COMMITMENT TO CHANGE IN PHARMACY SCHOOLS: 
DOES LEADERSHIP MATTER? 
 
Except where reference is made to the work of others, the work described in this 
dissertation is my own or was done in collaboration with my advisory committee.  This 
does not include proprietary or classified information. 
 
____________________________ 
Mohammad Waheedi 
 
Certificate of Approval: 
 
____________________________  ____________________________ 
Kenneth N. Barker    Bruce A. Berger, Chair 
Professor     Professor 
Pharmacy Care Systems   Pharmacy Care Systems 
 
____________________________  ____________________________ 
Bill G. Felkey     Anthony J. Guarino 
Professor     Associate Professor 
Pharmacy Care Systems Educational Foundations, 
Leadership, and Technology 
 
 
____________________________  ____________________________ 
Stanley G. Harris    Kem P. Krueger 
Professor     Associate Professor 
Management     Pharmacy Care Systems 
 
____________________________ 
Stephen L. McFarland 
Dean 
Graduate School 
COMMITMENT TO CHANGE IN PHARMACY SCHOOLS:  
DOES LEADERSHIP MATTER? 
 
Mohammad Waheedi 
 
 
 
A Dissertation 
Submitted to 
the Graduate Faculty of 
Auburn University 
in Partial Fulfillment of the 
Requirements for the 
Degree of 
Doctor of Philosophy 
 
 
 
Auburn, Alabama 
December 16, 2005 
COMMITMENT TO CHANGE IN PHARMACY SCHOOLS:  
DOES LEADERSHIP MATTER? 
 
 
 
Mohammad Waheedi 
 
Permission is granted to Auburn University to make copies of this dissertation at its 
discretion, upon the request of individuals or institutions and at their expense.  The author 
reserves all publication rights. 
 
      ____________________________ 
      Signature of Author 
 
      ____________________________ 
      Date 
 iii
DISSERTATION ABSTRACT 
COMMITMENT TO CHANGE IN PHARMACY SCHOOLS:  
DOES LEADERSHIP MATTER? 
 
Mohammad Waheedi 
Doctor of Philosophy, December 16, 2005 
(M.S., Auburn University, Alabama 2002) 
(B.S. in Pharmacy, University of Toledo, Ohio, 1997) 
 
207 Typed Pages 
Directed by Bruce A. Berger 
 
The challenges of achieving the new vision in pharmacy education have been 
cited as an important reason for advocating transformational leadership as the kind of 
educational leadership that is required to assist the pharmacy profession in creating a 
patient centered practice.  Based upon Bass?s transformational,  transactional, and laissez-
faire model of leadership, change leader behaviors and follower involvement in the 
change were hypothesized to determine followers? commitment to organizational change 
and commitment outcomes. A total of 190 faculty members in 24 US pharmacy schools 
undergoing substantive changes participated in this study.  Results from structural 
equation modeling analysis revealed that faculty members? recognition of the value of the 
change (affective commitment) and their sense of duty in supporting the change 
 iv
(normative commitment) were best predicted by their level of involvement in the change 
(participation in decision making, communication, and freedom to express doubts), rather 
than by the transformational behaviors of the change leader. Transactional contingent 
reward behaviors strongly predicted change involvement, and indirectly predicted 
affective and normative commitments.  In addition, affective commitment was 
diminished by avoidant behaviors of the change leader (failure to intervene when 
problems become serious), and normative commitment was diminished by the leader?s 
active management by exception behaviors (monitoring subordinates? failures).  Faculty 
members? behavioral support of the change had strong positive associations with both 
their affective and normative commitments.  Implications of these results for research and 
practice are also discussed.
 
 v
ACKNOWLEDGEMENTS 
 
I want to thank the faculty members who served on this dissertation committee for 
their support, conversations, and insights.  In particular, to Dr. Bruce A. Berger, many 
thanks for his guidance not only through the dissertation process, but also through my 
spiritual journey. He provided spiritual and emotional support when it was needed the 
most.  I am indebted to him for leaving graduate school a better person.  Thank you to Dr. 
Kenneth N. Barker, who started me on this process as my advisor, who believed in me 
despite all the troubles I had earlier in my graduate work, and set me on the right course.  
To Mr. Bill G. Felkey, thank you for your generosity and your continuous offering of 
help, whenever and in whatever I or my family needed.  To Dr. Kem P. Krueger, thank 
you for your presence and for providing the role model for what a teacher and colleague 
should be.  To Dr. Stanley G. Harris, thank you for opening the doors to me at the 
Department of Management, and serving as a patient and caring advisor to me on the 
topic, despite your profound expertise and my novice enthusiasm.  To Dr. Anthony J. 
Guarino, thank you for proving (p = 0.000) to me that genius and coolness can mix. 
Beside my dissertation committee members, this work would not have been 
completed without the help of Dean Lee Evans.  Thank you for the enjoyable and useful 
conversations and thank you for taking the risks so I did what I needed to do. 
 vi
For the staff of the Department of Pharmacy Care Systems, thank you to Tammy 
Hollis for the encouragement and the readiness to tackle any logistic problem I was faced 
with.  Thank you to Bobbi Gistarb for the assistance and support. 
Thank you to the graduate students for their friendship, kind words, and 
encouragement. 
And finally, but most importantly, thank you to my family: Rabab, Hasan, and 
Hussein, who have shared their life with this project and supported me to pursue my 
desire to complete this work.  I can imagine what you have been through living with a 
person that reads and study continuously.  I hope I can offer you the same kind of support 
in return.
 vii
Style manual or journal used: Publication Manual of the American Psychological 
Association Fifth edition.  
Computer software used: MS Word, MS Excel, MS FrontPage, MS Access, 
Javascript, Endnotes, SPSS 12, AMOS 5. 
  
 viii
TABLE OF CONTENTS 
LIST OF TABLES......................................................................................................................... xii 
LIST OF FIGURES ...................................................................................................................... xiii 
1.   INTRODUCTION ......................................................................................................................1 
1.1. Background and Motivation..................................................................................................1 
1.2. Problem Statement ................................................................................................................5 
1.3. Significance...........................................................................................................................6 
1.4. Summary of Methods ............................................................................................................7 
2.   REVIEW OF THE LITERATURE...........................................................................................10 
2.1. Commitment to Organizational Change..............................................................................10 
2.3 The Transformational Leadership Theory............................................................................15 
2.3.1. Transactional Leadership.............................................................................................20 
2.3.2. Transformational Leadership.......................................................................................21 
2.3.3. Laissez-faire ................................................................................................................25 
2.4. Change Involvement ...........................................................................................................25 
3.   STATEMENT OF THE PROBLEM ........................................................................................30 
3.1. Problem Statement ..............................................................................................................30 
3.2. Research Questions .............................................................................................................31 
3.3. Hypotheses ..........................................................................................................................31 
3.4. Concepts and Definitions ....................................................................................................34 
4. METHODS .................................................................................................................................41 
4.1. First Phase: Identifying a Change and a Change Leader.....................................................41 
4.1.1. Population and Sampling.............................................................................................41 
4.1.2. Data Collection Method...............................................................................................43 
4.1.3. Pre-test.........................................................................................................................45 
 ix
4.1.4. Data Analysis Methods................................................................................................45 
4.1.5. Validity........................................................................................................................48 
4.1.6. Response Rate .............................................................................................................48 
4.1.7. Changes Identified and their Change Leaders .............................................................49 
4.2. Phase 2: Change Leaders? Survey .......................................................................................50 
4.2.1. Population and Sampling.............................................................................................50 
4.2.2. Data Collection Method...............................................................................................51 
4.2.3. Pre-test.........................................................................................................................52 
4.2.5. Response Rate .............................................................................................................53 
4.2.6. Results .........................................................................................................................54 
4.3. Phase 3:  Determining the Interrelations Among the Study?s Variables .............................56 
4.3.1. Population and Sampling.............................................................................................56 
4.3.2. Data Collection Method...............................................................................................57 
4.3.3. Measures......................................................................................................................57 
4.3.4. Pre-test.........................................................................................................................63 
4.3.5. Data Analysis Methods................................................................................................63 
5. RESULTS ...................................................................................................................................65 
5.1. Response Rate .....................................................................................................................65 
5.2. Sample Description .............................................................................................................66 
5.3. Missing Data .......................................................................................................................73 
5.4. Score Reliability..................................................................................................................74 
5.5. Measurement Models ..........................................................................................................79 
5.6. Hypothesis Testing..............................................................................................................83 
6. DISCUSSION.............................................................................................................................94 
6.1. General Findings .................................................................................................................94 
6.1.1. Research Question 1 ....................................................................................................96 
6.1.2. Research Question 2 ..................................................................................................102 
6.1.3. Research Question 3 ..................................................................................................104 
 x
6.1.4. Research Question 4 ..................................................................................................107 
6.2. Limitations ........................................................................................................................108 
6.3. Implications.......................................................................................................................113 
6.3.1. Practical Implications ................................................................................................113 
6.3.2. Implications for Theory and Research.......................................................................116 
7. REFERENCES .........................................................................................................................118 
8. APPENDICES ..........................................................................................................................123 
Appendix A:  Invitation E-mail to Participate in the Phase 1 of the Study ..............................124 
Appendix B:  The Phase 1 Survey............................................................................................127 
Appendix C:  Screenshots of the Phase 1 Internet Survey .......................................................130 
Appendix D:  Follow-up E-mail to Non-respondent Schools ..................................................134 
Appendix E:  Reminder E-mail for Phase 1 .............................................................................136 
Appendix F:  Sample Invitation E-mail to Participate in Phase 2 ............................................138 
Appendix G:  Sample Informed Consent Letter Attached to E-mail Invitations in Phase 2 ....140 
Appendix H:  The Phase 2 Internet Survey ..............................................................................143 
Appendix I:  Information Letter E-mail for Phase 3 Internet Survey.......................................145 
Appendix J:  Reminder E-mail for Phase 3..............................................................................148 
Appendix K:  Phase 3 Faculty Questionnaire...........................................................................150 
Appendix L:  Screenshots of the Phase 3 Internet Survey........................................................155 
Appendix M:  Structural Equation Modeling (SEM) Results for Leadership Effects on 
Affective Commitment ......................................................................................160 
Appendix N:  SEM Results for Leadership Effects on Normative Commitment.....................167 
Appendix O:  SEM Results for Leadership Effects on Continuance Commitment..................175 
Appendix P:  SEM Results for Commitment Effects on Behavior and Leaders? Satisfaction .182 
Appendix Q:  SEM Results for an Exploratory Modification of Model 2................................189 
 
 
 xi
LIST OF TABLES 
Table 1:  Study Concepts and Definitions.....................................................................................................36 
Table 2:  Population and Sampling Summary for Phase 1 ............................................................................42 
Table 3:  Changes Identified and the Position of the Change Leader............................................................49 
Table 4:  Change leaders Responses for the Percentage of Change Goals Completed..................................55 
Table 5:  Description of Responses to Leader's Satisfaction Items ...............................................................56 
Table 6:  Measures of Commitment ..............................................................................................................58 
Table 7:  Measures of Leadership .................................................................................................................59 
Table 8:  Measures of Change Involvement..................................................................................................62 
Table 9: Phase 3 Response Distribution........................................................................................................65 
Table 10: Frequency of Number of Responses .............................................................................................66 
Table 11: Gender of the Participants .............................................................................................................66 
Table 12: Age Distribution of the Sample.....................................................................................................67 
Table 13: Years as a Faculty Member...........................................................................................................68 
Table 14: Academic Discipline by Gender, Compared to the Population as a Whole ..................................69 
Table 15: Distribution of Tenure and Non-tenure Track Compared to the Population .................................70 
Table 16: Distribution of Faculty Members with Administrative Positions..................................................71 
Table 17: Statistically Significant Correlations between Demographics and Study Scales ..........................72 
Table 18: Descriptive Statistics for All Measures .........................................................................................75 
Table 19: Correlations among Variables Included in Hypotheses Testing....................................................78 
Table 20: Correlations among Variables after the Specification of the Measurement Models .....................82 
Table 21:  Summary of Hypotheses Testing Findings...................................................................................95 
 
 xii
LIST OF FIGURES 
Figure 1:  Study Constructs and their Interrelationships .................................................................................6 
Figure 2: The First Model for Testing, Including Concepts, Causal Paths, and Hypotheses ........................34 
Figure 3:  The Second Model for Testing, Including Concepts, Causal Paths, and Hypotheses...................35 
Figure 4: Years as Faculty Member ..............................................................................................................68 
Figure 5: Avolio's (2004) Specification of the Leadership Constructs..........................................................80 
Figure 6:  The Final Measurement Model of the Leadership Constructs ......................................................81 
Figure 7: Model 1A, Simplified by Removing the Indicators and the Error Terms. .....................................84 
Figure 8: Model 1B Accounting for Variance of Normative Commitment...................................................87 
Figure 9: Model 1C Accounting for Variance of Continuance Commitment................................................89 
Figure 10: Model 2 Accounting for Variance for Supportive Behavior and Leader?s Satisfaction...............91 
Figure 11: Exploratory Modification for Model 2 Accounting for Variance for Behavioral Support and 
Leader?s Satisfaction. ...............................................................................................................106 
 xiii
1.   INTRODUCTION 
1.1. Background and Motivation 
Since the early 1990s, extensive changes have taken place in pharmacy education 
in the United States in order to facilitate the adoption of the profession?s new model of 
practice, pharmaceutical care.  Unlike the traditional pharmacy practice model, which is 
mainly concerned with fulfilling physicians? orders (known as the drug distribution 
model), the pharmaceutical care model aims at achieving definite positive outcomes for 
drug therapy.  To prepare pharmacy graduates for this new practice model, pharmacy 
schools have been undergoing fundamental changes in their curricula, students? and 
teachers? roles, and learning strategies.  For example, curricula have been revised to 
include clinical training and programs have changed from five year bachelors of science 
to six year doctorate of pharmacy degrees.  Problem-based learning methods have taken 
the place of traditional lectures in some courses. 
The principal investigator conducted an organizational diagnosis exercise in a 
school of pharmacy that had just gone through such a reorganization.  Organizational 
diagnosis is used to evaluate the functioning of an organization, or some aspects of the 
organization, in order to arrive at the causes of the problems and identify areas of 
potential improvement (Cummings & Worley, 1997).  The faculty members and the staff 
at the school of pharmacy were asked to describe the school?s strengths and weaknesses, 
and to provide their recommendations for improving the programs of the school. 
 1
The majority of the responses focused on the changes that had just taken place 
and the role of the school?s administration regarding these changes.  The findings 
indicated that while many of the respondents accepted the recent changes, others 
harbored concerns over them.  While some respondents praised the new ?vision of the 
dean? and the ?willingness to try innovative approaches to education,? others criticized 
the change as being ?too much,? ?too quickly,? and thought that the changes had been 
implemented inflexibly without considering the school?s resources.  In several instances, 
criticisms were directed specifically at the dean.  For example, one faculty member 
described the dean as ?ramrodding his own agenda through faculty and student groups? 
(Waheedi & Armenakis, 2003). 
In view of these findings, it was useful to examine the causes of this variability in 
the reactions of the faculty to these changes, and since the dean was the initiator of the 
changes in the school, to also ask whether the behavior of a change leader effects his or 
her subordinates? reaction. 
Within the organizational sciences, leadership behavior is taken to be a central 
factor in explaining processes and outcomes of change in organizations; however it is 
only one of several classes of variables. One of the prominent frameworks commonly 
used to understand organizational change was provided by Pettigrew (1987), and this 
model has been adopted by scholars in the organizational change literature (e.g., 
Armenakis & Bedeian, 1999; Pettigrew, Woodman, & Cameron, 2001).  This framework 
views organizational change as being made up of interactions of context variables, 
content variables and process variables.  The context variables can be either internal or 
external to the organization and include answers to the question of the change 
 2
justification, the ?why? of change.  Examples of internal context variables in the 
pharmacy academic sitting may include forces that exist within the school such as the 
availability of resources, technology or specialists that permit the change to occur.  
Examples of external context variables are accrediting agencies mandating the change or 
competitive pressures from other schools.  The content variables include the attributes of 
the change itself and provide answers to the ?what? of change.  Examples of differences 
in content can include alternative strategies used by the school, administrative structures, 
tasks, or reward systems. 
This scope of this study is limited to the third group of variables in this 
framework, the process variables.  These variables can be summarized by the actions, 
reactions, and interactions occurring during the planning and implementation of the 
organizational change.  The variables provide the answers to the questions concerning the 
?how? of change.  Although some of the changes in pharmacy schools have been 
necessitated by context variables such as the new requirements for licensing pharmacists, 
the choice lies in how to implement the change.  The process can be undertaken with or 
without adequate involvement of the faculty and in the presence or absence of certain 
leader behaviors.  The faculty members? reaction can vary accordingly, as shown by the 
exploratory study described above, and may take different forms, such as resistance, 
compliance or commitment. 
Among the process variables, change leader behaviors or attributes are considered 
a major factor.  Specifically, the role of transformational leadership in affecting change 
was highlighted first by the writings of Bass (1985), Bennis & Nanus (1985), and Tichy 
& Ulrich (1984).  Since then, the business press has assimilated these concepts into the 
 3
main stream until it has now spread as far as the pharmacy literature.  In July 2003, the 
American Association of Colleges of Pharmacy (AACP) president stated, "as an 
organization, AACP has come to recognize that transformational leadership of the kind 
seldom seen in professional life is required of us if we are to achieve our vision in 
pharmacy education and if we are to assist our profession and other health professionals 
in creating a truly patient centered, seamless and safe, outcomes focused health care 
system? (Wells, 2003). 
Searching the pharmacy literature on the topics of change and leadership, AACP 
appears to have provided the driving force for change in pharmacy schools through the 
publication of the report on The Commission to Implement Change in Pharmacy 
Education (1993).  Many of the changes implemented in the last 10 years in pharmacy 
schools were a result of the recommendations of the Commission papers (Yanchick, 
2005).  The AACP has also focused on leadership and leadership development, especially 
of new and future deans, which has been a characteristic of the organization for years 
(Lin et al., 2003). The 2002 AACP annual meeting focused on leadership and leadership 
development through its general and special sessions, while the 2003 meeting also 
contained similar programming.  However, although the association is clearly focused on 
leadership for the purpose of achieving changes in pharmacy academia, an evaluation of 
such an approach is lacking. 
In addition to leader behavior, several scholars of organizational change argue for 
the involvement of subordinates as a main process ingredient to facilitate positive 
employee reaction to the change (e.g., Conner & Patterson, 1982; Klein, 1996; 
Armenakis, Harris, & Mossholder, 1993; Coetsee, 1999; Wanberg & Banas, 2000; 
 4
Lovelace, Shapiro, & Weingart, 2001).  Accordingly, this study includes the following 
elements of involvement from these scholars: allowing for participation in decision 
making, sharing information about the change and allowing for adequate level of freedom 
of expression of doubts.  These process variables are tested within the theoretical frame 
of this study. 
1.2. Problem Statement 
In recent years, schools of pharmacy in the United States have experienced 
fundamental changes in their curricula, students? and teachers? roles, and learning 
strategies in pursuit of achieving the new vision of pharmacy, pharmaceutical care.  The 
American Association of Colleges of Pharmacy (AACP) acknowledges the difficulties 
facing leaders and strongly advocates leadership development as an approach for 
realizing the new vision, especially with regard to deans and future deans (Lin et al., 
2003).  Nevertheless, there has been no pharmacy research that investigates the 
relationship between leadership behaviors and followers? response to change.  The 
literature on organizational change recognizes the importance of leadership; however, it 
also considers the involvement of followers in the change decision as a main determinant 
of their commitment.  This study poses the following question: what are the effects of a 
change leader?s behaviors and the involvement of subordinates in the change on their 
commitment to organizational change.  Figure 1 provides a general depiction of the 
constructs of the study and their hypothesized relationships. 
 5
 
Figure 1:  Study Constructs and their Interrelationships 
1.3. Significance 
The study has implications for future practice, research, and theory.  For practice, 
this research provides evidence on the causes of commitment to change in pharmacy 
schools and should thus help AACP member schools decide whether to pursue the 
development of leadership, establish a formal participative system, and/or work on 
communication strategies to help them achieve high levels of commitment to change.  
Leadership development programs can benefit by the incorporating the behaviors 
identified in this study as important to enhance a leader?s competency within change 
implementation.  Schools that are in the process of recruiting a person to a leadership 
position can use those attributes and behaviors as part of their selection criteria.  Also, 
based on the results of the study, schools of pharmacy could adopt better methods for 
involving faculty in the decision and implementation of change. 
 6
For research, future work can refine the concepts and methods used to better fit 
them to the context of pharmacy education.  The research can also be extended to issues 
of leadership and change among pharmacists in their practice setting. 
Finally, for theory, this research began to explore a gap in the change 
management literature by connecting the different aspects of leadership, change 
involvement, and how they relate to commitment to organizational change and, in turn, to 
the degree of change success. 
1.4. Summary of Methods 
The population of this study was composed of all the faculty members at 
accredited schools of pharmacy in the United States. The study involved three phases: 
Phase 1: Identifying a Change and a Change Leader 
The purpose of the exploratory phase was to identify the changes that have 
occurred in each school and to identify the change leader linked to it.  The type of change 
of interest for this study was one that can be classified by the Accreditation Council for 
Pharmacy Education (ACPE) as ?substantive change,? which is defined as ?any change 
in the established mission or goals of the institution; the addition or deletion of courses, 
pathways or programs that represent a significant departure in either content or method of 
delivery, from those that were offered during the program?s previous accreditation cycle 
(e.g., a non-traditional doctor of pharmacy program, development of a joint delivery of 
program agreement, etc.)? and any other changes that the Dean feels require notification 
of ACPE? (American Council on Pharmaceutical Education, 1993, p.2).  An Internet 
survey containing a list of potential changes was sent to faculty members of the AACP 
members? schools. 
 7
The faculty members were asked whether the changes included in the list 
occurred in the last 3 years, whether they were completed or still ongoing, and which 
were of concern to them personally or would have an effect on the way they did their job.  
Also, for each change they were asked to provide the name of the main change leader.  In 
addition, an open ended question was included to offer an opportunity for respondents to 
list any other changes that were not included in the list.  The responses from this 
exploratory phase were analyzed to identify one change and a change leader for each 
school. 
Phase 2: Getting Change Leaders? Consent, Validating Faculty Responses, and 
Measuring Leaders? Satisfaction with the Change 
The second phase was directed to the change leader identified in each school in 
the first phase.  A short Internet survey was sent with two purposes.  The first was to 
obtain change leaders? consent to sending the phase 3 survey to the faculty members at 
their schools.  The second purpose was to collect data from the change leader to validate 
the faculty members? identification of the change and the change leader and to measure 
leaders? satisfaction with what had been accomplished from the change initiative.  This 
survey also had an optional open-ended question designed to collect additional 
information. 
Phase 3: Determining the Interrelations among the Study?s Variables 
The specific change for each school, with the change leader?s name, was included 
in an e-mail message for the faculty from that school, who were asked to fill out the 
phase 3 Internet survey.  This survey contained items aimed to measure (1) types and 
strengths of faculty commitment to organizational change, (2) their behavioral support of 
 8
the change, (3) their perceptions of the change leader behaviors, (4) their perception of 
the extent of their involvement in the change (extent of participation in the decision 
making, of communication, and of the freedom allowed to express their doubts about the 
change), and (5) their demographics.  Structural equations modeling (SEM) were used as 
the main analytical tool to test the hypotheses of the study.
 
