DEVELOPMENT OF PHARMACEUTICAL DISTRIBUTION MODEL...
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1 DEVELOPMENT OF PHARMACEUTICAL DISTRIBUTION MODEL FOR CUSTOMER SATISFACTION Submitted by Muhammad Usman Awan in accordance with the requirement for the degree of Doctor of Philosophy Supervisor: Prof. Dr. Abdul Raouf Co-Supervisor: Prof. Dr. Niaz Ahmad Akhtar (May 2008) Institute of Quality and Technology Management Faculty of Engineering and Technology Quaid-e-Azam campus, University of the Punjab Lahore - Pakistan
Transcript of DEVELOPMENT OF PHARMACEUTICAL DISTRIBUTION MODEL...
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DEVELOPMENT OF PHARMACEUTICAL DISTRIBUTION MODEL FOR CUSTOMER
SATISFACTION
Submitted by
Muhammad Usman Awan
in accordance with the requirement for the degree of
Doctor of Philosophy
Supervisor: Prof. Dr. Abdul Raouf Co-Supervisor: Prof. Dr. Niaz Ahmad Akhtar
(May 2008)
Institute of Quality and Technology Management Faculty of Engineering and Technology
Quaid-e-Azam campus, University of the Punjab Lahore - Pakistan
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THIS RESEARCH WORK HAS BEEN DONE IN COLLABORATION WITH
INSTITUTE FOR RETAIL STUDIES,
UNIVERSITY OF STIRLING, UK.
FOCAL PERSON FOR THIS COLLABORATION WAS PROFESSOR DR. LEIGH SPARKS
HIS CONTACT DETAILS ARE
Prof. Dr. Leigh Sparks Institute for Retail Studies
University of Stirling FK9 4LA, Stirling UK
0044 1786 467384 [email protected]
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CERTIFICATE
This is to certify that the research work described in this thesis is the original work
of the author and has been carried out under our direct supervision. We have
personally gone through all the literature review, data and results reported in this
manuscript and certify their authenticity. We further certify that the material
included in this thesis have not been used in part or full in a manuscript already
submitted or in the process of submission in partial / complete fulfillment of the
award of any other degree from University of the Punjab or any other institution.
We also certify that the thesis has been prepared according to the prescribed format
of University of the Punjab and we endorse its evaluation for the award of Ph.D.
degree through the official procedures of the University of the Punjab.
Prof. Dr. Abdul Raouf (Supervisor)
Sitara-e-Imtiaz Distinguished National Professor of HEC
Patron Institute of Quality and Technology Management
University of the Punjab
Prof. Dr. Niaz Ahmad Akhtar (Co-Supervisor)
Director Institute of Quality and Technology Management
University of the Punjab
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SUMMARY
There are two major concerns associated with customer satisfaction for companies
competing in present era of intense global competition. Companies have to increase
customer satisfaction by incorporating quality management in their strategic and long
term corporate plans. Similarly satisfaction of each member of the supply chain has to be
increased by developing closer partnership type arrangements (Christopher and Lee,
2004). In the development of such partnership type arrangements, service quality is an
important tool because the relationship of service quality with improved supply chain
performance is widely accepted (Mentzer et al., 1999, 2001; Perry and Sohal, 1999).
TQM is customer satisfaction based management philosophy. Previous studies in TQM
can be categorized along several main research objectives. These include identifying
critical TQM factors, examining issues and / or barriers in the implementation of TQM
and investigating the link between TQM factors and performance (Sebastianelli and
Tamimi, 2003). The objective of this research is related to the identification of TQM
critical success factors and then its relationship to customer satisfaction so the literature
related to TQM critical success factors and customer satisfaction is reviewed in detail in
this dissertation. It has also been concluded in this dissertation that service quality is an
antecedent of customer satisfaction.
However most of the previous research in TQM and service quality is based in developed
countries. This research is an effort to reduce the existing gap of developing countries
based TQM and service quality studies. The research is divided into two sections. In first
section, survey questionnaire obtained from 51 pharmaceutical distributors is used to
identify critical success factors of TQM. Relationship of TQM implementation to
customer satisfaction is also developed in this portion of research. Second portion of
research is related to development of service quality scale in distributors-retailers
interface of pharmaceutical supply chains. Data collected from 413 respondents was
analyzed. Structural equation modeling using AMOS 7.0 software developed a valid and
reliable scale comprising of 4 dimensions and 10 items. This research has practical
implications for pharmaceutical distribution companies as it identifies that top
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management has to increase its commitment for the implementation of TQM. Research
also develops a reliable and valid scale that can be used by to increase service quality in
distributors-retailers interface of pharmaceutical supply chains in Pakistan.
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DEDICATED TO
My Parents (Zahoor-ud-din and Shahida Bano), Wife
(Rizwana) and Daughter (Maryam)
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ACKNOWLEDGEMENTS All praises are for Allah Almighty, who created human beings and gave knowledge, and
provided me an opportunity to complete this research work for my Ph.D. studies.
I am grateful to my Supervisors, Prof. Dr. Abdul Raouf and Prof. Dr. Niaz Ahmad; as
without their kind guidance throughout this project, it was not possible for me to
complete it in stipulated time.
Special thanks and appreciation to Prof. Dr. Leigh Sparks, Institute for Retail Studies,
University of Stirling, UK for providing me intellectual guidance during my one year stay
at University of Stirling. Prof. Sparks not only guided me in analyzing the experimental
data but also spent a lot of time in brushing up all chapters of my dissertation. Prof.
Sparks provided me an opportunity to work with other Ph.D. students at University of
Stirling. I am highly indebted to Mr. Abraham Brown (a Ph.D. student at University of
Stirling) for helping me about the various statistical soft-wares used in my research. Mr.
Andrew Paddision (a senior lecturer at University of Stirling) helped me a lot when I was
writing the methodology chapter.
I really acknowledge the support of my friends Mr. Atif Shahbaz (Lecturer in Physics,
Government College University, Lahore) and Syed Atif Raza (Assistant Professor in
College of Pharmacy, University of the Punjab, Lahore) who encouraged me to enter in
Ph.D. program. Thanks are also due to my teachers who taught the Ph.D. course work. I
can not forget the time I passed with my beloved Ph.D. class fellow Colonel (retd) Latif
Aleem (late). May his soul rest in heaven (Amin). Colonel Aleem I really miss you a lot.
I particularly wish to thank Mr. Thomas Josef Steffen from Ms Schering Asia GmBH,
Mr. Najeeb-ur-rehman from Ms Muller and Phipps Pakistan and Mr. Tariq from Ms
Paramount distributors. It was not possible for me to complete field work of my research
with out their generous support. I would also like to acknowledge Mr. Muhammad
Khalid Khan, Mr. Muhammad Asif, Mr. Muhammad Abid Umer, Mr. Moazam Javed and
Mr. Muhammad Isteqar (staff members of my University) for their efforts and help,
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which they provided me during my research work. Financial support from Higher
Education Commission, Government of Pakistan during the whole period of my Ph.D.
study is also highly acknowledged.
Last, but certainly not least, I would like to thank my family members. My parents pray
for me at each step in my life and allowed me to stay one year away from my home (at
University of Stirling, UK) for the first time in my life. My wife promised me four years
ago when we married that she would always “support my endeavours” and time since
than has been proof of her commitment.
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ABBREVIATIONS
Total Quality Management TQM
Will Expectation WE
Should Expectation SE
Delivered Service DS
Perceived Service PS
Overall Perceived Service OSQ
Behavioral Intentions BI
Analysis of Moment Structure AMOS
Linear Structural Relations LISREL
Confirmatory Factor Analysis CFA
Comparative Fit Index CFI
Root Mean Square Error of Approximation RMSEA
Goodness of Fit Index GFI
Normed Fit Index NFI
Top Management Support TMS
Strategic Planning Process in Quality Management SPPQM
Quality Information Availability and Usage QIAU
Employee Training ET
Employee Involvement EI
Process Design PD
Supplier Quality SQ
Customer Orientation CFS
Bench Marking BM
Results of Implementing Quality Management RIQM
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TABLE OF CONTENTS
TITLE Page No.
CHAPTER 1 - INTRODUCTION 14 - 19 1.1. Research Problem 14 1.2. Purpose of the research 15 1.3. Significance of this Research 16 1.4. Structure of the thesis 18CHAPTER 2 – TQM, CUSTOMER SATISFACTION AND SERVICE QUALITY
20 - 39
2.1. Total Quality Management (TQM) 20 2.2. Critical Success Factors of TQM 22 2.2.1. TQM in Developing Countries 25 2.3. Customer Satisfaction 28 2.4. Service Quality 31 2.4.1 Models of Service Quality 31 2.5. Summary of the Chapter 38CHAPTER 3 – SERVICE QUALITY DIMENSIONS AND SERVICE QUALITY IN SUPPLY CHAINS
40 – 51
3.1. Service Quality Dimensions 40 3.2. Service Quality in Supply Chains 45 3.3. Pharmaceutical Sector of Pakistan 48 3.4. Summary of the Chapter 50CHAPTER 4 – METHODOLOGY 52 – 70 4.1. Research Questions 52
4.2. Research Strategy and Data Collection Methods 53 4.3. Selection and Refinement of the Questionnaires 57
4.3.1. Selection and Refinement of the Questionnaire (Research Questions 1 and 2)
57
4.3.1.1. Development of Theoretical Framework for Analysis
62
4.3.1.2. Sampling 654.3.2. Selection and Refinement of the Questionnaire (Research
Question 3) 66
4.3.2.1. Development of Theoretical Framework for Analysis
68
4.3.2.2 Sampling 70CHAPTER 5 – ANALYSIS OF TQM SURVEY QUESTIONNAIRE 71 - 86 5.1. Scale Purification 71 5.2. Correlation Analysis 78 5.3. Regression Analysis 80 5.3.1. Regression when CFS is Dependent Variable 81 5.3.1.1. Stepwise Regression when CFS is Dependent 82
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Variable 5.3.1.2. Summary of results when CFS is Dependent Variable
83
5.3.2. Regression when RIQM is Dependent Variable 845.3.2.1. Stepwise Regression when RIQM is Dependent
Variable 85
5.3.2.2. Summary of Result when RIQM is Dependent Variable
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CHAPTER 6 – ANALYSIS OF SERVICE QUALITY SURVEY QUESTIONNAIRE
87– 93
6.1. Scale Purification 87CHAPTER 7 – DISCUSSION AND CONCLUSION 94– 98 7.1. Discussion / Conclusion of TQM Survey Questionnaire Results 94
7.2. Discussion / Conclusion of Service Quality Survey Questionnaire Results
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7.3. Limitation and Suggestions for Future Research 97REFERENCES 99-109 APPENDICES 110-119 Appendix A: Rao et al., (1999) Questionnaire 110 Appendix B: Refined (TQM) Questionnaire Used in this Research 113 Appendix C: Cover Letter Send to Pharmaceutical Distributors 115 Appendix D: Parasuraman et al., (1988) Service Quality Dimensions and Items
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Appendix E: Service Quality Questionnaire Items (Along with Dimensions and Abbreviations used in Analysis)
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Appendix F: Cover Letter Send to Pharmaceutical Retailers 119
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LIST OF FIGURES Title Page No. Figure 1.1 Structure of the thesis 19 Figure 2.1 Components of TQM philosophy and their
interrelationships 21
Figure 2.2 The Gronroos service quality model 32 Figure 2.3 Parasuraman et al., (1985) Service Quality Model 34 Figure 2.4 Parasuraman et al., (1988) Servqual Model 35 Figure 2.5 Boulding et al., (1993) A Dynamic Process of Service
Quality 37
Figure 2.6 Zeithaml et al., (1996) The Behavioral and Financial Consequences of Service Quality
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Figure 3.1 Supply Chains Process Quality Model 45 Figure 4.1 Theoretical Framework for Regression Analysis on
Dependent Variable (CFS) 64
Figure 4.2 Theoretical Framework for Regression Analysis on Dependent Variable (RIQM)
65
Figure 4.3 Theoretical Framework for Development of Service Quality Scale
69
Figure 5.1 Framework for CFS 83 Figure 5.2 Framework for RIQM 86 Figure 6.1 CFA Model Development Using AMOS 7.0 89
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LIST OF TABLES
Title Page No. Table 1 Components of Various TQM Evaluation Models 22 Table 2 25 TQM critical success factors extracted from survey
based research 23
Table 3 14 “Vital Few” TQM Factors 24 Table 4 Attributes of Service Quality 43 Table 5 Comparison of Various TQM Measurement Instruments 58 Table 6 Comparison of RAO et al., (1999) Questionnaire and
Refined Questionnaire 62
Table 7 Summary of Goodness of Fit Statistics for Confirmatory Factor Analysis (CFA)
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Table 8 Reliability Analysis 76 Table 9 Item to Total Correlations 76 Table 10 Convergent and Discriminant Validity 78 Table 11 Correlation Among all Variables 79 Table 12 Correlation Among Variables Excluding CFS 80 Table 13 Variables Entered / Removed (b) 81 Table 14 Model Summary 81 Table 15 ANOVA (b) 81 Table 16 Coefficients (a) 81 Table 17 Variables Entered / Removed (a) 82 Table 18 Model Summary 82 Table 19 ANOVA (b) 82 Table 20 Coefficients (a) 82 Table 21 Variables Entered / Removed (b) 84 Table 22 Model Summary 84 Table 23 ANOVA (b) 84 Table 24 Coefficients (a) 84 Table 25 Variables Entered / Removed (a) 85 Table 26 Model Summary 85 Table 27 ANOVA (b) 85 Table 28 Coefficients (a) 85 Table 29 Sequence Wise List of Deleted Items 88 Table 30 Reliability Analysis 90 Table 31 Item to Total Correlations 91 Table 32 Correlation Among all Dimensions Emerged 92 Table 33 Dimensions and Items Constituting the Developed Scale 93
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CHAPTER 1 - INTRODUCTION
The inspiration for this research comes from my previous experiences. As quality
management officer in a pharmaceutical company, I was responsible for implementing
quality management principles of parent company Ms Schering AG, Germany in a
pharmaceutical company located in Lahore - Pakistan. I always realized that because of
culture, level of technical advancement, national corporate business practices, state
legislation and many other factors, “one size does not fit all” so it was not possible to
implement quality management practices exactly in a way these were implemented in Ms
Schering AG, Germany. Later, my experience as lecturer at University of the Punjab
developed my interest in the subject of supply chain management. The blend of these
experiences focused my attention on quality management in pharmaceutical supply
chains. Preliminary literature review gave me marvelous knowledge about both these
subjects (quality management and supply chain management). However I realized that in
both subjects there is little work done in context of developing countries. This research is
an effort to reduce this gap in addition to provide an insight to pharmaceutical
distribution companies about TQM implementation and to satisfy their customers by
providing better service quality. This chapter introduces the problem, purpose and
significance of the research. At the end of the chapter is summary of the arrangement of
the thesis.
1.1: RESEARCH PROBLEM
Quality is a prerequisite for the survival of any business and firms should continuously
aim to delight customers (Khamalah and Lingaraj, 2007). TQM development is the result
of this intense global competition and companies with international trade and global
competition have paid considerable attention to TQM philosophies, procedures, tools and
techniques (Mahour, 2006). Karuppusami and Gandinathan (2006) have defined TQM as
an integrative management philosophy aimed at continuously improving quality and
process to achieve customer satisfaction. The TQM studies have been carried out in three
different ways: contributions from quality leaders (e.g. Crosby, Deming, Ishikawa, Juran
and Feigenbaum), formal evaluation models e.g. European Quality Award (EQA),
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Malcolm Baldrige National Quality Award (MBNQA), the Deming Award and empirical
research (Claver et al. 2003). However according to Rao et al., (1997) and Al-Khalifa
and Aspinwall (2000), most TQM studies have focused on organizations in developed
countries and there is lack of information about the nature and stage of TQM
implementation in developing countries. Thiagarajan et al. (2001) argue that the scant
attention given to research in the developed nations, complicated by the acknowledged
limitations of transferring research findings across national boundaries, has made efforts
to learn and transfer empirically sound knowledge to developing economies all the more
difficult. It is important therefore to create specific TQM knowledge focused on the
particular requirements of developing countries. This research is an attempt to remedy a
small part of this lack of information about TQM implementation in developing
countries. This research also reduces the existing lack of supply chain specific service
quality studies. The objective of this research is therefore twofold. Firstly, there is a
question on the relationship of TQM to customer satisfaction in pharmaceutical
distribution companies in Pakistan (a developing country). This portion of research also
identifies critical success factors of TQM in pharmaceutical distribution companies in
Pakistan. Second portion of the research is about the development of service quality scale
in distributors-retailers interface of pharmaceutical supply chains in Pakistan.
1.2: PURPOSE OF THE RESEARCH
The purpose of this research is to develop pharmaceutical distribution model for customer
satisfaction. This can be achieved only by obtaining quantitative results from a sample of
both internal and external customers of pharmaceutical distribution companies.
Quantitative research questions related to the internal customers address the effect of
TQM practices on customer satisfaction. Subsequently, this portion of research attempts
to identify critical success factors of TQM implementation in pharmaceutical distribution
companies. The research questions related to the internal customers for this research are
therefore:
1) Does TQM implementation relate directly to the customer satisfaction in
pharmaceutical distribution companies in Pakistan?
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2) What are the critical success factors of TQM in pharmaceutical distribution
companies in Pakistan?
Pharmaceutical retailers are the external customers of pharmaceutical distribution
companies so it is important for pharmaceutical distribution companies to know that how
they can satisfy them. This can be done by knowing:
3) Which are the important service quality dimensions and items in the distributors-
retailers interface of pharmaceutical supply chains in Pakistan?
1.3: SIGNIFICANCE OF THIS RESEARCH
Most of the TQM related research cited in the literature is based on research in developed
countries (Rao et al. 1999). Quality gurus presented their ideas on the basis of their
individual experiences in developed countries. Formal evaluation models of TQM are
developed for companies operating primarily in the United States of America, Europe
and Japan. The demand for TQM can however no longer be the prerogative of the
developed world only. Some of the developing countries are breaking through traditional
trade barriers and open their markets to international competitors (Temtime and Solomon,
2002). TQM is thus becoming more significant in developing countries also. There is still
lack of information however about the nature and stage of implementation of TQM in
countries in some largely developing regions of the world including Asia, South America,
Africa and the Middle East (Sila and Ebrahimpour, 2003). The first aim of this research
is to reduce this lack of information about TQM in developing countries.
It is also the fact that in today’s global marketplace, individual firms no longer compete
as independent entities but compete as an integral part of supply chain links (Seth et al.
