.92
(0.87)
No
Exploitative
QM practices
(Survey)
Extensive customer
service
Process orientated
R&D
Strict quality control
0.77
0.73
0.71
0.59
0.53
0.50
0.54
0.78
(0.58)
No
Explorative
QM practices
(Survey)
Develop and refine
established products
Innovation in
manufacturing process
New product
development
0.82
0.65
0.86
0.67
0.42
0.74
0.61
0.82
(0.67)
No
Firm size
(Financial
report)
Number of employees
(log)
Total assets (log)
0.92
0.72
0.85
0.52
0.69
0.81
(0.57)
No
Firm age
(Financial
report)
Years since
establishment
1.00
Share of equity
(Financial
report)
Equity/total assets 1.00
Appendix B2. HTMT Criterion Results
Performance
Exploitative QM
practices
Explorative QM
practices
Performance
Exploitative QM
practices
0.63
[0.47; 0.77]
Explorative QM
practices
0.44
[0.26; 0.61]
0.83
[0.64; 0.99]
All HTMT criterion results are below the more conservative critical level of 0.85; also, the 95% bias-
corrected and accelerated (BCa) bootstrap confidence intervals (i.e., based on 5,000 bootstraps) indicate
that the HTMT values are significantly lower than 1. None of the intervals includes 1 (see also the table
above). Hence, discriminant validity has been established.
34
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