 9
2.   REVIEW OF THE LITERATURE 
This chapter presents a literature review related to the research problem addressed 
by this study.  As the problem centers on change, commitment to change and the effect of 
leadership, this chapter reviews the organizational change literature with a focus on these 
topics.  It consists of three sections: the first section describes previous work that 
attempted to measure and understand people?s commitment to organizational change, the 
second section describes a summary of transformational leadership theory as it relates to 
organizational change and, finally, the third section presents the concept of individuals? 
involvement in the change, which is theorized by several organizational change models to 
be a main antecedent of commitment to change.  The hypotheses investigated by this 
dissertation are developed and stated as the relevant literature and arguments are 
described. 
2.1. Commitment to Organizational Change 
The emergence of the concept of commitment to organizational change is a result 
of more than 50 years of development within theories of organizational change.  Kurt 
Lewin's (1951) change model is considered one of the earliest influences on planned 
change theory (Cummings & Worley, 1997).  Using analogies from the physical sciences, 
Lewin proposed that at any moment behavior is the result of two opposing forces: those 
that push for change and those striving to maintain the status quo.  For change to occur, 
one must increase the forces for change (e.g., increasing supervisory pressure), decrease 
 10
the forces against it (e.g., change performance norms among subordinates), or implement 
a combination of both.  Lewin suggested that modification of the forces against change is 
more beneficial because it leads to less tension and less resistance. 
This conceptualization of organizational change became an important framework 
on which scholars and practitioners have based their models and analyses.  Dent and 
Goldberg (1999) made the observation that resistance, one of the earliest concepts 
describing employee reaction to change, is considered to have originated from this 
framework.  They also noted that Lewin's notion of resistance was a system phenomenon, 
and hence it did not necessarily describe an individual psychological reaction. For many 
years, employee resistance to change was the focus of organizational change publications 
(e.g., Coch & French, 1948; Zander, 1950; Lawrence, 1969; Strebel, 1996) and resistance 
became a standard part of management vocabulary, as seen in almost all management 
textbooks (Dent & Goldberg, 1999). 
Although resistance as an employee reaction has been widely studied, the concept 
suffers from being only weakly defined. In a review of past literature, Piderit (2000) 
noted that resistance, as an individual phenomenon, has been conceptualized and 
operationalized in several different ways: sometimes as a behavior, other times as a 
cognitive state or as an emotional state. 
In contrast, the concept of commitment to change is a useful alternative to 
resistance.  Commitment is considered one of the main variables in theoretical models for 
organizational change and of effective innovation implementation in the workplace 
(Armenakis, Harris, & Field, 2001; Klein & Sorra, 1996).  Herscovitch and Meyer (2002) 
noted that ?commitment is arguably one of the most important factors involved in 
 11
employees? support for change initiatives,? (p. 474) but despite its importance, no one 
before them had conducted empirical work for its definition and measurement. 
In three studies, Herscovitch and Meyer (2002) provided a new conceptualization 
of commitment to organizational change, constructed scales for measurements and 
provided empirical support for the validity of the scales.  They conducted the studies in 
order to test the application of the three components model of workplace commitment 
(Meyer & Allen, 1984; Allen and Miller, 1990) in the context of employee commitment 
to organizational change.  Allen and Meyer?s (1990) model defines commitment to the 
organization as ?a psychological state that binds the individual to the organization? (p.14) 
which is composed of an affective dimension characterized by emotional attachment to 
the organization, a normative dimension marked by feeling of obligation, and a 
continuance dimension that reflects a person?s awareness that there are costs associated 
with leaving the organization.  Numerous studies have been conducted to examine this 
model with confirmatory of results including the predictions of different types of 
behaviors for affective, normative, and continuance commitment (For example, for a 
meta analysis see Meyer, Stanley, Herscovitch, & Topolnytsky, 2002) 
Herscovitch and Meyer (2002) adapted this conceptualization of commitment to 
the context of organizational change.  They defined the three components as: 
a) Affective commitment to organizational change, defined as ?a desire to provide 
support for the change based on a belief in its inherent benefits? (p. 475). 
b) Continuance commitment to organizational change, defined as ?recognition 
that there are costs associated with failure to provide support for the change? (p. 475). 
 12
c) Normative commitment to organizational change, defined as ?a sense of 
obligation to provide support for the change? (p. 475). 
In their validation studies of the commitment to organizational change instrument, 
they measured organizational commitment and also measured behavioral support for 
change.  They found that commitment to change goes beyond the components of 
organizational commitment in predicting employees? behavioral support for change.  
Further, they found compliance behavior to be correlated positively with all three 
dimensions, but cooperation and championing (discretionary) behavior correlated 
positively only with the affective and normative dimensions. 
This differential effect of the dimensions on outcomes is consistent with previous 
research, though in the context of organizational commitment.  A research study 
examining the relationship between organizational commitment and three measures of 
managerial performance found performance to be positively correlated with affective 
commitment, but found it to be negatively correlated with continuance commitment 
(Meyer, Paunonen, Gellatly, Goffin, & et al., 1989).  The authors concluded that when it 
comes to organizational commitment, it is the type (affective versus continuance) of 
commitment that matters the most. 
The findings from the previous two studies suggest that different types of 
commitments produce different effects.  Pharmacy school faculty members who are 
committed to the change because they want to change (affective or normative 
commitment) are expected to demonstrate more supporting behaviors towards the change 
than those who are committed because they are obligated to do so (continuance 
commitment).  Therefore the following hypotheses are proposed: 
 13
H1: A faculty member?s affective commitment to organizational change is 
positively associated with both compliance behavior and discretionary behavior 
related to the change. 
H2: A faculty member?s normative commitment to organizational change is 
positively associated with both compliance behavior and discretionary behavior 
related to the change. 
H3: A faculty member?s continuance commitment to organizational change is 
positively associated with compliance behavior but negatively associated with 
discretionary behavior related to the change. 
As with their expected effects on behaviors, the three components of commitment 
are also expected to have an effect on the extent of realization or achievement of the 
change initiative.  The higher the affective, normative, and continuance commitment the 
more likely the initiative is to be successfully implemented.  One way to monitor this is 
by measuring the level of satisfaction a change leader has with the implementation.  
Although different dimensions of commitment are expected to affect faculty behavioral 
support differently, exhibiting higher commitment levels to change, regardless of the 
dimension, is expected to increase the likelihood of achieving the change initiative, as 
perceived by the change leader. Therefore, the following hypothesis: 
H4: A faculty member?s commitment to organizational change is positively 
associated with a change leader?s satisfaction with what was accomplished from 
the change. 
 14
2.3 The Transformational Leadership Theory 
The study of leadership has been examined from many different perspectives.  It 
took 1182 pages for Bass and Stogdill?s Handbook of Leadership (1990) to provide a full 
review of leadership theory and research, while it took a 65-page journal article for 
House and Aditya (1997) to only provide a ?brief overview of the research paradigms 
that have been most prominent in the leadership literature? (p.410).  Covering such vast 
literature would entail going beyond the scope of this chapter, however, it is important to 
emphasize that this study should not be concerned with theories of leadership per se, but 
rather theories of change-oriented leadership.  For this reason, the study adopts Bass?s 
(1985) transformational, transactional, and laissez-faire leadership model over other 
models of leadership. 
Among the different approaches to the study of leadership, only transformational 
leadership (or its subsumed charisma factor) exclusively focuses on leadership as it 
relates specifically to organizational change.  Since the mid 1980s, a body of theoretical 
work has been developing on the role of transformational leadership in affecting change 
(e.g., Bass 1985, Bennis & Nanus, 1985, and Tichy & Ulrich, 1984).  This model has 
been suggested more than any other leadership model to link leadership behavior to 
organizational change, and within the pharmacy literature, it has been advocated as the 
kind of educational leadership that is required to achieve the new vision of pharmacy 
(Wells, 2003).  Transformational leadership has been defined as ?the process of 
influencing major changes in the attitudes and assumptions of organization members and 
building commitment for the organization?s mission or objectives? (Yukl, 1989, p. 204).  
Other dominant theories of leadership refer mainly to a dyadic relationship between 
 15
supervisors and subordinates in their day-to-day activity (e.g., how formally appointed 
superiors affect subordinates? motivation and satisfaction), but not necessarily concerned 
with leaderships as it relates to change or specifically how leaders affect change in people 
(House, 1996). 
Therefore, because of its relevance to organizational change, the transformational 
leadership model developed by Bass and Avolio (Bass, 1985; Avolio & Bass, 2002) was 
adopted for this study.  The model, as operationalized by the Multi-factor Leadership 
Questionnaire (MLQ), encompasses descriptions of three groups of leaders? behaviors: 
transactional leadership, transformational leadership, and laissez-faire or non-leadership.  
An important distinction needs to be made here between this model and what has been 
referred to as leadership styles (House & Aditya, 1997).  The categories of behaviors 
within the transformational and transactional leadership are independent of the leadership 
style, i.e., the manner in which the leader?s behaviors are expressed, such as autocratic or 
consultative style. For example, the same transformational leader behavior can be 
expressed autocratically, consultatively, or democratically. 
In relation to organizational change, Nadler and Tushman (1990) noted that 
various discussions of leadership in the context of organizational change led to: 
A picture of the special kind of leadership that appears to be critical during times 
of strategic organizational change.  While various words have been used to 
portray this type of leadership [e.g., transformational], we prefer a label 
charismatic leader.  It refers to a special quality that enables the leader to mobilize 
and sustain activity within an organization through specific personal actions 
combined with perceived personal characteristics (p. 82). 
 16
To be effective in organizational change, leaders need more than charisma; they 
must also demonstrate transactional behaviors, such as clarifying goals, setting up 
performance measures and applying rewards and punishments (Nadler & Tushman, 
1990). 
Transactional leadership is strongly related to the concept of exchange between a 
leader and subordinates, which has its roots in the theory of social exchange (Blau, 1964).  
It has similar variables to those used in the Leader Member Exchange (LMX) theory 
(Dansereau, Graen, & Haga, 1975).  The concepts of transformational leadership as it 
relates to organizations can be traced back to Weber's (1947) introduction of the concept 
of charisma.   He defined charisma as legitimacy that is derived from a leader?s 
exceptional powers or qualities, as opposed to traditions, rules, positions or laws.  Not 
until the mid-seventies, however, did a clear theory of transformational leadership 
emerge.  House (1977) speculated that personality traits such as self-confidence, 
motivation to attain and practice influence, and strong conviction in the moral correctness 
of his beliefs characterize an effective charismatic leader.  Burns (1978), qualitatively 
analyzed leadership cases to make a distinction between transformational and 
transactional leadership.  He wrote: 
The relations of most leaders and followers are transactional -- leaders approach 
followers with an eye to exchanging one thing for another: jobs for votes, or 
subsidies for campaign contributions? Transforming leadership, while more 
complex, is more potent.  The transforming leader recognizes and exploits the 
existing need or demand of a potential follower.  But, beyond that, the 
transforming leader looks for potential motives in followers, seeks to justify 
 17
higher needs, and engages the full person of the follower.  The result of 
transforming leadership is a relationship of mutual stimulation and elevation that 
converts followers into leaders and may convert leaders into moral agents (p.4). 
Bass (1985) developed items describing leaders? behaviors in order to 
operationalize Burns? theory.  In military and industrial settings, he measured 
subordinates ratings of their superiors on specific behaviors derived from Burns? 
definitions of transformational and transactional leadership.  Five factors emerged, two of 
which (contingent rewards and management by exception) were judged to be 
transactional, and three transformational.  Later work (Bass & Avolio, 1994) separated 
one of the transformational factors into two and thus obtained four factors characterizing 
transformational leadership behaviors (idealized influence or charisma, inspirational 
motivation, intellectual stimulation and individualized consideration). 
A few years later, Conger noted that the impact of this conceptualization and 
operationalization of leadership through the Multi-Factor Leadership Questionnaire 
(MLQ) has received more attention in the leadership literature than any other contribution 
(Conger, 1999). 
In relation to employees? commitment to organizational change, since the scale of 
commitment to organizational change was developed, no study has examined the effect 
of leadership on the scale variables.  An empirical study examined the effect of 
transformational leadership on commitment to change, but conceptualized commitment to 
change differently, as a composite of personal goals, capacity beliefs and context beliefs 
(Yu, Leithwood, & Jantzi, 2002).  Although they found a significant effect for 
 18
transformational leadership on commitment to organizational change, commitment was 
conceptualized and operationalized differently from the usage here. 
Other measures of employees? outcomes, including organizational commitment, 
established the effect of leadership.  For instance, Reichers (1986) carried out a study to 
measure the commitment of health professionals to several constituencies within and 
outside of the organization (e.g., manager, customer, organization). Among them, only 
commitment to top management?s goals and values was significantly correlated with 
organizational commitment. 
In another study, Becker (1992) examined whether commitments to several 
constituencies (e.g., top management, supervisors and work groups) contributed beyond 
organizational commitment to three outcome measures.  The study found that employees' 
commitment to top managers contributed significantly more than commitment to the 
organization.  Another study compared the effect of commitment to the supervisor or to 
the organization on the employees? performance, as measured by supervisors? ratings.  
Again, commitment to supervisors and their values was more strongly related to 
performance ratings than was commitment to the organization (Becker, Billings, Eveleth, 
& Gilbert, 1996). 
These findings suggest that organizational commitment is consistently correlated 
with employee performance outcomes, and that top management may have a significant 
and unique effect on both organizational commitment and performance outcomes.  
Commitment to organizational change, then, is expected to be highly affected by top 
management, and hence leadership.  Therefore, the concept of leadership is included as 
the main antecedent to commitment to change in this study. 
 19
2.3.1. Transactional Leadership 
According to Bass (1985), transactional leaders prefer operating within the 
existing system or culture, tend to avoid risk and rely on organizational rewards and 
punishments to motivate employee performance.  He describes transactional leaders as 
cost-benefit oriented, where they concentrate on rewarding efforts appropriately and 
ensure that behaviors confirm to expectations (Bass & Avolio, 1994). 
Transactional leadership behaviors include three factors in the Multi-Factor 
Leadership Questionnaire (MLQ).  The first factor is contingent reward, which refers to 
an exchange agreement between leader and follower: ?You do this, and you will receive 
this in return.?  The other two factors are active and passive management by exception.  
These are corrective leadership behavior, where in the active form the leader actively 
monitors subordinates? performance and corrects any deviations.    In the passive form, 
the leader does not monitor, but waits for mistakes to happen and then takes action. 
Avolio and Bass (2002) argued that contingent reward is reasonably effective, 
though not as effective as the transformational components in motivating others to 
achieve higher performance levels.   They also argued that management by exception 
tends to be ineffective, but in certain situations it may be needed.  In a meta-analytic 
review of the literature on the MLQ instrument, Lowe and Galen Kroeck (1996) found 
the contingent reward aspect of transactional leadership to be positively correlated with 
subordinates? perceptions of effectiveness.  Management by exception was found to be 
weakly correlated with effectiveness, and was negatively correlated when found to be 
statistically significant. 
 20
In relation to employee response to change initiatives, a study of leadership effect 
on Total Quality Management (TQM) behaviors and policies suggested that management 
by exception leadership behaviors are likely to result in a reluctance on the part of 
followers to take risks associated with change efforts or other improvement initiatives 
(Sosik & Dionne, 1997).  Therefore, one would expect that the more frequently a change 
leader practices transactional leadership (especially management by exception), the less 
likely the faculty members are to subscribe to the change goals, resulting in adverse 
effects on their affective and normative commitments to organizational change.   
Continuance commitment, on the other hand, is developed when the perceived 
cost of not following directions is high, and there is no alternative to individuals other 
than complying (Meyer & Herscovitch, 2001).  Faculty members can still be engaged 
with the change implementation, not because they want to, but because they have to.  In 
this situation, transactional leadership is expected to be associated with higher levels of 
the continuance commitment to organizational change.  In view of the above discussion, 
the following hypothesis can be proposed: 
H5: Transactional leadership on the part of a change leader will be negatively 
associated with the affective and normative dimensions of commitment to 
organizational change, but will be positively associated with the continuance 
dimension of commitment to organizational change. 
2.3.2. Transformational Leadership 
Transformational leaders transform followers? thoughts and attitudes so that they 
become motivated to perform beyond normal expectations.  They help followers buy in to 
their vision and make every effort to accomplish it.  The category of theory this 
 21
transformational leadership belongs to has been referred to the as "neocharismatic 
theory? (House & Aditya, 1997), or ?the new leadership theories? (Bryman, 1993). 
House and Aditya (1997) describes four common characteristics among these theories.  
First, they all attempt to explain the accomplishment of outstanding performance by 
leaders.  Second, they attempt to explain how certain leaders can induce high levels of 
motivation, trust and commitment among followers.  Third, they emphasize the symbolic 
or emotional aspects of the appeal used by certain leaders.  Fourth, they specify the 
effects on followers as increased self-esteem, motivation and identification with the 
leader?s vision. 
How do they accomplish such effects?  To better understand this, Bass (1985) 
developed items describing leaders? behaviors, subjected them to testing, and came up 
with three factors, later expanded to four factors, that characterized the behaviors and 
attributes of transformational leaders (Bass & Avolio, 1994).  The four factors are: 
1. Charisma or idealized influence.  This refers to the role modeling 
behaviors that gain admiration and trust.  For example, making personal sacrifices for 
others, going beyond self-interest for the good of the group, remaining calm amidst crisis, 
displaying competence and being respected by subordinates. 
2. Inspirational leadership.  This refers to a leader?s behavior such as 
articulating attractive future state that result in creating a sense of meaning and challenge 
in the associates. 
3. Intellectual stimulation.  This includes behaviors such as questioning 
assumptions, reframing problems and approaching them with a fresh perspective.  Also 
 22
included are behaviors that support followers? participation and creativity in problem-
solving. 
4. Individualized consideration. These behaviors include coaching and 
mentoring to fulfill individual?s need for growth, and paying attention to and accepting 
differences in individual's needs and adjusting the support behavior accordingly. 
These behaviors are expected to induce commitment to the leader's vision and 
generate extra effort and satisfaction among subordinates (Avolio & Bass, 2002). 
Empirical evidence generally supports the effects of transformational leadership 
on a variety of performance measures in organizations.   A meta-analysis of studies that 
used the MLQ found transformational leadership to be reliable and a good predictor of 
work unit effectiveness in 39 studies (Lowe & Galen Kroeck, 1996).  A recent study by 
Waldman and others (2001) examined transformational and transactional leadership at 
the CEO level in 48 Fortune 500 companies, and found companies? outcomes to depend 
on a CEOs charismatic leadership. Transformational leaders greatly influence all aspects 
of the organizational cultures they operate in (Carlson & Pamela, 1995), an indication of 
their potential influence on employees? commitment to change. 
It has been suggested that regardless of the commitment target (e.g., organization, 
career, occupation, organizational change), basic processes are involved in the 
development of affective, continuance and normative commitment (Meyer & 
Herscovitch, 2001).  Affective commitment is developed when a) involvement strategies 
are used, b) recognition of the value occurs, c) individuals derive identity from the target 
and d) associate with it.  Continuance commitment is developed when there is no 
alternative other than the target.  Normative commitment is developed when individuals 
 23
receive benefits that make them need to reciprocate.  If these mechanisms of commitment 
formation are applicable to the context of organizational change, it is plausible to expect 
transformational leadership to have positive effects on affective and normative 
commitment and negative effect on continuance commitment. 
Yu, Leithwood and Jantzi (2002) studied the effect of transformational leadership 
on teachers? commitment to change in Hong Kong primary schools.  They conceptualized 
commitment to change as a composite of personal goals, capacity beliefs and context 
beliefs, which are more related to the affective and normative than the continuance 
dimension.  They found a significant effect of transformational leadership on 
commitment to organizational change. 
Since transformational leaders by definition build bonds through individualized 
consideration and idealized influence and work toward a shared vision of the future 
through inspirational motivation and intellectual stimulation, subordinates may 
experience higher affective and normative commitment to organizational change.  Since 
threats and punishment and other forms of coercion are not within transformational 
leadership behaviors, followers are also expected to have lower levels of continuance 
commitment to change (i.e. they do not feel that they have to comply).  This leads to the 
following hypothesis: 
H6: Transformational leadership on the part of a change leader will be positively 
associated with the affective and normative dimensions of commitment to 
organizational change, but negatively associated with the continuance dimension 
of commitment to organizational change. 
 24
2.3.3. Laissez-faire 
The MLQ also measures laissez-faire leadership, which is actually the set of 
behavioral characteristics of non-leadership.  These behaviors are characterized by an 
avoidance of important issues, absence when involvement is needed and avoidance of 
decision-making.  Avolio and Bass (2002) considered this as the most ineffective 
leadership style.   
In a change involving the implementation of TQM, Sosik and Dionne (1997) 
noted that change requires socio-emotional support from leaders to encourage 
subordinates to seek out new opportunities to improve the status quo, and laissez-faire 
leadership is incompatible with the leadership behavior needed in this context. Therefore, 
maintaining a faculty's focus and effort requires deans to actively support and reiterate 
the vision and strategies of implementation. Failure to do so is expected to lower all 
aspects of commitment to change, leading to the following hypothesis: 
H7: Laissez-faire or non-leadership on the part of a change leader will be 
negatively associated with the three dimensions of commitment to organizational 
change. 
2.4. Change Involvement 
The Blackwell Encyclopedic Dictionary of Organizational Behavior states that the 
term ?employee involvement? is commonly used to express a wide range of practices in 
organizations, which all have in common ?the increasing employee influence over how 
their work is carried out or over other areas of organizational policy and practice? 
(Nicholson, Schuler, & Van de Ven, 1998, p.153).  Common methods to increase 
employee involvement include communication and practices that increase influence on 
 25
decision making (e.g., quality circles and consultative committees).  Scholars and 
managers assume that keeping employees informed about the issues related to their work 
and allowing them to make decisions on these issues will benefit both the organization 
and the employee.  Meta-analyses of the literature on participative decision making 
suggest that participation improves employee attitudes and performance, at least under 
some conditions (Cotton, Vollrath, Froggatt, Lengnick-Hall, & Jennings, 1988; Sagie, 
1994). 
Researchers have noted that the terms ?participation? and ?involvement? have 
been used interchangeably throughout the literature, with numerous different definitions 
(Shadur, Kienzle, & Rodwell, 1999).  In this study, the term ?change involvement? is 
borrowed from Thompson and Van de Ven (2002) to describe faculty members? 
perception of the extent of their influence over the change. 
The relation between change involvement and commitment to organizational 
change is the main focus of Armenakis, Harris, and Mossholder (1993) conceptual model 
for institutionalizing change.  Their model includes participation, communication, and 
management of information as they key elements determining employee commitment to 
change.  It proposes that among other strategies, active participation and persuasive 
communication facilitate moving employees through four phases of psychological 
responses to change, namely through readiness to adoption, then to commitment, and 
ultimately to institutionalization. 
No research was found that establishes a link between transformational leadership 
and employee involvement.  Sagie (1997) noted that the theory of transformational 
leadership combines autocratic and democratic elements, citing Kuhnert, who described 
 26
the transformational leader as one exhibiting a ?strong sense of inner purpose and 
direction? while at the same time is ?able to energize followers to take actions that 
support? the purpose (Kuhnert, 1994, p.18).  Sagie also cited Yammarino, describing two 
dimensions of transformational leadership, inspirational motivation and idealized 
influence, as being directive in their effect on followers, while the other two dimensions, 
individualized consideration and intellectual stimulation, as imply that the 
transformational leader respects the autonomy of his or her followers and solicits ideas 
from them (Yammarino, 1994).  A paper discussing leadership in the context of K-12 
education stated that transformational leaders, unlike transactional leaders, ?are more 
concerned about gaining overall cooperation and energetic participation from 
organizational members? (Mitchell & Tucker, 1992, p.33). 
This study attempts to investigate whether change involvement mediates the 
effect of transformational leadership on faculty commitment to organizational change,   
suggesting the following hypotheses: 
H8: Transactional leadership on the part of a change leader will be positively 
associated with faculty change involvement. 
H9: Transformational leadership on the part of a change leader will be positively 
associated with faculty change involvement. 
H10: Laissez-faire or non-leadership on the part of a change leader will not be 
associated with faculty change involvement. 
H11: Faculty change involvement will be positively associated with affective and 
normative commitment, but negatively associated with continuance commitment. 
 27
Change involvement is conceptualized in this study as a latent variable that is 
composed of three factors: 
1. Participation in change decision 
2. Communication during the change 
3. Freedom to express doubts about the change 
These three factors are proposed here to account for the majority of processes 
within the change involvement variable.  The first two factors, participation and 
communication, are well established dimensions of the involvement concept and have 
been proposed as determinants of positive reactions to change by several organizational 
change models (e.g., Conner & Patterson, 1982; Klein, 1996; Armenakis, Harris, & 
Mossholder, 1993; Coetsee, 1999; Wanberg & Banas, 2000; Lovelace, Shapiro, & 
Weingart, 2001).  The third factor, freedom  to express doubts, is defined here as the 
degree to which faculty members perceive pressures to conform to group norms about not 
expressing their own beliefs and opinions about the change (Van de Ven & Chu, 1989). 
Freedom to express doubts was included because of its relevance to the research 
context of the study.  A consistent finding of the previously mentioned exploratory 
survey of pharmacy faculty members at a school pharmacy and an informal discussion 
with a change leader at a school of pharmacy suggested to the investigator that 
participation in decision making may be short of describing involvement.  Although 
faculty were given the opportunity to participate in the decision making process through 
their committee membership, one respondent to the survey stated that ?many faculty do 
not appear to vote their conscience on many issues, not sure if this is out of fear of 
retribution from administration.?  In a follow-up discussion with the change leader, he 
 28
gave examples of faculty members who came to decision-making committees and 
supported the decisions reached, but went back to their departments and talked about how 
bad it was, or how they did not agree with what was decided. 
Research supports the existence of such a phenomenon and its effect on 
commitment.  For example, Thompson and Van de Ven (2002) studied determinants of 
the commitment of physicians to the profession and to the organization during 
organizational change, and found several ?organizational enabling characteristics? to be 
antecedents to commitment.  The enablers were: 1) change involvement (measured by the 
extent of being informed of changes and participation in decision making), 2) freedom to 
express doubts, and 3) work discretion (measured by influence on the type of work and 
influence on policies and procedures).  These findings suggested a strong positive effect 
for the enabling characteristics on commitment to both the organization and to the 
profession during organizational change. 
In addition, research by Lovelace, Shapiro, and Weingart (2001) suggested that 
employees? freedom to express doubts is related to leadership.  They tested a model that 
relates communication, leaders? effectiveness, and performance in the context of new 
product teams? performance.  They found that freedom to express doubts mediates the 
positive correlation between leader effectiveness and new product teams? effectiveness.  
When team members feel encouraged to express their differences in developing the 
innovation and do not feel pressure to censure, they can incorporate the differences in the 
developed innovation. 
 29
3.   STATEMENT OF THE PROBLEM 
3.1. Problem Statement 
In recent years, schools of pharmacy in the United States have undergone 
fundamental changes in their curricula, students? and teachers? roles, and learning 
strategies in pursuit of achieving the new vision of pharmacy, namely pharmaceutical 
care.  The American Association of Colleges of Pharmacy (AACP) acknowledges the 
difficulties facing leaders as a result of these upheavals and strongly advocates leadership 
development as an approach for realizing the new vision, especially within deans and 
future deans (Lin et al., 2003).  Nevertheless, there has been no research investigating the 
relationship between the behaviors of change leaders in pharmacy schools and faculty 
members? response to change.  The literature on change management recognizes the 
importance of leadership; however, it assumes the involvement of followers in the change 
decision to be the main determinant of their commitment (Armenakis, Harris, & Field, 
2001). This study aims to fill this gap by exploring these relationships. 
The following is the problem addressed by this study in the context of an 
academic pharmacy setting: how does commitment to change vary according to whether 
the change leader approaches followers with transactional processes (?do this for me and 
I do this for you?), with transformational processes (engaging the full person of the 
follower), or in a laissez-faire (non-leadership) manner?  Also, how does the level of 
 30
involvement of followers in the change mediate the effect of leaders? behaviors on 
commitment? 
3.2. Research Questions 
1. How do behaviors of a change leader affect a faculty member?s commitment 
to organizational change? 
2. How does involvement in change affect a faculty member?s commitment to 
organizational change? 
3. How does faculty members? commitment to change affect their support for 
change initiatives in pharmacy schools? 
4. How does faculty members? commitment and their behavioral support affect 
the satisfaction of a change leader with change accomplished? 
3.3. Hypotheses 
The research hypotheses are as follows: 
? H1a: A faculty member?s affective commitment to organizational change 
is positively associated with compliance behavior related to the change. 
? H1b:  A faculty member?s affective commitment to organizational change 
is positively associated with discretionary behavior related to the change. 
? H2a: A faculty member?s normative commitment to organizational change 
is positively associated with compliance behavior related to the change. 
? H2b: A faculty member?s normative commitment to organizational change 
is positively associated with discretionary behavior related to the change. 
 31
? H3a: A faculty member?s continuance commitment to organizational 
change is positively associated with compliance behavior related to the 
change. 
? H3b: A faculty member?s continuance commitment to organizational 
change is negatively associated with discretionary behavior related to the 
change. 
? H4a: A faculty member?s affective commitment to organizational change 
is positively associated with a change leader?s satisfaction with what was 
accomplished from the change. 
? H4b: A faculty member?s normative commitment to organizational change 
is positively associated with a change leader?s satisfaction with what was 
accomplished from the change. 
? H4c: A faculty member?s continuance commitment to organizational 
change is positively associated with a change leader?s satisfaction with 
what was accomplished from the change. 
? H5a: Transactional leadership on the part of a change leader will be 
negatively associated with affective commitment. 
? H5b: Transactional leadership on the part of a change leader will be 
negatively associated with normative commitment 
? H5c: Transactional leadership on the part of a change leader will be 
positively associated with continuance commitment. 
? H6a: Transformational leadership on the part of a change leader will be 
positively associated with affective commitment. 
 32
? H6b: Transformational leadership on the part of a change leader will be 
positively associated with normative commitment. 
? H6c: Transformational leadership on the part of a change leader will be 
negatively associated with continuance commitment. 
? H7a: Laissez-faire or non-leadership on the part of a change leader will be 
negatively associated with affective commitment. 
? H7b: Laissez-faire or non-leadership on the part of a change leader will be 
negatively associated with normative commitment. 
? H7c: Laissez-faire or non-leadership on the part of a change leader will be 
negatively associated with continuance commitment. 
? H8: Transactional leadership on the part of a change leader will be 
positively associated with faculty change involvement. 
? H9: Transformational leadership on the part of a change leader will be 
positively associated with faculty change involvement. 
? H10: Laissez-faire or non-leadership on the part of a change leader will 
not be associated with faculty change involvement. 
? H11a: Faculty change involvement will be positively associated with 
affective commitment. 
? H11b: Faculty change involvement will be positively associated with 
normative commitment. 
? H11c: Faculty change involvement will be negatively associated with 
continuance commitment. 
 33
3.4. Concepts and Definitions 
The hypotheses will be tested in two models.  Figure 2 illustrates the first four 
hypothesis concepts and their relationships.  
Affective
Commitment
Continuance
Commitment
Normative
Commitment
Change Leader
Satisfaction
Compliance
Discretionary
Behavior
H
1
a
H
2
b
H
4
a
H
4
c
H4b
H2
a
H
3
b
H
3
a
H
1b
 
Figure 2: The First Model for Testing, Including Concepts, Causal Paths, 
and Hypotheses 
 
The next group of hypotheses (H5 to H11) were grouped together in another 
model.  Figure 3 illustrates one example of the three models that were tested, which were 
identical for all the concepts, except that each model examined a different one of the 
dimensions of commitment: affective, normative, and continuance. 
 34
Transformational
Leadership
Laissez-faire
Transactional
Leadership
Commitment**Change
Involvement
H
8
H
1
0
H
9
H
6
H11
H
7
H
5
 
Figure 3:  The Second Model for Testing, Including Concepts, Causal 
Paths, and Hypotheses. 
**One commitment component was used in each of the three separate 
models tested: the affective, normative, and continuance. 
 