2006). Christopher (1992) also argued that a key aspect of business is that supply chains
compete, not companies. According to Waters (2003), organizations do not work in
isolation; they act as a customer when buy materials from their own suppliers and act as a
supplier when they deliver materials to their own customers. A wholesaler for example
acts as a customer when buying goods from manufacturers, and then acts as a supplier
when selling goods to retailers. It is important to satisfy each member of the supply
chain. There is a change in the landscape of supply chain management in recent years and
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satisfaction of each member of the supply chain can be increased only by putting aside
the traditional arms-length relationship and by developing closer partnership type
arrangements (Christopher and Lee, 2004). In the development of such partnership type
arrangements, service quality is an important tool because the relationship of service
quality with improved supply chain performance is widely accepted (Mentzer et al.,
1999, 2001; Perry and Sohal, 1999). Regardless of this universal recognition for
realizing the importance of service quality in supply chains, it is little researched
(Nix, 2001). Most of the previous service quality research has been aimed at the end-use
customer (Faulds and Mangold, 1995; Perry and Sohal, 1999). There have been very few
studies on the development of service quality measurement scales in supply chains
(Beinstock et al. 1997; Mentzer et al. 1999, Rafele, 2004). These few studies are also
confined to specific sectors and are based in developed countries. Generalization of
findings of these studies in the global economy is not possible without further empirical
research (Rafele, 2004).
The second aim of this research is to reduce this research gap as this research is also
focused on service quality scale development at the distributors-retailers interface of
the pharmaceutical supply chains in a developing country. The author could find no
studies on the identification of critical success factors of TQM all sorts of companies in
Pakistan. Also little work has been done to examine the applicability of service quality
measurement scales to the service industries in developing countries (Jain and Gupta,
2004) and author of this thesis could find no studies on the development of supply chain
specific service quality measurement scale studies in any of the developing countries.
The pharmaceutical distribution sector was chosen as the object of the portion of research
related to TQM implementation because of its sectoral importance. No previous TQM
studies either in developed or developing countries appear to have focused on the
pharmaceutical distribution sector. Pharmaceutical supply chains are chosen as the object
of the portion of research related to service quality. Pharmaceutical supply chains also do
not appear in previous supply chains specific service quality measurement scale
development studies. The distributors-retailers interface is chosen as it has many non-
contractual dimensions in contrast to the manufacturers-distributors interface of supply
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chains, which is frequently characterized by contractual agreements (Mangold and
Faulds, 1993).
This research will therefore contribute significantly to reduce the existing lack of TQM
and service quality studies in developing countries. This research will develop customer
satisfaction model for pharmaceutical distribution companies keeping in view the
requirements of external customers. As TQM implementation also helps to increase
customer satisfaction, the research will identify the relation of TQM to customer
satisfaction in pharmaceutical distribution companies. Critical success factors for TQM
implementation in pharmaceutical distribution companies in Pakistan are also identified
in this research.
1.4: STRUCTURE OF THE THESIS
Introduction, literature review, methodology, findings, discussion and conclusion are
components of this thesis. The first section introduces the problem, purpose and
significance of this research. The second section includes two chapters that intend to scan
past researches. Literature review helps to clarify the research objectives and provides a
theoretical framework that facilitates to define research problems and questions in section
three. Both chapters in literature review section have very different themes but are
connected in order to generate the framework to develop pharmaceutical distribution
model for customer satisfaction. Chapter two examines the philosophy of TQM and its
relationship with customer satisfaction. Critical success factors of TQM and
implementation of TQM in developing countries are discussed in detail. An effort has
been made to understand what customer satisfaction really is and how it can be achieved
by improving service quality. Literature related to various service quality models is also
discussed in this chapter. Third chapter is about the literature related to service quality
dimensions and service quality in supply chains. Context of the research is also described
in chapter three. The methodology, which is the third section of the thesis, is in chapter
four. At the start of this chapter research problems are defined and research questions are
identified. Decisions on the research approach for both portions of research are also made
in this chapter. Fourth section includes two chapters i.e. chapter five and six. Chapter five
is about the findings obtained from the portion of research related to TQM
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implementation in pharmaceutical distribution companies. Findings obtained from the
portion of research related to development of service quality scale in distributors-retailers
interface of pharmaceutical supply chains is in chapter six. The eventual aim of chapter
seven (fifth section) is to bring the findings analyzed in chapter five and six to answer the
research questions of this research. In this chapter the implications of the research are
concluded, limitations of the research are presented and suggestions for future research
are made. The structure of this thesis is therefore close to the “linear-analytic structure”
proposed by Yin (1994) and can be illustrated as:
FIGURE 1.1: STRUCTURE OF THE THESIS
Section 1 Introduction
Chapter 1
Section 2 Literature Review
Chapter 2 – 3
Section 3 Methodology
Chapter 4
Section 4 Findings
Chapter 5 –6
Section 5 Discussion and conclusion
Chapter 7
References & Appendices
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CHAPTER 2 – TQM, CUSTOMER SATISFACTION AND SERVICE QUALITY
In this chapter the literature related to TQM, customer satisfaction and service quality is
reviewed in detail with the objective to explore the relationship between these three fields
of research. Section 2.1 identifies customer focus as the core component of TQM
philosophy. The primary research is based in a developing country (Pakistan) so literature
related to critical success factors of TQM in context of developing countries is discussed
in detail in section 2.2. Literature related to the concept of customer satisfaction is
reviewed in section 2.3. Because service quality is a major determinant of customer
satisfaction, service quality models constitute the major portion of section 2.4.
2.1: TOTAL QUALITY MANAGEMENT (TQM) In 1949 JUSE (Union of Japanese Scientists and Engineers) formed a committee of
scholars, engineers and government officials devoted to improve productivity and
postwar quality of life in Japan (Kanji, 1990). This step is historically considered as the
origin of TQM philosophy (Mahour 2006). This management philosophy was confined to
Japan until the early 1980s. It became international when previously unchallenged
American industries lost substantial market share in both American and world markets.
To regain the competitive edge, American companies began to adopt productivity
improvement programs, which had proven themselves successful in other developed
countries. One of these “improvement programs” was TQM. Since then, both the popular
press and academic journals have published a plethora of accounts describing both
successful and unsuccessful efforts at implementing TQM (Kaynak 2003).
According to Fynes and Voss (2002), one of the most problematic issues confronting
researchers in quality management is the search for an appropriate definition. There is no
consensus on the definition of TQM (Reed et al. 1996) as different people define it
differently. ISO 8402:1994 defines TQM as: “Management approach of an organization
centered on quality, based on the participation of all its members and aiming at long-term
success through customer satisfaction and benefits to all members of the organization and
to society”. Ugboro and Obeng (2000) also concluded that TQM is an approach used in
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directing organizational efforts toward the goal of customer satisfaction. Khan (2003)
proposed a philosophy of TQM on the basis of four tenets and suggested that the absolute
customer focus is the core component of TQM philosophy. Other tenets of this
philosophy are employee empowerment, involvement and development, continuous
improvement and use of systematic approach to management (figure 2.1). Figure 2.1
shows that absolute customer focus is the core component of TQM philosophy.
FIGURE 2.1: COMPONENTS OF TQM PHILOSOPHY AND THEIR
INTERRELATIONSHIPS
Source: Khan (2003) Previous studies in TQM can be categorized along several main research objectives.
These include identifying critical TQM factors, examining issues and / or barriers in the
implementation of TQM and investigating the link between TQM factors and
performance (Sebastianelli and Tamimi, 2003). The objective of this research is related to
the identification of TQM critical success factors and then its relationship to customer
EMPLOYEE EMPOWERMENT, INVOLVEMENT
AND DEVELOPMENT
ABSOLUTE CUSTOMER
FOCUS
CONTINUOUS IMPROVEMENT
USE OF SYSTEMATIC
APPROACH TO MANAGEMENT
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satisfaction so the literature related to TQM critical success factors and customer
satisfaction is reviewed in next sections (2.2 and 2.3). However because the research is
based in a developing country (Pakistan), problems in implementing TQM in developing
countries are also discussed (subsection 2.2.1).
2.2: CRITICAL SUCCESS FACTORS OF TQM Various studies have been carried out attempting to identify critical success factors of
TQM. They tend to emphasize three different areas (Tari, 2005; Claver et al., 2003) i.e.
contribution from quality leaders, formal evaluation models and empirical research. Dale
(1999) identifies management leadership, training, employee’s participation, process
management, planning and quality measures for continuous improvement as consistent
findings in the work of quality leaders such as Crosby, Deming, Juran, Ishikawa and
Feigenbaum. The Malcolm Baldrige National Quality Award (MBNQA), European
Quality Award (EQA) and Deming application prize are common formal TQM
evaluation models used in the United States of America, Europe and Japan respectively.
The main components of these awards are summarized in Table 1. Leadership is the top
component of two of these awards.
TABLE 1: COMPONENTS OF VARIOUS TQM EVALUATION MODELS MBNQA EQA Deming Application Prize
Leadership Strategic Planning Human resources - orientation Process management Information and -analysis Customer and market -focus Business results
Leadership Employee management Policy and strategy Alliances and resources Process management People results Customer results Society results Key results
Policies Organization Information Standardization Development and usage of human -resources Activities ensuring quality Activities for maintenance and control Activities for improvement, result and future plans
Source: Tari (2005) According to Karuppusami and Gandhinathan (2006), Sila and Ebrahimpour (2005) and
Sebastianelli and Tamimi (2003), the research by Saraph et al. (1989) was the first
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empirical research, which focused on the operationalization of TQM through the
identification of critical success factors. Since then the factors that determine success
and/or failure in TQM have attracted the attention of many researchers (Najeh and Kara-
Zaitri, 2007). Among these, studies by Sila and Ebrahimpour (2002, 2003), and
Karuppusami and Gandhinathan (2006) are significant because these researchers
summarize previous research in a systematic manner.
Sila and Ebrahimpour (2002) reviewed 347 survey based TQM studies published
between 1989 to 2000 and determined that during this period 76 studies in 23 countries
focused on the identification of TQM critical success factors. Sila and Ebrahimpour
(2002) used factor analysis to identify the 25 most commonly extracted TQM critical
success factors from these 76 studies. These factors are given in Table 2.
TABLE 2: 25 TQM CRITICAL SUCCESS FACTORS EXTRACTED FROM SURVEY BASED RESEARCH Sr. No. FACTORS
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20 21. 22. 23. 24.
Top management commitment Social responsibility Strategic planning Customer focus and satisfaction Quality information and performance Bench marking Human resources management Training Employee involvement Employee empowerment Employee satisfaction Team work Employee appraisal-rewards and recognition Process management Process control Product/service design Supplier management Continuous improvement Quality assurance Zero defects Quality culture Communication Quality systems Just-in-time
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Sr. No. FACTORS 25. Flexibility
Source: Sila snd Ebrahimpour (2002) Sila and Ebrahimpour (2003) extended their previous research and analyzed and
compared these 25 factors across studies in 23 countries. They found that top
management commitment was the critical success factor covered in each country
included in the research.
Karuppusami and Gandhinathan (2006) used 37 TQM scale development studies
published between 1989 and 2003 to identify 56 critical success factors of TQM. They
selected these studies because the reliability and validity of the critical success factors
were statistically tested during these studies. On the basis of Pareto analysis,
Karuppusami and Gandhinathan (2006) sorted these 56 critical success factors in
descending order and divided them into two groups entitled “vital few” and “useful
many”. In the “vital few” group 14 factors accounted for 80% of the critical success
factors of TQM while the remaining 42 “useful many” factors accounted for 20% of
occurrences frequency only. The 14 factors identified as the “vital few” are given in
Table 3. Karuppusami and Gandhinathan (2006) also confirmed the finding of Sila &
Ebrahimpour (2003) that top management commitment is the most critical success factor
for TQM.
TABLE 3: 14 “VITAL FEW” TQM FACTORS Sr. No. Factors
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.
Top management commitment Supplier management Process management Customer focus Training Employee relations Product / service design Quality data Role of quality department Human resource management and development Design and conformance Cross functional quality teams Bench marking
25
14. Information and analysis Source: Karuppusami and Gandhinathan (2006) This brief review of literature related to critical success factors of TQM therefore
suggests that top management / leadership support is overall the most common, important
and critical success factor in the implementation of TQM.
However most of the previous research in TQM cited in the review papers above is based
on research in developed countries. Quality gurus presented their ideas on the basis of
their individual experiences in developed countries. Formal evaluation models of TQM
are developed for companies operating primarily in the United States of America, Europe
and Japan. This research is based in a developing country (Pakistan) so it is essential to
identify the role of top management in previous TQM studies in developing countries.
Next subsection of this chapter is therefore about TQM implementation in developing
countries.
2.2.1: TQM IN DEVELOPING COUNTIRES Most of the developing countries have unique characteristics like lack of democracy,
instability, corruption, shortage of skilled labour force and raw materials, under
utilization of available production capacity, the inferiority and lack of quality standards,
high scrap, low purchasing power of customers, inadequate consumers know how, lack of
balance between import and export, foreign exchange constraints, incomplete
infrastructure etc. (Curry and Kadasah; 2002, Madu, 1997; Mersha, 1997) so the term
“poor quality” is synonymous with the products manufactured in these countries
(Mohanty and Lakhe, 2004). However, some of the developing countries are breaking
the traditional trade barriers and opening their markets to international competitors, so the
demand for quality can no longer be the prerogative of the developed world (Temtime
and Solomon, 2002). Speaking at Pakistan’s first convention on quality, quality guru
Crosby stated that nothing is more important to the prosperity of a developing nation than
quality. The only way a developing nation can increase its trade activities and develop a
sustainable basis is to improve the quality of its products and services (Djerdjour and
Patel, 2000).
26
According to Thiagarajan et al. (2001), while TQM in the West lacks theoretical support,
knowledge of in developing economies is almost totally lacking. The scant attention
given to research in the developed nations, confused by the acknowledged limitations of
most of the research findings across national boundaries, has made any efforts to readily
learn and transfer empirically sound knowledge to developing economies all the more
difficult. It is therefore, important to create TQM knowledge base keeping in view the
specific requirements of the developing countries as most of studies on quality
management practices have focused on developed countries only (Rao et al., 1997; Al-
Khalifa and Aspinwall, 2000) and there is still some lack of information about the nature
and stage of TQM implementation in some regions of the world such as Asia, South
America, Africa and the Middle East (Sila and Ebrahimpour, 2003). This research is an
attempt to reduce this lack of information about TQM implementation in developing
countries.
Mahour (2006) identified training and culture as two important barriers in implementing
TQM in developing countries. Literature review in the previous section concluded
that top management support is the critical success factor of TQM implementation
so in the following paragraphs these three factors (top management support,
employee training and culture are discussed with reference to developing countries.
Top management in developing countries is mostly not committed to quality initiatives
and is reluctant to delegate authority (Djerdjour and Patel, 2002). Studies (Al-Khalifah
and Aspinwall, 2000; Temtime and Solomon, 2002, Mersha, 1997) further indicate top
management support is the critical barrier in implementing TQM in developing countries.
Kaplinsky (1995) identifies reasons for lack of top management support for TQM in
developing countries and conclude that in developing countries, many enterprises are
family-owned and corporate growth and effective management are constrained by the
reluctance of the family to devolve responsibility to professionally trained outsiders.
A second critical barrier in implementation of TQM in developing countries is a cultural
change. Bruun and Mefford (1996) recommend that TQM programs in developing
27
countries should be accompanied by changes in organizational culture as programs that
are highly successful in the industrialized developed countries often fail in the developing
countries because these programs are uncritically adopted without any regard to their
congruence with the internal work culture of developing countries (Mendonca and
Kanungo, 1996). Yong and Wilkinson (1999) examine cultural issue with in the quality
management context from a human resource perspective and argue that “ Even in
culturally homogenous societies, the issue of cultural change plays a key role in
determining the success of quality management implementation, but because of the
competitive push for the adoption of TQM and the pervasiveness of prescriptive market
driven consultancy packages, managers have already neglected to tailor quality initiatives
to suit their own organizational cultures. Madu (1997) argues that as multinational
corporations have adopted strategies that work well with in the confines of developing
economies cultures, developing countries have to tailor quality management practices
according to their own culture, as issue is not whether quality management practices
should be adopted but how to implement these practices.
Another important concern about TQM implementation in developing Islamic countries
like Pakistan is that TQM is alien, not relevant to Islamic cultural and religious norms.
Khan (2001) criticizes those who advocate this judgment and argues that there are several
Ahadis (sayings of Prophet Muhammad P.B.U.H.) relating to ‘selling of goods,’ which
highlight the responsibility of the seller to explain all the shortcomings of the product
explicitly so as to adjust the buyer’s expectations to the appropriate level. After a clear
understanding of all the weaknesses of the product, when the buyer experiences the actual
product, he would, at the minimum, be satisfied if not delighted. Islamic norms of
business transactions insist on ensuring customer satisfaction that is also the core
component of the TQM philosophy. Therefore, it is incorrect to say that the TQM
philosophy is alien to Islamic cultural or religious norms and that it would not be
applicable in an Islamic country like Pakistan.
The third important factor affecting systemic adoption of TQM is employee training and
education as TQM demands a high degree of involvement of all employees and this
requires that all employees in the firm receive enough education and training (Gonzalez
28
and Guillen, 2002). According to Madu (1997), if the people of developing economies
are better trained and educated, they will be more able to contribute to planning their
future and the future of their companies but training infrastructure in these countries is
frequently underdeveloped and teaching techniques are still modeled on the now-outdated
managerial practices of mass production (Kaplinsky, 1995).
The important question is who can effectively change the culture and allocate sufficient
resources for employee education and training? Implementing quality management
requires a change of organizational culture and effective leadership is needed to be able
to transform the organization in a way that change may become acceptable. Similarly in
the perspective of culture, it is the responsibility of management to develop training
programs and enrich the knowledge of workers to understand the need for behavioral
modifications in order to adopt quality management (Madu, 1997). Therefore it may be
concluded that if top management is working effectively, other barriers in the
implementation can be over come and lack of top management support is the major
barrier in implementation of TQM in developing countries. This conclusion fortifies the
conclusion drawn in section 2.2.1 that top management support is the most critical
success factor of TQM.
2.3: CUSTOMER SATISFACTION The word “satisfaction” is formed combining Latin words satis (enough) and facere (to
do or make) (Rust et al. 1996). Since the mid-1980s, when quality management became a
widely practiced way to improve product quality, reduce costs and improve customer
service, the issue of customer satisfaction has brought about a great deal of ongoing
debate (Gustafsson and Johnson, 2004; Wirtz and Lee, 2003).
The definition of satisfaction also shows a strong heterogeneity (Florence et al. 2006).
Different authors have defined satisfaction in different ways but Giese and Cote (2000)
found that three overall components within virtually every definition of satisfaction might
be identified as these capture the specifics of the concept. These components are
* A response (affective or cognitive).
29
* The response concerns a particular focus (e.g. expectations, product and
consumption experience).
* The response takes place at a particular point in time (e.g. after choice, after
transaction, after consumption, based on accumulated experience).
The primary thread of debate in the satisfaction literature nowadays is focused on the
nature of the cognitive and affective processes that result in the consumer’s state of mind
referenced to as satisfaction (Jaronski, 2004). The cognitive dimension is the set of
information individuals accumulate through direct or indirect experience where as the
affective dimension is positive or negative evaluation (Florence et al. 2006). According
to this stream of satisfaction research, Yi (1991) categorized customer satisfaction
definitions either as an evaluation process or as an outcome of evaluation process. Oliver
(1981), Yi (1991) and Fornell (1992) describe satisfaction as an evaluation process where
as Tse and Wilton (1988) describes satisfaction as an outcome of evaluation process.
Satisfaction as an evaluation process is based on the disconfirmation of expectations
paradigm. Consumers form expectations towards product/service performance and these
expectations later serve as standards against which actual product/service performance is
evaluated (Oliver, 1980; Churchill and Suprenant, 1982) so it is actually the comparison
of expectations and actual perceived performance that results either in confirmation or
disconfirmation. If expectations are met, confirmation takes place, otherwise
disconfirmation occurs. Disconfirmation may be positive (when perceptions exceed
expectations) or negative (when expectations exceed perceptions). Therefore satisfaction
is the result of confirmation and positive disconfirmation where as negative
disconfirmation guides to dissatisfaction. Use of the term “positive disconfirmation” was
confusing so Anderson and Sullivan (1993) adopted the term “affirmation” as a substitute
for the term “positive disconfirmation”.
The framework of customer satisfaction as an outcome of an evaluation process is based
on the satisfaction as states the paradigm developed by Oliver (1989). Oliver (1997) also
found that satisfaction relates to pleasurable emotions, those approaching excitement or
delight and tending toward contentment and relaxation; whereas dissatisfaction relates to
30
unpleasant, disappointing and angering emotions. Zeithaml and Bitner (2000) found that
satisfaction is related to relief. Studies by Folkes et al. (1987), Mooradian and Oliver
(1995) also investigated the relationship between satisfaction and emotion. These studies
documented that satisfaction is clearly related to affective evaluations and affective
evaluations are antecedents to satisfaction. Although cognitive states have some
influence on satisfaction, the concept is strongly related to affective states, or emotions
(Wicks, 2004).
Practically all research on customer satisfaction agrees that customer satisfaction is a key
component of economic success (Horvath, 2001). There are two different types of
evaluations of customer satisfaction from the economic psychology perspective. One is
transaction-specific satisfaction and the other is cumulative satisfaction (Johnson et al.,
1995). Satisfaction that occurs strictly at time of the service delivery is referred to as
transaction-specific satisfaction (Parasuraman et al., 1988; Bitner, 1990) whereas
cumulative satisfaction approach defines satisfaction as customer’s overall experience to
date with a product or service provider (Johnson and Fornell, 1991). Fornell et al. (1996)
argue that the cumulative satisfaction construct is better able to predict subsequent
behaviors and economic performance over a more transaction specific view because
customers make repurchase evaluations and decisions based on their purchase and
consumption experience to date, not just a particular transaction or episode (Johnson et
al., 2001).
The review of literature in this section concludes that satisfaction is mainly influenced by
affective states (emotions) and cumulative satisfaction has more vital role in economic
success of the companies as compared to the transaction specific satisfaction. The next
question is how to measure customer satisfaction?
Many experts concur that the most powerful competitive trend currently shaping
marketing and business strategy is service quality (Abdullah, 2006) because of its
apparent relationship to customer satisfaction (Bolton and Drew, 1991a). It has been a
long-standing debate in the literature whether service quality is an antecedent for
satisfaction or vice versa. Bitner (1990) and Bolton and Drew (1991b) suggest that
31
satisfaction is an antecedent of service quality. Zeithaml et al. (1993) used both terms as
synonymous because both use expectations and perceptions as key antecedent constructs
and both are related to the behavioral intentions, which affect financial success of the
business organizations. De Ryter et al. (1997) merged the concepts of service quality and
satisfaction in an integrative model and tested the model empirically. This model
concluded that satisfaction should be treated as a superordinate construct to service
quality as higher levels of service quality results in increased satisfaction. In this
research, the determinants of service quality are used as antecedents of customer
satisfaction. The following section therefore reviews literature about what service quality
is and how various authors conceptualize service quality concept.
2.4: SERVICE QUALITY Service quality has been a frequently studied topic in service marketing literature (Su et
al., 2008). Various definitions of service quality have been proposed in the past (Jain and
Gupta, 2004) although it is an elusive and abstract construct that is difficult to define and
measure (Cronin and Taylor, 1992). Different authors have defined it differently but most
widely accepted definitions are those proposed by Parasuraman et al., (1988) and Cronin
and Taylor (1992). Parasuraman et al., (1988) define service quality as the difference
between what the customer feels that a service provider should offer and his perception of
what the service provider actually offers. However Cronin and Taylor (1992) argue that
only perceptions of performance derive service quality and expectations have no value in
calculating service quality. The objective of literature review in subsection 2.3.1 is to
relate concept of service quality to financial success of the company via customer
satisfaction.
2.4.1: MODELS OF SERVICE QUALITY The model presented by Gronroos (1984) is considered as the first service quality model
(Wicks, 2004). In this model the author identified technical quality, functional quality
and image as dimensions of service quality (figure 2.2). Technical quality is defined as
“what the consumer receives as a result of interactions with a service firm” and functional
quality just “the way in which the technical quality is transferred” where as image is built
32
up by both technical and functional quality of service. Gronroos concluded that to
manage service quality, there must be no gap between the expected service and the
perceived service so the Gronroos also used the “Disconfirmation paradigm” used by
Oliver in 1980 in his classic model of customer satisfaction.
FIGURE 2.2: THE GRONROOS SERVICE QUALITY MODEL
On the foundations of model proposed by Gronroos, Parasuraman et al., (1985)
developed the gap model (figure 2.3) to measure the elements of service quality.
The various gaps envisaged in this Parasuraman et al., (1985) model (figure 2.3) are: Gap 1: Difference between consumers’ expectation and management’s perceptions of
those expectations, i.e. not knowing what consumers expect.
Gap 2: Difference between management’s perceptions of consumer’s expectations and
service quality specifications, i.e. improper service-quality standards.
Gap 3: Difference between service quality specifications and service actually delivered
i.e. the service performance gap.
Gap 4: Difference between service delivery and the communications to consumers about
service delivery, i.e. whether promises match delivery?
Perceived Service
Image
Technical Quality
Functional Quality
Expected Service
Perceived Service Quality
33
Gap 5: Difference between consumer’s expectation and perceived service. This gap
depends on size and direction of the above-mentioned four gaps. This gap constitutes the
theoretical basis of this gap model (commonly called SERVQUAL model) and states:
“The quality that a consumer perceives in a service is a function of the magnitude and
direction of the gap between expected service and perceived service” and mathematically
can be expressed as:
( )ijij
kj EPSQ −=∑= =1
where:
SQ = Overall service quality
k = number of attributes.
Pij = Performance perception of stimulus i with respect to attribute j.
Eij = Service quality expectation for attribute j that is the relevant norm for stimulus i.
34
FIGURE 2.3: PARASURAMAN ET AL., (1985) SERVICE QUALITY MODEL
Parasuraman et al., (1985) recognized reliability, responsiveness, competence, access,
courtesy, communication, credibility, security, understanding/knowing the customer and
tangibles as determinants of service quality. Subsequent work by Parasuraman et al.,
(1988) merged these determinants into the five-component 22-item scale known as
SERVQUAL (figure 2.4) on the basis of factor analysis (Cronin and Taylor, 1992).
Reliability, responsive and tangibles were retained as such as identified in 1985 whereas
communication, competence, credibility, courtesy and security merged as a construct
Word of Mouth Communications Personal Needs
Past Experience
Expected Service
Perceived Service
Service Delivery (including pre- and post-contacts)
Translation of Perceptions into Service
Quality Specs.
Management Perceptions of Consumer Expectations
External Communications to
Consumers
GAP5
GAP4
GAP3
GAP1
GAP2
CONSUMER
MARKETER
35
“assurance” where as access and understanding/knowing the customer merged to form
the construct empathy.
FIGURE 2.4: PARASURAMAN ET AL., (1988) SERVQUAL MODEL
Source: Cronin and Taylor (1992) Parasuraman et al., (1988) described these five dimensions as follow: Tangibility: Appearance of physical facilities, equipment and communication material
Reliability: Ability to perform the promised service dependably and accurately
Responsiveness: Willingness to help customers and provide prompt service
Assurance: Knowledge and courtesy of the employees and their ability to convey trust
and confidence
Empathy: The caring and individualized attention, organization provides to its customers
For a number of years, the dominant operationalization of service quality has been
Parasuraman et al., (1988) SERVQUAL scale. The foundation of the measure rested on
the authors suggestion that service quality should be represented as the difference, or
‘‘gap,’’ between service expectations and actual service performance (i.e., the
disconfirmation paradigm) but Cronin and Taylor (1992) argue that, if service quality is
Reliability Responsiveness
Assurance Empathy
Perceived Service Quality
Tangibles
X1 X2 X3 X4 X10 X11 X12 X13 X14 X15 X16 X17 X5 X6 X7 X8 X9 X18 X19 X20 X21 X22
36
to be considered ‘‘similar to an attitude,’’ as proposed by Parasuraman et al., (1985,
1988), its operationalization could be better represented by an attitude-based
conceptualization. Therefore, they proposed that the expectations scale be discarded in
favor of a performance-only measure of service quality that they term SERVPERF
(Brady et al., 2002).
ijkj PSQ 1=∑=
where:
SQ = Overall service quality
k = number of attributes.
Pij = Performance perception of stimulus i with respect to attribute j.
The use of performance-only measures is suggested by a number of other studies
(Babakus and Boller, 1992; Boulding et al., 1993) though still there is no consensus that
which of the two scales (SERVQUAL or SERVPERF) is more suitable for service
quality measurement (Jain and Gupta, 2004).
Another major strategic implication in Parasuraman et al., (1988) model was proposed by
Boulding et al., (1993). Boulding et al., (1993) reported that firms can try either to
increase perceptions or lower expectations in their quest to increase overall service
quality. Boulding et al., (1993) concluded that although expectations directly do not
affect service quality, it does not mean that they have no effect at all. Boulding et al.,
(1993) classified expectations as “will expectations” (WE) and “should expectations”
(SE) and recommended that firms should manage customers “will expectations” (WE) up
and “should expectations” (SE) down if they want to increase customer perceptions of
overall service quality.
The second important contribution of Boulding et al., (1993) model is to link service
quality to behavioral intentions. Overall perceived service (OSQ)------Behavioral
intentions (BI) link of this model propose that overall perceived service quality is related
to the behavioral intentions of the customers.
37
FIGURE 2.5: BOULDING ET AL., (1993) A DYNAMIC PROCESS MODEL OF
SERVICE QUALITY
In this model WE = Will Expectation, SE = Should Expectation, DS = Delivered Service
PS = Perceived Service
OSQ = Overall Perceived Service
BI = Behavioral Intentions
Bitner (1990), Bolton and Drew (1991a,b), Cronin and Taylor (1994) and Venetis and
Ghauri (2004) also find that service quality has a positive impact on customer’s
behavioral intentions. Zeithaml et al., (1996) supported this relationship of perceived
service quality to behavioral intentions and concluded that behavior of the customers has
direct influence on the financial health of the company as service excellence enhances
customers’ inclination to buy again, to buy more, to become less price sensitive and to
tell others about their positive experiences. The model (figure 2.6) proposed by Zeithaml
et al., (1996) suggests that when service quality is superior, behavioral intentions of the
customers are favorable and thus customers are retained. This customer retention results
in financial gains and the case is vice versa when service quality is inferior as behavioral
intentions are unfavorable and customers defect from the company.
WE
SE
DS
PS OSQ BI
38
FIGURE 2.6: (ZEITHAML ET AL., 1996) THE BEHAVIORAL AND FINANCIAL CONSEQUENCES OF SERVICE QUALITY
The review of models proposed by Gronroos (1984), Parasuraman et al., (1985,1988),
Boulding et al., (1993) and Zeithaml et al., (1996) in this section strengthens the
relationship of service quality to the behavioral intentions of the customers and financial
gains for the business organizations.
2.5: SUMMARY OF THE CHAPTER In this chapter the literature related to TQM, customer satisfaction and service quality is
reviewed in a systematic order. The chapter starts with brief history of the TQM. Review
of TQM literature suggests that absolute customer focus is the core component of TQM
philosophy. Available literature suggests that top management support is one of the most
critical success factors of TQM, however in developing countries mostly top management
is not committed to TQM implementation. This research will recheck this finding.
Though there is significant heterogeneity in defining customer satisfaction, it has been
concluded that affective processes are the main antecedents of satisfaction and from the
economic psychology perspective, cumulative satisfaction is more important.
Relationship between customer satisfaction and service quality is established in which
service quality is an ancestor of customer satisfaction. Various models of service quality
are presented in section 2.3. This section suggests that service quality relates to the
Favorable
BEHAVIORAL INTENTIONS
SERVICE QUALITY
Superior
Inferior
Remain
BEHAVIOR
Defect
+$ Ongoing Revenue
Increased Spending Price Premium
Referred Customers
FINANCIAL CONSEQUENCES
– $ Decreased Spending
Lost Customers Costs to Attract New
Customers
Unfavorable
39
behavioral intentions and favorable behavioral intentions are must for financial success of
the firms. This means higher the service quality; higher are the chances of financial
success because of increased customer satisfaction.
40
CHAPTER 3 - SERVICE QUALITY DIMENSIONS AND SERVICE QUALITY IN SUPPLY CHAINS
In the chapter two, it is concluded that TQM is a management philosophy based on
customer satisfaction and that an increase in service quality directly effects customer
satisfaction. This conceptual and empirical link of service quality to customer satisfaction
has turned service quality into a core-marketing instrument (Venetis and Ghauri, 2004).
Curiosity over the measurement of service quality is therefore high and researchers have
devoted a great deal of attention to service quality research (Abdullah, 2006).
Johnston (1995) categorizes service quality studies into five major debates. First there is
debate over similarities and differences between the constructs of service quality and
customer satisfaction. The second debate is about the worth of the expectation-perception
gap view of service quality. Thirdly there is concern with the development of models that
help understanding of how the perception gap arises and how managers can minimize its
effects. Fourthly the definition and use of “zone of tolerance” in service quality is
debated. Finally the identification of dimensions of service quality is critical. The
research intention of this research is related to this fifth debate because according to
Chowdhary and Prakash (2007) the question “Is there a universal set of determinants that
determine the service quality across a section of services?” is still unanswered. Therefore
literature related to dimensions of service quality is reviewed in section 3.1. Section 3.2 is
about service quality in supply chains because this research is based in a supply chains
setting. The sector selected for this research is pharmaceutical sector so section 3.3 is
about Pakistani pharmaceutical market.
3.1: SERVICE QUALITY DIMENSIONS Whilst there has been considerable progress as to how service quality should be
measured, there is little advancement as to what should be measured. Researchers
generally have adopted one of two perspectives. These perspectives are the “Nordic
perspective” and the “American perspective” (Brady and Cronin, 2001). The “Nordic
perspective” was proposed by Gronroos (1984) and the “American perspective” was
proposed by Parasuraman et al. (1985, 1988).
41
In the “Nordic perspective”, Gronroos (1984) identified 2 dimensions of service quality
(technical quality and functional quality). He defined technical quality as “what the
consumer receives as a result of interactions with a service firm” and identified
employees technical ability, employees knowledge, technical solutions, computerised
systems and machine quality as its 5 attributes. Gronroos (1984) defined functional
quality as “the way in which the technical quality is transferred” and identified behaviour,
attitude, accessibility, appearance, customer contact, internal relationships, service-
mindedness as its 7 attributes. He concluded that the technical and functional quality of
service built up the corporate “image” of the company.
The “Nordic perspective” of service quality was the first to be published in scholastic
literature. However, the first seriously dedicated program of research to answer the
questions “what’s the best way to define service quality?” and “what’s the best way to
measure it?” was launched by Parasuraman et al. (1985,1988) (Schneider and White,
2004). This program developed the “American perspective” of service quality.
Parasuraman et al. (1985) built up a 34-item service quality scale comprising 10
dimensions (reliability, responsiveness, competence, access, courtesy, communication,
credibility, security, understanding/knowing the customer and tangibles). Subsequent
work by Parasuraman et al. (1988) resulted in the service quality measurement scale with
22-items on 5 dimensions. The dimensions reliability, responsiveness and tangibles were
retained as identified in 1985 whereas communication, competence, credibility, courtesy
and security merged as a new dimension “assurance”. Access and understanding /
knowing the customer merged to form the dimension “empathy”. Parasuraman et al.
(1988) codified this scale as SERVQUAL and defined its 5 dimensions as:
Tangibility: Appearance of physical facilities, equipment and communication material.
Reliability: Ability to perform the promised service dependably and accurately.
Responsiveness: Willingness to help customers and provide prompt service.
Assurance: Knowledge and courtesy of the employees and their ability to convey trust
and confidence.
42
Empathy: The caring and individualized attention, organization provides to its
customers.
While there is no global consensus that either the “Nordic perspective” or the “American
perspective” is the more appropriate approach, the “American perspective” dominates the
literature (Schneider and White, 2004) because the development of the “American
perspective” generated a “cottage industry” of replicate studies in various conditions,
sectors and countries. Parasuraman et al. (1988) claimed that the 5 dimensions and 22
items proposed in their “American perspective” are generic in nature and applicable to all
service organizations.
However, the service quality measurement scale developed by Parasuraman et al. (1988)
has been the subject of criticism since its development (Johnston, 1995). Buttle (1996)
provides a detailed critique of the issues surrounding the 5 dimensions of the
Parasuraman et al. (1988) service quality scale, mainly on the basis of number of
dimensions and contextual stability.
Carman (1990) found that the 5 dimensions of service quality measurement scale
proposed by Parasuraman et al. (1988) are not so generic that users should not add new
dimensions they believe are important. He found that if a dimension is extremely
significant to customers it is possible to be decomposed into a number of sub-dimensions
and vice versa. Babakus and Boller (1992) also empirically assessed the scale proposed
by Parasuraman et al. (1988) and suggested that the number of service quality dimensions
is dependent on the service being offered. Seth et al. (2006) summarized some of the
service quality studies published from 1984 to 2000 over a variety of service industries
(Table 4).