Table 1 lists the definitions of the concepts involved in the study.  The first 
column lists the concepts, the second lists a constitutive definition, and the third column 
describes how the concept has been operationalized in this study. 
 35
Table 1:  Study Concepts and Definitions 
Concept Constitutive Definition Operational Definition 
Organizational 
Change 
Any change within the pharmacy 
school that can be classified by the 
ACPE as ?substantive change? 
which is defined as ?any change in 
the established mission or goals of 
the institution; the addition or 
deletion of courses, pathways or 
programs that represent a significant 
departure in either content or 
method of delivery, from those that 
were offered during the program?s 
previous accreditation cycle (e.g., a 
non-traditional doctor of pharmacy 
program, development of a joint 
delivery of program agreement, 
etc.)? and any other changes that 
the Dean feels require notification 
of ACPE.? (ACPE, 1993) 
A ?yes? given on any of the 9 
changes offered to the faculty 
members in the first phase survey 
(Appendix B), or provided by 
them in response to the open-
ended question at the end of that 
survey, given the following 
qualifications: 
(1) the change occurred in the last 
three years, (2) the change is at 
least 70% completed (mean 
percentage scores provided by 
respondents), (3) the mean score 
of the three items measuring the 
importance of the change equals 
or greater to 3 (on a 5-point scale), 
and (4) a change leader is 
identified with the change. 
Change Leader A person who leads and manages 
the change within an organization. 
A dean or associate/assistant dean 
that is agreed to be the change 
leader of the identified change by 
at least half of the respondents 
from a school for that particular 
change. 
Commitment to 
Organizational 
Change 
?A force (mind-set) that binds an 
individual to a course of action 
deemed necessary for the successful 
implementation of a change 
initiative? (Herscovitch & Meyer, 
2002). 
Scores on each of the three scales 
of commitment dimensions 
(affective, normative and 
continuance), each of which are 
measured by six items (Table 6, 
Ch.4). 
 36
Concept Constitutive Definition Operational Definition 
Affective 
Commitment to 
Change 
?A desire to provide support for the 
change based on a belief in its 
inherent benefits? (Herscovitch & 
Meyer, 2002). 
Scores on the affective 
commitment scale which contains 
six items (Table 6, Ch.4). 
Normative 
Commitment to 
Change 
?A sense of obligation to provide 
support for the change? 
(Herscovitch & Meyer, 2002). 
Scores on the normative 
commitment scale which contains 
six items (Table 6, Ch.4). 
Continuance 
Commitment to 
Change 
?A recognition that there are costs 
associated with failure to provide 
support for the change? 
(Herscovitch & Meyer, 2002). 
Scores on the continuance 
commitment scale which contains 
six items (Table 6, Ch.4). 
Transformational 
Leadership 
A class of leader behaviors who aim 
to increase the subordinates? 
awareness of what is right and 
important and to raise their 
motivational level so that they 
identify with the needs of the leader. 
Scores on each of the four scales 
of transformational leadership: 
charisma/idealized influnce, 
inspirational motivation, 
intellectual stimulation, and 
individualized consideration 
(Table 7, Ch.4). 
Charisma or 
Idealized Influnce 
A class of behavior and/or personal 
attributes of a leader proposed to 
cause followers? admiration, 
respect, trust and emulation of such 
leader. 
The score on six items.  Three of 
the items for charisma and three 
for idealized influnce (Table 7, 
Ch.4). 
Inspirational 
Motivation 
A class of leader behaviors that 
verbalize and clarify shared vision 
and goals for the future.  
The score on the three items 
representing the construct (Table 
7, Ch.4). 
 37
Concept Constitutive Definition Operational Definition 
Intellectual 
Stimulation 
A class of leader behavior that gets 
subordinates to question the tried 
ways of solving problems, and 
encourages them to question the 
methods they use to improve upon 
them. 
The score on the three items 
representing the construct (Table 
7, Ch.4). 
Individualized 
Consideration 
A class of behavior of a leader 
focuses on understanding the needs 
of each follower and works 
continuously to get them to develop 
to their full potential. 
The score on the three items 
representing the construct (Table 
7, Ch.4). 
Transactional 
Leadership 
A class of leader behaviors that rely 
on organizational rewards and 
punishments to motivate employee 
performance. 
Scores on each of the three scales 
of transactional leadership: 
Contingent Reward, Active 
Management by Exception, and 
Passive Management by 
Exception (Table 7, Ch.4). 
Contingent 
Reward 
A class of leader behaviors that 
clarifies what is expected from 
followers and what they will receive 
if they meet expected levels of 
performance. 
The score on the three items 
representing the construct (Table 
7, Ch.4). 
Active 
Management by 
Exception 
A class of leader behaviors that 
focuses on monitoring task 
execution for any problems that 
might arise and correcting those 
problems to maintain current 
performance levels. 
The score on the three items 
representing the construct (Table 
7, Ch.4). 
 38
Concept Constitutive Definition Operational Definition 
Passive 
Management by 
Exception 
A class of leader behaviors that 
tends to react only after problems 
have become serious to take 
corrective action, and often avoids 
making any decisions at all. 
The score on the three items 
representing the construct (Table 
7, Ch.4). 
Laissez-faire  A class of leader behaviors that can 
be described best by absence of 
behaviors; lack of transactions and 
low involvement with subordinates. 
The score on the three items 
representing the construct (Table 
7, Ch.4). 
Change 
Involvement 
Faculty members? perception of the 
extent of their influence over the 
change (Thompson & Van de Ven, 
2002). 
Scores on each of the three scales 
of change involvement: 
Participation in Decision Making; 
Communication Intensity; 
Freedom to Express Doubts 
(Table 8, Ch.4). 
Participation in 
Decision Making 
The degree to which the faculty 
members perceive themselves as 
having a role in the decisions made 
in relation to the change. 
The score on the five items 
representing the construct (Table 
8, Ch.4). 
Communication Faculty members? perception of the 
degree they have been kept 
informed throughout the change. 
The score on the six items 
representing the construct (Table 
8, Ch.4). 
Freedom to 
Express Doubts 
The degree to which faculty 
members perceive there to be 
pressure to conform to group norms 
by not expressing their own beliefs 
and opinions about the change (Van 
de Ven & Chu, 1989). 
The score on the three items 
representing the construct (Table 
8, Ch.4). 
 39
Concept Constitutive Definition Operational Definition 
Change Leader 
Satisfaction 
Degree to which a change leader 
reports satisfaction with what was 
accomplished from the change at        
his/her school. 
The scores on two-item on the 
satisfaction scale created for the 
study (Appendix H, items 2 and 3) 
Compliance Showing minimum support for 
change by going along with the 
change and not engaging in 
behaviors aimed at preventing the 
success of the change (Herscovitch 
& Meyer, 2002). 
A score from 0 to 60 in 
Herscovitch & Meyer (2002) 101 
point behavioral support scale.  
Higher scores indicate higher 
levels of compliance. 
Discretionary 
Behavior 
Actions that involve going along 
with the spirit of the change and 
being prepared to make modest 
sacrifices (Herscovitch & Meyer, 
2002). 
A score from 61 to 100 in 
Herscovitch & Meyer (2002) 101-
point behavioral support scale. 
 40
4. METHODS 
The design of this study can be described as a non-experimental cross-sectional 
study based on individuals' self-reports through Internet survey questionnaires.  This 
research was conducted through three separate phases, with the three surveys being sent 
out at different times.  The following describes the methods and procedures used for each 
phase of the study. 
4.1. First Phase: Identifying a Change and a Change Leader 
Since the focus of this research is on change and leadership in pharmacy schools, 
there was a need to first identify which schools of pharmacy had undergone a recent 
change and whether such changes can be linked to a leader within each school.  This 
exploratory first phase was thus conducted. 
4.1.1. Population and Sampling 
The population of this phase was composed of all the faculty members at the 89 
accredited schools of pharmacy in the US whose names were listed in the AACP Roster 
(Microsoft Excel datasheet received from the AACP by e-mail on October 12, 2004).  
The roster contained 4157 entries from 89 schools.  However, the final population that 
was eligible for sampling consisted of a subset of the 89 schools, as described in Table 2.  
The table displays the number of schools and individuals who were initially excluded, 
 41
those who were excluded later due to the absence of any response confirming reception 
of e-mail invitations, and those remaining that composed the final population. 
Table 2:  Population and Sampling Summary for Phase 1 
 Schools Individuals 
AACP Roster 89 4157 
Excluded 8 160 
Sent Invitations 81 3997 
Zero Response 4 126 
Final Population 77 3871 
Responded 77 421 
 
From the 89 schools in the AACP Roster, eight were excluded; seven because 
they were established relatively recently (within the last five years) and thus unlikely to 
have a substantive change in the last three years; and one school due to a technical failure 
in the survey Web site created for it.  The 3997 individual faculty members from the 
remaining 81 schools were sent an e-mail invitation to participate in the first phase survey 
with an embedded hyperlink directing potential respondents to an Internet site containing 
the first phase survey.  Appendix A contains the information letter sent in the first phase 
and Appendix B contains a copy of the survey.  Appendix C shows screen shots of parts 
of the phase 1 survey as it should have appeared to the participants. 
One week after sending the invitation e-mails, there had been no response from 16 
of the schools.  To check whether this was due to a failure of the e-mail message to reach 
these schools, such as blocking by a spam detection device, a personalized e-mail 
 42
message was sent to 15 schools by the chair of the dissertation committee who knew one 
faculty member from each school (Appendix D).  The e-mail asked the recipients to 
respond by confirming whether they had received the recruitment e-mail or, if not, to 
supply the contact information for the information technology specialist at their schools.  
None of the 15 schools reported of a failure of the original message to reach them. 
One further reminder message was sent by e-mail one week after the first contact 
(Appendix E).  After this reminder message, there were only four schools with absolutely 
no response and these were subtracted from the potential population. 
Four hundred and twenty one individuals responded, representing 77 schools.  
After an analysis of their responses (identification of a change and connecting the change 
to a change leader) 54 schools were eligible for the second phase. 
4.1.2. Data Collection Method 
The purpose of this phase was to identify the changes that had occurred in each 
school and identify the change leader responsible for each.  The following describes the 
sections of the survey and the types of question included (Appendices B and C): 
1. Introduction page: 
Once potential participants followed the hyperlink embedded within the 
recruitment e-mail, they arrived at the introduction page.  This page contained the title of 
the study and a paragraph describing the purpose of the first phase and defining what the 
researcher meant by a change, including the ACPE?s definition of ?substantive change? 
and some examples.  A hot-button link to start the survey was provided below the 
introductory paragraph. 
2. Items aimed at the identification of the change and the change leader: 
 43
Two types of items were used to identify the change.  First, a list of specific 
changes that had been identified from the pharmacy literature were given to the 
participants and they were asked whether any of the changes had occurred in the last 
three years at their schools.  The second type of question was open-ended and asked 
whether the participants could list one or more additional changes that fit the definition 
provided.  Both types of questions, the closed-ended and the open-ended, were followed 
by a request to name the main leader for the change identified. 
3. Items aimed at ascertaining the importance of the change: 
The researcher wanted to exclude changes that had little effect on the way the 
faculty members did their jobs, or were of little or no concern to them.  Three questions 
were developed to measure the importance of the identified change to the respondents: 
?this change affected the way I do my job,? ?this change is of concern to me,? and ?this 
change doesn?t matter to me.?  Responses were made using a 5-point Likert-type scale 
ranging from 1 (strongly disagree), to 5 (strongly agree). 
4. Item aimed at ascertaining the percentage completed from the change: 
Another way the researchers sought to qualify changes eligible for inclusion in the 
second phase was to ascertain whether they were completed, in progress, or in the early 
stages.  To control for the potential effects of variability in the  amount completed of the 
change on the studied variables, only changes that had been completed or near 
completion (within 70% completion, as identified by respondents) were included in the 
second phase. 
5. Closing: 
 44
The questionnaire ended with a ?Submit? button which participants could click on 
to submit their answers.  Submission was followed by another page that contained a note 
thanking the participants and telling them that a follow-up e-mail regarding the final 
phase of the study would follow within two months. 
4.1.3. Pre-test 
The draft of the questionnaire was tested on paper, prior to developing the Internet 
version, first by two graduate students, and then by two faculty members.  In general, the 
pre-test showed there to be little difficulty in understanding the questions, although 
several changes were made to grammar and word choices.  The final Internet version was 
also pre-tested for understanding by one faculty member.  Corrections made here were 
limited to font choice and size.  Overall, the Internet survey was shown to be adequate in 
eliciting the information desired. 
4.1.4. Data Analysis Methods 
The submitted data were collected automatically in Microsoft (MS) Access 
datasheets, one for each school involved.  Later, all the schools? data were manually 
imported to one MS Excel datasheet, where they were prepared for analysis.  Finally, 
cases in the imported data were randomly compared with their corresponding cases in the 
original schools? MS Access datasheets to check for accurate transfer of the data. 
Each school?s data were analyzed separately.   For the question: ?did one of the 
following changes take place within your school during the past three years?? the 
responses with ?yes? to a particular change were summed up and recorded as a 
proportion of the total number of participants from the particular school.  The names of 
 45
the change leaders mentioned in relation to a change were recorded, with their relative 
frequency to other change leaders. 
The percentage of completion for a change was determined by computing the 
mean of the scores from all the respondents in relation to the particular change within the 
particular school.  The importance of the change was computed similarly using the mean, 
but for all three items measuring importance.  Each of three items was rated using a 5-
point scale, with anchors labeled as 1 (strongly disagree) to 5 (strongly agree).  One item, 
?this change doesn't matter to me,? was reversely coded.  The responses to the three items 
were averaged to provide an importance score for the individual, and then individuals? 
scores were averaged to arrive at the importance index for that particular change in a 
particular school. 
The decision rules for selecting a change for a school were as follows: 
? A change must be at least 70% completed as measured by averaging the 
responses from the relevant item for a particular school.  This rule was 
created to control for the potential effects of the amount completed of the 
change on the variables under study.  Changes at earlier stages were 
excluded because some of the implementation processes, such as 
behaviors of a change leader or participation in decision making, may not 
had the chance to manifest, thus would pose a threat to the reliability and 
validity of responses. 
? The change must be rated 3 or more on the importance index.  This rule 
was applied to insure a minimum level of internal state of interest in the 
change, thus the respondents would more likely have sufficient knowledge 
 46
and ability to recall particulars of the change, change leader?s behavior, 
and other variables when they receive the third phase survey.  This is 
needed in order to have more valid and reliable responses to the survey 
items in the third phase.  The faculty member with certain level of interest 
or concern would be at a certain degree of arousal to engage in specific 
information processing in relation to the variables under study.  In the 
marketing literature this phenomenon is referred to as consumer 
involvement (Andrews, Durvasula, & Akhter, 1990).  For example, under 
high involvement situations brand beliefs is expected to strongly predict 
attitudes, but under low involvement, beliefs are not necessarily related to 
attitudes. 
? A change must be mentioned by the majority of respondents (more than 
50%) from a particular school.  This rule was applied in an attempt to 
increase the validity of the change chosen.  If only a few faculty members 
from a school agree on a change one would expect problems with face 
validity for the potential respondents in the next phases. 
? A dean or associate/assistant dean must be identified as the leader of the 
change.  The theoretical framework for this study contains behaviors of a 
change leader that assumes a hierarchical situation between the leader and 
a follower.  For example, in order for the concepts of leader?s contingent 
reward behaviors or management by exception behaviors to apply, the 
change leader cannot be at equal organizational level with a follower, or 
 47
from a different department where the follower is not accountable to the 
change leader. 
? At least half of the respondents from a school on a particular change must 
agree on the change leader.  This rule is applied so that the validity of the 
identification of the leader is increased.  In some situations, several 
individuals were identified as change leaders for one change in one school, 
and therefore, this rule excluded such a change if there were no majority 
agreement on one person, so when a leader?s name sent in the third phase 
of the study, it will have more validity to most of the respondents from a 
particular school. 
4.1.5. Validity 
The change and change leader identified from the faculty members? responses 
were validated by the change leader responding to the following item during the second 
phase: ?are you a primary leader for (the specific change inserted here)??  The respondent 
had two choices; yes or no.  Also, the change leader had the opportunity to write in 
further comments.  Only one of the change leaders challenged the validity of her change 
leadership, and therefore was dropped from the sample. 
4.1.6. Response Rate 
The phase 1 population was composed of 3871 faculty members from 77 schools.  
The sample was composed of 421 faculty members who responded to the phase 1 Internet 
survey, for an 11% response rate.  The distribution of the response frequency ranged from 
 48
1 to 15 responses per school with a mean of about five and a half responses per school 
(S.D. = 3.19). 
For phase 1, the purpose was to identify changes and the change leaders 
responsible for each in each school, and therefore no other descriptive statistics were 
collected for either the participants or for the school. 
4.1.7. Changes Identified and their Change Leaders 
The analysis of the responses from the 77 schools identified 10 different changes 
from 57 schools (Table 3).  According to the criteria used for the analysis (discussed 
above), for 20 schools a change or a change leader could not be identified.   
Table 3:  Changes Identified and the Position of the Change Leader 
Change Identified AD Dean Total
Conversion from five year B.S. to six year Pharm. D. 1 8 9 
Implementation of problem-based learning in place of traditional lectures. 3 2 5 
Major change in curriculum 1 6 7 
Establishing a distance learning site for a traditional Pharm. D. program 1 10 11 
Change in the established mission or goals 1 7 8 
Changes in admission standards 3 4 7 
Implementation of dress code  (professional attire) 2 3 5 
Change in college structure (departmentalization) 0 1 1 
Increase in class size/enrollment 0 3 3 
Implementation of a faculty incentive plan 0 1 1 
Grand Total 12 45 57 
 
 49
In Table 3, the first column lists the changes identified and the last column 
contains the total number of schools who experienced that particular change.  The second 
and third columns state the number of deans or associate/assistant deans (AD) identified 
with each change. 
Three of these 57 schools were dropped from inclusion in the second phase.  Two 
of these schools had undergone a change of curriculum twice during the last three years, 
during which two different deans were responsible for the changes.  The third school had 
two campuses with two deans.  The responses from these two campuses could not be 
separated to indicate conclusively in which campus the change occurred or which dean 
was responsible for which change.  Excluding these three schools brought the total 
number of schools to be targeted in the second phase of the study to 54. 
4.2. Phase 2: Change Leaders? Survey 
An informed consent from the identified change leader was needed in order to 
send the third phase survey to the faculty members at a particular school.  In addition to 
obtaining consent from the change leaders, this second phase aimed at collecting 
information to validate the data collected from the faculty about the identified change and 
the change leader and to measure the leaders? satisfaction with what had been 
accomplished by the change initiative.  This survey also included an optional open-ended 
question with which to collect additional information. 
4.2.1. Population and Sampling 
The change leaders from the 54 schools identified from the first phase constitute 
the population of this phase.  A recruitment e-mail message was sent directly to the 
identified change leaders at each of the 54 schools (Appendix F).  Attached to the e-mail 
 50
message were two documents in a Microsoft Word format: (1) an Informed Consent letter 
(Appendix G), and (2) a copy of the third phase faculty survey.  A summary report of the 
study results was promised for consenting individuals.  One week after sending these e-
mails, a telephone call was attempted for each non-respondent change leader. 
4.2.2. Data Collection Method 
The e-mail message sent to the change leaders asked the recipient to first read the 
attachment containing the questionnaire to be sent to faculty in the third phase.  The goal 
was to allow change leaders to make an informed decision as to whether or not to allow 
the collection of such data from the faculty members at their schools.  After reading this 
attachment, they were asked then to open the second attachment and read the informed 
consent letter (Appendix G).  To communicate their decision to the researcher, they were 
asked to follow the Web address provided at the bottom of the informed consent letter.  
This would take them to the Web site containing the second phase change leaders survey 
(Appendix H).  The components of this instrument were as follows: 
1. Getting Consent 
Arriving at the Web site, a participant was given three options: either (A) 
participate AND allow other faculty members to participate; (B) NOT participate BUT 
allow other faculty members to participate; or (C) NOT participate AND NOT authorize 
others in the school to participate.  Consents were documented electronically by 
collecting the leaders? responses to the first two options.  Faculty members from a school 
with a non-consenting leader did not receive the third phase faculty survey. 
2. Items aimed at validating the first phase findings 
 51
Two items were included to check whether the change leader agreed with the 
faculty members? responses.  The first item asked the identified change leader whether he 
or she was in fact the primary leader for the change under investigation within his or her 
school.  The second item asked him or her to provide an estimate of the percentage of the 
goals actually accomplished by the change to compare it with the estimate the faculty 
provided in the first phase. 
3. Items aimed at ascertaining change leaders? satisfaction 
Two items were developed to measure the change leader?s satisfaction with what 
had been accomplished by the change under study: ?how satisfied are you with how 
much (quantity) was accomplished?? and ?how satisfied are you with the quality of what 
was accomplished??  These two items were rated on a five-point scale ranging from 
?very unsatisfied? to ?very satisfied.? 
4. Items aimed at collecting additional information 
At the end of the survey, an open-ended question was included to allow the 
participant to mention in their own words any perceived factor(s) that could have affected 
the way the faculty members responded to the change.  
5. Closing 
The participant was asked to click on a hot-button provided in order to submit his 
or her response.  Another page then opened with a thank you note and a prompt to close 
the Web browser window. 
4.2.3. Pre-test 
The survey instrument and the processes involved in collecting the data from the 
change leaders were pre-tested with one of the potential participants among the 54 
 52
targeted change leaders.  An appointment was arranged for a meeting with this 
individual.  A few minutes before the appointment, the principal investigator sent the 
invitation e-mail with the attachments as planned for the phase 2 participants.  Then 
during the meeting, the pre-test participant was asked to open the e-mail and follow the 
directions.  The principal investigator observed the process and responded to inquiries. 
Notes were taken for suggested improvements in the wording, for clarification of 
the purpose of the study, and for minimizing any potential misunderstanding.  For 
example, realizing the confusion that could occur when a change leader opened the 
attachment containing the faculty survey (for phase 3) and the possibility of 
misunderstanding its purpose, as a result of the pre-test, it was decided to incorporate a 
note into the faculty survey attachment: 
?Note for the change leader:  This survey is NOT for you, the change leader, to 
complete.  Only if you approve, this survey will be sent to your faculty.  Please 
indicate whether you approve sending the survey to your faculty by following the 
link within the Informed Consent document you received.  At that site, there is 
also a 4-item survey for the change leader to complete.? 
4.2.5. Response Rate 
Among the 54 individuals, 24 responded (nearly a 44% response rate) by 
consenting to allow the researcher to send the third phase survey to the faculty members 
at their schools.  However, among the consenting change leaders, only 18 filled out the 
change leader?s survey.  No descriptive statistics for the change leaders or for the schools 
they work at were collected.  A comparison of consenting and non-consenting change 
leaders was thus not possible. 
 53
4.2.6. Results 
The following tables summarize the data collected from 18 of the 24 consenting 
leaders who filled the leader?s survey.  For the item validating whether that person was in 
fact the change leader, all the respondents confirmed that they were indeed the main 
change leaders at their schools except one.  This person responded with a ?no? when 
asked if she was the main change leader, but followed with the following comment: 
?I came in when the change had already been implemented. I was assigned to 
carry out the goals of the change and modify the program to maintain the quality 
as I see fit. Today is not a good day to ask me what I think has been 
accomplished.? 
Although this person was refusing to be called the change leader, her comment 
shows that she was in charge of implementation of at least part of the change, which 
supports the responses from the faculty in phase 1 that identified her as the main change 
leader.  Therefore, the data from her school were admitted. 
For the second question, which asked how much of the change had been 
accomplished, the findings are displayed in Table 4.  Seventeen of the change leaders 
responded to this item (one missing value).  The majority confirmed the phase 1 faculty 
responses that the change was 70% completed, although several change leaders did not 
give such confirmation. 
 54
Table 4:  Change leaders Responses for the Percentage of Change Goals 
Completed 
Percentage 
of change 
goals 
accomplished 
100% 90% 80% 70% 60% 20% 10% Total 
Number of 
Responses 
5 3 2 3 2 1 1 17 
 
Recall that only changes with at least 70%, as rated by the faculty in the first 
phase, were sent to change leaders in this second phase, thus, Table 4 shows some 
discrepancy between faculty responses and change leaders responses in meeting this cut 
off value in at least three cases.  The discrepancy between the faculty members? 
responses and the leaders? responses could be due to two issues.  The first is a problem 
with different wording of the question.  Here the leaders were asked for percentage of 
goals accomplished, while the faculty members were asked for percentage of change 
accomplished.  Alternatively, it could be due to a difference in perception or knowledge 
related to the change.  For the change leaders, who are more closely observing the change 
unfold, the change goals tend to be in the early stages of completion, while faculty 
members, who were not as involved with the details of the change, could not make such a 
judgment. 
Table 5 displays the statistics for the satisfaction items.  One item asked about 
satisfaction with how much (quantity) was accomplished, and the other item asked about 
satisfaction with the quality of what was accomplished.  The descriptive statistics for the 
two items were close to each other ranging from 2 to 5 with a mean of about 4.1. 
 55
Table 5:  Description of Responses to Leader's Satisfaction Items 
  N Minimum Maximum Mean S.D. 
Satisfaction 
with Quantity 18 2 5 4.11 0.83 
Satisfaction 
with Quality 18 2 5 4.06 0.80 
 
4.3. Phase 3:  Determining the Interrelations Among the Study?s Variables 
The purpose of phase 3 was to answer the research questions addressed by the 
study and to test the hypotheses.  This involved the administration of an Internet survey 
that measured the variables of the study (leadership behaviors, commitment to change, 
change involvement) and the analysis of the collected data using structural equation 
modeling.  What follows is a description of the methods and procedures involved.  The 
results are included in the next chapter. 
4.3.1. Population and Sampling 
Only the 24 schools of consenting leaders were included in third phase survey.  
The AACP Roster showed a total of 1215 faculty members from these 24 schools.  All of 
them were sent the information letter via e-mail (Appendix I).  The e-mail message was 
undeliverable to 65 e-mail addresses, reducing the total number of invitations sent to 
1150.  A reminder message was sent two weeks later, again via e-mail (Appendix J).  The 
total number of responses was 190 from the 24 schools. 
 56
4.3.2. Data Collection Method 
An e-mail including the information letter (Appendix I) was sent to the faculty 
members of schools with consenting change leaders.  Faculty members were identified by 
24 schools? names from the AACP Roster (Microsoft Excel datasheet received from the 
AACP by e-mail on October 12, 2004).  The specific change and the change leader 
identified in phase 1 for each school were included in the e-mail message.  The faculty 
were invited to respond to an Internet survey (Appendix K contains the survey items).  If 
a recipient decided to participate, he or she could click on a hyperlink within the e-mail 
that directed them to the Internet site containing the survey questionnaire (Appendix L 
contains computer screenshots of the Internet format). 
Anonymity of data was strictly enforced.  The survey did not ask participants for 
any identifiable information, and the computer server did not collect identifiable 
information such as IP addresses. 
4.3.3. Measures 
The questionnaire measured variables related to the change and the change 
leadership (faculty commitment to the change, their behavioral support, their rating of the 
change leadership, the extent of their change involvement, their demographics and other 
control variables).   
Commitment to organizational change: 
The three components of commitment to organizational change were measured 
using the instrument developed by Herscovitch & Meyer (2002).  Table 6 lists each 
component and the items that make up its scale and the code utilized in this dissertation 
to represent the item. Responses were modified from a 7-point scale to a 5-point scale in 
 57
order to match the other measures in the instruments.  The 5-point scale ranged from 1 
(strongly disagree) to 5 (strongly agree). Higher scores indicated higher levels of 
commitment. 
Table 6:  Measures of Commitment 
Commitment components and their items Codes 
Affective Commitment 
I believe in the value of this change. 
This change is good for this organization. 
I think that administration is making a mistake by introducing this change. 
This change serves an important purpose. 
Things would be better without this change. 
This change is not necessary. 
 
AC1 
AC2 
AC3R 
AC4 
AC5R 
AC6R 
Normative Commitment 
I feel a sense of duty to work toward this change. 
I do not think it would be right for me to oppose this change. 
I would not feel badly about opposing this change. 
It would be irresponsible for me to resist this change 
I would feel guilty about opposing this change. 
I do not feel any obligation to support this change. 
 
NC1 
NC2 
NC3R 
NC4 
NC5 
NC6R 
Continuance Commitment 
I have no choice but to go along with this change. 
I feel pressure to go along with this change. 
I have too much at stake to resist this change. 
It would be too costly for me to resist this change. 
Resisting this change is not a viable option for me. 
 
CC1 
CC2 
CC3 
CC4 
CC6 
 58
Herscovitch and Mayer (2002) reported a reliability Cronbach?s alpha of .94 for 
affective, .94 for normative and .86 for continuance commitment.  Affective and 
continuance commitment were unrelated (r = -.05, ns), although normative commitment 
had significant correlations with both affective (r = .26, p < .01) and continuance 
commitment (r = .38, p < .01). 
Leadership: 
Leadership was measured with the 27-item brief version of the MLQ (Tejeda, 
Scandura, & Pillai, 2001).  Table 7 lists the instrument?s constructs and their items.  This 
instrument contains five transformational leadership subscales (charisma, idealized 
influence, inspirational motivation, intellectual stimulation, and individualized 
consideration), and three transactional leadership subscales (contingent reward, active 
management-by-exception, and passive management-by-exception). It also contains the 
measures of laissez-faire leadership.  Every item was rated on a five-point scale ranging 
from ?not at all,? through ?once in a while,? ?sometimes,? and ?fairly often,? to 
?frequently if not always.? 
Table 7:  Measures of Leadership 
Leadership Factors and their items Codes  
Charisma 
Displays extraordinary talent and competence in whatever he/she undertakes. 
His/her actions build my respect for him/her. 
Goes beyond his/her own self-interest for the good of our group. 
 
CHRSM1 
CHRSM2 
CHRSM3 
 59
Leadership Factors and their items Codes  
Idealized influence 
Emphasizes the importance of having a collective sense of mission. 
Clarifies the central purpose underlying our actions. 
Specifies the importance of having a strong sense of purpose. 
 
IDINFLC1 
IDINFLC2 
IDINFLC3 
Inspirational motivation 
Talks enthusiastically about what needs to be accomplished. 
Arouses awareness on what is essential to consider. 
Articulates a compelling vision of the future. 
 
INSPMT1 
INSPMT2 
INSPMT3 
Intellectual stimulation 
Gets me to look at problems from many different angles.  
Encourages me to express my ideas and opinions. 
Suggests new ways of looking at how we do our jobs. 
 
INTLST1 
INTLST2 
INTLST3 
Individualized consideration 
Promotes self-development. 
Provides useful advice for my development. 
Teaches me how to identify the needs and capabilities of others. 
 
INDCSD2 
INDCSD1 
INDCSD3 
Contingent reward 
Makes sure that we receive appropriate rewards for achieving performance 
targets. 
Tells me what to do to be rewarded for my efforts. 
Provides his/her assistance in exchange for my effort. 
 
CNGRW1 
 
CNGRW2 
CNGRW3 
 60
Leadership Factors and their items Codes  
Active management-by-exception 
Keeps track of my mistakes. 
Searches for mistakes before commenting on my performance. 
Directs his/her attention toward failure to meet standards. 
 
MBEA1 
MBEA2 
MBEA3 
Passive management-by-exception 
Problems must become chronic before he/she will take action. 
Things have to go wrong for him/her to take action. 
Fails to intervene until problems become serious. 
 
MBEP1 
MBEP2 
MBEP3 
Laissez-faire leadership 
Takes no action even when problems become chronic. 
Fails to follow-up requests for assistance. 
Delays responding to urgent questions. 
 
LSFR1 
LSFR2 
LSFR3 
 
In testing these 3-item scales for the leadership factors in four samples, Tejeda 
and collogues (2001) reported Cronbach?s alphas above the .70 for all the scales with all 
four samples, except for one sample for active management-by-exception (.61) and one 
sample with laissez-faire (.66).  Scales within transformational leadership had the largest 
internal consistency coefficients.  They concluded that the evidence supports the presence 
of internal consistency with the majority of the samples they used to test their briefer 
version of the MLQ.  
Change involvement 
Based on a review of the literature, change involvement was conceptualized in 
this study as a latent variable composed of three factors 1) participation in the change 
 61
decision 2) communication during the change 3) freedom to express doubts about the 
change.  The items used to measure them are provided in Table 8. 
Table 8:  Measures of Change Involvement 
Change involvement factors and their items Codes 
Participation in Decision Making 
I have assisted in the problem identification that led to the change. 
I have participated with fellow faculty in the design of this change. 
The decision-makers have asked for my input into this change. 
The decision-makers have listened to my opinion on the change initiative. 
The change initiative included suggestions I provided. 
 
PDM1 
PDM2 
PDM3 
PDM4 
PDM5 
Communication 
I was kept informed adequately. 
The faculty interacted frequently. 
There were breakdowns in communication among faculty. 
There were breakdowns in communication between faculty and administration. 
Information was quickly shared. 
There were extensive formal and informal communications throughout the 
change. 
 
CMM1 
CMM2 
CMM3R 
CMM4R 
CMM5 
CMM6 
Freedom to Express Doubt 
Criticizing or providing information which challenges the feasibility of the change 
was encouraged. 
I sometimes get the feeling that others were not speaking up although they 
harbored serious doubts about the direction being taken. 
Often I felt pressured to not "rock the boat" by speaking my mind about what's 
going on with this change. 
 