43
TABLE 4: ATTRIBUTES OF SERVICE QUALITY RESEARCHERS ATTRIBUTES Gronroos (1984) Technical quality, functional quality, corporate image Gronroos (1988) Recovery, attitudes and behaviour, accessibility and flexibility,
reputation and credibility, professionalism and skills, reliability and trustworthiness
Parasuraman et al. (1985)
Credibility, access, reliability, communication, understanding the customer, courtesy, competence, responsiveness, tangibles, security
Parasuraman et al. (1988)
Assurance, responsiveness, tangibles, reliability, empathy
Haywood-Farmer (1988)
Behavioral aspects (Timeliness, speed, communication verbal , non-verbal), courtesy, warmth, friendliness, tact, attitude, tone of voice, dress, neatness, politeness, attentiveness, anticipation, handling complaints, solving problems), professional judgement (diagnosis, advice, skill, guidance, innovation, honesty, confidentiality, flexibility, discretion, knowledge), physical facilities and processes (location, layout, de´cor, size, facility reliability, process flow, capacity, balance, control of flow, process flexibility, timeliness, speed, ranges of services offered, communication)
Lehtinen and Lehtinen (1991)
Physical quality (physical products + physical environment), interactive quality (interaction with persons and equipment’s), corporate quality, process quality, output quality
Mersha and Adlakha (1992)
Knowledge of service, thoroughness/accuracy of the service, consistency/reliability, willingness to correct errors, reasonable cost, timely/prompt service, courtesy, enthusiasm/helpfulness, friendliness, observance of announced business hours, follow up after initial service and pleasant environment
Ennew et al. (1993) Knows business, knows industry, knows market, gives helpful advice, wide range of services, competitive interest rates, competitive charges, speed of decisions, customized finance, deals with one person, easy access to sanctioning officer
Ghobadian (1994) Competence, access, reliability, responsiveness, credibility, understanding the customer, courtesy, communication, tangibles, security, customization
Rosen and Karwan (1994)
Reliability, responsiveness, tangibles, access, knowing the customer, assurance,
Johnston (1995) Responsiveness, care, availability, reliability, integrity, friendliness, courtesy, communication, competence, functionality, commitment, access, flexibility, aesthetics, cleanliness/ tidiness, comfort, security
Philip and Hazlett (1997)
Pivotal attributes (acquired information) Core attributes (reliability, responsiveness, assurance, empathy) Peripheral attributes (access, tangibles)
Dabholkar et al. (2000) Reliability, comfort, features, personal attention Source: Seth et al. (2006)
44
On the basis of overview of Table 4, it can be concluded that there seems to be no
agreement on the dimensions of service quality. Different authors have identified
different service quality dimensions in different studies. Chowdhary and Prakash (2007)
also report variations from unidimensionality to two, three, four, six and even eight factor
structures in the previous service quality studies.
Contextual stability is another issue. Cronin and Taylor (1992) suggest flexibility in the
Parasuraman et al. (1988) service quality measurement scale items and argue that high
involvement services such as healthcare or financial services have different service
quality items than low involvement services such as fast food or dry cleaning.
Researchers must also therefore consider the individual items of service quality for each
service industry. Brady and Cronin (2001) also suggest that from a theoretical
perspective, even if the 5 service quality dimensions proposed by Parasuraman et al.
(1988) are generic, something specific must be reliable, responsive, empathetic, assured
and tangible. To identify this “something” for each context is critical. Moreover, this
scale was developed in Western culture so its contextual stability across diverse cultures
is also an issue (Parikh, 2006). Based on Hofstede’s dimensions of culture, Donthu and
Yoo (1998) studied the effect of culture on consumer service quality expectations and
concluded that as a consequence of cultural orientation, consumers differ in their overall
expectations with regard to service quality dimensions.
On the basis of this literature review, it may be concluded that despite the fact that the
“American perspective” dominates the service quality literature and many service quality
studies are based on the service quality measurement scale proposed by Parasuraman et
al. (1988), there is actually no generic scale for measurement of service quality. There is
no universal set of dimensions and items that determine the service quality across a
section of service industries in different cultures, so service quality measurement must be
adapted to fit the context. Therefore there is a need for the development of context
specific service quality measurement scales. Such context specific service quality
measurement scales may help managers to gauge, manage and improve service quality in
particular sectors with more simplicity and effectiveness.
45
3.2: SERVICE QUALITY IN SUPPLY CHAINS In today’s global marketplace, individual firms no longer compete as independent entities
but compete as an integral part of supply chains links (Seth et al. 2006). Christopher
(1992) also argued that a key aspect of business is that supply chains compete, not
companies. According to Waters (2003), organizations do not work in isolation; they act
as a customer when they buy materials from their own suppliers and act as a supplier
when they deliver materials to their own customers. A wholesaler for example acts as a
customer when buying goods from manufacturers, and then acts as a supplier when
selling goods to retailers. It is therefore important to satisfy each member of the supply
chain. Beamon and Ware (1998) extended the concept of TQM into supply chains. Beamon and
Ware (1998) proposed a generic model (figure 3.1) to provide procedural approach to
assess, improve and control the quality of various supply chains processes.
FIGURE 3.1: SUPPLY CHAINS PROCESS QUALITY MODEL
Source: Beamon and Ware (1998) This model represents a shift from static models to customer satisfaction based model of
supply chains. This model consists of seven modules.
Module 4: Identify current quality
performance measures
Module 6: Improve process
Module 3: Define quality
Module 5: Evaluate current process and set
quality standards
Module 2: Identify customers & their
requirements, expectations, and
perceptions
Module 7: Control & monitor process
Module 1: Identify the process, technology and tasks being performed
46
The purpose of module 1 is to define the process and activities being performed. Once
these activities have been identified, then the activities are assigned to process stages.
These stages may include inbound and outbound transport, warehousing, production
planning/inventory control and customer service. In this research the area of research is
customer service.
The objective of module 2 is to identify customers (both external and internal) and their
requirements, expectations and perceptions.
Module 3 refines the definition of quality in the supply chains system and suggests that
during development of system definition of quality the following questions must be
answered:
- What are the goals of the supply chains process? (objectives)
- What are the internal and external customer requirements/expectations from the
supply chains process? (customer requirements)
- What is our competitor’s definition of quality? (benchmarking)
Beamon and Ware (1998) conclude that if the current supply chains process has a
definition of quality that does not reflect the stages of the process and the needs of the
customers, then the gaps should be identified and the definition refined.
The purpose of module 4 is to first identify the gaps associated with the various supply
chains stages and customer requirements. These gaps must be translated into
measurements, and then the aspects of quality for the process may be identified. In module 5, quantitative quality standards are developed after examining the data
collected in module 4.
Module 6 of process quality model is to improve the processes. The first step within this
module consists of identifying and prioritizing improvement areas. Once these areas have
been prioritized, then the areas that must receive immediate attention are identified,
considering time and cost restrictions.
47
Module 7 in the process quality model is to control and monitor the process. Beamon and Ware (1998) categorized first three (1-3) modules as initialization steps
(executed infrequently) and last four modules (4-7) as continuous improvement steps
(executed frequently). Process quality model therefore represents a shift in a supply
chains philosophy from static models to the continuous improvement based model.
Continuous improvement is one of the four tenets of TQM philosophy (as identified in
chapter 2).
Such models changed the landscape of supply chains management in recent years.
According to Christopher and Lee (2004), satisfaction of each member of the supply
chain can be increased by developing closer partnership type arrangements. In the
development of such partnership type arrangements, service quality is an important tool
because the relationship of service quality with improved supply chain performance is
widely accepted (Mentzer et al., 1999, 2001; Perry and Sohal, 1999).
Regardless of this universal recognition of the importance of service quality in supply
chains, yet it is little researched (Nix, 2001) and there is a need for empirical research
into the service quality experience of business to business customers (Madaleno et al.,
2007). Most of the previous service quality research has been aimed at the end-use
customer (Faulds and Mangold, 1995; Perry and Sohal, 1999). There have been very few
studies on the development of service quality measurement scales in supply chains
(Beinstock et al. 1997; Mentzer et al. 1999, Rafele, 2004). These few studies are also
confined to specific sectors and are based in developed countries. Generalization of
findings of these studies in the global economy is not possible without further empirical
research (Rafele, 2004).
To reduce this research gap, this research is also focused on service quality scale
development at the distributors-retailers interface of the pharmaceutical supply chains in
Pakistan. Pharmaceutical supply chains are chosen as the object of the research because
of the economic importance of the sector. Pharmaceutical supply chains too do not appear
in previous supply chains specific service quality measurement scale development
studies. The distributors-retailers interface is chosen as it has many non-contractual
48
dimensions in contrast to the manufacturers-distributors interface of supply chains, which
is frequently characterized by contractual agreements (Mangold and Faulds, 1993).
Pakistan (a developing country) is selected for this research because little work has been
done to examine the applicability of service quality measurement scales to the service
industries in developing countries (Jain and Gupta, 2004). The author could find no
studies on the development of supply chains specific service quality measurement scale
studies in the developing countries.
The aim of this research is also to develop a scale for the measurement of service quality
in the distributors-retailers interface of pharmaceutical supply chains using Pakistan as
the context. This research will contribute to reduce the current lack of supply chains
specific service quality scale development studies. It extends supply chains specific
service quality scale development research into developing countries and into a new
sector (distributors-retailers interface of pharmaceutical supply chains). The scale
developed as an outcome of this research will assist managers in pharmaceutical
distribution companies in Pakistan to gauge, manage and improve service quality.
As the sector selected for this research is distributor-retailer interface of pharmaceutical
supply chains in Pakistan, section 3.3 of this chapter provides the brief overview of
pharmaceutical sector of Pakistan. The section begins with brief history about evolution
of pharmaceutical industry in Pakistan, states current market situation and later identifies
various types of distribution set-ups pharmaceutical companies may choose to ensure
smooth, safe and cost-efficient distribution of pharmaceutical products.
3.3: PHARMACEUTICAL SECTOR OF PAKISTAN
To understand the present situation of pharmaceutical industry, the history of
pharmaceutical industry in Pakistan can be classified into three main phases. First phase
is from 1947 to 1971. At the time of independence from British rule in 1947, Pakistan
had no pharmaceutical industry and traders primarily based in India were importing
medicines to Pakistan. The growth of the pharmaceutical industry started by the
establishment of two government controlled pharmaceutical industries (one at Mianwali
and second near Islamabad) and continued till 1971.
49
The second phase (1971-1991) is the depressing phase for the pharmaceutical industry of
Pakistan as the government adopted discriminatory and restrictive registration policy by
the implementation of a drug generic act in 1972. Government also allowed import of
drugs, which resulted in large scale flooding of imported drugs in the local market.
The third phase is from 1991 to now. During this phase, to increase exports, achieve self-
sufficiency and earn foreign exchange, the government implemented by law a policy of
deregulation that allowed companies to play freely. Due to this policy by the government,
there has been a substantial growth in the pharmaceutical market in Pakistan in recent
years.
At present the pharmaceutical industry in Pakistan is a sizeable industry producing 125
categories of medicines with an annual turnover of US$ 1.2 billion and an annual growth
rate of 10-15% (Hameed, 2007). The total number of pharmaceutical companies is 379.
350 are the local companies and 29 are multinational companies (Asif and Awan, 2005).
To ensure smooth, safe and cost-efficient distribution of health care product (Oswald and
Boulton, 1995), the types of distribution setups a pharmaceutical company may choose in
Pakistan are the following (Maqsood and Sattar, 2003):
- Company’s own distribution
- National contractual distribution
- Regional contractual distribution Out of top 50 pharmaceutical companies, 2 are using their own distribution network and
5 are in national contract with a single distribution partner to supply medicines. These
distribution partners distribute medicines to 45000 – 50000 retail outlets (Butt et al.,
2005). The market share of these 7 pharmaceutical companies which are either using
company’s own distribution or national contractual distribution is more than 12%. Most
of the companies are therefore using regional contractual distribution. Maqsood and
Sattar (2003) identified the following parameters as basis of channel selection decision
for Pharmaceutical companies:
- Company profile
50
- Marketing focus
- Area Coverage
- Nature of association
- Services needed from distribution In section 3.2 of this chapter, it is mentioned that the manufacturers-distributors
relationship depends on contractual agreements. However, in the distributors-retailers
interface of the supply chains, the quality of customer service is the important dimension
to enhance channel cooperation, reduce channel conflict and increase sales levels and
productivity. This research therefore aims to identify the important dimensions of the
service that pharmaceutical retailers require from pharmaceutical distributors.
3.4: SUMMARY OF THE CHAPTER
In this chapter literature related to service quality dimensions and service quality in
context of supply chains is reviewed. Section 3.1 suggests that despite of wide acceptance
of “American perspective” on service quality, there is no universal set of determinants
that describe the service quality across a section of services. There is no universal set of
dimensions and items that determine the service quality across a section of service
industries in different cultures, so service quality measurement must be adapted to fit the
context. Therefore there is a need for the development of context specific service quality
measurement scales. Such context specific service quality measurement scales may help
managers to gauge, manage and improve service quality in particular sectors with more
simplicity and effectiveness.
In section 3.2, it is concluded that in spite the general acknowledgment for realizing the
importance of service quality in supply chains, it is little researched. Previous service
quality research has been aimed at the end-use customer and there have been very few
studies on the development of service quality measurement scales in supply chains.
These studies are also confined to specific sectors and are based in developed countries.
Generalization of findings of these studies in the global economy especially in the
developing countries is not feasible without further pragmatic research (Rafele, 2004).
51
Section 3.3 of this chapter has provided the basic information about the sector selected
for this research.
52
CHAPTER 4 - METHODOLOGY This chapter provides a vital link between literature review (chapters two and three) and
the analysis of the fieldwork to be done for this research (chapters five and six) as the
methodology is explained in this chapter. In section 4.1 research questions are defined.
Section 4.2 explains decisions regarding approach, strategy and data collection methods.
Section 4.3 is about selection and refinement of questionnaires to be used in this research.
Section 4.3.1 is about selection and refinement of questionnaire related to research
questions 1 and 2. Section 4.3.2 is about selection and refinement of questionnaire related
to research question 3. Theoretical framework for analysis of questionnaire related to
TQM is given in section 4.3.1.1. Theoretical framework for analysis of service quality
scale development questionnaire is given in section 4.3.2.1. Sampling procedure adopted
for TQM related questionnaire is given in section 4.3.1.2. Sampling procedure adopted
for section of research related to service quality scale development is given in section
4.3.2.2.
4.1: RESEARCH QUESTIONS Literature review in chapter two identifies customer satisfaction as core component of
TQM philosophy and top management support as the most critical success factor for
successful TQM implementation. In chapter three it is concluded that dimensions of
service quality differ from sector to sector and there is no universal set of service quality
dimensions. This research is therefore divided into two major sections. In one section,
managers of Pakistani pharmaceutical distribution companies judge the impact of
implementing TQM on customer satisfaction and then identify the critical success factors
for implementation of TQM in their organizations. In second section, pharmaceutical
retailers identify the important elements of service quality provided by pharmaceutical
distributors. Following are therefore the questions developed for this research:
1) Does TQM implementation relates directly to the customer satisfaction in
pharmaceutical distribution companies in Pakistan?
2) What are the critical success factors of TQM in pharmaceutical distribution
companies in Pakistan?
53
3) Which are the important service quality dimensions and items in distributors-
retailers interface of pharmaceutical supply chains in Pakistan?
Once the research questions are defined, the next step is to make decisions regarding the
choices in research design.
4.2: RESEARCH STRATEGY AND DATA COLLECTION METHODS Quantitative (deductive) and qualitative (inductive) are the two commonly used research
approaches. These research approaches are based on “positivism” and “phenomenology”.
Each of these approaches has its own advantages and disadvantages. These approaches
can be used either in isolation or in combination in various applications. The most
important question is which research approach (quantitative or qualitative or combination
of these two approaches) should be adopted for this particular research.
Creswell (1994) suggests that the most important criteria for selecting a research
approach is the nature of the research topic and argues that a topic on which there is a
wealth of literature from which theoretical framework can be defined lends itself more
readily to the quantitative (deductive) approach. This research is about TQM and service
quality. According to Kaynak (2003), popular press and academic journals have
published a lot of material describing both successful and unsuccessful efforts about the
implementation of TQM. According to Abdullah (2006), curiosity over the measurement
of service quality is high and researchers have devoted a great deal of attention to service
quality research also. Therefore, there is no problem for defining theoretical framework
for both sections of this research using available literature.
Creswell (1994) suggests time as another important criterion for decision making while
selecting research approach. According to Saunders et al. (2000), quantitative research
can be quicker to complete and it is normally possible to predict accurately the time
schedules where as qualitative research can be much more protracted. Research projects
undertaken for academic courses are time constrained. This research is also an academic
research and constrained by time so deductive approach is the preferred approach.
54
Third important criterion about selection of research approach is risk associated with
particular research approach. According to Creswell (1994), quantitative approach is a
lower risk strategy where as in qualitative approach, researchers live with the fear that no
useful data patterns and theory may emerge. This research is first research about TQM
and service quality in pharmaceutical supply chains in Pakistan so to adopt a lower risk
strategy is preferred.
Another important criterion may be the budget for the research. As the sample for one
section of study is distributed all over Pakistan and for second section in two
metropolitan cities of Pakistan so quantitative research approach may be much less
expensive as compared to the qualitative research.
Therefore on the basis of nature of the research topic, time, associated risk and budget
constraints quantitative research is the preferred approach for both sections of this
research.
There may be several arguments against the exclusive use of quantitative approach. Most
strong argument is that most of the work published in the area of TQM is in context of
developed countries (Rao et al., 1999; Al-Khalifa and Aspinwall, 2000) and there is still
lack of information about nature and stage of implementation of TQM in some
developing regions of the world such as Asia, South America, Africa and the Middle East
(Sila and Ebrahimpour, 2003). Similarly little work has been conducted to examine the
applicability of service quality measurement scales to the service industries in developing
countries (Jain and Gupta, 2004) so it may be unjustified to make theoretical framework
on the basis of literature relevant to developed countries without any exploration of
country and sector specific requirements.