FXD1 
 
FXD2R 
 
FXD3R 
 
 62
 
Behavioral support 
To assess compliance behavior and discretionary behavior, the 101-point 
behavioral continuum provided by Herscovitch and Meyer (2002) was used.  Anchor 
points were labeled from left to right as active resistance (0 to 20), passive resistance (21 
to 40), compliance (41 to 60), cooperation (61 to 80), and championing (81 to 100).  
Compliance behaviors scores were in the range from 0 to 60 and discretionary behavior 
scores were in the range from 61 to 100. 
4.3.4. Pre-test 
The sample questionnaire was pre-tested to ensure that it was readable, 
interpretable, and to explore any difficulties that could arise in the administration process 
with the sample.  Two persons pre-tested it; one was a potential respondent, who used a 
paper and pencil version of the questionnaire, and the other was a graduate student who 
tested the Internet version.  These two individuals provided comments which resulted in 
minor changes in the original instrument. 
4.3.5. Data Analysis Methods 
Structural equation modeling (SEM) was employed to test the hypotheses. 
Specifically, a two-step strategy recommended by Anderson and Gerbing (1988) using 
AMOS 5 was used.  In the first step, a separate estimation of the measurement model 
using confirmatory factor analysis was performed before the simultaneous estimation of 
the structural model.  This allowed for assessment of the reliability and validity of the 
measures.  In the next step, a specification of the relationships among constructs was built 
 63
in a structural model where the overall fit was estimated and the path loading assessed for 
significance and strength. 
Four separate models were constructed and tested as described in the previous 
chapter under concepts and definitions.  The models were assessed by fit measures 
recommended by the following fit indices: chi-square, the comparative fit index (CFI), 
and the Root Mean Square Error of Approximation (RMSEA). 
 64
5. RESULTS 
This chapter presents the results for the last phase of the study, phase 3, which 
involved answering the research questions posed for this dissertation and the testing of 
the hypotheses.  The results of the earlier two phases of the study were included under the 
description of the methods in the previous chapter. 
5.1. Response Rate 
From the 1150 faculty members at the 24 schools sent the invitation to participate, 
190 submitted phase 3 Internet surveys, approximately a 17% response rate.  Table 9 
shows descriptive statistics for the response frequency per school, which ranged from 3 to 
19, with a mean of 7.92 responses per school (S.D. = 4.66). 
Table 9: Phase 3 Response Distribution 
Number of 
schools 
Sum of 
Responses 
Mean 
Response 
Standard 
Deviation 
Minimum Maximum 
24 190 7.92 4.66 3 19 
 
Table 10 lists the number of responses with their frequencies.  The most common 
number of responses (the mode) was 5, which came from 6 schools.
 65
Table 10: Frequency of Number of Responses 
N Responses 3 4 5 6 7 9 10 11 14 15 17 19 Total
Frequency   
(N Schools) 
2 3 6 2 3 1 1 1 2 1 1 1 24 
Sum of 
Responses 
6 12 30 12 21 9 10 11 28 15 17 19 190 
 
5.2. Sample Description 
The gender distribution of the faculty members is shown in Table 11. 
Table 11: Gender of the Participants 
Gender Frequency Relative 
Frequency 
Valid Relative 
Frequency 
Population 
Data 
Female 90 47.4% 50.3% 40.8% 
Male 89 46.8% 49.7% 59.2% 
Total 179 94.2% 100% 100% 
Missing 11 5.8%   
Total 190 100%   
 
Half of the sample was composed of females and half of males.  These 
proportions differ from the typical population of faculty members at schools of pharmacy 
in the US, which generally consists of about 60% males and 40% females.  The 
difference in gender distribution between the sample and the population was found to be 
significant (Chi-square = 6.39, df = 1, p < 0.05), which indicates a response bias. 
Table 12 displays the age distribution of the sample.  Age data were collected as 
categories of 5-year intervals.  
 66
Table 12: Age Distribution of the Sample 
Age Group Frequency 
Relative 
Frequency 
Valid Relative 
Frequency 
Grouped for 
Comparison 
Population 
Data 
25-30 24 12.6% 13.8% 13.8% 5.3% 
31-35 34 17.9% 19.5% 
36-40 16 8.4% 9.2% 
28.7% 24.2% 
41-45 18 9.5% 10.3% 
46-50 27 14.2% 15.5% 
25.8% 28% 
51-55 18 9.5% 10.3% 
56-60 21 11.1% 12.1% 
22.4% 28.3% 
61-65 11 5.8% 6.3% 
Over 65 5 2.6% 2.9% 
9.2% 14.2% 
Total 174 91.6% 100% 100% 100% 
Missing 16 8.4%    
Total 190 100%    
 
All age groups were represented in the sample; however some groups had 
different proportions from that of the typical population.  The youngest age group (30 or 
below) was represented more strongly in the sample (13.8%) than in the general 
population (5.3%), and the older age groups (fifties and above) were in lower than 
expected proportions in the sample (31.6%) than in the population as a whole (42.5%), 
while the age groups in the middle (the thirties and forties) were generally closer to the 
population than other age groups.  This difference in age distribution was found to be 
statistically significant (Chi-square = 27.92, df = 4, p < 0.05), again indicating a response 
bias. The sample of faculty members who participated in this study was generally 
composed of younger faculty than would generally be found in the population of faculty 
members in US schools of pharmacy.  
 67
The measures of central tendency for the number of years a person has been a 
faculty member in a school of pharmacy are displayed in Table 13.  The average was 
about 12 and half years with about an 11 year standard deviation.  The mode was two 
years; reflecting the skewed nature of data, as shown in Figure 4. 
Table 13: Years as a Faculty Member 
N Mean 
Standard 
Deviation 
Median Mode 
Minimum Maximum 
172 12.4 10.8 9.0 2 0 41 
 
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 27 28 29 30 32 33 35 37 38 40 41
0
5
10
15
20
F
r
equency
How many years have you been a faculty member at a school of pharmacy?
 
Figure 4: Years as Faculty Member 
 
Table 14 shows the distribution of academic disciplines by gender and a 
comparison with population data.  
 68
Table 14: Academic Discipline by Gender, Compared to the Population as 
a Whole 
Academic Discipline Frequency Relative 
Frequency 
Valid Relative 
Frequency 
Population 
Data 
Pharmacy Practice 
     Male 
     Female 
112 
(41) 
(68) 
58.9% 63.3% 
(23.7%) 
(39.3%) 
50.8% 
22.7% 
28.1% 
Biological Sciences 
    Male 
    Female 
19 
(14) 
(5) 
10% 10.7% 
(8.1%) 
(2.9%) 
14.8% 
11.4% 
3.5% 
Social/Adm. Sciences 
     Male 
     Female 
18 
(14) 
(4) 
9.5% 10.2% 
(8.1%) 
(2.3%) 
8.5% 
5.8% 
2.7% 
Pharmaceutics 
     Male 
     Female 
11 
(7) 
(3) 
5.8% 6.2% 
(4.0%) 
(1.7%) 
11.9% 
9.3% 
2.6% 
Chemistry 
     Male 
     Female 
9 
(8) 
(1) 
4.7% 5.1% 
(4.6%) 
(0.6%) 
11.8% 
10.1% 
1.7% 
Continuing Education 1 0.5% 0.6% 0.8% 
Libraries 1 0.5% 0.6% 0.8%
Others 6 3.2% 3.4% 0.6% 
Total 177 93.2% 100% 100%
Missing 13 6.8%   
Total 190 100%
 
The most noteworthy finding was the over representation of pharmacy practice 
faculty, especially females, in the sample (59% in the sample vs. 51% in the population) 
and the under representation of faculty from biological sciences (10% in the sample vs. 
15% in the population), pharmaceutics (6% in the sample vs. 12% in the population) and 
chemistry (5% in the sample vs. 12% in the population).  Faculty members from the 
 69
social and administrative discipline were represented in the sample relatively closely to 
the population as a whole (9.5% in the sample vs. 8.5% in the population).  Chi square 
analysis of these groups (without gender specification), resulted in significant difference 
(Chi-square = 37.73, df = 7, p < 0.05). 
Other descriptive data collected included whether respondents were in tenure 
track positions and whether they held an administrative position.  Tables 15 and 16 
display these data, respectively.  As shown in Table 15, in the sample more people were 
in a tenure track position (53.3%) than non-tenure (46.7%).  In the population as a whole, 
people in tenure track also outnumbered those in non-tenure track positions, but with a 
greater gap than in the sample (58% tenure vs. 42% non-tenure).  However, this 
difference between the sample and the population was found to be not significant (Chi-
square = 1.53, df = 1, which is not significance at the .05 level).  . 
Table 15: Distribution of Tenure and Non-tenure Track Compared to the 
Population 
Tenure Track  Frequency Relative 
Frequency 
Valid Relative 
Frequency 
Population 
Data 
Yes 97 51.1% 53.3% 57.9% 
No 85 44.7% 46.7% 42.1%
Total 182 95.8% 100% 100% 
Missing 8 4.2%   
 190 100%
 
Finally, Table 16 shows the distribution of faculty members who hold an 
administrative position versus those who do not.  Only about 21% reported being in an 
administrative position where other faculty members report directly to them.  Similar 
population data were not found to compare with the sample. 
 70
Table 16: Distribution of Faculty Members with Administrative Positions 
Hold Administrative 
Position 
Frequency Relative Frequency Valid Relative 
Frequency 
No 145 76.3% 78.4% 
Yes 40 21.1% 21.6%
Total 185 97.4% 100% 
Missing 5 2.6%  
 190 100% 
 
Exploring correlations between demographic variable from one side and the 
various scales entering hypotheses testing found the statically significant correlations 
listed in Table 17. 
 71
Table 17: Statistically Significant Correlations between Demographics and 
Study Scales 
 Age Tenure 
Track 
0 = No 
1 = Yes 
Administrative 
Position 
0 = No 
1 = Yes 
Affective Commitment  -.20*  
Normative Commitment    
Continuance Commitment    
Participation in Decision making    
Communication   -.23**  
Freedom to Express Doubt   -.15*  
Charisma  .16*
Inspirational Motivation  -.17*  
Intellectual Stimulation   17* 
Individualized Consideration   .25** 
Contingent Reward   .23** 
Passive Management by 
Exception 
 .19* -.16* 
Laissez-faire -.21**
Compliance Behavior -.16* -.19*  
Discretionary Behavior   .17* 
**  Correlation is significant at the 0.01 level (2-tailed). 
*  Correlation is significant at the 0.05 level (2-tailed). 
 
Gender and number of years as a faculty member did not correlate significantly 
with any of the scale measures; therefore, they were not included in Table 17.  Age was 
only correlated with compliance behavior (r = -.16, p < .05).  Younger faculty members 
scored higher in compliance behavior than older faculty members.  Holding a tenure track 
position had a significant positive correlation with a leader?s passive management by 
exception behaviors (r = .19, p < .05), but had significant negative correlations with five 
variables.  A tenure track position was negatively correlated with affective commitment 
 72
(r = -.20, p < .05), perception of communication intensity (r = -.23, p < .01), perception of 
freedom to express doubt (r = -15, p < .05), compliance behavior (r = -.19, p < .05), and 
with leader?s inspirational motivation (r = -.17, p < .05). 
Being in an administrative position had significant positive correlations with 
charisma (r = .16, p < .05), intellectual stimulation (r = 17, p < .05), individualized 
consideration (r = .25, p < .01), contingent reward (r = .23, p < .01), and discretionary 
behavior (r = .17, p < .05).  However, administrative position had significant negative 
correlations with passive management by exception (r = -.16, p < .05) and perception of a 
laissez-faire type leader (r = -.21, p < .01). 
Since academic discipline contained 8 nominal categories, the correlation analysis 
can be considered meaningless, and therefore was not included in Table 17.  To 
investigate the effect of academic discipline a series of one-way analysis of variance 
(ANOVA) tests were conducted for each of the scale variables in Table 17.   
As a function of academic discipline, significant differences were found in the 
scores of effective commitment (F (5, 160) = 3.03, p < .05), continuance commitment (F 
(5, 160) = 2.96, p < .05), compliance behavior (F (5, 157) = 2.57, p < .05), and 
discretionary behavior (F (5, 157) = 2.75, p < .05).  The Scheffe and the Bonferroni post-
hoc tests revealed only one significant difference: with continuance commitment, values 
for biological sciences faculty were significantly higher than faculty from the social and 
administrative sciences discipline.  No other specific post-hoc contrasts were significant. 
5.3. Missing Data 
Before hypotheses testing, missing value analysis using SPSS was conducted to 
examine the data for patterns of missing data.  The focus of the analysis was on two 
 73
issues.  The first was on frequently missed items, which may indicate that the question 
concerned was confusing.  The second focus was on an individual respondent?s skipping 
of a large portion of a measurement scale.  If a participant missed more than one third of 
the items of a scale, he or she was considered to miss the whole scale value. 
Ten cases were deleted from the 190 participant as they were deemed to have 
skipped either the three commitment scales or several of the leadership scales.  Among 
the180 submissions remaining, 148 cases (82.2%) had no missing item values, and 175 
cases (97.2%) had no missing scale values.  There were no consistencies in missing a 
particular scale value among the five who missed a scale. 
 The top three most frequently missed items were all from the management by 
exception-active scale: ?keeps track of my mistakes,? ?directs his/her attention toward 
failure to meet standards? (both missing by 5 cases), and ?searches for mistakes before 
commenting on my performance? (missing by 4 cases).  Only one other item was missed 
by 4 cases, and this belonged to the laissez-faire scale: ?takes no action even when 
problems become chronic.?  All other items were missing in 3 or fewer cases; 33 items 
had no missing values.   
Based on the above, and on the fact that 10 cases had been deleted earlier for 
missing multiple scale values, it was concluded that there was insufficient evidence to 
declare any of the items or scales to be problematic and to justify deletion. 
5.4. Score Reliability 
Table 18 contains the descriptive statistics for all the variables included in the 
analysis and Cronbach?s alpha reliability results for each measure.  A coefficient alpha of 
0.7 or greater generally indicates an acceptable reliability. 
 74
Table 18: Descriptive Statistics for All Measures 
Scale Cronbach's
Alpha   
(if item deleted) 
Mean SD Skew 
Affective Commitment 
AC1 
AC2 
AC3R 
AC4 
AC5R 
AC6R 
.956  
(.953) 
(.944) 
(.944) 
(.945) 
(.952) 
(.950) 
3.72 
3.82 
3.77 
3.78 
3.75 
3.61 
3.60 
1.007 
1.075 
1.084 
1.159 
1.046 
1.105 
1.120 
-0.83 
-0.85 
-0.87 
-0.89 
-0.86 
-0.76 
-0.80 
Normative Commitment 
NC1 
NC2 
NC3R 
NC4 
NC5 
NC6R 
.786 
(.778) 
(.740) 
(.745) 
(.738) 
(.779) 
(.735) 
3.51 
3.98 
3.25 
3.66 
3.35 
2.92 
3.92 
0.742 
0.858 
1.121 
1.109 
1.158 
1.180 
0.973 
-0.33 
-1.03 
-0.32 
-0.34 
-0.39 
-0.13 
-1.06 
Continuance Commitment 
CC1 
CC2 
CC3 
CC4 
CC6 
.860 
(.839) 
(.836) 
(.818) 
(.834) 
(.827) 
2.88 
2.77 
2.96 
2.75 
2.86 
3.11 
0.956 
1.233 
1.223 
1.157 
1.168 
1.159 
-0.01 
0.24 
-0.10 
0.26 
0.05 
-0.21 
Participation in Decision Making 
PDM1 
PDM2 
PDM3 
PDM4 
PDM5 
.907 
(.915) 
(.891) 
(.875) 
(.876) 
(.871) 
3.12 
2.94 
3.24 
3.26 
3.17 
2.92 
1.019 
1.142 
1.247 
1.282 
1.200 
1.098 
-0.19 
-0.03 
-0.26 
-0.46 
-0.28 
-0.06 
Communication 
CMM1 
CMM2 
CMM3R 
.850 
(.802) 
(.832) 
(.846) 
2.96 
3.19 
3.11 
2.88 
.81884 
1.157 
1.111 
1.015 
-.179 
-.310 
-.384 
.152 
 75
Scale Cronbach's 
Alpha   
(if item deleted) 
Mean SD Skew 
CMM4R 
CMM5 
CMM6 
(.854) 
(.810) 
(.804) 
2.78 
2.84 
2.99 
1.135 
1.021 
1.068 
.157 
-.097 
-.241 
Freedom to Express Doubt 
FXD1 
FXD2R 
FXD3R 
.788 
(.764) 
(.680) 
(.689) 
2.9702 
2.88 
2.62 
3.41 
.94959 
1.143 
1.171 
1.092 
-.190 
-.087 
.439 
-.425 
Charisma 
CHRSM1 
CHRSM2 
CHRSM3 
.916 
(.896) 
(.841) 
(.901) 
3.6130 
3.73 
3.64 
3.47 
1.15747 
1.162 
1.245 
1.339 
-.639 
-.749 
-.669 
-.493 
Idealized Influnce 
IDINFLC1 
IDINFLC2 
IDINFLC3 
.892 
(.850) 
(.852) 
(.837) 
3.60 
3.64 
3.47 
3.68 
1.11344 
1.236 
1.304 
1.144 
-.733 
-.822 
-.493 
-.740 
Inspirational Motivation 
INSPMT1 
INSPMT2 
INSPMT3 
.850 
(.766) 
(.805) 
(.804) 
3.7037 
4.05 
3.35 
3.71 
1.05344 
1.100 
1.257 
1.239 
-.673 
-1.14 
-.449 
-.663 
Intellectual  Stimulation 
INTLST1 
INTLST2 
INTLST3 
.860 
(.746) 
(.803) 
(.853) 
3.2528 
3.14 
3.36 
3.43 
1.21386 
1.247 
1.352 
1.177 
-.330 
-.164 
-.396 
-.448 
Individualized Consideration 
INDCSD1 
INDCSD2 
INDCSD3 
.842 
(.858) 
(.692) 
(.763) 
3.1657 
3.76 
3.11 
2.63 
1.11498 
1.140 
1.416 
1.271 
-.056 
-.754 
-.117 
.224 
Contingent Reward 
CNGRW1 
CNGRW2 
CNGRW3 
.837 
(.753) 
(.787) 
(.781) 
2.9148 
2.74 
2.69 
3.30 
1.05740 
1.171 
1.213 
1.275 
-.017 
.089 
.145 
-.355 
 76
Scale Cronbach's 
Alpha   
(if item deleted) 
Mean SD Skew 
Active Management by Exception 
MBEA1 
MBEA2 
MBEA3 
.49 
(-.052*) 
(.033) 
(.861) 
2.4296 
2.11 
1.80 
3.34 
.85783 
1.152 
1.147 
1.178 
.741 
.835 
1.387 
-.439 
Passive Management by Exception 
MBEP1 
MBEP2 
MBEP3 
.918 
(.839) 
(.918) 
(.884) 
2.2148 
2.24 
2.19 
2.21 
1.08464 
1.217 
1.142 
1.148 
.702 
.685 
.646 
.630 
Laissez-faire or Non-leadership 
LSFR1 
LSFR2 
LSFR3 
.757 
(.712) 
(.637) 
(.676) 
2.10 
2.22 
2.01 
2.07 
.89078 
1.112 
1.060 
1.101 
.844 
.787 
.786 
.847 
*The value is negative due to a negative average covariance among items. This violates reliability 
model assumptions. 
 
All of the measured scores showed acceptable reliability coefficients except for 
one: active management by exception.  Deleting one item from the scale (MBEA3: 
?directs his/her attention toward failure to meet standards?) improved the Cronbach?s 
alpha level from 0.49 to 0.86.  The subsequent analyses for hypotheses testing used this 
new 2-item measure for active management by exception; ?keeps track of my mistakes? 
(MBEA1), and ?searches for mistakes before commenting on my performance? 
(MBEA2). 
Table 19 displays the correlation among the measures based on 180 participants. 
 77
Table 19: Correlations among Variables Included in Hypotheses Testing 
 Measure 1 2 3 4 5 6 7 8 
1 Affective 
Commitment 
1 
       
2 Normative 
Commitment 
.56** 1 
      
3 Continuance 
Commitment 
-.34** .20** 1 
     
4 Participation in 
Decision 
Making 
.60** .42** -.27** 1 
    
5 Communication .53** .35** -.25** .78** 1    
6 Freedom to 
Express Doubt 
.65** .28** -.52** .66** .66** 1 
  
7 Charisma .57** .35** -.25** .46** .48** .56** 1  
8 Idealized 
Influnce 
.50** .29** -.24** .48** .49** .53** .83** 1 
9 Inspirational 
Motivation 
.51** .33** -.25** .45** .50** .55** .86** .89** 
10 Intellectual  
Stimulation 
.57** .34** -.27** .53** .54** .63** .83** .84** 
11 Individualized 
Consideration 
.47** .32** -.22** .50** .49** .55** .78** .79** 
12 Contingent 
Reward 
.46** .36** -.18* .48** .56** .55** .71** .72** 
13 Active MBE -.18* -.22** .12 -.19** -.16* -.21** -.27** -.14 
14 Active MBE 2-
item 
-.34** -.34** .16* -.33** -.30** -.37** -.40** -.34** 
15 Passive MBE -.55** -.28** .25** -.47** -.55** -.54** -.70** -.65** 
16 Laissez-faire -.48** -.30** .26** -.46** -.51** -.53** -.69** -.66** 
17 Behavioral 
Support 
.78** .61** -.17* .63** .50** .56** .52** .47** 
**  Correlation is significant at the 0.01 level (2-tailed). 
*  Correlation is significant at the 0.05 level (2-tailed). 
 78
Table 19 (continued) 
 Measure 9 10 11 12 13 14 15 16 
9 Inspirational 
Motivation 
1        
10 Intellectual  
Stimulation 
.82** 1       
11 Individualized 
Consideration 
.78** .84** 1      
12 Contingent 
Reward 
.73** .81** .81* 1     
13 Active MBE -.23** -.17* -.09 -.08 1    
14 Active MBE 2-
item 
-.38** -.33** -.28** -.26** .88** 1   
15 Passive MBE -.64** -.66** -.59** -.58** .20** .33* 1  
16 Laissez-faire -.65** -.68** -.61** -.59** .28* .42** .83* 1 
17 Behavioral 
Support 
.51** .53** .50** .49* -.29** -.42* -.42** -.43* 
**  Correlation is significant at the 0.01 level (2-tailed). 
*  Correlation is significant at the 0.05 level (2-tailed). 
5.5. Measurement Models 
For specification of the measurement model using CFA, it was necessary to use 
data without missing values in order for AMOS to produce modification indexes.  These 
missing values were replaced by the mean of the corresponding series for this stage.  
However, when going on to work with the full model, the original data for the 180 cases, 
including any missing values, was used. 
Confirmatory factor analyses were performed to verify the dimensionality of the 
scales to be used in hypotheses testing.  For leadership, the hypothesized original Bass?s 
(1985) specification factor structure was tested first.  AMOS was unsuccessful in the 
minimization process and was unable to estimate the parameters of the model. When this 
occurs, it is usually a sign that the model fits the data very poorly, either because the 
 79
model is wrong or because the sample size is too small (AMOS output).  Therefore, this 
original factor structure specification was rejected. 
The second specification attempted was Avolio?s (2004) specification of the full 
leadership model as a hierarchy of four high level factors and 12 lower level factors, as 
shown in Figure 5.  This specification was also rejected for the same reason as above 
(AMOS was unable to estimate the parameters). 
 
Figure 5: Avolio's (2004) Specification of the Leadership Constructs 
 
Another variant of Avolio?s hierarchy model was tried as a first-order CFA.  The 
lower latent variables were deleted and their measured indicators were regressed directly 
to the four main factors.  This model was also rejected because minimization was 
unsuccessful and parameters could not be estimated. 
Using previous empirical investigation of the factor structure reported by Avolio 
(2004), as well as the modification indexes provided by AMOS, a series of CFAs was 
 80
conducted until a well fitted model was obtained.  The final model for leadership was 
specified as in Figure 6.  Transformational leadership factors (charisma, idealized 
influnce, inspirational motivation, intellectual stimulation, and individualized 
considerations) were indistinguishable and produced a single factor.  Including all of 
these items to represent transformational leadership would decrease its efficiency and 
make the model more sensitive to sample size.  Hence, only 5 items were used to 
represent the transformational leadership factor, as shown in the Figure 6.  As for the 
transactional leadership, 3 factors were distinguishable as proposed by theory, although 
they did not all load on one factor.  Active management-by-exception and contingent 
reward each formed a separate factor while passive management by exception loaded best 
on the laissez-faire factor.  When the leadership factors were specified this way, a well 
fitted model resulted, with Chi-square (88, N = 180) = 166.848, p < .000, CFI = 0.958, 
RMSEA = .071 (90% CI = 0.054, 0.087).  Figure 6 displays the standardized estimates 
for this model. 
Transform
INTLST3
e1
.81
CHRSM1
e2
.85
INSPMT1
e3
.85
INSPMT3
e4
.79
IDINFLC1
e5
.82
Avoident
LSFR2
e6
LSFR1
e7
MBEP3
e8
MBEP2
e9
MBEP1
e10
.81
.76
.90
.85
.97
Contingent
Reward
CNGRW3
e11
.80
CNGRW2
e12
.73
CNGRW1
e13
.83
MBE-A
MBEA2
e14
MBEA1
e15
1.00
.77
-.77
-.53
.42
-.41
-.71
.84
 
Figure 6:  The Final Measurement Model of the Leadership Constructs 
 
 81
Similarly for the change involvement construct, a series of CFAs were conducted 
in order to validate the measurement model.  The proposed model of one latent variable 
(change involvement) composed of three factors (participation in decision making, 
communication, and freedom to express doubts) was rejected for poor fit.  Two distinct 
factors were distinguishable: one of which combined items from participation in decision 
making and communication, and the other factor contained the items for the freedom to 
express doubt construct.  This was also rejected for poor fit.  The final change 
involvement construct was composed of only one factor that contained five items, three 
from participation in decision making, and two from communication.  Table 20 lists the 
correlation among the measures based on the specified measurement models. 
Table 20: Correlations among Variables after the Specification of the 
Measurement Models 
 Measure 1 2 3 4 5 6 7 8 
1 Affective 
Commitment 
1 
       
2 Normative 
Commitment 
.56** 1 
      
3 Continuance 
Commitment 
-.34** .20** 1 
     
4 Transformational 
Leadership 
.50** .32** -.25** 1 
    
5 Contingent 
Reward 
.46** .36** -.18* .71** 1 
   
6 Active MBE -.34** -.34** .16* -.42** -.26** 1   
7 Avoidant 
Behaviors 
-.53** -.29** .25** -.68** -.60** .36** 1 
 
8 Change 
Involvement 
.59** .43** -.22** .45** .50** -.30** -.48** 1 
9 Behavioral 
Support 
.78** .61** -.17* .50** .49** -.42** -.43** .61** 
**  Correlation is significant at the 0.01 level (2-tailed). 
*  Correlation is significant at the 0.05 level (2-tailed). 
 
 82
5.6. Hypothesis Testing 
Four structural equations models were used to test the hypotheses of the study.  
The first three models examined whether leadership dimensions and change involvement 
accounted for variance in affective commitment (Model 1A), normative commitment 
(Model 1B), or continuance commitment (Model 1C).  Each of the dimensions of 
leadership (transformational, contingent reward, active management by exception, 
avoidant) in these three models is specified to have direct effects on commitment in 
addition to indirect effects through the mediating variable change involvement.  The 
fourth model (Model 2) examined the effect of the three dimensions of commitment on 
change leader satisfaction, both directly and indirectly through the mediating variables 
compliance and discretionary behaviors. 
Figures 7, 8, 9, and 10 present brief versions of Models 1A, 1B, 1C, and 2, 
respectively, which contain only the paths between the latent variables.  The full models 
with their indicators and error terms are included in the appendixes (Appendices M, N, O 
and P).  The AMOS text outputs for the parameters estimates and fit indexes are also 
included in these Appendices. 
5.6.1. Hypotheses accounting for variability in Change Involvement and Affective 
Commitment 
Leadership dimension paths to affective commitment and the mediating effect of 
change involvement were tested by the structural equation Model 1A, as illustrated in 
Figure 7. This model had a good fit: Chi-square (df = 261, N = 180) = 363.176, p < .000, 
CFI = 0.971, RMSEA = 0.047 (90% CI = 0.035, 0.058).  Standardized parameter 
estimates for Model 1A are shown in Figure 7.  Affective commitment was predicted by 
 83
change involvement (Beta = .42, p < .001) and by avoidant behaviors (Beta = -.22, p < 
.05).  Change involvement was predicted by contingent reward (Beta = .49, p < .01), by 
active management by exception (Beta = -.17, p < .05), and by avoidant behaviors (Beta 
= -.26, p < .05), but not by transformation leadership. 
 
Transformational
Leadership
Avoidant
Contingent
Reward
Active Management
by Exception
Affective
Commitment
Change
Involvement
0.37**
0.84**
- 0.49**
- 0.71**
- 0.74**
- 0.38**
0
.
4
9
*
*
-
 
0
.
1
7
*
-
 
0
.
2
6*
-
0
.
1
8
0
.1
0.0
1
0.42**
- 
0
.2
2
*
-0.
13
 
Figure 7: Model 1A, Simplified by Removing the Indicators and the Error 
Terms. 
Statistically significant paths are in bold: ** p < 0.01, * p < 0.05. 
 