According to Kent (1999), qualitative research has traditionally been seen as a
“preliminary” to a larger scale quantitative research. Bryman (1992) also suggests that
qualitative research may help to provide background information on context and scale
construction / refinement for larger scale quantitative study. Same pattern is therefore
adapted in both sections of this research so before launching the larger scale quantitative
55
study, it is suggested to explore the local groundedness by initial qualitative research
using focus group discussions. Morgan (1993) suggests the use of focus groups to adapt
research instruments to new populations. Therefore though the approach selected for this
research is quantitative, the first step suggested in both sections of research is to refine an
existing research instrument using focus group discussions. Details of the selection and
refinement of questionnaire are in section 4.3.
In quantitative research, survey is a popular and common strategy because it allows the
collection of a large amount of data from a sizeable population in highly economical way.
Because in this research large amount of data is required so survey is the best research
strategy. This research is a cross-sectional study (because constrained by time) and
according to Robson (1993) cross-sectional studies often employ the survey strategy.
This research is a first one about TQM and service quality in pharmaceutical supply
chains in Pakistan so the main prospect of using the survey method is to assure that any
subsequent evaluation of the features of sample population is precise and the findings can
be generalized.
The next issue is the issue of sampling. According to Saunders et al. (2000) researchers
prefer probabilistic (random) sampling methods over non probabilistic ones. However in
applied social research there may be circumstances where it is not feasible, practical or
theoretically sensible to do random sampling (Trochim 2006). This research is a first
research about TQM and service quality in pharmaceutical supply chains in Pakistan.
According to Asif and Awan (2005), there is severe lack of applied research in
pharmaceutical sector of Pakistan. Due to lack of evidence to show the existence of any
reliable sampling frame, non-probability sampling is the only sampling option for both
sections of this research.
The next issue is selection of the appropriate data collection method. As this is the first
TQM and service quality research study in pharmaceutical supply chains in Pakistan so it
is impossible to use any secondary data. Observation, interviews and questionnaires as
three sources of primary data collection. Kumar (1999) conclude that if potential
56
respondents are scattered over a wide geographical area, the use of questionnaires may be
the only choice of collecting data.
Saunders et al. (2000) classify questionnaire as self-administered or interviewer
administered. Interviewer administered questionnaire may be by telephone questionnaire
or by structured interview. Self administered questionnaire may be online questionnaire,
postal questionnaire or delivery and collection questionnaire. The option of interviewer
administered questionnaire may be ruled out as this method is costly and interviewer may
introduce bias both during telephone interviews or structured interviews. The option of
online questionnaire is not suitable because response rates from this approach are likely
to be very low and there are considerable problems of non-response bias as the
respondent has to take extra steps to locate and complete the questionnaire (Saunders et
al. 2000).
Delivering and collecting questionnaire is a valid option for section of research related to
third research question as that portion of research is based in two metropolitan cities of
Pakistan only but in the portion of research related to research question 1 and 2,
respondents are scattered over all over Pakistan (a wide geographical area) so the use of
postal questionnaires has been opted for collecting data irrespective of its several
limitations.
This section provides framework how to proceed in both sections of this research.
Quantitative research approach is the suitable research approach for both sections of this
research. However the use of focus group discussion is recommended for questionnaire
refinement purposes (section 4.3). The research is a cross sectional research so survey is
the best research strategy. Respondents related to research questions 1 and 2 are spread
allover the Pakistan so postal questionnaire is the best option for data collection for first
portion of research. Delivering and collecting questionnaire is the preferred option for
section of research related to third question.
57
4.3: SELECTION AND REFINEMENT OF THE QUESTIONNAIRES As two questionnaires are to be used in this research, this section is further divided into
two subsections. Issues related to selection and refinement of questionnaire related to
research questions 1 and 2 after focus group discussion are discussed in subsection 4.3.1.
Subsection 4.3.1.1 provides theoretical framework for analysis of TQM survey results.
The procedure adopted for sampling is given in subsection 4.3.1.2.
Matters related to selection and refinement of questionnaire related to service quality is
discussed in subsection 4.3.2. Subsection 4.3.2.1 provides theoretical framework for
analysis of service quality survey results. The procedure adopted for sampling is given in
subsection 4.3.2.2.
4.3.1: SELECTION AND REFINEMENT OF THE QUESTIONNAIRE (RESEARCH QUESTIONS 1 AND 2) Various questionnaires have been previously used in TQM studies. Basic information
about six TQM measurement instruments used in various TQM studies is summarized in
table 5 (Mahour 2006; Singh and Smith 2006).
58
TABLE 5: COMPARSION OF VARIOUS TQM MEASUREMENT INSTRUMENTS Characteristics Instruments
Authors Saraph et al. (1989)
Flynn et al. (1994)
Ahire et al. (1996)
Grandzol and Gershon (1998)
Rao et al. (1999)
Joseph et al. (1999)
Number of constructs
8 11 12 07 13 10
Respondents Divisional quality managers
Multiple respondents
Plant managers
Chief executive officers
Chief executive officers, quality managers
Chief executive officers, general managers, chief quality managers
Number of responses / companies
162 / 20
716 / 45
371 275 780 50 / 25
Industry focus Across industry
Machinery, Electronics, and transportation companies
Motor vehicle parts and accessories
Suppliers to USA Navy’s and aviation supply office
Across industry
Across industry
Methodology Principal components and Cronbach’s α
Principal components and Cronbach’s α
Confirmatory factor analysis (LISREL) and Cronbach’s α + Werts-Linn-Jorsekog coefficient
Confirmatory factor analysis (LISREL) and Cronbach’s α
Confirmatory factor analysis (LISREL) and Cronbach’s α + Werts-Linn-Jorsekog coefficient
Factor analysis and Cronbach’s α
Country US US US US Multi-country, US, India, China, Mexico, and Taiwan
India
The questionnaire proposed by Rao et al. (1999) was selected for refinement by focus
group discussion. This questionnaire is attached as an appendix A. There were many
59
reasons for the selection of this particular questionnaire. The most important reason for
selection of this questionnaire was its validation in both developed and developing
countries – including a neighboring developing country, India. Questionnaires proposed
by Saraph et al. (1989), Flynn et al. (1994), Ahire et al. (1996) and Grandzol and
Gerhson (1998) were validated only in the United States. The questionnaire proposed by
Joseph et al. (1999) was also not selected because it was validated only in India. The
questionnaire proposed by Rao et al. (1999) has also been used for another doctorate
study in neighboring country, Iran (Mahour 2006). Rao et al. (1999) questionnaire also
has highest number of constructs as compared to other questionnaires. One view is that
the higher the number of constructs in the questionnaire, the easier it is to refine the
constructs. Third reason for selection of this questionnaire was its validation on the basis
of highest number of responses as compared to the other questionnaires. Fourth reason
for selection of this questionnaire was its validation across industries in both
manufacturing and services sectors. Once the questionnaire for refinement was selected
using available TQM literature, next step was to conduct focus group discussion to refine
the selected questionnaire. The next paragraphs explain the details of focus group
discussion conducted to refine the questionnaire proposed by Rao et al. (1999).
Morgan (1993) suggests the use of focus groups to adapt survey questionnaires to new
populations so the purpose of this focus group discussion was to refine the questionnaire
proposed by Rao et al. (1999) before launching the survey for this section of research
keeping in view the country specific and sector specific scenario. Focus group research
framework provided by Carson et al. (2001) was used for this focus group discussion.
According to Carson et al. (2001) there are no general rules concerning the optimal
number of groups and increasing the number of groups does not ensure increased
accuracy. The purpose of this focus group was just to refine the questionnaire so only one
focus group discussion was arranged. There is no consensus in the literature as to the
number of participants in each focus group but groups larger then twelve are usually not
recommended due to the constraints large groups put on each person’s opportunity to
share insights and observations (Carson et al. 2001). Ten representatives of
pharmaceutical distribution companies were invited for this focus group discussion. The
60
site selected for this focus group discussion was the committee room of Institute of
Quality and Technology Management, University of the Punjab, Lahore, Pakistan. It was
decided to start the discussion after office times (09:00 to 17:00) so that the daily
working routine of invited participants was not affected. As the objective of this focus
group discussion was to refine the questionnaire, the Rao et al. (1999) questionnaire was
delivered to the offices of pharmaceutical distribution companies one week before
discussion so that the participants could have an understanding of the questionnaire well
before the discussion.
Author of this dissertation (My self) was the moderator for this focus group discussion
along with two of my colleagues (lecturers at Institute of Quality and Technology
Management, University of the Punjab, Lahore, Pakistan) served as assistant moderators.
The assistant moderators kept notes of the session.
There were two issues to be decided in this focus group discussion. One was to refine the
title/number of constructs in the questionnaire and the second one was to refine the items
in each of the constructs. After focus group discussion, the moderator and the assistant
moderators prepared the initial draft of the refined questionnaire. In this initial draft, the
number of constructs was reduced from thirteen to ten. The construct “quality
citizenship” in the Rao et al. (1999) questionnaire was dropped. The construct product/
process design was renamed as “process design” and constructs “quality information
usage” and “quality information availability” were merged as new construct “quality
information availability and usage”. The constructs “internal quality results” and
“external quality results” were also emerged as new construct “results of implementing
quality management”.
The construct “quality citizenship” was dropped because all of the participants in the
focus group discussion were of the view that this construct is unnecessary extension of
the construct “top management support”. The construct “product / process design” was
re-named as “process design” because the sector selected for this research is a services
sector and the term product design is more associated with manufacturing sector. The
constructs “quality information availability” and “quality information usage” were
61
merged into new construct “quality information availability and usage” because of the
argument by the majority of the participants that quality information availability and
quality information usage are highly integrated activities and separation of these two
constructs may confuse respondents. Similar argument was the reason for merger of
constructs “internal quality results” and “external quality results” into the new construct
“results of implementing quality management”.
The next issue was to refine the items for each construct. In this exercise, the number of
items were dropped or modified mainly because of lack of relevance of items in the
pharmaceutical distribution sector of Pakistan, inability to conceive the content of items
by the practitioners and replication of items
The initial draft of refined questionnaire proposed after focus group discussion was
checked by statisticians, linguistics experts and supervisors of the research. After some
minor modifications the refined questionnaire with ten constructs and thirty five items
was finalized for this section of research. The finalized version of refined questionnaire is
attached as appendix B.
Table 6 provides the comparison of constructs and number of items in each construct in
Rao et al. (1999) questionnaire and questionnaire refined after focus group discussion.
62
TABLE 6: COMPARISON OF RAO ET AL. (1999) QUESTIONNAIRE AND REFINED QUESTIONNAIRE
Rao et al. (1999) questionnaire Refined questionnaire
Title of the construct No. of items Title of the construct No. of items
Top management support 7 Top management support 5
Strategic planning process of quality management
4 Strategic planning process of quality management
2
Quality information availability
3
Quality information usage 3
Quality information
availability and usage
4
Employee training 4 Employee training 3
Employee involvement 5 Employee involvement 4
Product / process design 5 Process design 3
Supplier quality 6 Supplier quality 2
Customer orientation 8 Customer orientation 6
Quality citizenship 4 This construct was deleted
Benchmarking 4 Benchmarking 2
Internal quality results 5
External quality results 4
Results of implementing
quality management
4
62 35
This sub-section may be concluded here as Rao et al. (1999) questionnaire has been
refined after focus group discussion. Before discussing the sampling issues for this
section of research, it may be appropriate to develop the theoretical framework for data
analysis.
4.3.1.1: DEVELOPMENT OF THEORETICAL FRAMEWORK FOR ANALYSIS The research questions related to this section of research are:
63
1) Does TQM implementation relates directly to the customer satisfaction in
pharmaceutical distribution companies in Pakistan?
2) What are the critical success factors of TQM in pharmaceutical distribution
companies in Pakistan?
These two research questions are interrelated. The first research question is about the
effect of implementation of TQM on customer satisfaction. The construct “customer
orientation” is the dependent variable and all other nine variables are independent
variables. The theoretical framework to answer the first research question in this section
is given in the figure 4.1.
64
FIGURE 4.1 - THEORETICAL FRAMEWORK FOR REGRESSION ANALYSIS ON DEPENDENT VARIABLE (CUSTOMER ORIENTATION)
In the second research question, the objective is to identify critical success factors in the
implementation of TQM so the construct “results of implementing quality management”
is the dependent variable. All other variables except “customer orientation” are
independent variables. The construct (variable) “customer orientation” is not included in
analysis in getting the answer of second research question because it is used as dependent
variable to get the answer of first research where the construct “results of implementing
Quality information availability and usage
Top management support
Process design
Strategic planning process of quality management
Employee training
Employee involvement
Benchmarking
Supplier quality
Customer Orientation
Results of implementing quality management
65
quality management” is independent variable. Theoretical framework to answer the
second research question in this section is given in the figure 4.2.
FIGURE 4.2: THEORETICAL FRAMEWORK FOR REGRESSION
ANALYSIS ON DEPENDENT VARIABLE (RESULTS OF IMPLEMENTING QUALITY MANAGEMENT)
Once the theoretical framework was developed for analysis of the results, the next step
was to launch the survey phase of this research. The next subsection (4.3.1.2) describes
the sampling procedure and dispatch of questionnaire to the sample population.
4.3.1.2: SAMPLING This research is the first research related to pharmaceutical distribution companies in
Pakistan. There are about 350 pharmaceutical distribution centers working in different
Quality information availability and usage
Top management support
Process design
Strategic planning process of quality management
Employee training
Employee involvement
Benchmarking
Supplier quality
Results of
implementing quality management
66
cities of Pakistan (Qassim, 2005) but there is no existing reliable sampling frame. As the
respondents were to be distributed all over Pakistan, it was not possible to build the
sampling frame from the ground-up by the researcher himself, so non-probability
purposive-convenience sampling was done. A multinational pharmaceutical company
based at Lahore (Pakistan) and distributing its medicines throughout Pakistan, using a
broad network of large distributors, supported this research by providing a list of its
distributors. There were 46 distribution centers for distributors of this pharmaceutical
company. Three other pharmaceutical distributors were also included in the sample
because these distributors were operating all over Pakistan and had contracts of exclusive
distribution with leading pharmaceutical companies. One of these distributors had 22
branches and the others had 12 and 10 branches respectively across Pakistan. The
questionnaire was therefore sent to 90 pharmaceutical distribution centers based all over
Pakistan via registered post. The covering letter for the research was written to the chief
executives of the pharmaceutical distribution centers (appendix C). The pharmaceutical
company which provided the list of its distributors encouraged its distributors to
participate in this research study. The other three distributors also encouraged their
branch managers to participate in the research. Details of the response rate and data
analysis are provided in chapter five.
4.3.2: SELECTION AND REFINEMENT OF THE QUESTIONNAIRE (RESEARCH QUESTION 3) The objective of this section of research is to develop a service quality scale in
distributors-retailers interface of pharmaceutical supply chains. This scale development
process started by refining the Parasuraman et al. (1988) service quality measurement
scale. Focus group discussion was used for this refinement.
There are several reasons for the selection of the Parasuraman et al. (1988) service
quality measurement scale as the foundation in this research. According to Schneider and
White (2004), the “American perspective” proposed by Parasuraman et al. (1988)
dominates the service quality literature. The service quality dimensions upon which the
Parasuraman et al. (1988) service quality measurement scale is based are therefore often
employed when discussing and measuring service quality in a variety of service sectors
67
(Kvist and Klefsjo, 2006). Rafele (2004) also claimed that the Parasuraman et al. (1988)
service quality measurement scale is applicable to all kinds of services including supply
chains.
For this particular research, therefore the service quality measurement scale proposed by
Parasuraman et al. (1988) was refined after focus group discussion. Original Parasuraman
et al. (1988) service quality questionnaire is attached as appendix D. Morgan (1993)
suggests such refinement of existing measurement instruments when the population for
the research is new as in this case. The focus group discussion was arranged at Institute
of Quality and Technology Management, University of the Punjab, Lahore – Pakistan and
lasted for approximately two hours. Eleven pharmaceutical retailers participated in this
discussion. Author of this thesis was the moderator for this focus group discussion and
was assisted by of assistant moderators. The main role of the moderator was to introduce
a topic in a way that participants are stimulated to respond and to manage the balance of
opinions. The main responsibility of the assistant moderators was to note the proceedings.
As a result of the focus group discussion and then subsequent evaluation of the initial
drafts of the refined service quality measurement scale by statisticians, linguistic experts
and the authors, a service quality measurement scale with 5 dimensions and 31 items
emerged (appendix E).
The number of dimensions in this refined service quality measurement scale was the
same as that of Parasuraman et al. (1988) as there was consensus among the participants
of the focus group discussion that these dimensions cover all dimensions of service
quality in the distributors-retailers interface of pharmaceutical supply chains in Pakistan.
However the number of items in the refined scale was increased to 31 as compared to 22
in the Parasuraman et al. (1988) service quality measurement scale. Nine new items were
added on the basis of sectoral relevance. Several of the existing items were modified to
increase the ability of practitioners to visualize the content of items. Of the 31 items in
this initially refined service quality measurement scale, 10 dealt with reliability, 5 with
tangibles, 7 with assurance, 5 with empathy and 4 with responsiveness. On the
recommendation of the focus group participants each item in the survey questionnaire
68
was written in English as well as in Urdu (national language of Pakistan). Service quality
dimensions were not specified on the survey questionnaire as focus group participants
thought that this may increase complexity for respondents. The scale used in the refined
questionnaire was a 7 – point numeric response scale (1 = extremely unimportant, 7 =
extremely important). Items used in the questionnaire along with dimensions and
abbreviations used for data analysis are given in appendix E.
4.3.2.1: DEVELOPMENT OF THEORETICAL FRAMEWORK FOR ANALYSIS Research question related to this portion of research is:
- Which are the important service quality dimensions and items in distributors-
retailers interface of pharmaceutical supply chains in Pakistan?
Theoretical framework for development of this service quality scale in distributors-
retailers interface of pharmaceutical supply chains is therefore given in figure 4.3.
Structural Equation Modeling technique is suggested for the development of this service
quality scale.
69
FIGURE 4.3: THEORETICAL FRAMEWORK FOR DEVELOPMENT OF SERVICE QUALITY SCALE
70
After the development of theoretical model for analysis next step was sampling.
4.3.2.2: SAMPLING Non-probability purposive-convenience sampling was undertaken for this section of
research also. The two biggest cities of Pakistan (Karachi and Lahore - with more then
15% of country’s population) were selected for the survey. People from all over Pakistan
come to these metropolitan cities for the treatment of their medical ailments. The
pharmaceutical retail business in these two cities is much more developed as compared to
the rest of the country. Pharmaceutical distributors therefore focus particularly on having
good working relationship with pharmaceutical retailers operating in these two cities.