The hypotheses tested by Model 1A are listed below, each followed by its results: 
? H5a: Transactional leadership on the part of a change leader will be 
negatively associated with affective commitment. 
After re-specification of the measurement model of the leadership dimensions 
(explained above), transactional leadership was divided in the new model by two factors; 
 84
contingent reward and active management by exception.  In Model 1A, both of the direct 
paths from these two factors to affective commitment failed to achieve significance (p = 
.95 for contingent reward, and p = .053 for active MBE); thus hypothesis H5a was not 
supported. 
? H6a: Transformational leadership on the part of a change leader will be 
positively associated with affective commitment. 
The direct path from transformational to affective commitment was not 
significant.  Hypothesis 6a was therefore not supported (p = .52). 
? H7a: Laissez-faire or non-leadership on the part of a change leader will be 
negatively associated with affective commitment. 
After the re-specification of the measurement model, laissez-faire was represented 
by avoidant behaviors (which incorporated passive MBE).  The direct path from avoidant 
to affective commitment was significant and negatively associated (Beta = -.22, p < 
0.05); thus hypothesis 7a was supported. 
? H8: Transactional leadership on the part of a change leader will be 
positively associated with faculty change involvement. 
Both of the paths from the factors representing transactional leadership to change 
involvement were significant, however they were in the opposite direction.  Contingent 
reward was positively associated (Beta = .49, p < 0.01), but active MBE was negatively 
associated (Beta = -.26, p < .05).  Because of this conflict between these two factors, both 
of which supposedly represent transactional leadership, hypothesis 8 cannot be supported.   
? H9: Transformational leadership on the part of a change leader will be 
positively associated with faculty change involvement. 
 85
The path between transformational leadership and change involvement did not 
achieve significance (p = .33).  Therefore, hypothesis H9 was not supported. 
? H10: Laissez-faire or non-leadership on the part of a change leader will 
not be associated with faculty change involvement. 
The path between avoidant behaviors and change involvement was significant 
(Beta = -.26, p < .05).  However, H10 stated that the path should not be significant (no 
association).  Therefore, H10 cannot be supported. 
? H11a: Faculty change involvement will be positively associated with 
affective commitment. 
Significance was achieved within the direct path from change involvement to 
affective commitment (Beta = -.42, p < .001).  Hypothesis 11a was supported. 
5.6.2. Hypotheses accounting for variability in Normative Commitment 
 Model 1B, illustrated in Figure 8, shows the effects of leadership dimensions and 
change involvement on normative commitment to organizational change. 
 86
Transformational
Leadership
Avoidant
Contingent
Reward
Active Management
by Exception
Normative
Commitment
Change
Involvement
0.38**
0.83**
- 0.5**
- 0.7**
- 0.74**
- 0.38**
0
.
4
9
*
*
-
 
0
.
1
6
*
-
 
0
.
2
6
*
-
 
0
.
1
7
-
 0
.1
7
0.3
1
0.30**
- 
0
.0
4
- 0
.31
**
 
Figure 8: Model 1B Accounting for Variance of Normative Commitment.  
Statistically significant paths are in bold: ** p < 0.01, * p < 0.05. 
 
Model 1B had a good fit to the data: Chi-square (261, N = 180) = 410.374, p < 
.000, CFI = 0.946, RMSEA = .057 (90% CI = .046, .067).  The standardized parameter 
estimates for Model 1B are shown in Figure 8, and the following are the hypotheses 
tested within it: 
? H5b: Transactional leadership on the part of a change leader will be 
negatively associated with normative commitment 
The path between contingent reward and normative commitment did not reach 
statistical significance (Beta = .31, p = .131), but active MBE had a statistically 
significant direct path to normative commitment (Beta = -.31, p < .05).  Since 
transactional leadership is represented by these two constructs in the model, hypothesis 
 87
H5b can only be partially supported by active MBE, with a statistically significant 
relationship to normative commitment. 
? H6b: Transformational leadership on the part of a change leader will be 
positively associated with normative commitment. 
The direct path between transformational leadership and normative commitment 
in Model 1B did not reach significance.  Hypothesis H6b was therefore not supported. 
? H7b: Laissez-faire or non-leadership on the part of a change leader will be 
negatively associated with normative commitment. 
The direct path between avoidant behaviors (the new construct in place of laissez 
faire) and normative commitment was not significant.  Therefore, hypothesis H7b was 
not supported. 
? H11b: Faculty change involvement will be positively associated with 
normative commitment. 
Change involvement had statistically significant direct path to normative 
commitment, therefore, hypothesis H11b was supported. 
5.6.3. Hypotheses Accounting for Variability in Continuance Commitment 
Figure 9 displays the structural equation model (Model 1C) used to test 
hypotheses accounting for variability in continuance commitment.  The model fit the data 
well; Chi-square (261, N = 180) = 434.566, p < .000, CFI = .941, RMSEA = .061 (90% 
CI = .061, .040).  The standardized parameter estimates for Model 1B are shown in 
Figure 9. 
 88
Transformational
Leadership
Avoidant
Contingent
Reward
Active Management
by Exception
Continuance
Commitment
Change
Involvement
0.33**
0.88**
- 0.57**
- 0.57**
- 0.55**
- 0.46**
0
.
4
8
*
*
-
 
0
.
1
6
*
-
 
0
.
2
6
*
-
0
.
1
7
-
 0
.2
1
0.1
2
0.14
0
.1
2
0.0
2
 
Figure 9: Model 1C Accounting for Variance of Continuance 
Commitment. 
Statistically significant paths are in bold: ** p < 0.01, * p < 0.05. 
 
The hypotheses tested in Model 1C were as follows: 
? H5c: Transactional leadership on the part of a change leader will be 
positively associated with continuance commitment. 
Both of the direct paths from contingent reward and active MBE (representing 
transactional leadership) were not statistically significant; therefore, hypothesis H5c was 
not supported. 
? H6c: Transformational leadership on the part of a change leader will be 
negatively associated with continuance commitment. 
The direct path between transformational leadership and normative commitment 
failed to achieve significance.  Hypothesis H6c was therefore not supported. 
 89
? H7c: Laissez-faire or non-leadership on the part of a change leader will be 
negatively associated with continuance commitment. 
Avoidant behaviors direct path to continuance commitment was not significant; 
therefore, hypothesis H7c was not supported. 
? H11c: Faculty change involvement will be negatively associated with 
continuance commitment. 
The direct path between change involvement and continuance commitment failed 
to achieve significance.  Hypothesis H11c was therefore not supported. 
5.6.3. Hypotheses Accounting for Variability in Faculty Behavior and Leader?s 
Satisfaction 
Model 2 (Figure 10) was used to test hypotheses that relate commitment to 
behavior and to leader?s satisfaction.  Model 2 had a good fit to the data: Chi-square (122, 
N = 180) = 227.951, p < .000, CFI = .949, RMSEA = .070 (90% CI = .056, .084.).  The 
standardized parameter estimates for Model 2 are shown in Figure 10. 
 
 90
Affective
Commitment
Continuance
Commitment
Normative
Commitment
Leader
Satisfaction
Compliance
Discretionary
Behavior
- 
0
.2
6
*
0
.3
8
*
*
0
.
6
7
*
*
0
.
4
8
**
0
.3
5
*
0.75**
- 0.40**
0.04
0
.
3
1
-
0
.
0
5
-0.32
0
.1
3
-
0
.
0
3
0
.
1
9
*
 
Figure 10: Model 2 Accounting for Variance for Supportive Behavior and 
Leader?s Satisfaction. 
Statistically significant paths are in bold: ** p < 0.01, * p < 0.05. 
 
The hypotheses that were tested using Model 2 were as follows: 
? H1a: A faculty member?s affective commitment to organizational change 
is positively associated with compliance behavior related to the change. 
The path between affective commitment and compliance behavior was significant 
(Beta = .67, p <.001), therefore, hypothesis H1a was supported by the data. 
? H1b:  A faculty member?s affective commitment to organizational change 
is positively associated with discretionary behavior related to the change. 
Significance was also achieved in the direct path between affective commitment 
and discretionary behavior was significant (Beta = .48, p <.001).  Hypothesis H1b was 
therefore supported. 
 91
? H2a: A faculty member?s normative commitment to organizational change 
is positively associated with compliance behavior related to the change. 
The path between normative commitment and compliance was not significant 
(Beta = .13, p = .366).  Hypothesis H2a was therefore not supported by the data. 
? H2b: A faculty member?s normative commitment to organizational change 
is positively associated with discretionary behavior related to the change. 
Normative commitment had a significant direct path to discretionary behavior 
(Beta = .35, p < .05); therefore, hypothesis H2b was supported. 
? H3a: A faculty member?s continuance commitment to organizational 
change is positively associated with compliance behavior related to the 
change. 
Continuance commitment had a significant path to compliance behavior (beta = 
.19, p < .05).  Hypothesis H3a was therefore supported. 
? H3b: A faculty member?s continuance commitment to organizational 
change is negatively associated with discretionary behavior related to the 
change. 
The path between continuance commitment and discretionary behavior was not 
significant (Beta = -.03, p = .752).  Hypothesis H3b was not supported by the data. 
? H4: A faculty member?s commitment to organizational change is 
positively associated with a change leader?s satisfaction with what was 
accomplished from the change. 
None of the paths from the dimensions of commitment to organizational change 
to leader?s satisfaction reached significance.  Therefore, hypothesis H4 was not 
 92
supported.  The effects on leader?s satisfaction were found through the mediating effects 
of behaviors; compliance behavior had significant negative path to leaders satisfaction 
(Beta = -.26, p < .05), while discretionary behavior had positive significant path to 
leader?s satisfaction (Beta = .38, p < .01). However, there were no specific hypotheses 
stated earlier for these two direct paths. 
 93
6. DISCUSSION 
This chapter discusses the findings of the study and its limitations.  It concludes 
with a section that describes the practical applications for pharmacy schools, the 
implications for theory, and suggestions for future research. 
6.1. General Findings 
This study was conducted to answer four research questions and to test 22 
hypotheses on the relationships between leadership behaviors, change involvement, 
commitment to organizational change, behavioral support for change, and change leader 
satisfaction.  Table 21 summarizes the study?s findings by listing the independent 
variable, the dependent variable, the hypothesized relationship and whether the structural 
equation modeling analysis supported the hypothesis for each.
 94
Table 21:  Summary of Hypotheses Testing Findings 
Hypothesis Independent 
Variable 
Dependent 
Variable 
Hypothesized 
Relationship 
Finding 
H1a Affective 
commitment 
Compliance 
behavior 
Positive Supported 
H1b Affective 
commitment 
Discretionary 
behavior 
Positive Supported 
H2a Normative 
commitment 
Compliance 
behavior 
Positive Not supported 
H2b Normative 
commitment 
Discretionary 
behavior 
Positive Supported 
H3a Continuance 
commitment  
Compliance 
behavior 
Positive Supported 
H3b Continuance 
commitment 
Discretionary 
behavior 
Negative Not supported 
H4 Commitment to
organizational 
change 
Change leader?s 
satisfaction 
Positive Not supported 
H5a Transactional 
Leadership 
Affective 
commitment 
Negative Not supported 
H5b Transactional 
Leadership 
Normative 
commitment 
Negative Partially 
supported 
H5c Transactional 
Leadership 
Continuance 
commitment 
Positive Not supported 
H6a Transformational 
Leadership 
Affective 
commitment 
Positive Not supported 
H6b Transformational 
Leadership 
Normative 
commitment 
Positive Not supported 
H6c Transformational 
Leadership 
Continuance 
commitment 
Negative Not supported 
H7a Laissez-faire 
Leadership 
Affective 
commitment 
Negative Supported 
H7b Laissez-faire 
Leadership 
Normative 
commitment 
Negative Not supported 
H7c Laissez-faire 
Leadership 
Continuance 
commitment 
Negative Not supported 
H8 Transactional 
Leadership 
Change 
involvement 
Positive Not supported 
H9 Transformational 
Leadership 
Change 
involvement 
Positive Not supported 
 95
Hypothesis Independent 
Variable 
Dependent 
Variable 
Hypothesized 
Relationship 
Finding 
H10 Laissez-faire 
Leadership 
Change 
involvement 
No relationship Not supported 
H11a Change 
involvement 
Affective 
commitment 
Positive Supported 
H11b Change 
involvement 
Normative 
commitment 
Negative Not supported 
H11c Change 
involvement 
Continuance 
commitment 
Negative Not supported 
 
The following discusses the findings related to each of the research questions 
addressed by the study in context of the past research, along with the implications for 
future research. 
6.1.1. Research Question 1 
Many studies have found transformational leadership and transactional leadership 
(especially the contingent reward component) to be good predictors of performance, both 
at the organizational and at the individual levels (Lowe et al., 1996).  Numerous authors 
have argued for the utility of transformational leadership in driving change (e.g., Nadler 
& Tushman, 1990), even in pharmacy academic literature (Wells, 2003).  However, no 
studies examining the effect of these leadership dimensions on commitment to 
organizational change was found; therefore the first research question was posed:  How 
do behaviors of a change leader affect a faculty member?s commitment to organizational 
change? 
The direct paths between each of the leadership dimensions and the commitment 
components were non-significant except in two situations.  First, avoidant type behaviors 
related negatively to affective commitment.  Change leaders with avoidant behaviors, 
 96
those who were absent when needed or waited for problems to arise before taking action, 
were found to hinder faculty members? affective commitment to organizational change.  
The faculty members? belief in the value of the change decreased as they perceived the 
change leader behaving in an avoidant manner.   
The second significant direct path, which was also negative, was between active 
management by exception (MBE) to normative commitment.  Active MBE leaders, those 
who were perceived as searching for mistakes in subordinates in order to correct them, 
were found to hinder the development of normative commitment.  That is the faculty 
members in this sample felt less obligated to support a change in cases where the leader 
showed more of these behaviors. 
The direct path between transactional leadership contingent reward was not 
significant, although it was strongly related to change involvement (explaining about 
25% of the variance for change involvement), which in turn was positively related to both 
affective and normative commitments.  This means transactional contingent reward 
behaviors (e.g., rewarding subordinates for achieving performance targets, clearly 
informing them what needs to be done to be rewarded) predicted affective and normative 
commitments, though indirectly through involving faculty members in the change. 
No role of transformational leadership was found.  Even when alternative 
structural equation models were explored, whether by respecification of paths, by 
removing the mediating variable change involvement, or even by removing the highly 
correlated contingent reward variable from the model, paths from transformational 
leadership to the commitment components failed to achieve significance.  Therefore, it 
 97
seems clear that in this study transformational leadership does not relate to faculty 
commitment to change. 
The absence of a significant relationship between transformational leadership and 
commitment to change is an even more important finding in view of the present study?s 
use of data from a single source, which is expected to exaggerate the relationship 
between perceptions of the behaviors of a change leader and attitudes toward the change.  
In a meta analytic review of research on this model, Lowe et al. (1996) found that when 
subordinates rated both the leaders? behaviors and the outcomes, the correlations were 
higher than if they came from different sources.  They commented that this could be due 
to mono-method bias in the self-report measures. 
One of the reasons why this study?s finding about transformational leadership was 
not consistent with previous research may be that the earlier work did not treat 
transformational leadership as a process variable that relates subordinates? attitude toward 
a specific change, but rather treated it as a context variable affecting general work 
attitudes or outcomes.  According to Pettigrew?s (1987) model, discussed in the 
introduction, organizational change can be understood as an interaction of content, 
context, and process variables, in which leader?s behavior can be a context variable if not 
linked directly to the processes during a specific change.  Unlike previous work, this 
study treated transformational leadership behaviors as a process variable and asked 
participants to rate these behaviors in relation to a specific change.  Scholars of 
organizational change have noted that despite the considerable amount of empirical 
research on transformational leadership that has identified strong positive relationships to 
various individual and organizational outcomes, and despite the writings of theorists 
 98
about the effect of transformational leadership on change, there is lack of empirical 
evidence on whether these leaders? behaviors relate to subordinates? positive attitudes 
toward the change (Almaraz, 1994; Groves, 2005). 
Two previous studies have attempted to bridge this gap in the literature, but 
neither treated leadership behaviors as a process variable linked to a specific 
organizational change. The first reported a positive relationship between transformational 
leadership and commitment to organizational change, although commitment was 
conceptualized differently, as a composite of personal goals, capacity beliefs and context 
beliefs (Yu, Leithwood, & Jantzi, 2002).  Furthermore, this study was conducted in a 
different culture, Hong Kong, with a different population, teachers in K-12 schools.  The 
other study was published recently by Groves (2005) and found a similar positive 
relationship between ratings of leaders as charismatic and followers? openness and 
acceptance of organizational change.  A weakness in Groves?s work, however, is that he 
relied on the leaders? inclusion of followers in the study, which might have introduced 
leaders? biases by including only those who were likely to evaluate the change and the 
leaders positively.   
Most importantly, these two earlier studies did not address the need for relating 
transformational leader?s behaviors during the change to attitude toward that specific 
change, but rather examined the respondents? general attitude towards new initiatives, 
without specifying what the exact initiatives were (Yu, Leithwood, & Jantzi, 2002), or to 
unidentified changes occurring during an elapsed year (Grove, 2005).  In contrast, the 
present study explicitly made this connection, and this could be the reason why the 
results are not in line with previous work.  Any relationship between transformational 
 99
leadership behaviors and commitment to organizational change may have been attenuated 
in this study by treating leadership behaviors as a process variable in the implementation 
of a specific change. 
A second reason why no significant relationship between transformational 
leadership and commitment was found in this study is that the transformational model of 
leadership assumes that people everywhere are attracted to the same types of leader?s 
behaviors, and that these should therefore be universally effective (Den Hartog, House, 
Hanges, Ruiz-Quintanilla, & Dorfman, 1999; Beyer, 1999). These researchers noted that 
different situations may make different leaders? behaviors ?more or less attractive, 
persuasive, and effective because potential followers may be more or less receptive to 
that type of leader? (Beyer, 1999, p. 310).  Bess and Goldman (2001) have noted that in 
higher education, professors are usually more skeptical and value their autonomy, which 
causes them to be less ?open? to leaders with charisma.  They noted further that:  
Because transformational leadership depends on peer support for significant 
organizational change, the diversity of faculty interests and orientations in the 
typical department usually presents problems for leaders. Despite putative 
common academic subject matter and disciplinary backgrounds, faculty diverge in 
both intellectual preferences and personal goals. Since as Bass (1985) notes, the 
?arousal? process in transformational leadership requires the use of appealing 
?symbols, images, and vision of a better state of affairs? (p. 66), it would take an 
extraordinarily broadly educated and informed chairperson to communicate 
effectively to each faculty member. (Bess & Goldman, 2001, p. 434) 
 100
Birnbaum (1992) conducted a five-year research study on the leadership of 
university presidents and provided further insights that might explain the non-significant 
finding in this study.  He found transformational leadership to be an anomaly in higher 
education that led only to disruption instead of positive outcomes. He posited that the 
goals and values of academic institutions are produced by their history, culture, and the 
socialization process of their members, and are therefore not likely to respond to a strong 
transformational leader.  He reported that the good leaders in higher education were the 
transactional type that acknowledged the values that were already adhered to by faculty, 
and were able through transactions to move the institution towards achieving them. 
 In view of these observations, subordinate receptivity to leaders? transformational 
behaviors can vary across contexts, and will not necessarily be universally endorsed, 
especially in higher education.  Thus, the finding of non significance in relation to 
transformational leadership in the present study is not necessarily inconsistent with 
theory; pharmacy educators may simply react less favorably to transformational 
leadership behaviors.  In terms of transactional leadership contingent reward, although it 
has non significant paths to affective and to normative commitment when tested 
simultaneously with other dimensions of leadership, it was strongly associated with 
change involvement, which in turn predicted the commitment components.  This means it 
related positively to affective commitment, though indirectly through the mediating effect 
of change involvement.  Therefore, in light of Birnbaum?s (1992) assertion that good 
leaders in higher education are of the transactional type, rather than the transformational 
type, the results of the present study provide additional empirical support. 
 101
Another reason why there was no support for transformational leadership effect 
could be simply due to the fact that all the changes had been almost completed at the time 
of data collection for this study and, therefore, within this late phase of implementation 
the transformational leadership behaviors were not as important as they would had been 
in an earlier stage of the change. 
Finally, these results can be considered to be consistent with other scholars of 
organizational change who have minimized the significance of the role of leadership and 
argued that although it is important, it is only one of several factors that feature in the 
process of organizational change (e.g., Pettigrew, 1987).  Transformational leadership did 
not relate to commitment in this study, although transactional leadership related 
indirectly, and other less emphasized leaders? behaviors in the literature, namely active 
MBE and avoidant behaviors, related directly. 
6.1.2. Research Question 2 
Employee participation in decision making improves employee attitudes and 
performance, as suggested by several meta-analyses (Cotton, Vollrath, Froggatt, 
Lengnick-Hall, & Jennings, 1988; Sagie, 1994).  Scholars of organizational change argue 
for the involvement of subordinates as a main process ingredient to facilitate employee 
commitment to the change (Armenakis, Harris & Field, 2001). Accordingly, this study 
posed the second research question: How does involvement in change affect a faculty 
member?s commitment to organizational change?
This study found change involvement to be strongly associated with two of the 
components of commitment to organizational change, affective and normative 
commitment, but not with continuance commitment.  This finding is consistent with 
 102
earlier studies that found participation in decision making, democratic decision making, 
or involvement contribute to employees? positive attitudes toward change.  For example, 
Coyle-Shapiro (1999) found employee involvement to be positively related to their 
assessment of the benefits of TQM, a concept that relates to affective commitment.  Sagie 
and associates found positive relationships between participation in change decisions and 
acceptance of change in both a simulated experiment (Sagie, Ellzur, & Koslowsky, 1990) 
and a field study (Sagie & Koslowsky, 1996). 
Several mechanisms have been proposed to account for the relationship between 
individual involvement and positive attitudes.  For example, participation in decision 
making has been reported to be associated with reduced uncertainty, increased perceived 
influence and decreased ambiguity, with the latter also being found to reduce emotional 
strain (Jackson, 1983).  Sagie and Koslowsky (1996) found an individual?s sense of 
control acted as mediator in the relationship between participation in decision making and 
change acceptance.  
Other mechanisms that may explain the processes through which change 
involvement generates commitment to organizational change were offered by Armenakis, 
Harris and Field?s (2001) model of institutionalizing change.  This model posits that 
participation and communication (among other strategies) are effective in leading to 
commitment when they result in employees? comprehension of the five components of 
the change message, which consists of: (1) discrepancy, ?is change really necessary?,? 
(2) appropriateness, ?is the proposed change an appropriate solution to the discrepancy,? 
(3) self-efficacy, ?can we successfully implement the change?,? (4) principal support, 
?are the leaders committed to the successful implementation?,? and (5) personal benefit, 
 103
?what?s in it for me??  Change involvement could facilitate self-discovery and learning 
about the problem facing the organization, hence leading to an understanding of the 
discrepancy, the first component of the change message they proposed.  Involvement can 
also facilitate learning about what improvements are expected if this change is 
implemented, and therefore help fulfill the second component of the change message, 
appropriateness.  The third component, self-efficacy, can be enhanced by involvement 
through generating a feeling that one has a say in the change and also through being 
exposed to the details needed to develop competencies to carry out the change.  
Participation also allows an opportunity for observing the leaders and how committed 
they are to change implementation, i.e., principal support.  The likelihood of including 
incentives that are motivating can increase with involvement, and thus fulfils the fifth 
component, personal benefit (Armenakis, Harris, & Field, 2001). 
6.1.3. Research Question 3 
Research by Herscovitch and Meyer (2002) found compliance behavior to be 
correlated positively with all three dimensions of commitment to organizational change, 
namely affective, normative, and continuance,  but cooperation and championing 
(discretionary) behavior correlated positively only with the affective and normative 
dimensions.  To verify whether these relationships hold in the pharmacy academic 
sample studied here, the third research question was posed: How does faculty members? 
commitment to change affect their support for change initiatives in pharmacy schools? 
The SEM analysis depicted in Model 2 (Figure 11, Ch. 5), shows, as hypothesized 
and in line with Herscovitch and Meyer?s findings, discretionary behavior was predicted 
by both affective and normative commitment, but not by continuance commitment.  That 
 104
is faculty members? belief in the value of the change (affective commitment) and their 
sense of obligation to support the change (normative commitment) was positively 
associated with their expending the effort to further the change, being ready to make 
some sacrifices, and demonstrating enthusiasm for a change by going above and beyond 
what is required (examples of discretionary behavior).  Continuance commitment to the 
change, a willingness to support the change in order to avoid costs associated with failure 
to do so, was not associated with discretionary behavior. 
Also consistent with previous work, compliance behavior was predicted by 
affective and continuance commitment.  However, in contrast to Herscovitch and Meyer 
(2002) findings, compliance was not predicted by normative commitment to the change.  
A possible reason for the non significant path between normative commitment and 
compliance is that the method used for measuring compliance and discretionary behavior 
might have been invalid.  The 101-point scale that measured behavioral support was split 
into two separate scales, compliance and discretionary, by assigning scores from 0 to 60 
into the new compliance variable, and assigning scores from 61 to 100 into the 
discretionary variable.  Cases with scores above 60 in the original behavioral scale 
received a 60 on the compliance scale (the maximum on this new scale), while cases with 
scores below 61, received a zero in the discretionary behavior scale (the minimum on this 
new scale).  This method of splitting one variable into two was not based on established 
methods and so the validly could not be verified; therefore, some doubt arose concerning 
the findings associated with Model 2. 
For exploratory purposes, Model 2 was modified by replacing the two proposed 
scales (compliance and discretionary behaviors) with the original intact 101-point 
 105
behavioral support scale.  Although this will not allow the related hypotheses to be tested, 
it will allow for the exploration of the simultaneous effect of the commitment dimensions 
on behavior more validly.  Figure 11 illustrates the variables and the standardized 
parameter estimates for the paths between them.  The modification improved the fit 
indexes over the original Model (see Appendix Q for details). 
Affective
Commitment
Continuance
Commitment
Normative
Commitment
Leader
Satisfaction
Behavioral
Support
0
.1
4
0
.
4
8
*
*
0
.
4
1
*
*
0.75**
- 0.40**
0.04
0
.
2
6
-
0
.
1
0
-0.2
8
-
0
.
0
3
 
Figure 11: Exploratory Modification for Model 2 Accounting for Variance 
for Behavioral Support and Leader?s Satisfaction. 
 Statistically significant paths are in bold: ** p < 0.01 
 
The exploratory model showed both affective and normative commitments to be 
strongly associated with behavioral support, but not continuance commitment.  As 
affective commitment to change (intention to support the change based on belief in the 
inherit value of the change) or normative commitment (intention to support based on a 
sense of obligation to reciprocate) increase, the behavioral support for the change 
 106
increases, but as continuance commitment (intention to support the change to avoid costs) 
increases, the behavioral support remains unchanged.  Although the modified model no 
longer discriminates between discretionary and compliance behavior, it is still consistent 
with previous work in that it emphasizes the importance of affective and normative 
commitment in predicting behavioral support in general, and question the value of 
continuance commitment. 
6.1.4. Research Question 4 
How does faculty members? commitment and their behavioral support affect the 
satisfaction of a change leader with change accomplished? 
None of the commitment components had statistically significant paths to change 
leader satisfaction, in either the original or the modified versions of Model 2.  The 
possible reasons for not finding such a relationship include a weakness in measurement, 
or an attempt to connect variables with weak theoretical bases. 
This weakness in measurement relates to a problem with the narrowness of the 
range of responses on the two items that made up the leader satisfaction score.  
Examination of the responses on these two items revealed means of 4.11 and 4.06 with 
standard deviations of about 0.8 for both.  These high mean values with low variances 
may indicate problems with the validity of these two items.  These two items were 
constructed specifically for the present study and their validity has not been sufficiently 
established. 
The other reason for not finding a statistically significant relationship between the 
commitment components and leader?s satisfaction is that this relationship may not be 
based on a strong theoretical foundation.  Commitment of faculty may not be sufficient to 
 107
make a change leader satisfied if he or she were faced with setbacks due to other factors, 
such as insufficient resources, unavailability of skills, or inadequate planning.  Another 
issue relates to the expectations of a change leader, and how they might differ from 
faculty members? expectations.  Through an informal discussion, a change leader told the 
principal investigator that a ?good transformational leader? is never satisfied, regardless 
of the outcome. 
To summarize, the results of this study suggest that affective and normative 
commitments to organizational change may be best predicted by the degree of employee 
involvement in the change, rather than by the transformational behaviors of the change 
leader. Transactional contingent reward behaviors strongly predicted change 
involvement, and indirectly predicted affective and normative commitments.  In addition, 
affective commitment was predicted by avoidant behaviors of the change leader, and 
normative commitment was predicted by the leader?s active management by exception 
behaviors.  Transformational leadership did not predict any commitment component. 
Continuance commitment was not predicted by any of the independent variables 
examined.  In terms of the outcomes of commitment, compliance and discretionary 
behavior were both strongly predicted by the level of the affective commitment.  
Normative commitment predicted discretionary behavior, while continuance commitment 
predicted compliance behavior. 
6.2. Limitations 
?The ideal of science is the controlled experiment? (Kerlinger & Lee, 2000, 
p.467).  An important limitation of this study is its nonexperimental cross-sectional 
design.  The principal investigator did not manipulate and control any of the independent 
 108
variables, nor did he assign participants to treatment and control groups.  Therefore, this 
design can not generate confidence that the relationships studied here are descriptive of 
the independent variables affecting dependent variables.  For example, one could ask: is 
the demonstrated relationship really between change involvement and affective 
commitment?  There are other variables that correlate with change involvement (e.g., 
being a member of the committee that implemented a change) that my produce the same 
or a stronger effect on change involvement.  Although the study attempted to hypothesize 
causality on the basis of theory, and utilized a suitable analysis method, namely structural 
equation modeling, to infer causality, because of the reduced control in this 
nonexperimental design, the probability that the independent variable is related to the 
dependent variable is less than in an experimental design (Kerlinger & Lee, 2000). 
Another related limitation to the above is the potential of response bias, a 
selection problem that threatens internal validity (Campbell and Stanley, 1963).  This 
threat is likely to occur whenever the researcher does not implement random selection 
and assignment of participants.  In this study, the self-selection of change leaders and 
faculty members, as epitomized by the relatively low response rate (11% for the first 
phase, 44% for the second, and 17% for the third), raises the possibility that the 
participants differed from nonparticipants in certain important characteristics.  If that is 
the case, then this may account for the difference in the dependent variables and present 
rival hypotheses.  
Several statistical tests were conducted in an attempt to detect whether the sample 
was in fact different from the population as a whole.  Some statistically significant 
differences were found between the participants and the general population of pharmacy 
 109
faculty on some of demographic variables collected.  However, when these demographics 
were correlated with the measured variables of the study, few significant relationships 
were revealed.  Being in an administrative position tended to make a faculty member rate 
the change leader more favorably, while being a faculty member in a tenure track 
position tended to rate the leader less favorably, in some aspects, and to have a lower 
affective commitment to the change.  Continuance commitment was associated more 
often with faculty from the biological sciences discipline than those from the social and 
administrative discipline.  Based on these few instances where statistically significant 
correlations between demographics and study variables were found, it is clearly possible 
that a response bias has occurred, thus presenting a serious threat to the internal validity 
of the study. 
Besides its effect on internal validity, the selection problem or response bias 
presents difficulties for the generalizability of the finding to the population of interest.  
Kerlinger and Lee (2000) refer to this problem as a threat to the external validity and 
discusses three concepts in relation to it: sample generalizability, ecological 
representativeness, and variable representativeness.  Sample generalizability in a study 
asks the question to what population the finding of this study can be generalized?  One of 
the intentions of this dissertation was to provide practical recommendations on change 
management for pharmacy schools in the US, but in view of the low response rate and the 
evidence of response bias, these recommendations should be applied cautiously as the 
finding might not be applicable to the whole population of schools, or faculty members 
within schools. 
 110
Ecological representativeness refers to the social setting in which the research 
study is conducted.  For example, the geographical location of the participants may limit 
the external validity to only this location.  In this study, the 24 schools included in the 
final phase represented every region of the continental United States; hence there is little 
concern for that aspect. However, there are other aspects of ecology, namely the function 
of the instrument and the process of survey administration, that it was not possible to 
control for.  What results would have been found if the participants had filled out a paper 
form of the survey instead of Internet format? What if they had received the invitation e-
mails from a person with a different gender, race, or ethnicity?   
Variable representativeness refers to questioning the assumption that variables in 
the study are constant.  For example, the intensity of affective commitment to a relatively 
minor organizational change that is tactical in nature may not be the same as the affective 
commitment to a strategic change that suggests a whole new direction for the school.  
When we talk of affective commitment to organizational change, what kind of 
organizational change do we mean?  Most changes included in the study involve changes 
in the production processes (changes in curriculum, methods of teaching, etc.), but what 
if a future organizational change were to involve a merger of two departments, 
institutional downsizing by closing certain departments, changes in the administrative 
structure of  the school, and so forth?  Would the findings of the study still be 
generalizable?  While the study?s findings might be used to provide some guidance for 
those conducting such change events, its external validity cannot be extended to cover 
such changes. 
 111
Another limitation of the study is the use of a single source for measuring the 
dependent and independent variables, which may result in what Crampton and Wagner 
(1994) called percept-percept inflation of the relationship.  With the exception of leaders? 
satisfaction, which was based on change leader response, all other measures were based 
on self-reports from faculty members.  However, the measurement model specification 
using confirmatory factor analysis resulted in measures that were clearly distinct from 
one another.  Also, the absence of statistically significant relationships between 
transformational leadership and the components of commitment or change involvement 
should minimize the concerns over threats from single source bias in this study. 
One of the limitations also is the decision to use change leader?s satisfaction as an 
outcome variable.  This may have introduced a bias toward evaluating the change more 
positively by the leader since the change leader is interested in the success of the change. 
An additional limitation to the study was due to the decision to include only a 
dean or associate/assistant dean as the leader of the change, and therefore excluding the 
instances were a leader was a department head or a faculty member with no 
administrative position. This decision was made because the theoretical framework for 
this study contains behaviors of a change leader that assume hierarchical situation 
between a leader and a follower.  A change leader at an equal organizational level with a 
follower, or from a different department where the follower is not accountable to, would 
have made some of the leaders behaviors not applicable.  Since many responses in the 
first exploratory phase of the study provided names of change leaders with no 
administrative positions, as would be expected in an academic setting, the decision not to 
include them posed a limitation for this study. 
 112
6.3. Implications 
6.3.1. Practical Implications 
The findings of this dissertation have practical implications for pharmacy schools 
concerned with change and developing a commitment to change.  The study had several 
statistically significant relationships with practical applications. 
Pharmacy schools that are interested in implementing change must be concerned 
with two types of commitment to organizational change.  The first of these is affective 
commitment, which is the intention to support a change based on a belief in its benefits.  
The second is normative commitment, the intention to support a change based on a sense 
of obligation to support it.  Affective and normative commitment to organizational 
change were both found to predict faculty members? discretionary behaviors toward the 
change.  These behaviors are exemplified by expending effort to further the change, 
going along with the spirit of the change, and being ready to make some sacrifices.  They 
also include championing, which consists of demonstrating enthusiasm for a change by 
going above and beyond what is formally required and promoting the change to others.  
Affective and normative commitment, along with their combined effect on discretionary 
behavior is expected to help in the implementation of a change. 
To foster these two types of commitment, pharmacy schools need to involve 
faculty members in the change.  Based on the results of this study, perception of the level 
of involvement in the change was found to be the best predictor of faculty members? 
affective and normative commitment.  Specifically, change involvement includes: (1) 
ensuring participation in the change decision, (2) increasing the intensity of 
 113
communication during the change, and (3) allowing ample opportunities to freely express 
opinions and doubts about the change. 
This study found transformational leadership to not relate to commitment or to the 
degree of subordinate involvement, a finding contrary to that of other research in 
different work settings or to the recommendations from the business press that claim 
transformational leadership to be universally effective.  The change leaders who were 
most closely associated with faculty perception of their involvement and their 
commitment were those who behaved in a transactional manner.  These transactional type 
leaders acknowledged the values that were already adhered to by faculty and were thus 
able to secure faculty commitment by involving them through clarifying what needed to 
be done to be rewarded, and making sure the faculty received appropriate rewards for 
their support. 
Also, in order to increase the probability of commitment in pharmacy faculty, 
change leaders should recognize and avoid two groups of counterproductive behaviors, 
namely avoidant type and active management by exception (MBE).  Change leaders who 
were perceived as closely monitoring the faculty in order to identify problems or were 
keeping track of mistakes (active MBE) tended to be related to lower levels of normative 
commitment.  The faculty members felt less obligated to support a change initiated by 
this type of change leader.  Avoidant behaviors are those that are characterized by the 
absence of leadership, such as avoiding making decisions, failing to intervene until 
problems become serious, and delaying responses for urgent questions.  These behaviors 
are generally detrimental to the development of affective commitment toward the 
proposed change. 
 114
These findings can be applied in the academic pharmacy setting in several ways.  
First, for a school that is contemplating the implementation of a change, it is 
recommended that the change leader should be prepared to expend time and effort in 
making sure that every faculty member is adequately involved with the change.  This 
should extend beyond the typical committee membership that is commonly utilized in the 
academic setting.  In this regard, Aremankis, Harris, and Mossholder (1993) recommend 
involving employees using oral communication, such as speeches and informal 
discussions, and written communication, such as newsletters and memos.  They also 
recommend several participation strategies, including formalized strategic planning 
activities, which can potentially involve all the faculty members, rather than a limited 
number of committee members.  This can be accomplished by circulating a draft of the 
change initiative to all faculty members requesting input, followed by revision of the 
draft and re-circulation. Aremankis, Harris, and Mossholder (1993) suggest that 
participation can be accomplished by designing experiential learning exercises and 
vicarious learning.  The later can be achieved by arranging for a representative group of 
faculty members to visit another school that already has the proposed change in place, 
allowing them to observe others applying the new techniques and hear others talk about 
their successes.  The last method of participation they recommend is called enactive 
mastery, which constitutes taking small incremental steps rather than full implementation 
in a single step. 
Another way the findings of this study can be useful in academic pharmacy 
setting is in the selection of the leader who will be in charge of the change.  A dean or 
associate/assistant dean with a track record of contingent reward behaviors would be 
 115
most suited to leading a change.  A history of behaviors such as rewarding subordinates 
for achieving performance targets, clearly informing them what needs to be done to be 
rewarded, and providing exchange opportunities are indicative of contingent reward 
behaviors.  Individuals who are less suitable to lead a change are those with behaviors 
characterized by following subordinates? mistakes and failures (active MBE) or by the 
absence of action when problems arise (avoidant behaviors).  These behaviors were 
found to be detrimental to the involvement of followers and to be related negatively to 
commitment to change. 
These aspects of leaders? behavior could also be incorporated in the training of 
individuals for the task of leading faculty through a change.  Schools of pharmacy may 
want to consider a new focus on training deans and other faculty members in 
administrative positions to exhibit contingent reward behaviors and to minimize 
corrective and avoidant behaviors in order to successfully motivate faculty members to 
achieve a proposed change.  Similarly, the AACP could benefit by incorporating these 
aspects in their leadership development programs. 
6.3.2. Implications for Theory and Research 
The findings of this study present a challenge to the long-standing theoretical 
assumption that transformational leadership behaviors result in positive attitudes toward 
change.  The speculation made here is that once transformational behavior is treated as a 
process variable, which is linked directly to processes during the change and the effect of 
which is related to a specific change, this relationship became non-significant.  It would 
be valuable to know whether these results can be replicated in other types of 
organizations or with cultures different from that in the pharmacy academic. 
 116
Consistent with previous research, this study has demonstrated that involvement 
in the change is associated with higher levels of affective and normative commitment to 
organizational change.  However, the new contributions made by this study comes from 
the finding that the likelihood of involvement and subordinates? affective and normative 
commitment are enhanced by transactional contingent reward behaviors, but dimensioned 
by active MBE and avoidant behaviors.  Future research could incorporate the 
relationships found to be significant in this study into a more general theory of 
organizational change. 
 
 
 
 
 
 
 
 
 
 
 
. 
 117
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 122
8. APPENDICES 
 
 123
Appendix A:  Invitation E-mail to Participate in the Phase 1 of the Study 
 124
From:  AU Pharmacy Care Systems 
To: (e-mail address of recipient) 
Date:  12/8/2004 9:50:25 AM 
Subject:  A Study of Commitment to Change in AACP Member Schools 
 
Commitment to Change in Pharmacy Schools: Does Change Leadership Matter? 
 
As a faculty member in a U.S. school of pharmacy, you are an important contact for a study 
examining faculty commitment to change in pharmacy schools.  You are invited to participate in 
this research study designed to elicit your opinion of change in your pharmacy school and factors 
affecting commitment to change.  The objective of the study is to examine factors affecting 
commitment to change which may help pharmacy schools make better decisions on managing 
future change.  This study is being conducted by Mohammad Waheedi, a doctoral student, under 
the supervision of Dr. Bruce A. Berger, professor and head of the Department of Pharmacy 
Systems, Auburn University.  You received this letter because you are part of the registry of the 
American Association of Colleges of Pharmacy. 
 
This research will have two phases. 
1) An exploratory phase that will identify specific changes that occurred in your school and 
identify the change leader; and 
2) An explanatory phase that connects change factors occurring during the change and the 
strengths of commitment faculty have, and connects the types of commitment to outcomes of 
successful change. 
 
You are invited to participate in the first exploratory phase.  You will receive a follow-up in about 
two months regarding the second phase of the study.  Participating in this phase does not oblige 
you to participate in the second phase, and vice versa. 
 
If you choose to participate, please click on the following hyperlink that should take you to the 
survey Web site.  This survey should take less than 10 minutes to complete. 
 
http://www.pharmacy.auburn.edu/survey/687605  
 
(If your e-mail program doesn't recognize Web addresses: copy the above address and paste it 
into your Web browser, then click Go or press Enter on your keyboard) 
 
Your responses to the survey will be completely anonymous.  No names or IP addresses will be 
collected by the database.  In fact, no one will be able to tell whether you participated.  This study 
is being conducted by a doctoral student in partial fulfillment for a doctoral degree requirement.  
Information collected through your participation will be published in a professional journal, and/or 
presented at a professional meeting.  If so, no person?s or school?s name will be included. 
 
There are no foreseeable risks with your participation.  By participating in this study today, you 
will benefit later by the study ?s results that should lead to the improvement of your approach to 
change implementation, and thus help you achieve high levels of commitment among your 
colleagues.  Your decision whether or not to participate will not jeopardize your future relations 
with Auburn University or the Department of Pharmacy Care Systems. 
 
If you have any questions we invite you to call or send us an e-mail.  Call me, Mohammad 
Waheedi, the director of this project, at 334-844-8310 (waheemo@auburn.edu).  Or you may call 
the supervisor of my dissertation Dr. Bruce A. Berger at 334-844-8302 (bergeba@auburn.edu). 
 
For more information regarding your rights as a research participant you may contact the Office of 
Human Subjects Research by phone or e-mail.  The people to contact there are Executive 
Director E.N. ?Chip? Burson (334) 844-5966 (bursoen@auburn.edu) or IRB Chair Dr. Peter 
Grandjean at (334) 844-1462 (grandpw@auburn.edu) . 
 125
  
HAVING READ THE INFORMATION PROVIDED, YOU MUST DECIDE WHETHER TO 
PARTICIPATE IN THIS RESEARCH PROJECT.  IF YOU DECIDE TO PARTICIPATE, THE 
DATA YOU PROVIDE WILL SERVE AS YOUR AGREEMENT TO DO SO.   THIS LETTER IS 
YOURS TO KEEP. 
 
Mohammad Waheedi, R.Ph., M.S. 
Doctoral student 
Auburn University 
334-844-8310 Work 
334-844-8307 Fax 
334-663-5123 Cell 
waheemo@auburn.edu  
 
Bruce A. Berger, Ph.D. 
Head and Professor of 
Pharmacy Care Systems 
128 Miller Hall 
Auburn University, AL 36849-5506 
334-844-8302 Office 
334-844-8307 Fax 
334-444-3160 Cell 
bergeba@auburn.edu  
 126
Appendix B:  The Phase 1 Survey 
 127
Phase 1 Survey 
 
The purpose of this exploratory phase is to identify changes that occurred in each 
pharmacy school and identify the change leader connected with the change.   The focus 
of this study is ?substantive change.?  ACPE defines substantive change as ?any change 
in the established mission or goals of the institution; the addition or deletion of courses, 
pathways or programs that represent a significant departure in either content or method of 
delivery, from those that were offered during the program?s previous accreditation cycle 
(e.g., a non-traditional doctor of pharmacy program, development of a joint delivery of 
program agreement, etc.); a substantial change in enrollment; a substantial change in the 
number of clock or credit hours required for successful completion of the program; a 
significant change in the length of the program; the establishment of an additional 
geographic location at which the program is offered; and any other changes that the Dean 
feels require notification of ACPE.?  
 
A list of potential changes is included below. Please click on the appropriate response for 
each change. In addition, there is an open box below where you may add any change that 
fits the definition above AND you believe has affected the way you do your work OR is 
of a concern to you personally. For each change you provide, please include the name of 
the primary change leader. 
 
Did one of the following changes take place within your school during the 
past THREE YEARS? 
 
     % 
Change 
Completed 
This 
change 
affected 
the way I 
do my job 
This 
change 
is of 
concern 
to me 
This 
change 
doesn?t 
matter 
to me 
Name 
a main  
leader 
for this 
change 
1. Conversion from 
five year B.S. to 
six year Pharm. D. 
Yes No I don?t 
know 
(drop down 
menu) 
(Scale) (Scale) (Scale) (Text) 
2. Implementation of 
problem-based 
learning in place of 
traditional lectures. 
Yes No I don?t 
know 
(drop down 
menu) 
(Scale) (Scale) (Scale) (Text) 
3. Major change(s) in 
curriculum 
Yes No I don?t 
know 
(drop down 
menu) 
(Scale) (Scale) (Scale) (Text) 
4. Change(s) in 
program length 
Yes No I don?t 
know 
(drop down 
menu) 
(Scale) (Scale) (Scale) (Text) 
5. Establishing a 
distance learning 
site for a traditional 
Pharm. D. program 
 
Yes No I don?t 
know 
(drop down 
menu) 
(Scale) (Scale) (Scale) (Text) 
6. Change in the 
established mission 
or goals of the 
institution 
Yes No I don?t 
know 
(drop down 
menu) 
(Scale) (Scale) (Scale) (Text) 
7. Changes in Yes No I don?t (drop down (Scale) (Scale) (Scale) (Text) 
 128
     % 
Change 
Completed 
This 
change 
affected 
the way I 
do my job 
This 
change 
is of 
concern 
to me 
This 
change 
doesn?t 
matter 
to me 
Name 
a main  
leader 
for this 
change 
admission 
standards 
know menu) 
8. Implementation of 
dress code 
(professional attire) 
Yes No I don?t 
know 
(drop down 
menu) 
(Scale) (Scale) (Scale) (Text) 
9. Establishing a post-
baccalaureate 
Pharm. D. program 
Yes No I don?t 
know 
(drop down 
menu) 
(Scale) (Scale) (Scale) (Text) 
 
 
Are there any other significant changes that have occurred in the last 3 years at your 
school which were of concern to you OR affected the way you do your work? If so: 
 
List one change which was of concern to you OR affected the way you do your work 
 
 
Who was the main leader for this change? 
 
 
 
List another change which was of concern to you OR affected the way you do your work 
 
 
 
Who was the main leader for this change? 
 
 
 129
Appendix C:  Screenshots of the Phase 1 Internet Survey
 130
 131
 
 132
 133
Appendix D:  Follow-up E-mail to Non-respondent Schools
 134
From:  Bruce Berger 
To: albert.wertheimer@temple.edu;  b-bryant@onu.edu;  
bennie.french@swosu.edu;  david.forbes@umontana.edu;  dphammer@u.washington.edu;  
druginfo@uwyo.edu;  dsarnoff@pacific.edu;  gbrazeau@buffalo.edu;  hodgefj@musc.edu;  
jlcolaiz@rci.rutgers.edu;  mary.gurney@sdstate.edu;  mdeyoung@usn.edu;  
michelle.easton@hampton.edu;  raymond.jang@uc.edu;  wmccormick@uh.edu 
Date:  12/15/2004 3:36:26 PM 
Subject:  Change Survey 
 
About one week ago one of my doctoral students (Mohammad Waheedi) sent an e-mail to AACP 
faculty at your School of Pharmacy.  The purpose of the e-mail was to request their participation 
in an important survey that examines major changes in U.S. schools of pharmacy.  The survey 
instrument takes less than 10 minutes to complete.  No one from you school has responded.  We 
have reason to believe that the e-mail message was not received due to possible spam 
blockages, etc.   
 
We would greatly appreciate it if you could let me know if the e-mail was received or not.  If it was 
not received could you please supply the name and phone number or e-mail address of the IT 
person at your school that might help us get the e-mail through?  This would be most 
appreciated. 
 
Thanks and Happy Holidays! 
 
Bruce 
 
Bruce A. Berger, PhD 
Head and Professor of 
Pharmacy Care Systems 
128 Miller Hall 
Auburn University, AL 36849-5506 
334-844-8302 Office 
334-844-8307 Fax 
334-444-3160 Cell 
   
 135
Appendix E:  Reminder E-mail for Phase 1
 136
From:  AU Pharmacy Care Systems 
To: (e-mail address of recipient) 
Date:  12/16/2004 12:10:05 PM 
Subject:  Reminder: First Phase of a Study of Commitment to Change in AACP Member 
Schools 
 
Dear faculty member, 
  
Recently you were sent an invitation to participate in an anonymous questionnaire asking your 
opinion about change in pharmacy schools.  For those who have responded, thank you very 
much.  Your response contributes to results that accurately represent the opinions of faculty 
members of the U.S. schools of pharmacy and would be greatly appreciated. 
  
As a reminder, no names or IP addresses will be collected by the database, so the responses will 
be completely anonymous.  I would be happy to answer any questions you may have. 
  
The survey will take less than 10 minutes to complete.  By clicking on the Web address below the 
survey will appear on your computer screen.  Once you have completed your responses to the 
questions, please click on the SUBMIT button to submit your responses. 
 
http://www.pharmacy.auburn.edu/survey/755109  
 
(If your e-mail program doesn't recognize Web addresses: copy the above address and paste it 
into your Web browser, then click Go or press Enter on your keyboard) 
 
Thanking you in anticipation. 
  
Sincerely, 
 
Mohammad Waheedi, R.Ph., M.S. 
Doctoral student 
Auburn University 
334-844-8310 Work 
334-844-8307 Fax 
334-663-5123 Cell 
waheemo@auburn.edu  
 
Bruce A. Berger, Ph.D. 
Head and Professor of 
Pharmacy Care Systems 
128 Miller Hall 
Auburn University, AL 36849-5506 
334-844-8302 Office 
334-844-8307 Fax 
334-444-3160 Cell 
bergeba@auburn.edu   
 137
Appendix F:  Sample Invitation E-mail to Participate in Phase 2
 138
From:  Mohammad Waheedi 
To: (e-mail address of recipient) 
Date:  3/10/2005 7:38:56 AM 
Subject:  Change and Leadership Study: Establishing a Distance Learning Site 
 
Dear (name of recipient), 
 
We initiated a study to identify changes in pharmacy schools and to identify change leaders so 
we can examine faculty members? commitment to change and factors affecting their commitment.  
Phase I of this research has been completed and within your school you have been identified as 
a leader of establishing a distance learning site for a traditional Pharm. D. program. 
 
Your assistance in this second phase would be greatly appreciated.  For the faculty members at 
your school to participate in the second phase, we need your approval.  A questionnaire that will 
be sent to faculty members is attached to this e-mail for you to review and see if you approve the 
collection of this data from your colleagues.  You are invited to participate in the leader 
satisfaction part of the second phase which should take about five minutes. 
 
Please take a look at the attached documents; first, open the document with the name 
facutly_survey and read it to get a feel for the types of questions your colleagues will be 
receiving.  Then please read the document with the name Informed_Consent and decide whether 
to participate and allow other faculty members at your school to participate OR to not participate 
but allow other faculty members to participate. 
 
All information will be treated in the strictest confidence and no names will be used.  Your school 
will be given a code number and all responses will be identified only by this code number.  We 
will publish only group data, from which no schools or individuals could be identified. 
 
Thanking you in anticipation. 
  
Mohammad Waheedi, R.Ph., M.S. 
Doctoral student 
Auburn University 
334-844-8310 Work 
334-844-8307 Fax 
334-663-5123 Cell 
waheemo@auburn.edu  
 
Bruce A. Berger, Ph.D. 
Head and Professor of 
Pharmacy Care Systems 
128 Miller Hall 
Auburn University, AL 36849-5506 
334-844-8302 Office 
334-844-8307 Fax 
334-444-3160 Cell 
bergeba@auburn.edu  
   
 139
Appendix G:  Sample Informed Consent Letter Attached to E-mail Invitations in 
Phase 2
 140
Informed Consent for Change Leader 
Commitment to Change in Pharmacy Schools: Does Change Leadership Matter? 
 
The first phase of this study has been already completed and faculty members from your 
school have identified you as the change leader for establishing a distance learning site 
for a traditional Pharm. D. program.  You are invited to participate in this research 
study, which is designed to examine factors affecting commitment to change which may 
help pharmacy schools make better decisions on managing future change.  This study is 
being conducted by Mohammad Waheedi, a doctoral student, under the supervision of 
Dr. Bruce A. Berger, professor and head of the Department of Pharmacy Systems, 
Auburn University. 
 
Please take a look at the attached questionnaire (faculty_survey.doc), which will be sent 
to faculty members at your school.  If you decide to participate in this research study, you 
may do so by choosing one of the following options: 
 
A. To fill out the leader satisfaction survey of the second phase, which takes about 
five minutes to complete AND allow other faculty members to fill out their survey. 
OR
B. To not fill out the leader?s survey BUT allow other faculty members to fill out 
their survey. 
 
Your participation in this research is vital in making the results representative of change 
leaders among pharmacy faculty.  The data collected from you and the faculty members 
will be stored anonymously.  Once this data collection phase is completed, your name 
and your school name will be replaced with a code.  There will be no way for the 
researcher or anyone reading the report of the study to link any data to your name, nor to 
the school where you work. 
 
This study is being conducted by a doctoral student in partial fulfillment for a doctoral 
degree requirement.  Information collected through your participation will be published 
in a professional journal, and/or presented at a professional meeting.  If so, no person?s or 
school?s name will be included. 
 
There are no foreseeable risks with your participation.  By participating in this study 
today you will benefit later by receiving a copy of an executive summary of the results of 
the study, which may provide you with insights for improving your approach to change 
implementation, and thus help you achieve high levels of commitment among your 
colleagues.  Your decision whether or not to participate will not jeopardize your future 
relations with Auburn University or the Department of Pharmacy Care Systems. 
 
If you have any questions we invite you to call us or send us an e-mail.  Call me, 
Mohammad Waheedi, the director of this project, at 334-844-8310 
(waheemo@auburn.edu).  Or you may call the supervisor of my dissertation Dr. Bruce A. 
Berger at 334-844-8302 (bergeba@auburn.edu). 
 141
 
For more information regarding your rights as a research participant you may contact the 
Office of Human Subjects Research by phone or e-mail.  The people to contact there are 
Executive Director E.N. ?Chip? Burson (334) 844-5966 (bursoen@auburn.edu) or IRB 
Chair Dr. Peter Grandjean at (334) 844-1462 (grandpw@auburn.edu) . 
  
HAVING READ THE INFORMATION PROVIDED, YOU MUST DECIDE 
WHETHER OR NOT YOU WISH TO PARTICIPATE IN THIS RESEARCH 
STUDY.   By clicking on the following link you will be taken to the survey website 
where you see the Change Leader Survey and you will have three options: 
 
A. To participate AND allow other faculty members to participate.  OR 
B. To not participate BUT allow other faculty members to participate. 
C. To not participate AND to not allow other faculty members to participate. 
 
http://www.pharmacy.auburn.edu/survey/374598/changeleader.asp
 
Hold Ctrl + click on the above link 
(If that fails to connect you to the Web site: copy the above address and paste it into your Web browser, 
then click Go or press Enter on your keyboard) 
 
If you choose not to participate, faculty members at your school will not receive the 
attached faculty survey. 
 
       
Mohammad Waheedi, R.Ph., M.S.    Bruce A. Berger, Ph.D. 
Project Director      Professor and Head 
Auburn University      Pharmacy Care Systems, 
Auburn University 
 
 142
Appendix H:  The Phase 2 Internet Survey 
 143
 
BY CLICKING HERE I AGREE TO PARTICIPATE AND 
ALLOW OTHER FACULTY MEMBERS AT MY PHARMACY 
SCHOOL TO PARTICIPATE  
I Agree to Participate  
AND 
Allow Others to Participate   
BY CLICKING HERE I DECLINE TO PARTICIPATE BUT 
ALLOW OTHER FACULTY MEMBERS AT MY PHARMACY 
SCHOOL TO PARTICIPATE  
I Decline to Participate  
BUT  
Allow Others to Participate  
I DO NOT WISH TO PARTICIPATE AND DO NOT 
AUTHORIZE OTHERS IN THIS PHARMACY SCHOOL TO 
PARTICIPATE  
Do not use any Data 
Collected from this 
Pharmacy School  
 
The purpose of this survey is to confirm your status as a main change leader, to establish the 
degree of your satisfaction in relation to change completion, and to collect any further information 
or thoughts you may have. 
1. Are you a primary leader for conversion from five year B.S. to six year Pharm. D.? 
Yes No  
2. What percentage of the goals for this change was accomplished? 
--
 
 
3. How satisfied are you with how much (quantity) was accomplished? 
Very Unsatisfied     Unsatisfied     Neutral     Satisfied     Very Satisfied  
 
4. How satisfied are you with the quality of what was accomplished? 
Very Unsatisfied     Unsatisfied     Neutral     Satisfied     Very Satisfied 
Optional: Anything important we need to know? 
Was there any factor(s) or event(s) that increased/decreased the commitment of the faculty 
members to this change in a significant way?  
 
 
 
 
Submit
 
 144
Appendix I:  Information Letter E-mail for Phase 3 Internet Survey 
 145
From:  Mohammad Waheedi 
To: Care Systems, AU Pharmacy 
Date:  3/24/2005 7:59:53 AM 
Subject:  Leadership and Change Study: (Name of change leader) and Establishing a 
Distance Learning Site 
 
Dear faculty member, 
 
If you responded in Phase I of this study, thank you very much.  There was an excellent response 
from the faculty members at the University of (Name of School) College of Pharmacy. Now we 
are beginning Phase II.  The objective of this phase is to examine factors affecting commitment to 
change which may help pharmacy schools make better decisions on managing future change.  
This study is being conducted by Mohammad Waheedi, a doctoral student, under the supervision 
of Dr. Bruce A. Berger, professor and head of the Department of Pharmacy Systems, Auburn 
University. We are contacting you only because the change leader at your school has consented 
to participate in this project. 
 
The first phase of the study has been completed, and faculty members from your school have 
identified several changes.  The following particular change was mentioned with the highest 
frequency.  Therefore, it was selected for this second phase of the research: 
 
Establishing a distance learning site for a traditional Pharm. D. program 
 
In addition, faculty members at your school suggested the following person as a leader of that 
change: 
 
(Name and job title of change leader) 
 
You are invited to participate in the second phase.  If you choose to participate, please click on 
the following hyperlink that should take you to the survey Web site.  Please refer to the above 
particular change and change leader in filling out the survey.  This survey should take about 15 
minutes to complete.  Your participation will make the results more representative of pharmacy 
faculty members, and would be greatly appreciated.  The change leader at your school has seen 
the questions and has approved collecting this data. 
 
http://www.pharmacy.auburn.edu/survey/738409/phase2.asp  
 
(If your e-mail program doesn't recognize Web addresses: copy the above address and paste it 
into your Web browser, then click Go or press Enter on your keyboard) 
 
Your responses to the survey will be completely anonymous.  No names or IP addresses will be 
collected by the database.  In fact, no one will be able to tell whether you participated.  Also, we 
guarantee the confidentiality of all information related to the change leader at your school. Once 
this data collection phase is completed, the change leader?s name and your school name will be 
replaced with a code.  There will be no way for the researcher or anyone reading the report of the 
study to link any data to the change leader?s name or to his or her school. 
 
This study is being conducted by a doctoral student in partial fulfillment for a doctoral degree 
requirement.  Information collected through your participation will be published in a professional 
journal, and/or presented at a professional meeting.  If so, no person?s or school?s name will be 
included. 
 
There are no foreseeable risks with your participation.  By participating in this study today, you 
will benefit later by the results of the study that should lead to the improvement of your approach 
to change implementation, and thus help you achieve high levels of commitment among your 
 146
colleagues.  Your decision whether or not to participate will not jeopardize your future relations 
with Auburn University or the Department of Pharmacy Care Systems. 
 