Two pharmaceutical distribution companies (based one each at Karachi and Lahore) were
contacted to support the data collection process. These 2 pharmaceutical distribution
companies had 1050 pharmaceutical retailers on their distribution lists. Questionnaires
along with a covering letter (appendix F) were provided to these pharmaceutical
distribution companies. The sales force of these 2 pharmaceutical distribution companies
distributed these questionnaires to the pharmaceutical retailers and then collected the
completed questionnaires after one week. Questionnaire delivery and collection method
was used for this survey because this method helps to increase response rate (Saunders et
al. 2000). 1050 questionnaires were distributed to pharmaceutical retailers in both cities.
Details of the response rate and data analysis are given in chapter six.
71
CHAPTER 5 – ANALYSIS OF TQM SURVEY QUESTIONNAIRE
In this chapter, results from the statistical analysis conducted on the data collected from
pharmaceutical distributors are presented. The survey questionnaire was sent to the 90
pharmaceutical distribution centers working throughout Pakistan. In total 51 usable
responses were received. Response rate (56.7%) is satisfactory. Section 5.1 of this
chapter is about scale purification. Correlation analysis is in section 5.2. In section 5.3,
regression analysis is presented.
5.1: SCALE PURIFICATION The primary approach for scale purification when a theoretical foundation drives survey
development is to rely on confirmatory factor analysis (CFA) to ensure scale
unidimensionality, followed by scale reliability and construct validity assessments
(Anderson and Gerbing, 1982). CFA using LISREL 8.8 was conducted for each of the 10
constructs used in the questionnaire to determine unidimensionality of the constructs. The
following abbreviations are used for all ten constructs in the analysis in this chapter.
Top Management Support = TMS
Strategic Planning Process in Quality Management= SPPQM
Quality Information Availability and Usage = QIAU
Employee Training = ET
Employee Involvement = EI
Process Design = PD
Supplier Quality = SQ
Customer orientation = CFS
Bench Marking = BM
Results of Implementing Quality Management = RIQM
According to Doll and Vonderembse (1991) in a customer oriented organization,
customer satisfaction drives all company action so the terms customer orientation and
customer focus and satisfaction are used as synonyms in this chapter. All nine variables
72
are independent variables when CFS is the dependent variable (research question 1).
Eight variables (excluding CFS) are independent variables when RIQM is dependent
variable (research question 2).
All the constructs except EI and CFS emerged as constructs for which no item deletion
was required to obtain the required values of assessing criteria. One item was deleted
each from the constructs EI and CFS. From the construct EI, first item (effectiveness of
employee involvement program in the company) and from the construct CFS second item
(level to which executives demonstrate with their actions that customer satisfaction is
important.) was deleted. Thus the number of items for final analysis was reduced to 33
after CFA.
According to Sila and Ebrahimpour (2005), empirical evidence in CFA is generally
assessed using criteria such as the comparative fit index (CFI), the root mean square error
of approximation (RMSEA), the significance of parameter estimates, and the amount of
explained variance. Goodness of fit index (GFI) is another measure of overall fit
(Mahour, 2006). Table 7 summarizes the results of CFA.
Comparative Fit Index (CFI): This index compares the proposed model with a null model
assuming that there are no relationships between the measures. A CFI value greater then
0.90 indicates an acceptable fit to the data (Bentler, 1992). Table 7 indicates that all the
CFI values are above 0.99, which suggests very good model fit.
Goodness of Fit Index (GFI): This index indicates the relative amount of variance and
covariance jointly explained by the model. GFI values range from zero to one, with
higher values indicating better fit. According to Chau (1997), scores in the 0.8-0.89 range
are interpreted as reasonable fit whereas scores of 0.9 and above represent good fit. All
values of GFI in Table 7 range from 0.87 to 1.00, which suggests very good model fit.
Root Mean Square Error of Approximation (RMSEA): RMSEA is an index used to assess
residuals and adjusts parsimony in the model. Its value must be equal to or less than 0.08
for an adequate model fit (Hu and Bentler, 1999). Table 7 indicates that all RMSEA
values are less then 0.08 indicating adequate model fit.
73
Parameter estimates: Table 7 shows that all the parameter estimates i.e. factor loadings
are statistically significant.
Amount of explained variance: The amount of explained variance for all constructs in
Table 7 range from 0.09 to 0.97 thus indicating acceptable squared factor loadings.
74
TABLE 7: SUMMARY OF GOODNESS OF FIT STATISTICS FOR CONFIRMATORY FACTOR ANALYSIS (CFA)
Construct No. of
items
Chi-
Square
test
P- value
Comparative
Fit Index
(CFI)
Goodness
of Fit
Index
(GFI)
RMSEA Factor
Loading R-Square
TMS 05 5.28 0.38257 1.00 0.87 0.034 1.15, 2.86, 1.22,
1.32, 1.27
0.55, 0.61, 0.88, 0.72,
0.68
SPPQM 02 5.50 0.48154 1.00 0.93 0.000 8.82, 12.67 0.73, 0.73
QIAU 04 1.05 0.59152 1.00 0.97 .000 0.47, 0.46, 1.07,
0.62 0.26, 0.55, 0.80, 0.57
ET 03 0.42 0.51832 1.00 0.98 0.000 0.73, 0.91, 0.60 0.68, 0.94, 0.42
EI 03 The model is saturated. The fit is perfect 0.29, 0.86, 0.91 0.23, 0.61, 0.76
PD 03 0.73 0.39129 1.00 0.97 0.000 0.92, 1.92, 0.28 0.41, 0.97, 0.094
75
SQ 02 5.50 0.48154 1.00 0.93 0.000 3.30, 3.81 0.27, 0.34
CFS 05 5.72 0.33420 0.99 0.90 0.054 0.68, 0.89, 0.89,
0.72, 0.82
0.43, 0.58, 0.60, 0.29,
0.64
BM 02 5.50 0.48154 1.00 0.93 0.000 8.71, 8.17 0.69, 0.69
RIQM 04 0.23 0.89310 1.00 1.00 0.000 0.69, 2.74, 1.30,
2.09 0.28, 0.71, 0.72, 0.41
Once the unidimensionality of the constructs was demonstrated using CFA, the reliability
of the each construct and the overall questionnaire with the remaining items was
evaluated by the determination of Cronbach’s coefficient alpha (Table 8). In general
reliability coefficients of 0.70 or more are considered adequate (Cronbach, 1951;
Nunnally, 1978; Murphy and Balzer, 1989). Only the values of constructs PD and SQ are
less then 0.70. These values (0.61 and 0.44 respectively) are still acceptable as Van de
Ven and Ferry (1980) suggest 0.35 as the limit of acceptable value of Cronbach’s
coefficient alpha. The overall value of Cronbach’s coefficient alpha for the 33 items
remained in the questionnaire after CFA was 0.84. This value is acceptable.
TABLE 8: RELIABILITY ANALYSIS Construct No. of items Cronbach’s Alpha TMS 05 0.88 SPPQM 02 0.79 QIAU 04 0.73 ET 03 0.78 EI 03 0.73 PD 03 0.61 SQ 02 0.44 CFS 05 0.72 BM 02 0.74 RIQM 04 0.74 According to Mentzer et al. (1999), Cronbach’s coefficient alpha is a meaningless
calculation with a two or less item scale, since its purpose is to compare each item to the
remaining items in the scale as a group. So, item to total correlation (ITC) were evaluated
for the constructs SPPQM, SQ and BM as these constructs had only two items. All these
values are above 0.70 (Table 9) so all item to total correlation (ITC) values are
acceptable.
TABLE 9: ITEM TO TOTAL CORRELATIONS Construct Item to total correlation
for item 1 Item to total correlation for
item 2 SPPQM 0.922** 0.900** SQ 0.796** 0.718** BM 0.757** 0.900**
77
After assessing unidimensionality and reliability, the next issue was to assess content,
convergent and discriminant validity of the questionnaire. According to Nunnally (1978),
content validity depends on how well the researchers created measurement items using
the relevant literature to cover the content domain of the variable being measured. The
evaluation of content validity is therefore a judgmental process not open to numerical
evaluation (Mahour, 2006). As mentioned previously the selection of construct items in
this study was based on extensive review of the literature and then subsequent refinement
by focus group discussion with representatives of pharmaceutical distribution companies
in Pakistan. The instrument thus has strong content validity.
The convergent validity of each scale was checked with Bentler-Bonett Normed Fit Index
(NFI) obtained during CFA. According to Ahire et al. (1996) this index measures the
extent to which different approaches to measuring a construct produces the same results.
A value of 0.90 and above demonstrates strong convergent validity (Hartwick and Barki,
1994). The Bentler-Bonett coefficient for all the constructs refined after CFA was greater
then 0.90, indicating high convergent validity (Table 10).
Discriminant validity measures the degree to which a construct and its indicators are
different from another construct and its indicators (Bagozzi et al., 1991). Evidence of
discriminant validity can be assessed in multiple ways (Mentzer et al., 1999). One of the
ways is by comparing the Cronbach’s alpha of a construct to its correlations with other
model variables (Sila and Ebrahimpour, 2005). According to Ghiselli et al. (1981), if the
value of alpha is sufficiently larger than the average of its correlations with other
variables, this is an evidence of discriminant validity. The difference between the alpha
value of each construct and the average correlation of each construct with the other
constructs was adequately large (0.31 – 0.69), providing evidence of discriminant validity
(Table 10).
78
TABLE 10: CONVERGENT AND DISCRIMINANT VALIDITY Constructs Convergent Validity
(Bentler-Bonett NFI) Discriminant Validity (Cronbach’s
alpha – average correlation between other constructs)
TMS 0.98 0.69 SPPQM 0.97 0.54 QIAU 0.99 0.54 ET 0.99 0.56 EI Model saturated. Fit is perfect 0.50 PD 0.96 0.46 SQ 0.97 0.31 CFS 0.96 0.58 BM 0.97 0.56 RIQM 1.00 0.56 Correlation analysis was done using SPSS 15.0. Details of the correlation analysis are
given in section 5.2.
5.2: CORRELATION ANALYSIS Table 11 presents the correlation among all variables. Kendall’s tau coefficient was used
as Field (2005) recommends its use in the case of a small non-parametric data set.
Hypothetically, the higher the value of correlation between two variables, the more
related to each other these variables are. Table 11 indicates that there are in total 12
significant correlations. However the first dependent variable CFS has only 2 significant
correlations, one with construct PD (r = .399**) and other with construct RIQM (r = .441
**).
79
TABLE 11: CORRELATION AMONG ALL VARIABLES CONSTRUCT TMS SPPQM QIAU ET EI PD SQ CFS BM RIQM
TMS r p N
1.000
51
.483** .000
45
.230* .028
51
.238
.053 38
.247
.060 34
.077
.503 45
.097
.385 47
.045
.674 51
.223
.058 43
.048
.660 49
SPPQM r p N
1.000
45
.228
.052 45
.302* .029
33
.275
.065 29
-.060 .640
41
.564** .000
43
-009 .941
45
.268* .039
39
-.041 .733
44 QIAU r
p N
1.000
51
.552* .000
38
.169
.201 34
.185
.115 45
.050
.657 47
.064
.555 51
-.063 .597
43
.180
.099 49
ET r p N
1.000
38
.238
.112 27
.169
.201 36
.017 .895
35
.102
.424 38
.000 1.000
32
.338** .009
36 EI r
p N
1.000
34
.289* .043
31
.184
.210 30
.131
.327 34
.338* .026
28
.201
.142 32
PD r p N
1.000
45
.007
.956 43
.399** .001
45
.016
.901 37
.297* .014
44 SQ r
p N
1.000
47
.039
.742 47
.179
.157 40
-.070 .549
45 CFS r
p N
1.000
51
.083
.500 43
.441** .000
49 BM r
p N
1.000
43
-.020 .871
41 RIQM r
p N
1.000
50 * Correlation is significant at the 0.05 level (2-tailed) ** Correlation is significant at the 0.01 level (2-tailed) Table 12 presents the correlation among all variables excluding CFS. There are in total
13 significant correlations. The second dependent variable RIQM has only 2 significant
correlations, one with construct PD (r = .377 **) and other with construct ET (r = .267*).
PD has therefore significant correlation with both dependent variables.
80
TABLE 12: CORRELATION AMONG VARIABLES EXCLUDING CFS CONSTRUCT TMS SPPQM QIAU ET EI PD SQ BM RIQM
TMS r p N
1.000
51
.517** .000
51
.230* .028
51
.250* .021
48
.230* .036
47
.087
.437 47
.131
.218 51
.234
.028 51
.042
.695 50
SPPQM r p N
1.000
51
.232
.033 51
.235* .036
48
.363** .001
47
-.099 .396
47
.507** .000
51
.340** .002
51
-.109 .326
50
QIAU r p N
1.000
51
.497** .000
48
.128
.251 47
.176
.122 47
.064
.554 51
.013
.901 51
.194
.072 50
ET r p N
1.000
48
.165
.141 47
.166
.145 47
-.019 .862
48
.036
.749 48
.267* .017
47 EI r
p N
1.000
47
.124* .285
46
.259* .022
47
.263
.020 47
.101
.374 46
PD r p N
1.000
47
-.048 .680
47
.055
.633 47
.377** .001
47 SQ r
p N
1.000
51
.209
.055 51
-.111 .313
50 BM r
p N
1.000
51
.027
.803 50
RIQM r p N
1.000
50 * Correlation is significant at the 0.05 level (2-tailed) ** Correlation is significant at the 0.01 level (2-tailed) The next step in the analysis was regression analysis because regression analysis
determines which independent variable(s) explain variability in the outcome, how much
variability in the dependent variable is explained by the independent variable(s) and
which variable(s) is significant over other variables in explaining the variability of the
dependent variable (Mahour, 2006). Details about regression analysis are given in section
5.3.
5.3: REGRESSION ANALYSIS In this section, regression analysis is done initially taking CFS as dependent variable
(section 5.3.1) and then RIQM as dependent variable ((section 5.3.2).
81
5.3.1. REGRESSION WHEN CFS IS DEPENDENT VARIABLE Tables 13 –16 report the results of the regression analysis on CFS as dependent variable.
All independent variables are entered in the regression model (Table 13).
Table 13: Variables Entered/Removed (b)
Model Variables Entered Variables Removed Method 1 RIQM, SQ, BM, ET, TMS, PD, EI,
QIAU, SPPQM (a) . Enter
a. All requested variables entered. b. Dependent Variable: CFS Table 14: Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate 1 .595(a) .355 -.371 1.84074
a. Predictors: (Constant), RIQM, SQ, BM, ET, TMS, PD, EI, QIAU, SPPQM Table 15: ANOVA (b)
Model Sum of Squares df Mean Square
F Sig.
1 Regression 14.893 9 1.655 0.488 .847(a) Residual 27.107 8 3.388 Total 42.000 17
a. Predictors: (Constant), RIQM, SQ, BM, ET, TMS, PD, EI, QIAU, SPPQM b. Dependent Variable: CFS Table 16: Coefficients (a)
Model Unstandardized Coefficients
Standardized Coefficients
t Sig.
B Std. Error Beta B Std. Error 1 (Constant) 16.747 5.713 2.931 .019 TMS -.209 .223 -.492 -.937 .376 SPPQM .083 .461 .119 .180 .862 QIAU .119 .344 .175 .344 .739 ET -.075 .285 -.138 -.264 .799 EI -.011 .246 -.019 -.043 .967 PD .655 .619 .519 1.057 .321 SQ -.048 .527 -.046 -.092 .929 BM -.150 .401 -.171 -.375 .717 RIQM .088 .224 .203 .394 .704
a. Dependent Variable: CFS
82
Table 14 shows that the regression model reports 35.5% of variability of CFS. Table 15
(ANOVA - analysis of variance) indicates that the model is not significant at α = 0.05.
Table 16 point out that none of the variable(s) is a statistically significant predictor of
dependent variable (CFS). As none of the variable(s) emerged as a significant predictor
of dependent variable by simple regression, the next step is the stepwise regression.
Stepwise regression makes it possible to identify predictors that are considered useful at
an early stage but lose their usefulness when additional predictors are brought into the
model (Mahour, 2006).
5.3.1.1: STEPWISE REGRESSION WHEN CFS IS DEPENDENT VARIABLE Tables 17 –20 show the results of a stepwise regression analysis on CFS as dependent
variable. PD emerged as the single significant variable (Table 17).
Table 17: Variables Entered/Removed (a)
Model Variables Entered
Variables Removed
Method
1 PD . Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).
a. Dependent Variable: RIQM Table 18: Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate 1 .745(a) .556 .456 1.61596
a. Predictors: (Constant), BM Table 19: ANOVA (b)
Model Sum of Squares df Mean Square F Sig. 1 Regression 143.710 1 143.710 55.033 .000(a) Residual 114.899 44 2.611 Total 258.609 45
a. Predictors: (Constant), BM b. Dependent Variable: RIQM Table 20: Coefficients (a)
Model Unstandardized Coefficients
Standardized Coefficients t Sig.
B Std. Error Beta
83
1 (Constant) 12.934 1.355 9.548 .000 PD .769 .104 .745 7.418 .000
a. Dependent Variable: RIQM Table 18 indicates that 55.6% of variability of CFS is explained by this regression model.
Analysis of variance (ANOVA) indicates that the model is significant at α = 0.05 (Table
19). Table 20 also point out that PD is significant predictor of CFS.
5.3.1.2: SUMMARY OF RESULT WHEN CFS IS DEPENDENT VARIABLE The first regression model (Tables 13-16) in regression analysis on CFS as dependent
variable revealed that none of the independent variable(s) is a statistically significant
predictor of the dependent variable (CFS). In stepwise regression (Tables 17-20) PD
emerged as the statistically significant predictor that explained more then 55 % of the
variability of dependent variable. Here it is important question why RIQM has not
emerged as the significant predictor variable, because in theory stepwise regression
selects the first variable as the variable that has the highest correlation with the dependent
variable (Mahour 2006). Variable RIQM has the highest correlation with dependent
variable CFS (Table 11) but this variable has not emerged in the stepwise regression
model. Since RIQM has significant correlation with PD also it may be concluded that
most of the variability explained by RIQM has been explained by PD. Therefore it may
be concluded that two variables have a significant role in the development of a theoretical
framework for CFS. These variables are PD and RIQM. PD has direct role as it emerged
as a single significant variable in the stepwise regression. RIQM has indirect role as it is
significantly correlated with both CFS and PD and the variability explained by RIQM has
already been explained by PD in regression analysis. Figure 5.1 shows the framework
developed for dependent variable (CFS) on the basis of correlation and regression
analysis.