If you have any questions we invite you to call us or send us an e-mail.  Call me, Mohammad 
Waheedi, the director of this project, at 334-844-8310 (waheemo@auburn.edu).  Or you may call 
the supervisor of my dissertation Dr. Bruce A. Berger at 334-844-8302 (bergeba@auburn.edu). 
 
For more information regarding your rights as a research participant you may contact the Office of 
Human Subjects Research by phone or e-mail.  The people to contact there are Executive 
Director E.N. ?Chip? Burson (334) 844-5966 (bursoen@auburn.edu) or IRB Chair Dr. Peter 
Grandjean at (334) 844-1462 (grandpw@auburn.edu) . 
  
HAVING READ THE INFORMATION PROVIDED, YOU MUST DECIDE WHETHER TO 
PARTICIPATE IN THIS RESEARCH PROJECT.  IF YOU DECIDE TO PARTICIPATE, THE 
DATA YOU PROVIDE WILL SERVE AS YOUR AGREEMENT TO DO SO.   THIS LETTER IS 
YOURS TO KEEP. 
  
Mohammad Waheedi, R.Ph., M.S. 
Doctoral student 
Auburn University 
334-844-8310 Work 
334-844-8307 Fax 
334-663-5123 Cell 
waheemo@auburn.edu  
 
Bruce A. Berger, Ph.D. 
Head and Professor of 
Pharmacy Care Systems 
128 Miller Hall 
Auburn University, AL 36849-5506 
334-844-8302 Office 
334-844-8307 Fax 
334-444-3160 Cell 
bergeba@auburn.edu  
 147
Appendix J:  Reminder E-mail for Phase 3
 148
From:  Mohammad Waheedi 
To: (e-mail address of recipient) 
Date:  4/7/2005 8:03:26 AM 
Subject:  Reminder: Last Phase of a Study of Change and Leadership (Assistant Dean 
? and Problem-based Learning) 
 
Reminder: Last Phase of a Study of Change and Leadership (Assistant Dean ? and 
Problem-based Learning) 
 
Dear faculty member, 
 
Recently you were sent an invitation to participate in an anonymous questionnaire asking your 
opinion about change in pharmacy schools.  For those who have responded, thank you very 
much.  Your response contributes to results that accurately represent the opinions of faculty 
members of the U.S. schools of pharmacy and would be greatly appreciated. 
 
As a reminder, no names or IP addresses will be collected by the database, so the responses will 
be completely anonymous.  I would be happy to answer any questions you may have. 
 
The survey will take about 10 minutes to complete.  By clicking on the Web address below the 
survey will appear on your computer screen.  Once you have completed your responses to the 
questions, please click on the SUBMIT button to submit your responses. 
 
http://www.pharmacy.auburn.edu/survey/925219/phase2.asp  
 
(If your e-mail program doesn't recognize Web addresses: copy the above address and paste it 
into your Web browser, then click Go or press Enter on your keyboard) 
 
Thanking you in anticipation. 
 
Sincerely, 
  
Mohammad Waheedi, R.Ph., M.S. 
Doctoral student 
Auburn University 
334-844-8310 Work 
334-844-8307 Fax 
334-663-5123 Cell 
waheemo@auburn.edu  
 
Bruce A. Berger, Ph.D. 
Head and Professor of 
Pharmacy Care Systems 
128 Miller Hall 
Auburn University, AL 36849-5506 
334-844-8302 Office 
334-844-8307 Fax 
334-444-3160 Cell 
bergeba@auburn.edu
 149
Appendix K:  Phase 3 Faculty Questionnaire
 150
 
Consider the following specific change when answering questions 1 to 32: 
(The specific change for a school was inserted here) 
 
1 2 3 4 5 
Strongly 
Disagree 
Disagree Neutral Agree Strongly
Agree 
 
  SDA DA N A SA 
1. I feel a sense of duty to work toward this change. 1 2 3 4 5 
2. I believe in the value of this change. 1 2 3 4 5 
3. I do not feel any obligation to support this change. 1 2 3 4 5 
4. I would not feel badly about opposing this change. 1 2 3 4 5 
5. I think that administration is making a mistake by 
introducing this change. 
1 2 3 4 5 
6. I would feel guilty about opposing this change. 1 2 3 4 5 
7. It would be too costly for me to resist this change. 1 2 3 4 5 
8. This change is good for this organization. 1 2 3 4 5 
9. I do not think it would be right for me to oppose 
this change. 
1 2 3 4 5 
10. Resisting this change is not a viable option for me. 1 2 3 4 5 
11. I feel pressure to go along with this change. 1 2 3 4 5 
12. This change is not necessary. 1 2 3 4 5 
13. I have too much at stake to resist this change. 1 2 3 4 5 
14. This change serves an important purpose. 1 2 3 4 5 
15. It would be irresponsible for me to resist this 
change 
1 2 3 4 5 
16. I have no choice but to go along with this change. 1 2 3 4 5 
17. Things would be better without this change. 1 2 3 4 5 
 
For item 18 below, rate your behavioral response to the change initiative.  On the following 
continuum click on the point that best matches the actions you took in response to the change 
initiative. 
 
Consider the following definitions when providing your answer: 
 0 to 20: Active Resistance: demonstrating opposition in response to change by engaging 
in overt behaviors that are intended to ensure that the change fails. 
21 to 40: Passive Resistance: demonstrating opposition in response to change by 
engaging in covert or subtle behaviors aimed at preventing the success of the change. 
41 to 60: Compliance: demonstrating minimum support for change by going along with 
the change, but doing so reluctantly. 
61 to 80: Cooperation: demonstrating support for change by exerting effort when it 
comes to the change, going along with the spirit of the change, and being prepared to 
make modest sacrifices. 
81 to 100: Championing: demonstrating extreme enthusiasm for change by going above 
and beyond what is formally required to ensure the success of the change in promoting the 
change to others. 
 
18.     In relation to the change initiative, my actions can be best characterized as: 
 
 151
Active 
Resistance 
Passive 
Resistance 
Compliance Cooperation Championing 
|---------------------|----------------------|---------------------|-------------------|-----------------| 
0                         20                           40                         60                      80                100 
 
Processes in Implementing Change 
The following questions include processes that may be present or absent throughout the planning 
and the implementation. In relation to the change initiative of question, please indicate your level 
of agreement: 
 
  SDA DA N A SA 
19. The decision-makers have asked for my input into this 
change. 
1 2 3 4 5 
20. The decision-makers have listened to my opinion on the 
change initiative. 
1 2 3 4 5 
21. I have participated with fellow faculty in the design of this 
change. 
1   2 3 4 5 
22. There were breakdowns in communication between faculty 
and administration. 
1 2 3 4 5 
23. Criticizing or providing information which challenges the 
feasibility of the change was encouraged.  
1 2 3 4 5 
24. There were breakdowns in communication among faculty. 1 2 3 4 5 
25. I sometimes get the feeling that others were not speaking up 
although they harbored serious doubts about the direction 
being taken. 
1 2 3 4 5 
26 I have assisted in the problem identification that led to the 
change. 
1 2 3 4 5 
27. I was kept informed adequately. 1 2 3 4 5 
28. The change initiative included suggestions I provided. 1 2 3 4 5 
29. The faculty interacted frequently. 1 2 3 4 5 
30. There were extensive formal and informal communications 
throughout the change. 
1 2 3 4 5 
31. Information was quickly shared. 1 2 3 4 5 
32. Often I felt pressured not "rock the boat" by speaking my 
mind about what's going on with this change. 
1 2 3 4 5 
  
Leadership Questions 
 
The following statements are descriptive of the identified change leader at your school: 
(Name of the change leader inserted here) 
Please indicate how frequently this change leader displays the behaviors described below 
throughout the planning and the implementation of the change. 
. 
 
1 2 3 4 5 
Not at all Once in a 
while 
Sometimes Fairly often Frequently, if 
not always 
 152
 
  
Not 
at all 
Once 
in a 
while 
Sometimes 
Fairly 
often 
Frequently 
if not 
always 
33. His/her actions build my respect for 
him/her. 
1 2 3 4 5 
34. Promotes self-development. 1 2 3 4 5 
35. Specifies the importance of having a 
strong sense of purpose. 
1   2 3 4 5 
36. Takes no action even when problems 
become chronic. 
1 2 3 4 5 
37. Directs his/her attention toward 
failure to meet standards. 
1 2 3 4 5 
38. Fails to intervene until problems 
become serious. 
1 2 3 4 5 
39. Displays extraordinary talent and 
competence in whatever he/she 
undertakes. 
1 2 3 4 5 
40. Things have to go wrong for him/her 
to take action. 
1 2 3 4 5 
41. Suggests new ways of looking at how 
we do our jobs. 
1 2 3 4 5 
42. Fails to follow-up requests for 
assistance. 
1 2 3 4 5 
43. Problems must become chronic 
before he/she will take action. 
1 2 3 4 5 
44. Emphasizes the importance of having 
a collective sense of mission. 
1 2 3 4 5 
45. Gets me to look at problems from 
many different angles. 
1 2 3 4 5 
46. Makes sure that we receive 
appropriate rewards for achieving 
performance targets. 
1 2 3 4 5 
47. Goes beyond his/her own self-interest 
for the good of our group. 
1 2 3 4 5 
48. Articulates a compelling vision of the 
future. 
1 2 3 4 5 
49. Delays responding to urgent 
questions. 
1 2 3 4 5 
50. Provides his/her assistance in 
exchange for my effort. 
1 2 3 4 5 
51. Tells me what to do to be rewarded 
for my efforts. 
1 2 3 4 5 
52. Talks enthusiastically about what 
needs to be accomplished. 
1 2 3 4 5 
53. Provides useful advice for my 
development. 
1 2 3 4 5 
54. Encourages me to express my ideas 
and opinions. 
1 2 3 4 5 
55. Keeps track of my mistakes. 1 2 3 4 5 
 153
  
Not 
at all 
Once 
in a 
while 
Sometimes 
Fairly 
often 
Frequently 
if not 
always 
56. Searches for mistakes before 
commenting on my performance. 
1 2 3 4 5 
57. Teaches me how to identify the needs 
and capabilities of others. 
1 2 3 4 5 
58. Arouses awareness on what is 
essential to consider. 
1 2 3 4 5 
59. Clarifies the central purpose 
underlying our actions. 
1 2 3 4 5 
 
 
Demographic Questions 
 
60. How many years have you been a faculty member at a 
school of pharmacy? 
 (Text box) 
61. 
What is your academic field?  
(Drop down menu 
with academic fields) 
62. Do you hold an administrative position where other 
faculty members report to you? 
 Yes or No 
63. What is your gender?  Female or Male 
64. 
Please indicate the range in which your age falls.  
(Drop down menu 
with age ranges) 
65. Are you in a tenure track position?  Yes or No 
 
 
 
 
Optional:  Anything important we need to know?
 
Was there any external factor(s) or event(s) that affected the change process or its 
implementation in a significant way? 
 
 
 
 
Thank you very much! 
 154
Appendix L:  Screenshots of the Phase 3 Internet Survey 
 155
 
 
 156
 
 
 157
 
 
 158
 159
Appendix M:  Structural Equation Modeling (SEM) Results for Leadership Effects 
on Affective Commitment  
 160
 
 
 
Transform.
Leadership
IDINFLC1
e1
.80
INSPMT3
e2
.77
INSPMT1
e3
.84
CHRSM1
e4
.83
INTLST3
e5
.78
Avoidant
LSFR2
e6
LSFR1
e7
MBEP3
e8
MBEP2
e9
MBEP1
e10
.72
.72.88.83
.96
Contingent
Reward
CNGRW3
e11
CNGRW2
e12
CNGRW1
e13
.84.71
.80
Active MBE
MBEA2
e14
MBEA1
e15
1.00
.76
Affective
Commitment
AC1 e16
AC2 e17
AC3R e18
AC4 e19
AC5R e20
.83
.93
.93
.93
.83
Change
Involvement
PDM2
e21
PDM3
e22
PDM5
e23
CMM1
e24
CMM2
e25
.80.85
.87
.79
.67
e28
e29
.10
.01
-.13
-.22
-.18
.49
-.16
-.26
-.38
.38
.83
-.50
-.70
-.74
.42
 
Maximum Likelihood Estimates 
Regression Weights: (Group number 1 - Default model) 
 Estimate S.E. C.R. P
Change_Involvement <--- Transform._Leadership -.178 .183 -.968 .333 
Change_Involvement <--- Contingent_Reward .453 .160 2.825 .005 
Change_Involvement <--- Active MBE -.144 .069 -2.073 .038 
Change_Involvement <--- Avoidant -.338 .144 -2.345 .019 
Affective_Commitment <--- Transform._Leadership .092 .142 .648 .517 
Affective_Commitment <--- Contingent_Reward .008 .128 .060 .952 
Affective_Commitment <--- Active MBE -.106 .055 -1.938 .053 
Affective_Commitment <--- Avoidant -.262 .114 -2.304 .021 
Affective_Commitment <--- Change_Involvement .377 .077 4.879 *** 
IDINFLC1 <---Transform._Leadership 1.000    
INSPMT3 <--- Transform._Leadership .970 .085 11.430 *** 
INSPMT1 <---Transform._Leadership .938 .073 12.814 ***
 161
  Estimate S.E. C.R. P
CHRSM1 <---Transform._Leadership .978 .078 12.602 *** 
INTLST3 <--- Transform._Leadership .929 .080 11.561 ***
LSFR2 <---Avoidant 1.000    
LSFR1 <--- Avoidant 1.049 .109 9.611 ***
MBEP3 <--- Avoidant 1.316 .111 11.801 *** 
MBEP2 <--- Avoidant 1.235 .111 11.105 ***
MBEP1 <--- Avoidant 1.535 .119 12.923 *** 
CNGRW3 <--- Contingent_Reward 1.000   
CNGRW2 <--- Contingent_Reward .808 .079 10.265 *** 
CNGRW1 <--- Contingent_Reward .871 .073 11.861 ***
MBEA2 <--- Active MBE 1.000   
MBEA1 <--- Active MBE .775 .051 15.285 ***
AC1 <---Affective_Commitment 1.000    
AC2 <---Affective_Commitment 1.130 .067 16.881 ***
AC3R <--- Affective_Commitment 1.215 .072 16.860 ***
AC4 <---Affective_Commitment 1.087 .065 16.688 ***
AC5R <--- Affective_Commitment 1.029 .074 13.873 ***
PDM2 <---Change_Involvement 1.000   
PDM3 <--- Change_Involvement 1.091 .085 12.813 ***
PDM5 <---Change_Involvement .963 .072 13.317 ***
CMM1 <--- Change_Involvement .919 .079 11.708 *** 
CMM2 <---Change_Involvement .751 .079 9.553 ***
Standardized Regression Weights: (Group number 1 - Default model) 
   Estimate 
Change_Involvement <--- Transform._Leadership -.176
Change_Involvement <--- Contingent_Reward .487
Change_Involvement <--- Active MBE -.165
Change_Involvement <--- Avoidant -.259
Affective_Commitment <--- Transform._Leadership .101
Affective_Commitment <--- Contingent_Reward .009
Affective_Commitment <--- Active MBE -.134
Affective_Commitment <--- Avoidant -.222
Affective_Commitment <--- Change_Involvement .417
IDINFLC1 <--- Transform._Leadership .800
INSPMT3 <--- Transform._Leadership .774
INSPMT1 <--- Transform._Leadership .843
CHRSM1 <--- Transform._Leadership .833
INTLST3 <--- Transform._Leadership .781
LSFR2 <--- Avoidant .722
 162
   Estimate 
LSFR1 <--- Avoidant .724
MBEP3 <--- Avoidant .877
MBEP2 <--- Avoidant .827
MBEP1 <--- Avoidant .965
CNGRW3 <--- Contingent_Reward .845
CNGRW2 <--- Contingent_Reward .715
CNGRW1 <--- Contingent_Reward .799
MBEA2 <--- Active MBE .996
MBEA1 <--- Active MBE .760
AC1 <--- Affective_Commitment .832
AC2 <--- Affective_Commitment .933
AC3R <--- Affective_Commitment .934
AC4 <--- Affective_Commitment .928
AC5R <--- Affective_Commitment .833
PDM2 <--- Change_Involvement .801
PDM3 <--- Change_Involvement .849
PDM5 <--- Change_Involvement .875
CMM1 <--- Change_Involvement .793
CMM2 <--- Change_Involvement .675
 
Intercepts: (Group number 1 - Default model) 
  Estimate S.E. C.R. P 
IDINFLC1  3.644 .092 39.575 *** 
INSPMT3  3.711 .092 40.171 *** 
INSPMT1  4.050 .082 49.401 *** 
CHRSM1  3.728 .087 43.044 *** 
INTLST3  3.428 .088 39.066 *** 
LSFR2 2.006 .079 25.392 ***
LSFR1  2.212 .083 26.630 *** 
MBEP3  2.211 .086 25.837 *** 
MBEP2  2.189 .085 25.708 *** 
MBEP1  2.244 .091 24.737 *** 
CNGRW3  3.307 .095 34.830 *** 
CNGRW2  2.696 .091 29.698 *** 
CNGRW1  2.746 .087 31.444 *** 
MBEA2  1.811 .086 21.006 *** 
MBEA1  2.126 .088 24.224 *** 
AC1 3.817 .081 47.169 ***
AC2  3.767 .082 46.197 *** 
AC3R 3.764 .088 42.903 ***
AC4  3.745 .079 47.464 *** 
AC5R 3.606 .083 43.340 ***
 163
PDM2  3.243 .093 34.899 *** 
PDM3 3.256 .096 34.067 ***
PDM5  2.917 .082 35.643 *** 
CMM1 3.189 .086 36.981 ***
CMM2  3.106 .083 37.498 *** 
Covariances: (Group number 1 - Default model) 
Estimate S.E. C.R. P
Active MBE <--> Contingent_Reward -.463 .108 -4.282 ***
Active MBE <--> Avoidant .331 .076 4.381 ***
Transform._Leadership <--> Contingent_Reward .878 .126 6.962 ***
Active MBE <--> Transform._Leadership -.568 .103 -5.490 ***
Avoidant <--> Contingent_Reward -.568 .093 -6.116 ***
Transform._Leadership <--> Avoidant -.553 .088 -6.254 ***
Correlations: (Group number 1 - Default model) 
 Estimate
Active MBE <--> Contingent_Reward -.379 
Active MBE <--> Avoidant .380 
Transform._Leadership <--> Contingent_Reward .832 
Active MBE <--> Transform._Leadership -.505 
Avoidant <--> Contingent_Reward -.696
Transform._Leadership <--> Avoidant -.735 
Variances: (Group number 1 - Default model) 
Estimate S.E. C.R. P
Transform._Leadership  .973 .154 6.317 *** 
Avoidant .582 .105 5.525 ***
Contingent_Reward 1.147 .173 6.625 ***
Active MBE   1.301 .140 9.300 *** 
e28 .601 .103 5.845 ***
e29 .397 .061 6.498 *** 
e14 .010
e1 .546 .068 8.042 ***
e2  .613 .074 8.275 ***
e3 .348 .046 7.495 ***
e4 .412 .054 7.653 *** 
e5 .538 .065 8.222 ***
e6 .535 .060 8.974 ***
e7  .581 .065 8.868 ***
e8 .304 .039 7.781 ***
e9 .410 .049 8.433 *** 
e10 .102 .029 3.585 ***
e11 .460 .075 6.098 ***
e12  .717 .089 8.060 ***
e13 .493 .069 7.102 ***
e15 .571 .062 9.211 *** 
e16 .361 .042 8.595 ***
 164
e17  .154 .023 6.810 *** 
e18 .176 .026 6.737 ***
e19 .156 .022 7.015 ***
e20 .380 .044 8.589 ***
e21 .552 .070 7.866 ***
e22  .457 .064 7.173 *** 
e23 .282 .043 6.577 ***
e24 .495 .062 7.976 ***
e25 .669 .077 8.736 ***
Model Fit Summary 
CMIN 
Model NPAR CMIN DF P CMIN/DF 
Default model 89 363.176 261 .000 1.391 
Saturated model 350 .000 0   
Independence model 25 3825.863 325 .000 11.772 
Baseline Comparisons 
Model 
NFI
Delta1 
RFI
rho1 
IFI
Delta2 
TLI
rho2 
CFI 
Default model .905 .882 .971 .964 .971 
Saturated model 1.000  1.000  1.000 
Independence model .000 .000 .000 .000 .000 
Parsimony-Adjusted Measures 
Model PRATIO PNFI PCFI 
Default model .803 .727 .780 
Saturated model .000 .000 .000 
Independence model 1.000 .000 .000 
NCP 
Model NCP LO 90 HI 90 
Default model 102.176 55.980 156.415 
Saturated model .000 .000 .000 
Independence model 3500.863 3305.333 3703.710 
FMIN 
Model FMIN F0 LO 90 HI 90 
Default model 2.029 .571 .313 .874 
 165
Model FMIN F0 LO 90 HI 90 
Saturated model .000 .000 .000 .000 
Independence model 21.374 19.558 18.466 20.691 
RMSEA 
Model RMSEA LO 90 HI 90 PCLOSE 
Default model .047 .035 .058 .672 
Independence model .245 .238 .252 .000 
AIC 
Model AIC BCC BIC CAIC 
Default model 541.176 571.424   
Saturated model 700.000 818.954   
Independence model 3875.863 3884.360  
ECVI 
Model ECVI LO 90 HI 90 MECVI 
Default model 3.023 2.765 3.326 3.192 
Saturated model 3.911 3.911 3.911 4.575 
Independence model 21.653 20.561 22.786 21.700 
HOELTER 
Model 
HOELTER
.05 
HOELTER
.01 
Default model 148 157 
Independence model 18 19 
 
 166
                                                   
 
Appendix N:  SEM Results for Leadership Effects on Normative Commitment  
 167
 
Transform.
Leadership
IDINFLC1
e1
.80
INSPMT3
e2
.77
INSPMT1
e3
.84
CHRSM1
e4
.83
INTLST3
e5
.78
Avoidant
LSFR2
e6
LSFR1
e7
MBEP3
e8
MBEP2
e9
MBEP1
e10
.72
.73
.88
.83
.96
Contingent
Reward
CNGRW3
e11
CNGRW2
e12
CNGRW1
e13
.84
.72
.80
Active MBE
MBEA2
e14
MBEA1
e15
1.00.76
Normative
Commitment
NC6R e16
NC2 e17
NC3R e18
NC4 e19
NC5 e20
.68
.69
.68
.68
.47
Change
Involvement
PDM2 e21
PDM3 e22
PDM5 e23
CMM1 e24
CMM2 e25
.81
.85
.87
.79
.68
e28
e29
-.50
-.38
.38
-.70
-.74
.83
-.17
.04
-.31
.31
-.17
.48
-.16
-.26
.30
  
Maximum Likelihood Estimates 
Regression Weights: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Change_Involvement <--- Transform._Leadership -.176 .185 -.950 .342 
Change_Involvement <--- Contingent_Reward .454 .161 2.812 .005 
Change_Involvement <--- Active MBE -.143 .070 -2.051 .040 
Change_Involvement <--- Avoidant -.342 .145 -2.348 .019 
Normative_Commitment <--- Transform._Leadership -.111 .138 -.804 .421 
Normative_Commitment <--- Avoidant .032 .108 .292 .770 
Normative_Commitment <--- Active MBE -.178 .055 -3.253 .001 
Normative_Commitment <--- Contingent_Reward .190 .126 1.509 .131 
Normative_Commitment <--- Change_Involvement .196 .072 2.719 .007 
IDINFLC1 <---Transform._Leadership 1.000    
INSPMT3 <--- Transform._Leadership .969 .085 11.433 *** 
INSPMT1 <--- Transform._Leadership .936 .073 12.819 ***
CHRSM1 <--- Transform._Leadership .977 .078 12.597 *** 
 168
   Estimate S.E. C.R. P 
INTLST3 <---Transform._Leadership .930 .080 11.598 ***
LSFR2 <--- Avoidant 1.000    
LSFR1 <--- Avoidant 1.051 .109 9.640 ***
MBEP3 <--- Avoidant 1.314 .111 11.800 *** 
MBEP2 <--- Avoidant 1.234 .111 11.112 ***
MBEP1 <--- Avoidant 1.534 .119 12.930 *** 
CNGRW3 <---Contingent_Reward 1.000    
CNGRW2 <--- Contingent_Reward .808 .079 10.283 *** 
CNGRW1 <---Contingent_Reward .871 .073 11.887 ***
MBEA2 <--- Active MBE 1.000   
MBEA1 <--- Active MBE .776 .051 15.261 *** 
NC6R <--- Normative_Commitment 1.000    
NC2 <--- Normative_Commitment 1.157 .155 7.457 ***
NC3R <--- Normative_Commitment 1.143 .153 7.446 *** 
NC4 <--- Normative_Commitment 1.179 .160 7.378 ***
NC5 <--- Normative_Commitment .842 .155 5.445 ***
PDM2 <--- Change_Involvement 1.000    
PDM3 <--- Change_Involvement 1.085 .084 12.963 ***
PDM5 <--- Change_Involvement .946 .071 13.286 *** 
CMM1 <--- Change_Involvement .913 .077 11.813 ***
CMM2 <--- Change_Involvement .749 .078 9.651 *** 
Standardized Regression Weights: (Group number 1 - Default model) 
   Estimate 
Change_Involvement <--- Transform._Leadership -.173 
Change_Involvement <--- Contingent_Reward .485 
Change_Involvement <--- Active MBE -.163 
Change_Involvement <--- Avoidant -.260 
Normative_Commitment <--- Transform._Leadership -.166 
Normative_Commitment <--- Avoidant .036 
Normative_Commitment <--- Active MBE -.307 
Normative_Commitment <--- Contingent_Reward .308 
Normative_Commitment <--- Change_Involvement .297 
IDINFLC1 <--- Transform._Leadership .801 
INSPMT3 <--- Transform._Leadership .773
INSPMT1 <--- Transform._Leadership .843 
CHRSM1 <--- Transform._Leadership .832
INTLST3 <--- Transform._Leadership .782 
LSFR2 <--- Avoidant .722
LSFR1 <--- Avoidant .726 
 169
   Estimate 
MBEP3 <--- Avoidant .876
MBEP2 <--- Avoidant .827 
MBEP1 <--- Avoidant .965
CNGRW3 <--- Contingent_Reward .845 
CNGRW2 <--- Contingent_Reward .715
CNGRW1 <--- Contingent_Reward .799 
MBEA2 <--- Active MBE .996
MBEA1 <--- Active MBE .760 
NC6R <--- Normative_Commitment .683
NC2 <--- Normative_Commitment .686
NC3R <--- Normative_Commitment .684 
NC4 <--- Normative_Commitment .676
NC5 <--- Normative_Commitment .474
PDM2 <--- Change_Involvement .807 
PDM3 <--- Change_Involvement .851
PDM5 <--- Change_Involvement .867 
CMM1 <--- Change_Involvement .793
CMM2 <--- Change_Involvement .678 
Intercepts: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
IDINFLC1  3.644 .092 39.575 ***
INSPMT3  3.711 .092 40.171 ***
INSPMT1  4.050 .082 49.401 ***
CHRSM1   3.728 .087 43.044 ***
INTLST3   3.428 .088 39.066 ***
LSFR2   2.006 .079 25.392 ***
LSFR1   2.212 .083 26.631 ***
MBEP3   2.211 .086 25.837 ***
MBEP2   2.189 .085 25.708 ***
MBEP1   2.244 .091 24.737 ***
CNGRW3  3.307 .095 34.832 ***
CNGRW2  2.694 .091 29.704 ***
CNGRW1  2.746 .087 31.445 ***
MBEA2   1.810 .086 21.045 ***
MBEA1   2.126 .088 24.249 ***
NC6R   3.912 .073 53.805 ***
NC2   3.251 .084 38.879 ***
NC3R   3.661 .083 44.273 ***
NC4   3.352 .086 38.789 ***
 170
   Estimate S.E. C.R. P 
NC5   2.918 .088 33.118 ***
PDM2   3.243 .093 34.900 ***
PDM3   3.256 .096 34.067 ***
PDM5   2.917 .082 35.643 ***
CMM1   3.189 .086 36.981 ***
CMM2   3.106 .083 37.498 ***
Covariances: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Active MBE <--> Transform._Leadership -.564 .103 -5.467 *** 
Active MBE <--> Contingent_Reward -.459 .108 -4.260 *** 
Active MBE <--> Avoidant .327 .075 4.343 *** 
Avoidant <--> Contingent_Reward -.568 .093 -6.117 *** 
Transform._Leadership <--> Avoidant -.554 .089 -6.258 *** 
Transform._Leadership <--> Contingent_Reward .879 .126 6.964 *** 
Correlations: (Group number 1 - Default model) 
   Estimate 
Active MBE <--> Transform._Leadership -.502
Active MBE <--> Contingent_Reward -.377
Active MBE <--> Avoidant .376
Avoidant <--> Contingent_Reward -.695
Transform._Leadership <--> Avoidant -.735
Transform._Leadership <--> Contingent_Reward .832
Variances: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Transform._Leadership   .974 .154 6.325 ***
Avoidant   .583 .105 5.529 ***
Contingent_Reward   1.146 .173 6.627 ***
Active MBE   1.296 .139 9.301 ***
e28  .612 .104 5.901 ***
e29  .291 .066 4.386 ***
e14   .010    
e1  .544 .068 8.031 ***
e2  .614 .074 8.276 ***
e3   .349 .047 7.498 ***
e4  .414 .054 7.662 ***
e5  .535 .065 8.207 ***
 171
   Estimate S.E. C.R. P 
e6   .534 .060 8.968 ***
e7  .577 .065 8.858 ***
e8  .306 .039 7.775 ***
e9   .410 .049 8.422 ***
e10  .103 .029 3.559 ***
e11  .461 .075 6.136 ***
e12   .715 .089 8.072 ***
e13  .493 .069 7.125 ***
e15  .570 .062 9.211 ***
e16   .501 .068 7.409 ***
e17  .660 .089 7.397 ***
e18  .652 .088 7.436 ***
e19   .722 .096 7.503 ***
e20  1.072 .122 8.778 ***
e21  .537 .069 7.743 ***
e22   .452 .064 7.070 ***
e23  .298 .044 6.704 ***
e24  .493 .062 7.924 ***
e25   .664 .076 8.702 ***
 
Model Fit Summary 
CMIN 
Model NPAR CMIN DF P CMIN/DF 
Default model 89 410.374 261 .000 1.572 
Saturated model 350 .000 0   
Independence model 25 3102.968 325 .000 9.548 
Baseline Comparisons 
Model 
NFI
Delta1 
RFI
rho1 
IFI
Delta2 
TLI
rho2 
CFI 
Default model .868 .835 .947 .933 .946 
Saturated model 1.000  1.000  1.000 
Independence model .000 .000 .000 .000 .000 
Parsimony-Adjusted Measures 
Model PRATIO PNFI PCFI 
 172
Model PRATIO PNFI PCFI 
Default model .803 .697 .760 
Saturated model .000 .000 .000 
Independence model 1.000 .000 .000 
NCP 
Model NCP LO 90 HI 90 
Default model 149.374 98.269 208.413 
Saturated model .000 .000 .000 
Independence model 2777.968 2603.206 2960.100 
FMIN 
Model FMIN F0 LO 90 HI 90 
Default model 2.293 .834 .549 1.164 
Saturated model .000 .000 .000 .000 
Independence model 17.335 15.519 14.543 16.537 
RMSEA 
Model RMSEA LO 90 HI 90 PCLOSE 
Default model .057 .046 .067 .150 
Independence model .219 .212 .226 .000 
AIC 
Model AIC BCC BIC CAIC 
Default model 588.374 618.622   
Saturated model 700.000 818.954   
Independence model 3152.968 3161.464   
ECVI 
Model ECVI LO 90 HI 90 MECVI 
Default model 3.287 3.002 3.617 3.456 
Saturated model 3.911 3.911 3.911 4.575 
Independence model 17.614 16.638 18.632 17.662 
HOELTER 
Model 
HOELTER
.05 
HOELTER
.01 
Default model 131 139 
 173
Model 
HOELTER
.05 
HOELTER
.01 
Independence model 22 23 
 
 
 
 174
Appendix O:  SEM Results for Leadership Effects on Continuance Commitment
 175
Transform.
Leadership
IDINFLC1
e1
.80
INSPMT3
e2
.77
INSPMT1
e3
.84
CHRSM1
e4
.83
INTLST3
e5
.78
Avoidant
LSFR2
e6
LSFR1
e7
MBEP3
e8
MBEP2
e9
MBEP1
e10
.72.73
.88
.83
.96
Contingent
Reward
CNGRW3
e11
CNGRW2
e12
CNGRW1
e13
.84
.72
.80
Active MBE
MBEA2
e14
MBEA1
e15
1.00
.76
Continuance
Commitment
CC1 e16
CC2 e17
CC3 e18
CC4 e19
CC6 e20
.70
.71
.81
.76
.75
Change
Involvement
PDM2
e21
PDM3
e22
PDM5
e23
CMM1
e24
CMM2
e25
.80 .85
.87
.79
.68
e28
e29
-.50
-.38
.38
-.69
-.74
.83
-.20
.11
.02
-.17
.48
-.16
-.26
-.14
.12
 
Maximum Likelihood Estimates 
Regression Weights: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Change_Involvement <---Transform._Leadership -.173 .184 -.939 .348 
Change_Involvement <---Contingent_Reward .449 .161 2.785 .005 
Change_Involvement <---Active MBE -.143 .070 -2.063 .039 
Change_Involvement <---Avoidant -.341 .145 -2.358 .018 
Continuance_Commitment <---Transform._Leadership -.178 .189 -.942 .346 
Continuance_Commitment <---Avoidant .126 .148 .849 .396 
Continuance_Commitment <---Active MBE .013 .072 .176 .860 
Continuance_Commitment <---Change_Involvement -.117 .096 -1.221 .222 
Continuance_Commitment <---Contingent_Reward .098 .170 .574 .566 
IDINFLC1 <---Transform._Leadership 1.000    
INSPMT3 <---Transform._Leadership .967 .085 11.408 *** 
INSPMT1 <---Transform._Leadership .938 .073 12.835 *** 
CHRSM1 <---Transform._Leadership .976 .078 12.591 *** 
INTLST3 <---Transform._Leadership .931 .080 11.607 *** 
 176
   Estimate S.E. C.R. P 
LSFR2 <---Avoidant 1.000    
LSFR1 <---Avoidant 1.051 .109 9.640 *** 
MBEP3 <---Avoidant 1.313 .111 11.801 *** 
MBEP2 <---Avoidant 1.234 .111 11.116 *** 
MBEP1 <---Avoidant 1.534 .119 12.934 *** 
CNGRW3 <---Contingent_Reward 1.000    
CNGRW2 <---Contingent_Reward .814 .079 10.261 *** 
CNGRW1 <---Contingent_Reward .878 .074 11.856 *** 
MBEA2 <---Active MBE 1.000    
MBEA1 <---Active MBE .776 .051 15.283 *** 
CC1 <---Continuance_Commitment 1.000   
CC2 <---Continuance_Commitment 1.014 .119 8.556 *** 
CC3 <---Continuance_Commitment 1.095 .115 9.565 *** 
CC4 <---Continuance_Commitment 1.031 .114 9.040 *** 
CC6 <---Continuance_Commitment 1.013 .113 8.927 *** 
PDM2 <---Change_Involvement 1.000    
PDM3 <---Change_Involvement 1.096 .085 12.926 *** 
PDM5 <---Change_Involvement .956 .072 13.230 *** 
CMM1 <---Change_Involvement .914 .078 11.646 *** 
CMM2 <---Change_Involvement .750 .079 9.555 *** 
Standardized Regression Weights: (Group number 1 - Default model) 
   Estimate 
Change_Involvement <--- Transform._Leadership -.171 
Change_Involvement <--- Contingent_Reward .481 
Change_Involvement <--- Active MBE -.164 
Change_Involvement <--- Avoidant -.261 
Continuance_Commitment <--- Transform._Leadership -.205 
Continuance_Commitment <--- Avoidant .112 
Continuance_Commitment <--- Active MBE .017 
Continuance_Commitment <--- Change_Involvement -.136 
Continuance_Commitment <--- Contingent_Reward .121 
IDINFLC1 <--- Transform._Leadership .801 
INSPMT3 <--- Transform._Leadership .772 
INSPMT1 <--- Transform._Leadership .843 
CHRSM1 <--- Transform._Leadership .832 
INTLST3 <--- Transform._Leadership .782 
LSFR2 <--- Avoidant .722 
LSFR1 <--- Avoidant .726 
MBEP3 <--- Avoidant .876 
 177
   Estimate 
MBEP2 <--- Avoidant .827 
MBEP1 <--- Avoidant .965 
CNGRW3 <--- Contingent_Reward .841 
CNGRW2 <--- Contingent_Reward .717 
CNGRW1 <--- Contingent_Reward .802 
MBEA2 <--- Active MBE .996 
MBEA1 <--- Active MBE .760 
CC1 <--- Continuance_Commitment .698 
CC2 <--- Continuance_Commitment .714 
CC3 <--- Continuance_Commitment .815 
CC4 <--- Continuance_Commitment .760 
CC6 <--- Continuance_Commitment .750 
PDM2 <--- Change_Involvement .803 
PDM3 <--- Change_Involvement .855 
PDM5 <--- Change_Involvement .871 
CMM1 <--- Change_Involvement .789 
CMM2 <--- Change_Involvement .675 
Intercepts: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
IDINFLC1   3.644 .092 39.575 ***
INSPMT3   3.711 .092 40.171 ***
INSPMT1   4.050 .082 49.401 ***
CHRSM1   3.728 .087 43.044 ***
INTLST3   3.428 .088 39.066 ***
LSFR2   2.006 .079 25.392 ***
LSFR1   2.212 .083 26.632 ***
MBEP3   2.211 .086 25.837 ***
MBEP2   2.189 .085 25.708 ***
MBEP1   2.244 .091 24.737 ***
CNGRW3   3.307 .095 34.828 ***
CNGRW2   2.695 .091 29.700 ***
CNGRW1   2.746 .087 31.445 ***
MBEA2   1.812 .086 21.021 ***
MBEA1   2.127 .088 24.234 ***
CC1   2.767 .092 30.101 ***
CC2   2.956 .091 32.428 ***
CC3   2.750 .086 31.880 ***
CC4   2.856 .087 32.798 ***
CC6   3.098 .087 35.701 ***
 178
   Estimate S.E. C.R. P 
PDM2   3.243 .093 34.899 ***
PDM3   3.256 .096 34.067 ***
PDM5   2.917 .082 35.643 ***
CMM1   3.189 .086 36.981 ***
CMM2   3.106 .083 37.498 ***
Covariances: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Active MBE <--> Transform._Leadership -.568 .103 -5.487 *** 
Active MBE <--> Contingent_Reward -.460 .108 -4.269 *** 
Active MBE <--> Avoidant .330 .076 4.369 *** 
Avoidant <--> Contingent_Reward -.565 .093 -6.102 *** 
Transform._Leadership <--> Avoidant -.554 .089 -6.258 *** 
Transform._Leadership <--> Contingent_Reward .875 .126 6.950 *** 
Correlations: (Group number 1 - Default model) 
   Estimate 
Active MBE <--> Transform._Leadership -.505
Active MBE <--> Contingent_Reward -.378
Active MBE <--> Avoidant .379
Avoidant <--> Contingent_Reward -.695
Transform._Leadership <--> Avoidant -.735
Transform._Leadership <--> Contingent_Reward .832
Variances: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Transform._Leadership   .974 .154 6.323 ***
Avoidant   .583 .105 5.530 ***
Contingent_Reward   1.136 .173 6.580 ***
Active MBE   1.300 .140 9.299 ***
e28   .606 .103 5.862 ***
e29   .669 .134 5.003 ***
e14   .010    
e1   .544 .068 8.038 ***
e2   .617 .074 8.289 ***
e3   .347 .046 7.490 ***
e4   .414 .054 7.671 ***
e5   .534 .065 8.207 ***
e6   .534 .060 8.968 ***
 179
   Estimate S.E. C.R. P 
e7   .578 .065 8.858 ***
e8   .306 .039 7.778 ***
e9   .410 .049 8.422 ***
e10   .103 .029 3.563 ***
e11   .470 .076 6.186 ***
e12   .712 .089 8.038 ***
e13   .486 .069 7.039 ***
e15   .571 .062 9.211 ***
e16   .776 .096 8.089 ***
e17   .729 .092 7.956 ***
e18   .448 .068 6.579 ***
e19   .574 .077 7.469 ***
e20   .588 .078 7.572 ***
e21   .549 .070 7.796 ***
e22   .440 .063 6.971 ***
e23   .290 .044 6.593 ***
e24   .501 .063 7.962 ***
e25   .668 .077 8.712 ***
 
Model Fit Summary 
CMIN 
Model NPAR CMIN DF P CMIN/DF 
Default model 89 434.566 261 .000 1.665 
Saturated model 350 .000 0   
Independence model 25 3254.903 325 .000 10.015 
Baseline Comparisons 
Model 
NFI
Delta1 
RFI
rho1 
IFI
Delta2 
TLI
rho2 
CFI 
Default model .866 .834 .942 .926 .941 
Saturated model 1.000  1.000  1.000 
Independence model .000 .000 .000 .000 .000 
Parsimony-Adjusted Measures 
Model PRATIO PNFI PCFI 
Default model .803 .696 .756 
Saturated model .000 .000 .000 
 180
Model PRATIO PNFI PCFI 
Independence model 1.000 .000 .000 
NCP 
Model NCP LO 90 HI 90 
Default model 173.566 120.112 234.914 
Saturated model .000 .000 .000 
Independence model 2929.903 2750.576 3116.583 
FMIN 
Model FMIN F0 LO 90 HI 90 
Default model 2.428 .970 .671 1.312 
Saturated model .000 .000 .000 .000 
Independence model 18.184 16.368 15.366 17.411 
RMSEA 
Model RMSEA LO 90 HI 90 PCLOSE 
Default model .061 .051 .071 .040 
Independence model .224 .217 .231 .000 
AIC 
Model AIC BCC BIC CAIC 
Default model 612.566 642.815   
Saturated model 700.000 818.954   
Independence model 3304.903 3313.399   
ECVI 
Model ECVI LO 90 HI 90 MECVI 
Default model 3.422 3.124 3.765 3.591 
Saturated model 3.911 3.911 3.911 4.575 
Independence model 18.463 17.461 19.506 18.511 
HOELTER 
Model 
HOELTER
.05 
HOELTER
.01 
Default model 124 131 
Independence model 21 22 
 
 181
Appendix P:  SEM Results for Commitment Effects on Behavior and Leaders? 
Satisfaction 
 182
 
Affective
Commitment
AC1
e1
.
8
3
AC2
e2
.
9
3
AC3R
e3
.93
AC4
e4
.
9
4
AC5R
e5
.
8
3
Continuance
Commitment
CC1
e6
CC2
e7
CC3
e8
CC4
e9
CC6
e10
.
7
8
.
7
6
.72
.
6
4
.
7
3
Normative
Commitment
Leader
Satisfaction
SATQT
e16
.
6
6
SATQLT
e17
.
9
9
e18
COMPLIAN
DISCETIO
e19
e20
NC1
e21
.
6
9
NC4
e22
.
6
3
NC3R
e23
.
6
4
NC6R
e24
.
7
1
-.32
-
.0
5
.3
1
-.2
6
.38
-
.
0
3
.
6
7
.
4
8
.1
3
.3
5
.75
-.40
.47
-.2
5
.
1
9
.04
  
Maximum Likelihood Estimates 
Regression Weights: (Group number 1 - Default model) 
  Estimate S.E. C.R. P 
DISCETIO <--- Continuance_Commitment -1.020 3.224 -.316 .752 
COMPLIAN <--- Affective_Commitment 7.554 1.689 4.471 *** 
DISCETIO <--- Affective_Commitment 19.681 5.709 3.447 *** 
COMPLIAN <--- Normative_Commitment 2.163 2.396 .903 .366 
DISCETIO <--- Normative_Commitment 21.468 8.475 2.533 .011 
COMPLIAN <--- Continuance_Commitment 1.968 .966 2.037 .042 
Leader_Satisfaction <--- Normative_Commitment -.344 .237 -1.452 .146 
Leader_Satisfaction <--- Continuance_Commitment -.033 .089 -.368 .713 
Leader_Satisfaction <--- Affective_Commitment .220 .165 1.332 .183 
Leader_Satisfaction <--- COMPLIAN -.016 .007 -2.171 .030 
Leader_Satisfaction <--- DISCETIO .007 .002 2.788 .005 
AC1 <--- Affective_Commitment 1.000    
AC2 <--- Affective_Commitment 1.129 .067 16.746 *** 
 183
   Estimate S.E. C.R. P 
AC3R <--- Affective_Commitment 1.209 .073 16.621 *** 
AC4 <--- Affective_Commitment 1.100 .065 16.942 *** 
AC5R <--- Affective_Commitment 1.030 .075 13.812 *** 
CC1 <--- Continuance_Commitment 1.000    
CC2 <--- Continuance_Commitment .964 .097 9.898 *** 
CC3 <--- Continuance_Commitment .863 .093 9.314 *** 
CC4 <--- Continuance_Commitment .772 .095 8.134 *** 
CC6 <--- Continuance_Commitment .884 .093 9.536 *** 
SATQT <--- Leader_Satisfaction 1.000    
SATQLT <--- Leader_Satisfaction 1.571 .151 10.423 *** 
NC1 <--- Normative_Commitment 1.000    
NC4 <--- Normative_Commitment 1.239 .186 6.654 *** 
NC3R <--- Normative_Commitment 1.200 .161 7.468 *** 
NC6R <--- Normative_Commitment 1.163 .143 8.114 *** 
Standardized Regression Weights: (Group number 1 - Default model) 
   Estimate 
DISCETIO <--- Continuance_Commitment -.027
COMPLIAN <--- Affective_Commitment .668
DISCETIO <--- Affective_Commitment .483
COMPLIAN <--- Normative_Commitment .126
DISCETIO <--- Normative_Commitment .346
COMPLIAN <--- Continuance_Commitment .186
Leader_Satisfaction <--- Normative_Commitment -.323
Leader_Satisfaction <--- Continuance_Commitment -.050
Leader_Satisfaction <--- Affective_Commitment .314
Leader_Satisfaction <--- COMPLIAN -.259
Leader_Satisfaction <--- DISCETIO .383
AC1 <--- Affective_Commitment .830
AC2 <--- Affective_Commitment .930
AC3R <--- Affective_Commitment .927
AC4 <--- Affective_Commitment .936
AC5R <--- Affective_Commitment .831
CC1 <--- Continuance_Commitment .783
CC2 <--- Continuance_Commitment .761
CC3 <--- Continuance_Commitment .719
CC4 <--- Continuance_Commitment .637
CC6 <--- Continuance_Commitment .734
SATQT <--- Leader_Satisfaction .660
SATQLT <--- Leader_Satisfaction .995
 184
   Estimate 
NC1 <--- Normative_Commitment .691
NC4 <--- Normative_Commitment .634
NC3R <--- Normative_Commitment .641
NC6R <--- Normative_Commitment .710
Intercepts: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
COMPLIAN   55.676 .762 73.053 ***
DISCETIO   56.180 2.747 20.452 ***
AC1   3.817 .081 47.169 ***
AC2   3.767 .082 46.197 ***
AC3R   3.763 .088 42.918 ***
AC4   3.744 .079 47.426 ***
AC5R   3.606 .083 43.340 ***
CC1   2.767 .092 30.101 ***
CC2   2.956 .091 32.428 ***
CC3   2.750 .086 31.880 ***
CC4   2.856 .087 32.798 ***
CC6   3.098 .087 35.723 ***
SATQT   4.558 .439 10.382 ***
SATQLT   4.653 .679 6.853 ***
NC1   3.978 .064 62.167 ***
NC4   3.349 .086 38.740 ***
NC3R   3.661 .083 44.273 ***
NC6R   3.914 .073 53.888 ***
Covariances: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Normative_Commitment <--> Affective_Commitment .397 .065 6.080 *** 
Affective_Commitment <--> Continuance_Commitment -.349 .081 -4.315 *** 
Normative_Commitment <--> Continuance_Commitment .021 .052 .399 .690 
e8 <--> e9 .336 .073 4.577 *** 
e21 <--> e22 -.140 .051 -2.746 .006 
Correlations: (Group number 1 - Default model) 
   Estimate 
Normative_Commitment <--> Affective_Commitment .748 
Affective_Commitment <--> Continuance_Commitment -.404 
Normative_Commitment <--> Continuance_Commitment .037 
 185
   Estimate 
e8 <--> e9 .467 
e21 <--> e22 -.253 
Variances: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Affective_Commitment   .807 .119 6.790 ***
Continuance_Commitment   .926 .159 5.825 ***
Normative_Commitment   .349 .073 4.813 ***
e19   49.050 5.538 8.857 ***
e20   518.134 61.127 8.476 ***
e18   .327 .074 4.397 ***
e17   .010    
e1   .365 .042 8.684 ***
e2   .161 .022 7.177 ***
e3   .192 .027 7.212 ***
e4   .138 .020 6.908 ***
e5   .383 .044 8.677 ***
e6   .586 .086 6.811 ***
e7   .625 .087 7.154 ***
e8   .643 .084 7.628 ***
e9   .806 .098 8.215 ***
e10   .618 .083 7.490 ***
e16   .514 .061 8.396 ***
e21   .383 .051 7.585 ***
e22   .797 .100 8.002 ***
e23   .721 .086 8.350 ***
e24   .466 .060 7.780 ***
 
Model Fit Summary 
CMIN 
Model NPAR CMIN DF P CMIN/DF 
Default model 67 227.951 122 .000 1.868 
Saturated model 189 .000 0   
Independence model 18 2232.144 171 .000 13.053 
Baseline Comparisons 
 186
Model 
NFI
Delta1 
RFI
rho1 
IFI
Delta2 
TLI
rho2 
CFI 
Default model .898 .857 .950 .928 .949 
Saturated model 1.000  1.000  1.000 
Independence model .000 .000 .000 .000 .000 
Parsimony-Adjusted Measures 
Model PRATIO PNFI PCFI 
Default model .713 .641 .677 
Saturated model .000 .000 .000 
Independence model 1.000 .000 .000 
NCP 
Model NCP LO 90 HI 90 
Default model 105.951 67.304 152.418 
Saturated model .000 .000 .000 
Independence model 2061.144 1912.366 2217.303 
FMIN 
Model FMIN F0 LO 90 HI 90 
Default model 1.273 .592 .376 .851 
Saturated model .000 .000 .000 .000 
Independence model 12.470 11.515 10.684 12.387 
RMSEA 
Model RMSEA LO 90 HI 90 PCLOSE 
Default model .070 .056 .084 .013 
Independence model .259 .250 .269 .000 
AIC 
Model AIC BCC BIC CAIC 
Default model 361.951 377.863   
Saturated model 378.000 422.888   
Independence model 2268.144 2272.419   
ECVI 
Model ECVI LO 90 HI 90 MECVI 
Default model 2.022 1.806 2.282 2.111 
 187
Model ECVI LO 90 HI 90 MECVI 
Saturated model 2.112 2.112 2.112 2.363 
Independence model 12.671 11.840 13.544 12.695 
HOELTER 
Model 
HOELTER
.05 
HOELTER
.01 
Default model 117 127 
Independence model 17 18 
 188
Appendix Q:  SEM Results for an Exploratory Modification of Model 2
 189
Affective
Commitment
AC1
e1
.
8
3
AC2
e2
.
9
3
AC3R
e3
.9
3
AC4
e4
.
9
4
AC5R
e5
.
8
3
Continuance
Commitment
CC1
e6
CC2
e7
CC3
e8
CC4
e9
CC6
e10
.
7
8
.
7
6
.7
2
.
6
4
.
7
4
Normative
Commitment
Leader
Satisfaction
SATQT
e16
.
6
6
SATQLT
e17
.
9
9
e18
BEHAVIOR
e20
NC1
e21
.
6
8
NC4
e22
.
6
4
NC3R
e23
.
6
5
NC6R
e24
.
7
1
-.28
-
.
1
0
.2
6
.1
4
-
.
0
3
.
4
8
.4
1
.75
-.40
.46
-.2
5
.04
 
 
Maximum Likelihood Estimates 
Regression Weights: (Group number 1 - Default model) 
   Estimate S.E. C.R. P Label 
BEHAVIOR <--- Continuance_Commitment -.619 1.562 -.396 .692  
BEHAVIOR <--- Affective_Commitment 10.239 2.754 3.718 ***  
BEHAVIOR <--- Normative_Commitment 13.388 4.242 3.156 .002  
Leader_Satisfaction <--- Normative_Commitment -.301 .256 -1.173 .241  
Leader_Satisfaction <--- Continuance_Commitment -.063 .091 -.688 .491  
Leader_Satisfaction <--- Affective_Commitment .177 .156 1.132 .258  
Leader_Satisfaction <--- BEHAVIOR .004 .005 .846 .397  
AC1 <--- Affective_Commitment 1.000    
AC2 <--- Affective_Commitment 1.126 .067 16.864 ***  
AC3R <--- Affective_Commitment 1.205 .072 16.713 *** 
AC4 <--- Affective_Commitment 1.095 .064 17.032 ***  
AC5R <--- Affective_Commitment 1.029 .074 13.932 *** 
CC1 <--- Continuance_Commitment 1.000     
 190
   Estimate S.E. C.R. P Label 
CC2 <--- Continuance_Commitment .968 .098 9.829 ***  
CC3 <--- Continuance_Commitment .869 .094 9.292 *** 
CC4 <--- Continuance_Commitment .779 .096 8.144 ***  
CC6 <--- Continuance_Commitment .889 .094 9.498 *** 
SATQT <--- Leader_Satisfaction 1.000     
SATQLT <--- Leader_Satisfaction 1.572 .152 10.313 *** 
NC1 <--- Normative_Commitment 1.000     
NC4 <--- Normative_Commitment 1.263 .190 6.652 *** 
NC3R <--- Normative_Commitment 1.236 .164 7.515 ***  
NC6R <--- Normative_Commitment 1.189 .147 8.098 *** 
 
Standardized Regression Weights: (Group number 1 - Default model) 
   Estimate 
BEHAVIOR <--- Continuance_Commitment -.031 
BEHAVIOR <--- Affective_Commitment .481 
BEHAVIOR <--- Normative_Commitment .407 
Leader_Satisfaction <--- Normative_Commitment -.281 
Leader_Satisfaction <--- Continuance_Commitment -.096 
Leader_Satisfaction <--- Affective_Commitment .256 
Leader_Satisfaction <--- BEHAVIOR .138 
AC1 <--- Affective_Commitment .833 
AC2 <--- Affective_Commitment .930 
AC3R <--- Affective_Commitment .927 
AC4 <--- Affective_Commitment .935 
AC5R <--- Affective_Commitment .833 
CC1 <--- Continuance_Commitment .779 
CC2 <--- Continuance_Commitment .760 
CC3 <--- Continuance_Commitment .722 
CC4 <--- Continuance_Commitment .641 
CC6 <--- Continuance_Commitment .736 
SATQT <--- Leader_Satisfaction .656 
SATQLT <--- Leader_Satisfaction .995 
NC1 <--- Normative_Commitment .680 
NC4 <--- Normative_Commitment .637 
NC3R <--- Normative_Commitment .651 
NC6R <--- Normative_Commitment .715 
Intercepts: (Group number 1 - Default model) 
   Estimate S.E. C.R. P Label 
 191
   Estimate S.E. C.R. P Label 
BEHAVIOR   69.108 1.438 48.061 ***  
AC1   3.817 .081 47.169 ***  
AC2   3.767 .082 46.197 ***  
AC3R   3.763 .088 42.919 ***  
AC4   3.744 .079 47.438 ***  
AC5R   3.606 .083 43.340 ***  
CC1   2.767 .092 30.101 ***  
CC2   2.956 .091 32.428 ***  
CC3   2.750 .086 31.880 ***  
CC4   2.856 .087 32.798 ***  
CC6   3.099 .087 35.727 ***  
SATQT   3.727 .375 9.948 ***  
SATQLT   3.346 .580 5.774 ***  
NC1   3.978 .064 62.167 ***  
NC4   3.350 .086 38.758 ***  
NC3R   3.661 .083 44.273 ***  
NC6R   3.914 .073 53.880 ***  
Covariances: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Normative_Commitment <--> Affective_Commitment .391 .065 6.036 *** 
Affective_Commitment <--> Continuance_Commitment -.348 .081 -4.299 *** 
Normative_Commitment <--> Continuance_Commitment .023 .051 .458 .647 
e8 <--> e9 .331 .073 4.511 *** 
e21 <--> e22 -.137 .051 -2.710 .007 
Correlations: (Group number 1 - Default model) 
   Estimate 
Normative_Commitment <--> Affective_Commitment .746 
Affective_Commitment <--> Continuance_Commitment -.402 
Normative_Commitment <--> Continuance_Commitment .042 
e8 <--> e9 .463 
e21 <--> e22 -.246 
Variances: (Group number 1 - Default model) 
   Estimate S.E. C.R. P 
Affective_Commitment   .812 .119 6.821 ***
Continuance_Commitment   .919 .159 5.785 ***
Normative_Commitment   .339 .072 4.741 ***
e20   110.304 13.933 7.916 ***
e18   .354 .081 4.381 ***
 192
   Estimate S.E. C.R. P 
e17   .010   
e1   .359 .042 8.648 ***
e2   .161 .023 7.108 ***
e3   .193 .027 7.171 ***
e4   .139 .020 6.874 ***
e5   .378 .044 8.643 ***
e6   .594 .087 6.837 ***
e7   .627 .088 7.139 ***
e8   .638 .084 7.579 ***
e9   .799 .098 8.173 ***
e10   .616 .083 7.454 ***
e16   .515 .061 8.396 ***
e21   .394 .051 7.744 ***
e22   .791 .098 8.042 ***
e23   .706 .085 8.316 ***
e24   .459 .059 7.769 ***
 
Model Fit Summary 
CMIN 
Model NPAR CMIN DF P CMIN/DF 
Default model 61 200.618 109 .000 1.841 
Saturated model 170 .000 0   
Independence model 17 2112.502 153 .000 13.807 
Baseline Comparisons 
Model 
NFI 
Delta1 
RFI 
rho1 
IFI 
Delta2 
TLI 
rho2 
CFI 
Default model .905 .867 .954 .934 .953 
Saturated model 1.000  1.000  1.000 
Independence model .000 .000 .000 .000 .000 
Parsimony-Adjusted Measures 
Model PRATIO PNFI PCFI 
Default model .712 .645 .679 
Saturated model .000 .000 .000 
Independence model 1.000 .000 .000 
NCP 
Model NCP LO 90 HI 90 
 193
Model NCP LO 90 HI 90 
Default model 91.618 55.713 135.353 
Saturated model .000 .000 .000 
Independence model 1959.502 1814.709 2111.680 
FMIN 
Model FMIN F0 LO 90 HI 90 
Default model 1.121 .512 .311 .756 
Saturated model .000 .000 .000 .000 
Independence model 11.802 10.947 10.138 11.797 
RMSEA 
Model RMSEA LO 90 HI 90 PCLOSE 
Default model .069 .053 .083 .023 
Independence model .267 .257 .278 .000 
AIC 
Model AIC BCC BIC CAIC 
Default model 322.618 336.258   
Saturated model 340.000 378.012   
Independence model 2146.502 2150.303   
ECVI 
Model ECVI LO 90 HI 90 MECVI 
Default model 1.802 1.602 2.047 1.879 
Saturated model 1.899 1.899 1.899 2.112 
Independence model 11.992 11.183 12.842 12.013 
HOELTER 
Model 
HOELTER
.05 
HOELTER
.01 
Default model 120 131 
Independence model 16 17 
 
 194