FIGURE 5.1: FRAMEWORK FOR CUSTOMER FOCUS AND SATISFACTION
(CFS) Results of
Implementing Quality Management (RIQM)
Process Design (PD)
Customer Focus and Satisfaction (CFS)
84
5.3.2: REGRESSION WHEN RIQM IS DEPENDENT VARIABLE Tables 21 – 24 report the results of the regression analysis on RIQM as dependent
variable. Variables entered in the regression model are TMS, SPPQM, QIAU, ET, EI,
PD, SQ and BM (Table 21).
Table 21: Variables Entered/Removed (b)
Model Variables Entered Variables Removed Method 1 BM, ET, PD, SQ, TMS, EI, QIAU, SPPQM
(a) . Enter
a. All requested variables entered. b. Dependent Variable: RIQM Table 22: Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate 1 .693(a) .480 .367 2.39195
a. Predictors: (Constant), BM, ET, PD, SQ, TMS, EI, QIAU, SPPQM Table 23: ANOVA (b)
Model Sum of Squares df Mean Square F Sig. 1 Regression 195.111 8 24.389 4.263 .001(a) Residual 211.693 37 5.721 Total 406.804 45
a. Predictors: (Constant), BM, ET, PD, SQ, TMS, EI, QIAU, SPPQM b. Dependent Variable: RIQM Table 24: Coefficients (a)
Model Unstandardized Coefficients
Standardized Coefficients
t Sig.
B Std.
Error Beta B Std.
Error 1 (Constant) 4.923 3.197 1.540 .132 TMS -.130 .121 -.177 -1.076 .289 SPPQM .319 .334 .210 .955 .346 QIAU .168 .197 .146 .851 .400 ET .070 .206 .057 .341 .735 EI .170 .194 .130 .875 .387 PD .699 .177 .540 3.950 .000 SQ -.476 .267 -.280 -1.783 .083 BM .179 .227 .108 .789 .435
a. Dependent Variable: RIQM
85
Table 21 shows that the regression model explains 36.7% of variability of dependent
variable (RIQM). Analysis of variance (ANOVA) indicates that the model is significant
at α = 0.05 (Table 22). PD emerged as the only statistically significant predictor of RIQM
having p-value 0.000. For all other variables p-value is higher then 0.05. In order to
check is there any other variable that may be significant at an early stage but then lost its
usefulness when additional predictors are brought into the regression model, stepwise
regression analysis is done in the following section.
5.3.2.1: STEPWISE REGRESSION WHEN RIQM IS DEPENDENT VARIABLE Tables 25 – 28 show the results of stepwise regression analysis on RIQM and PD merged
as only significant variable.
Table 25: Variables Entered/Removed (a)
Model Variables Entered Variables Removed Method 1 PD . Stepwise (Criteria: Probability-of-
F-to-enter <= .050, Probability-of-F-to-remove >= .100).
a. Dependent Variable: RIQM Table 26: Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate 1 .603(a) .363 .349 2.42613
a. Predictors: (Constant), PD Table 27: ANOVA (b)
Model Sum of Squares df Mean Square F Sig. 1 Regression 147.816 1 147.816 25.113 .000(a) Residual 258.988 44 5.886 Total 406.804 45
a. Predictors: (Constant), PD b. Dependent Variable: RIQM Table 28: Coefficients (a)
Model Unstandardized Coefficients Standardized Coefficients
B Std. Error Beta
t Sig.
1 (Constant) 6.902 2.034 3.394 .001
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PD .780 .156 .603 5.011 .000 a. Dependent Variable: RIQM PD emerged as the significant variable in this regression model and PD explain 36.3% of
variability of dependent variable (RIQM). ANOVA (analysis of variance) indicate that
model is statistically significant at α = 0.05 (Table 27). Table 28 supports the conclusion
that there is a linear relationship between PD and RIQM.
5.3.1.2: SUMMARY OF RESULT WHEN RIQM IS DEPENDENT VARIABLE The regression models (Tables 21 – 28) in regression analysis on RIQM as dependent
variable revealed that PD is only statistically significant predictor of the RIQM. In
correlation analysis (when CFS is not included in correlation analysis - Table 12) PD has
highest correlation with RIQM. Figure 5.2 shows the framework developed for RIQM on
the basis of correlation and regression analysis.
FIGURE 5.2: FRAMEWORK FOR RESULTS OF IMPLEMENTING QUALITY MANAGEMENT (RIQM)
Process Design (PD) Results of Implementing Quality Management (RIQM)
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CHAPTER 6 – ANALYSIS OF SERVICE QUALITY SURVEY QUESTIONNAIRE
In this chapter, results from the statistical analysis conducted on the data collected from
pharmaceutical retailers are presented. The survey questionnaire was distributed to the
1050 pharmaceutical retailers in two biggest cities of Pakistan (Karachi and Lahore). In
total 413 usable responses were collected back. Response rate (39.3%) is satisfactory.
Section 6.1 of this chapter is about scale purification. Scale purified in this process is
model for customer satisfaction in distributors-retailers interface of pharmaceutical
supply chains in Pakistan.
6.1: SCALE PURIFICATION The first step in the data analysis was to group the questionnaire items according to the 5
service quality dimensions agreed in the focus group discussion. The objective of this
portion of research is to develop service quality measurement scale in the distributors-
retailers interface of pharmaceutical supply chains so the next step was to do
Confirmatory Factor Analysis (CFA). CFA ensures scale unidimensionality. Scale
reliability and construct validity are assessed once the scale unidimensionality is ensured
(Anderson and Gerbing, 1982). The Structural Equation Modeling (SEM) program
AMOS 7.0 was used for data analysis
The covariance matrix between the 5 service quality dimensions was created. Seven runs
of CFA were conducted. The process continued until satisfactory goodness of fit statistics
was obtained. During this process, one dimension (empathy) completely disappeared. In
total, 21 of an initial 31 items were deleted. This intensity of item deletion is not
exceptional in scale development studies as the final scale may contain even one fifth of
the original items (Bienstock et al., 1997). The sequence list of 21 items deleted is given
in Table 29. Each item deleted affects all other items also, so only a few items were
deleted per CFA run. These items were found to be inadequate on model estimates
examination after each CFA run based on the amount of explained variance. The lower
the amount of explained variance for any item, the more poorly it is loaded in the model,
thus making it a choice for deletion from the model.
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Table 29: SEQUENCE WISE LIST OF DELETED ITEMS Sr. No. Item
1. Personnel handling drugs are professional in appearance. 2. All required information is available on invoice provided. 3. Distributors effectively handle the counterfeit drugs issue. 4. Distribution center has office working hours suitable to you. 5. Distributors effectively handle the expired drugs issue. 6. Temperature and humidity are controlled during transportation of drugs. 7. When you have any problem, distributor shows a sincere interest in solving it. 8. Distribution center personnel’s fulfill your specific requirements 9. Distribution center has field staff working hours suitable to you. 10. Distributor provides legal support when needed 11. Order taking methods (including frequency) are accurate. 12. Shipments contain wrong / damaged items. 13. Shipments contain incorrect quantity. 14. Distribution center personnel’s give you individual attention. 15. Methods designed for payments are convenient to you. 16. Vehicles used in transportation are visually in a good condition. 17. Personnel at the distribution center are trained. 18. Order delivery methods (including frequency) are accurate. 19. When distributors promise to deliver by certain time, they do so. 20. Distributors always provide warranty 21. Distributors provide services at short notice (if required).
After the deletion of the 21 items, a scale with 4 dimensions and 10 items emerged
(Figure 6.1).
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FIGURE 6.1: CFA MODEL DEVELOPED USING AMOS 7.0
0.065
90
The scale emerged after CFA was assessed for goodness for fit statistics. Empirical
evidence in CFA is generally assessed using criteria such as the Comparative Fit Index
(CFI), the Root Mean Square Error of Approximation (RMSEA), the significance of
parameter estimates, and the amount of squared multiple correlations (Sila and
Ebrahimpour, 2005).
CFI: This index compares the proposed model with a null model assuming that there are
no relationships between the measures. A CFI value greater then 0.90 indicates an
acceptable fit to the data (Bentler, 1992). CFA model developed in this analysis indicates
CFI value (0.98) which suggests a very good model fit.
RMSEA: RMSEA is an index used to assess residuals and adjusts parsimony in the
model. Its value must be equal to or less than 0.08 for an adequate model fit (Hu and
Bentler, 1999). In the CFA model developed, RMSEA value is 0.065 indicating adequate
model fit.
Parameter estimates: All the factor loadings in the CFA model developed are statistically
significant at 0.001 level of significance.
Amount of squared multiple correlation: The amount of squared multiple correlations for
all dimensions in the model developed range from 0.62 to 0.92 thus indicating acceptable
squared factor loadings.
Once the unidimensionality of the scale developed was demonstrated using CFA, the
reliability of the scale developed was evaluated by the determination of Cronbach’s
coefficient alpha. Reliability coefficients of 0.70 or more are considered adequate
(Cronbach, 1951; Nunnally, 1978). The overall value of Cronbach’s coefficient alpha for
the 10 items in the scale developed after CFA is 0.91. This value is acceptable. Each sub-
scale also has Cronbach’s coefficient alpha value above 0.70.
TABLE 30: RELIABILITY ANALYSIS
Construct/Dimension No. of items Cronbach’s Alpha Tangible 03 0.94 Responsiveness 02 0.87
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Assurance 03 0.85 Reliability 02 0.92 However as mentioned in chapter five, according to Mentzer et al. (1999), Cronbach’s
coefficient alpha is a meaningless calculation with a two or less item scale, since its
purpose is to compare each item to the remaining items in the scale as a group. So, Item
to Total Correlations (ITC) was evaluated for the sub-scales “reliability” and
“responsiveness” as these sub-scales has only two items. All these values are above 0.70
so all ITC values are acceptable.
TABLE 31: ITEM TO TOTAL CORRELATIONS
Construct Item to total correlation for item 1
Item to total correlation for item 2
Responsiveness 0.863** 0.870** Reliability 0.887** 0.905** After assessing unidimensionality and reliability, the next issue was to assess content,
convergent and discriminant validity of the scale developed. Content validity depends on
how well the researchers created measurement items using the relevant literature to cover
the content domain of the variable being measured (Nunnally, 1978). The evaluation of
content validity is therefore a judgmental process not open to numerical evaluation
(Mahour, 2006). As mentioned previously the selection of dimensions and items in this
study was based on the Parasuraman et al. (1988) service quality measurement scale
extensively used in published service quality literature. Subsequent refinement of this
widely used scale occurred through focus group discussion with representatives of
pharmaceutical retailers. The instrument thus has strong content validity.
Convergent validity measures the extent to which different approaches to measuring a
construct produces the same results (Ahire et al., 1996). A value of 0.60 or higher for all
factor loadings in CFA model developed demonstrates strong convergent validity (Chin
et al., 1996). In the CFA model developed, all the factor loadings ranged from 0.79 to
0.96 so all items in the scale developed have strong convergent validity.
Discriminant validity measures the degree to which a construct and its indicators are
different from another construct and its indicators (Bagozzi et al., 1991). Evidence of
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discriminant validity can be assessed in multiple ways (Mentzer et al., 1999). One of the
ways is by comparing the Cronbach’s alpha of a construct to its correlations with other
model variables (Sila and Ebrahimpour, 2005). According to Ghiselli et al. (1981), if the
value of alpha is sufficiently larger than the average of its correlations with other
variables, this is evidence of discriminant validity. The difference between the alpha
value of each construct and the average correlation of each construct with the other
constructs was adequately large (reliability = 0.43, assurance = 0.32, tangibles = 0.39,
responsiveness = 0.38). According to Sila and Ebrahimpour (2005) all these values are
acceptable for discriminant validity. Table 32 indicates that all the dimensions emerged
in scale developed are significantly correlated with each other.
TABLE 32: CORRELATION AMONG ALL DIMENSIONS EMERGED
CONSTRUCTS TAN RESP ASSU RELI
TAN
r p n
1.000 .
396
.380(**) .000 381
.464(**) .000 381
.509(**) .000 373
RESP
r p n
1.000 .
384
.594(**) .000 380
.437(**) .000 374
ASSU
r p n
1.000 .
386
.423(**) .000 376
RELI
r p n
1.000 .
377** Correlation is significant at the 0.01 level (2-tailed). Assessment of unidimensionality using goodness of fit statistics, scale reliability,
construct validity (content validity, convergent validity and discriminant validity) and
correlation analysis therefore confirmed that the model which emerged during CFA
(Figure 6.1) is good model. It has 4 dimensions (reliability, assurance, tangibles,
responsiveness) and 10 items. This model constitutes a service quality scale for
measurement of service quality in the distributors-retailers interface of pharmaceutical
supply chains in Pakistan. The list of 10 items which emerged in the CFA model (Figure
6.1) is given in Table 33.
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TABLE 33: DIMENSIONS AND ITEMS CONSTITUTING THE DEVELOPED SCALE Sr. No. Item RELIABILITY
1. Records are kept confidential. 2. Payment information is kept confidential
ASSURANCE 3. Personnel in the distribution center are consistently courteous with you. 4. Personnel in the distribution center have the knowledge to answer your
queries. 5. Personnel in the distribution center have the authority to solve your
problems. TANGIBLES
6. Distribution center has modern equipment (Computers, air-conditioning etc.).
7. Distributor has sufficient physical facilities for storing drug products. 8. The physical facilities at distribution center are visually clean.
RESPONSIVENESS 9. Distributor responds immediately to your enquiries. 10. Distributor responds immediately to your complaints.
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CHAPTER 7 – DISCUSSION AND CONCLUSION
The objective of this research is to develop a pharmaceutical distribution model for
customer satisfaction. Customer satisfaction can be achieved only if both internal and
external customers are satisfied. In chapter 2, it is concluded that TQM implementation
increases customer satisfaction as TQM is management philosophy based on customer
satisfaction. In literature review chapters it is also concluded that service quality is an
antecedent of customer satisfaction so customer satisfaction can be increased by
improving service quality. This research is thus divided into two sections as stated in
chapter four. Data related to research questions 1 and 2 is analyzed in chapter five. Data
related to research question 3 is analyzed in chapter six. This chapter is divided into three
sections. In section 7.1, results from TQM survey questionnaire are discussed / concluded
and in section 7.2 results related to service quality survey questionnaire are discussed /
concluded. In section 7.3 limitations of this research and suggestions for future research
are presented.
7.1: DISCUSSION / CONCLUSION OF TQM SURVEY QUESTIONNAIRE RESULTS
The first two questions for this research are:
Does TQM implementation relates directly to the customer satisfaction in pharmaceutical
distribution companies in Pakistan?
What are the critical success factors of TQM in pharmaceutical distribution companies in
Pakistan?
Correlation analysis among all variables (Table 11) indicates that variable customer
orientation (CFS) is significantly correlated with only two variables i.e. results of
implementing quality management (RIQM) and process design (PD). However in
regression and stepwise regression analysis only process design (PD) emerged as
significant predictor of customer orientation (CFS). Variable results of implementing
quality management (RIQM) has the highest correlation with dependent variable
customer orientation (CFS) but this variable has not emerged in the stepwise regression
95
model. Since variable results of implementing quality management (RIQM) has
significant correlation with variable process design (PD) also it may be concluded that
most of the variability explained by results of implementing quality management (RIQM)
has been explained by process design (PD). Therefore it is concluded that two variables
have a significant role in the development of a theoretical framework for customer
orientation (CFS). These variables are process design (PD) and results of implementing
quality management (RIQM). Process design (PD) has direct role as it emerged as a
single significant variable in the stepwise regression. Results of implementing quality
management (RIQM) has indirect role as it is significantly correlated with both customer
orientation (CFS) and process design (PD) as the variability explained by variable results
of implementing quality management (RIQM) has already been explained by variable
process design (PD). Therefore it may be suggested that TQM implementation only
relates indirectly to the customer satisfaction in pharmaceutical distribution companies in
Pakistan.
The results related to the second question when results of implementing quality
management (RIQM) is dependent variable, indicate that only construct “process design”
(PD) has a vital role in shaping TQM in pharmaceutical distribution companies in
Pakistan. Though the literature (Karuppusami and Gandhinathan, 2006; Flynn et al.,
1995; Sila and Ebrahimpour, 2002) provides strong support for “process design” in
effective implementation of TQM in organizations, it is note worthy that top management
support (TMS) (the most critical success factor identified in the literature review) did not
emerge as a significant factor in regression or stepwise regression analysis. Top
management support (TMS) was even not correlated significantly to the dependent
variable results of implementing quality management (RIQM). It may be argued that the
dependent variable is significantly correlated with employee training (ET), which is
significantly correlated with top management support (TMS) so indirectly top
management support (TMS) is correlated with dependent variable. However this is not
enough reason to conclude that top management support (TMS) has an indirect effect on
dependent variable results of implementing quality management (RIQM) because
96
employee training (ET) did not emerge as a significant factor in regression or stepwise
regression analysis.
Previous studies related to issues and / or barriers in TQM implementation issues in
developing countries (Djerdjour and Patel, 2002; Temtime and Solomon, 2002; AL-
Khalifah and Aspinwall, 2000 and Mersha, 1999) have concluded that top management in
developing countries is not committed to TQM. Pakistan is also a developing country, so
it may be suggested that as far as the commitment of top management for implementing
TQM is concerned, the pharmaceutical distribution companies of Pakistan are not an
exception from most of previous TQM studies undertaken in other developing countries
because top management support (TMS) did not emerge as critical success factor in this
study. As only one construct emerged as the significant factor in this study and direct
relationship of TQM to customer satisfaction could not be established, it is concluded that
TQM has not been yet incorporated in the strategic and long term plans of pharmaceutical
distribution companies in Pakistan. To satisfy the customers, pharmaceutical distributors
have to recognize and implement TQM as an operational and business level strategy.
7.2: DISCUSSION / CONCLUSION OF SERVICE QUALITY SURVEY QUESTIONNAIRE RESULTS The third question for this research is:
- Which are the important service quality dimensions and items in distributors-
retailers interface of pharmaceutical supply chains in Pakistan?
This research resulted in the development of a valid and reliable scale for measuring
service quality in the distributors-retailers interface of pharmaceutical supply chains in
Pakistan. The literature review concluded that despite of wide acceptance of the
“American perspective” of service quality proposed by Parasuraman et al. (1988), service
quality measurement must be adapted to fit the context as there is no universal set of
dimensions and items that determine the service quality across a section of industries and
cultures. The findings of this research confirms this conclusion as the service quality
measurement scale developed in this research (figure 6.1) has four service quality
97
dimensions only and the dimension “empathy” proposed by Parasuraman et al. (1988)
did not emerge as a significant dimension in the scale developed in this study.
7.3: LIMITATION AND SUGGESTIONS FOR FUTURE RESEARCH: Like all other studies, this both sections of this research have certain limitations. In
section related to TQM survey, the data was obtained through a postal survey and relied
on the perceptions of the respondents. The response size of the study was also small
(N=51) though the response rate and significance were high. Small response size
prevents more complex analysis such as structural equation modeling. Such analysis may
need to be conducted with larger response sizes in the future. Similarly for section of
research related to service quality scale development, the data was obtained from those
pharmaceutical retailers only which were on the panel of the pharmaceutical distributors
supporting this research. There may be pharmaceutical retailers which are not on this
panel and therefore may be excluded from the survey sample. This study was limited to
the 2 biggest cities of Pakistan only. For pharmaceutical retailers working in small cities,
service quality dimensions may be different from those identified in this research.
Nonetheless, this study may be a good foundation for future research in several ways as
this study attempted to focus on both internal and external customer’s satisfaction aspects
for pharmaceutical distribution companies. This study identified that “process design” is
the critical success factor in implementation of TQM in pharmaceutical distribution
companies in Pakistan. In investigating the perception of chief executives in
pharmaceutical distribution companies regarding “process design”, qualitative studies are
recommended so that the reasons for emergence of “process design” as the only critical
success factor may be identified. It is possible that because of high regulatory
requirements in the pharmaceutical distribution sector, the companies may have to focus
more on “process design”. Studies should also be conducted in pharmaceutical
distribution companies in other countries to see if “process design” is as significant
elsewhere for this sector. Pharmaceutical distribution is an integral part of pharmaceutical
supply chains so future research can also examine critical success factors of TQM in
pharmaceutical manufacturing and retailing companies, so that pharmaceutical supply
98
chain specific critical success factors of TQM may be identified. Because this study is the
first known study on the identification of critical success factors of TQM in Pakistan,
future research should be undertaken as well in other business sectors in Pakistan so that
generalizations can be made about critical success factors of TQM in companies in
Pakistan specifically and perhaps for developing countries generally. Though being
based in a previously neglected country and sector this study provides a significant
contribution to the literature about TQM in developing countries. It also identifies
considerable scope for TQM critical success factor studies in Pakistan and other
developing countries to provide better conceptualization and understanding of practice of
TQM.
The findings of second portion of this study should be useful for both practitioners and
researchers. Practitioners (pharmaceutical distributors) can use this service quality
measurement scale to evaluate the extent of service quality they provide to their
customers (pharmaceutical retailers) and to spot those dimensions and items of service
quality where their organizations require improvement for satisfaction of their customers
(pharmaceutical retailers). The model developed (figure 6.1) can be recognized as good
model for satisfaction of customers of pharmaceutical distribution companies. For
researchers, second portion of study contributes significantly to the existing supply chains
specific service quality scale development literature by developing a service quality
measurement scale for a previously neglected sector. This study identified that “empathy”
is not a critical dimension of service quality in distributors-retailers interface of
pharmaceutical supply chains in Pakistan. In investigating the perception of
pharmaceutical retailers regarding the dimension “empathy”, qualitative studies are
recommended so that the reasons for non emergence of “empathy” as the significant
service quality dimension may be identified. Studies could also be conducted in the
distributors-retailers interface of pharmaceutical supply chains in other cities of Pakistan
and in other countries to see whether the service quality dimensions and items identified
in this study are significant elsewhere in such situations. By building up the number of
such studies more concrete generalizations can be made.
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APPENDIX A: RAO ET AL. (1999) QUESTIONNAIRE
Instructions: Please respond to the following questions by circling one of the numbers [1] to [5] or [x] to the right of the question. The numbers represent the strength or degree of your assessment, agreement, perception or opinion, as the case may be, to the question item. Scale: [x] Unable to respond [5] Very High [4] High [3] Medium [2] Low [1] Very Low I. TOP MANAGEMENT SUPPORT Extent to which the top company executive assumes responsibility for quality performance x 5 4 3 2 1 Acceptance of responsibility for quality by major department heads with in the company x 5 4 3 2 1 Degree of participation by top management in the quality improvement process x 5 4 3 2 1 Extent to which the top management has objectives for quality performance x 5 4 3 2 1 Extent to which quality goals are made specific within the company x 5 4 3 2 1 Importance attached to quality by the top management in relation to cost and schedule objectives x 5 4 3 2 1 Amount of review of quality issues in the top management meetings x 5 4 3 2 1 II. STRATEGIC PLANNING PROCESS OF QUALITY MANAGEMENT Extent to which quality management is considered in the company strategic plan x 5 4 3 2 1 Extent to which customer satisfaction is considered in the company strategic plan x 5 4 3 2 1 Extent to which top management supports long-term quality improvement process x 5 4 3 2 1 Extent to which quality goals and policy are understood within the company x 5 4 3 2 1 III. QUALITY INFORMATION AVAILABILITY. Availability of quality data (error rate, defect rates, scrap, rework, return, etc) x 5 4 3 2 1 Extent to which necessary quality data is available on time x 5 4 3 2 1 Extent to which quality data are available to managers and supervisors x 5 4 3 2 1 IV. QUALITY INFORMATION USAGE Extent to which necessary quality data is available to hourly employee x 5 4 3 2 1 Extent to which quality data is used by top management in decision making x 5 4 3 2 1 Extent to which quality data is used by hourly workers in their operations x 5 4 3 2 1 V. EMPLOYEE TRAINING Extent to which quality-related training is given to hourly employees through the company/division x 5 4 3 2 1 Extent to which training in the basic statistical technique (such as histograms and control charts) is provided in the company/division as a whole x 5 4 3 2 1 Availability of resources for employee training in the company/division x 5 4 3 2 1
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Extent to which training in specific work skills (technical and vocational) is given to employees throughout the company x 5 4 3 2 1 VI. EMPLOYEE INVOLVEMENT Effectiveness of employee involvement program in the company/division x 5 4 3 2 1 Extent to which hourly/non-supervisory employee participate in quality decisions x 5 4 3 2 1 Extent to which employee are held responsible for the output of their process x 5 4 3 2 1 Extent to which quality awareness building among employee is ongoing x 5 4 3 2 1 Extent to which the company/division measure employee morale x 5 4 3 2 1 VII. PRODUCT/PROCESS DESIGN Extent to which new product/service design is reviewed before the product/service is produces x 5 4 3 2 1 Clarity of product/service specification x 5 4 3 2 1 Clarity of product/service procedures x 5 4 3 2 1 Extent to which implementation/producibility is considered in the product/service design process x 5 4 3 2 1 Extent to which process design minimizes the chances of employee errors x 5 4 3 2 1 VIII. SUPPLIER QUALITY Extent to which suppliers are selected based on quality rather than price x 5 4 3 2 1 Degree to which your company relies on few dependable suppliers x 5 4 3 2 1 Extent to which your company provides technical assistance to your suppliers x 5 4 3 2 1 Extent to which the supplier is involved in your product development process x 5 4 3 2 1 Extent to which you build long term relationship with your suppliers x 5 4 3 2 1 Clarity of specifications provided to your suppliers x 5 4 3 2 1 IX. CUSTOMER ORIENTATION Extent to which your company/division is totally committed to create satisfied customers x 5 4 3 2 1 Extent to which your company’s goals exceed customers’ expectation x 5 4 3 2 1 Extent to which executives demonstrate with their actions that customer satisfaction is important x 5 4 3 2 1 Extent to which employees know which attributes of the products or services your company’s customer value most x 5 4 3 2 1 Extent to which information from customers is used is designing company’s products and service x 5 4 3 2 1 Extent to which top management frequently contacts customers x 5 4 3 2 1 Extent to which the customers’ complaints are resolved x 5 4 3 2 1 Extent to which employees are encouraged to satisfy customers x 5 4 3 2 1 X. QUALITY CITIZENSHIP Extent to which public health issues are considered as a company/division responsibility x 5 4 3 2 1 Extent to which public safety issues are considered as a company/division responsibility x 5 4 3 2 1 Extent to which environmental issues are considered as a company/division responsibility x 5 4 3 2 1
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Extent to which organization extends its quality commitment to the external community x 5 4 3 2 1 XI. BENCHMARKING Extent to which company/division studies the best practices of other companies to about how to do things better x 5 4 3 2 1 Extent to which your company/division compares the current quality levels for products and services features with those of competitors x 5 4 3 2 1 Extent to which your company/division compares the current quality levels for products and services features with those of the world leaders x 5 4 3 2 1 Extent to which your company/division compares the current quality levels for products and services features with those of competitors x 5 4 3 2 1 XII. INTERNAL QUALITY RESULTS Extent to which scrap levels have been reduced by quality management x 5 4 3 2 1 Extent to which rework levels have been reduced by quality management x 5 4 3 2 1 Extent to which your company’s manufacturing throughput times has been reduced by quality management x 5 4 3 2 1 Extent which productivity of your company has been increased by quality management x 5 4 3 2 1 Extent to which costs of your company have been reduced by quality management x 5 4 3 2 1 XIII. EXTERNAL QUALITY RESULTS Extent to which customer complaints have been reduced by quality management x 5 4 3 2 1 Extent to which the competitive position of your company/division has been enhanced by quality management x 5 4 3 2 1 Extent to which quality management has contributed to keeping your company/division in business x 5 4 3 2 1 Extent to which profits of your company/division have been increased by quality management x 5 4 3 2 1
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APPENDIX B: REFINED QUESTIONNAIREUSED IN THIS RESEARCH ASSESSMENT OF TQM IMPLEMENTATION Instructions: Please respond to the following questions by circling one of the numbers [1] to [5] or [U] Scale: [1] Very Low [2] Low [3] Medium [4] High [5] Very High [U] Unable to respond I. TOP MANAGEMENT SUPPORT Level to which the top management assumes responsibility for quality performance 1 2 3 4 5 UDegree of participation by top management in the quality improvement process 1 2 3 4 5 ULevel to which quality goals are made specific within the company 1 2 3 4 5 UImportance attached to quality by the top management in relation to cost and schedule objectives 1 2 3 4 5 UFrequency of analysis of quality issues by the top management 1 2 3 4 5 UII. STRATEGIC PLANNING PROCESS OF QUALITY MANAGEMENT Level to which quality management is considered in the company strategic plan 1 2 3 4 5 ULevel to which customer satisfaction is considered in the company strategic plan 1 2 3 4 5 UIII. QUALITY INFORMATION (AVAILABILITY & USAGE). Level to which necessary quality data is available on time to managers and supervisors 1 2 3 4
5 U
Level to which necessary quality data is available on time to Customers 1 2 3 4 5 ULevel to which quality data is used by top management in decision making 1 2 3 4 5 ULevel to which quality data is used by workers in their operations 1 2 3 4 5 UIV. EMPLOYEE TRAINING Level to which quality-related training is given to employees 1 2 3 4 5 UAvailability of adequate resources for employee training 1 2 3 4 5 ULevel to which training in specific work skills (technological and professional) is given to employees 1 2 3 4 5 UV. EMPLOYEE INVOLVEMENT Effectiveness of employee involvement program in the company 1 2 3 4 5 ULevel to which workers participate in quality decisions 1 2 3 4 5 ULevel to which employee are held responsible for the output of their process 1 2 3 4 5 ULevel to which quality awareness building among employee is constant 1 2 3 4 5 UVI. PROCESS DESIGN Level to which new service design is reviewed before the service is provided 1 2 3 4 5 ULevel to which implementation is considered in the service design process 1 2 3 4 5 ULevel to which process design minimizes the chances of employee errors 1 2 3 4 5 U
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VII. SUPPLIER QUALITY Level to which the supplier is involved in your service development process 1 2 3 4 5 ULevel to which you build long term relationship with your suppliers. 1 2 3 4 5 UVIII. CUSTOMER ORIENTATION Level to which your company/division is totally committed to create satisfied customers. 1 2 3 4 5 ULevel to which executives demonstrate with their actions that customer satisfaction is important. 1 2 3 4 5 ULevel to which employees know which attributes of the services your company’s customer value most. 1 2 3 4 5 ULevel to which information from customers is used is designing company’s policy. 1 2 3 4 5 ULevel to which the customers’ complaints are resolved. 1 2 3 4 5 ULevel to which employees are encouraged to satisfy customers. 1 2 3 4 5 UIX. BENCHMARKING Level to which company studies the best practices of other companies to about how to do things better. 1 2 3 4 5 ULevel to which your company compares the current quality levels with those of competitors. 1 2 3 4 5 UX. RESULTS OF IMPLEMENTING QUALITY MANAGEMENT Level to which costs of your company have been reduced by quality management. 1 2 3 4 5 ULevel to which customer complaints have been reduced by quality management implementation. 1 2 3 4 5 ULevel to which the competitive position of company has been enhanced by quality management. 1 2 3 4 5 ULevel to which profits of your company/division have been increased by quality management. 1 2 3 4 5 U
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APPENDIX C: COVER LETTER SEND TO PHARMACEUTICAL DISTRIBUTORS
No.: D/653/IQTM
Date: 03.11.2006
----------------------------- ----------------------------- ----------------------------- Subject: SURVEY QUESTIONNAIRE
Dear Sir,
Mr. Muhammad Usman Awan is doing his Ph.D. studies at this institute. Title of his Ph.D. research is “Development of Pharmaceutical Distribution Model for Customer Satisfaction”. The attached questionnaire for this study has been prepared in collaboration with Institute for Retail Studies, University of Stirling, UK. The attached questionnaire will help us in estimating the level of Quality Management implementation at your organization. Your response will be treated as confidential and no individual or company will be identified in any way to any one. We will be glad to send you a complimentary copy of the project report when it is ready. Since this is pure academic work, your earliest response will be highly appreciated. Thanks & best regards
Dr. Niaz Ahmad Professor & Co-Supervisor
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APPENDIX D: PARASURAMAN ET AL. (1988) SERVICE QUALITY DIMENSIONS AND ITEMS
S.No DIMENSIONS ITEMS 1. Tangibles They should have up-to-date equipment. 2. - do - Their physical facilities should be visually appealing. 3. - do - Their employees should be well dressed and appear neat. 4. - do - The appearance of the physical facilities of these firms
should be in keeping with the type of services provided. 5. Reliability When these firms promise to do something by a certain
time, they should do so. 6. - do - When customers have problems, these firms should be
sympathetic and reassuring. 7. - do - These firms should be dependable. 8. - do - They should provide their services at the time they promise
to do so. 9. - do - They should keep their records accurately. 10. Responsiveness They shouldn't be expected to tell customers exactly when
services will be performed. 11. - do - It is not realistic for customers to expect prompt service
from employees of these firms. 12. - do - Their employees don't always have to be willing to help
customers. 13. - do - It is okay if they are too busy to respond to customer
requests promptly. 14. Assurance Customers should be able to trust employees of these firms.
15. - do - Customers should be able to feel safe in their transactions
with these firms' employees. 16. - do - Their employees should be polite.
17. - do - Their employees should get adequate support from these
firms to do their jobs well. 18. Empathy These firms should not be expected to give customers
individual attention. 19. - do - Employees of these firms cannot be expected to give
customers personal attention. 20 - do - It is unrealistic to expect employees to know what the needs
of their customers are. 21. - do - It is unrealistic to expect these firms to have their customers'
best interests at heart. 22. - do - They shouldn't be expected to have operating hours
convenient to all their customers.
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APPENDIX E: SERVICE QUALITY QUESTIONNAIRE ITEMS (ALONG WITH DIMENSIONS AND ABBREVIATIONS USED IN ANALYSIS)
S.No Item Dimension along with Abbreviation used In
Analysis 1. Distribution center has modern equipment
(Computers, air-conditioning etc.). Tangible (TAN1)
2. Distributor has sufficient physical facilities for storing drug products.
Tangible (TAN2)
3. The physical facilities at distribution center are visually clean.
Tangible (TAN3)
4. Vehicles used in transportation are visually in a good condition.
Tangible (TAN4)
5. Personnel handling drugs are professional in appearance.
Tangible (TAN5)
6. Personnel at the distribution center are trained. Assurance (ASS1) 7. Temperature and humidity are controlled during
transportation of drugs. Reliability (REL1)
8. Order taking methods (including frequency) are accurate.
Assurance (ASS2)
9. Order delivery methods (including frequency) are accurate.
Assurance (ASS3)
10. When distributors promise to deliver by certain time, they do so.
Responsiveness (RES1)
11. When you have any problem, distributor shows a sincere interest in solving it.
Reliability (REL2)
12. Shipments contain wrong / damaged items. Reliability (REL3) 13. Shipments contain incorrect quantity. Reliability (REL4) 14. Distributors effectively handle the expired drugs
issue. Reliability (REL5)
15. Distributors effectively handle the counterfeit drugs issue.
Reliability (REL6)
16. Distributors respond immediately to your enquiries. Responsiveness (RES2) 17. Distributors respond immediately to your
complaints. Responsiveness (RES3)
18. Distributors provide services at short notice (if required)
Responsiveness (RES4)
19. Personnel in the distribution center are consistently courteous with you
Assurance (ASS4)
20. Personnel in the distribution center have the knowledge to answer your queries.
Assurance (ASS5)
21. Personnel in the distribution center have the authority to solve your problems.
Assurance (ASS6)
22. Distribution center personnel’s give you individual Empathy (EMP1)
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S.No Item Dimension along with Abbreviation used In
Analysis attention
23. Distribution center personnel’s fulfill your specific requirements
Empathy (EMP2)
24. Distribution center has office working hours suitable to you.
Empathy (EMP3)
25. Distribution center has field staff working hours suitable to you.
Empathy (EMP4)
26. Methods designed for payments are convenient to you.
Empathy (EMP5)
27. All required information is available on invoice provided
Reliability (REL7)
28. Records are kept confidential. Reliability (REL8) 29. Payment information is kept confidential Reliability (REL9) 30. Distributors always provide warranty Assurance (ASS7) 31. Distributors provide legal support when needed Reliability (REL10)
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APPENDIX F: COVER LETTER SEND TO PHARMACEUTICAL RETAILERS
No.: D/1119/IQTM
Date: 14.05.2007
----------------------------- ----------------------------- ----------------------------- Subject: SURVEY QUESTIONNAIRE
Dear Sir,
Institute of Quality and Technology Management, University of the Punjab in collaboration with Institute for Retail Studies, University of Stirling, UK is doing a research related to service quality in pharmaceutical supply chains in Pakistan. Objective of this research is to develop a service quality scale in distributors-retailers interface of pharmaceutical supply chains.
The attached questionnaire will help us in developing this service quality scale. Your response will be treated as confidential and no individual or company will be identified in any way to any one. The information provided will be used for research purposes only. Thanks & best regards
Dr. Niaz Ahmad Professor & Co-Supervisor
