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A STUDY ON INDIVIDUAL READINESS FOR ORGANIZATIONAL CHANGE
by
MYUNGWEON CHOI
(Under the Direction of Wendy E. A. Ruona)
ABSTRACT
The purpose of this study was to examine the conditions that foster individual readiness
for organizational change. Three research questions guided this study: (1) What is the
relationship between the change strategy perceived by those responding to a planned change and
their readiness for change? (2) What is the relationship between the learning culture perceived by
those responding to a planned change and their readiness for change? (3) How does the impact of
the change on individuals’ jobs affect the two relationships presented in the first two research
questions? To answer these research questions, this study employed a survey research design.
Quantitative survey data were collected in a healthcare organization in the Southeastern region of
the United States.
Concerning the role of change strategies, statistical analysis of the survey data supported
the arguments that (1) the power-coercive change strategy has negative effects on individual
readiness for change and that (2) both the normative-reeducative change strategy and the
empirical-rational change strategy have positive effects on readiness for change. Further data
analysis revealed that (3) the normative-reeducative change strategy is not able to mitigate the
negative effects of the power-coercive change strategy on individual readiness for change and
that (4) the empirical-rational change strategy needs to be combined with the normative-
reeducative change strategy to further increase individual readiness for change. Second,
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regarding the role of learning culture, the analysis results supported the arguments that (5) the
learning culture can promote an environment in which individuals tend to be more ready for
change and that (6) the learning culture can create conditions in which the normative-reeducative
change strategy is effective in fostering readiness for change. Finally, the results showed that (7)
at times of a change that has a huge impact on individuals’ jobs, the normative-reeducative
change strategy and learning culture become more effective in shaping individual readiness for
change. Additional analysis on the relative importance among the study variables revealed that (8)
change strategies are the most important set of variables in understanding individual readiness
for change, followed by the elements of learning culture.
INDEX WORDS: Readiness for Change, Change Strategies, Learning Culture, Human Resource
Development, Organization Development
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A STUDY ON INDIVIDUAL READINESS FOR ORGANIZATIONAL CHANGE
by
MYUNGWEON CHOI
B.A., Seoul National University, Korea 2000
M.A., Seoul National University, Korea 2002
A Dissertation Submitted to the Graduate Faculty of The University of Georgia
in Partial Fulfillment of the Requirements for the Degree
DOCTOR OF PHILOSOPHY
ATHENS, GEORGIA
2011
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© 2011
Myungweon Choi
All Rights Reserved
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A STUDY ON INDIVIDUAL READINESS FOR ORGANIZATIONAL CHANGE
by
MYUNGWEON CHOI
Major Professor: Wendy E. A. Ruona
Committee: Laura L. Bierema
Khalil Dirani
Lillian T. Eby
Karen E. Watkins
Electronic Version Approved:
Maureen Grasso
Dean of the Graduate School
The University of Georgia
May 2011
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ACKNOWLEDGEMENTS
First of all, I’d like to thank my advisor, Dr. Wendy Ruona, for all the things she has
done for me and my study. I know that this dissertation study would not have been possible
without her advice, guidance, support, and care. Having her as my advisor was the best thing that
happened to me during my doctoral studies. She was, and still is, the perfect advisor for me and
will be a great scholarly partner of mine all through my academic life.
I also deeply appreciate what my dissertation committee members did for me and for this
study. I thank Dr. Laura Bierema for her insightful questions and encouragements, Dr. Lillian
Eby and Dr. Khalil Dirani for their advice on data analysis, and Dr. Karen Watkins for her deep
insights on my study framework. It was a great honor and an enjoyable experience for me to
have these great scholars on my dissertation committee.
I would like to thank my colleagues in the Department of Lifelong Education,
Administration, and Policy at the University of Georgia. They were my friends and mentors.
With their friendship, I felt less lonely during this journey. Also, I thank many people I met at
the University of Georgia. In particular, I owe a lot to Dr. Karen Braxley who corrected my
English for the last five years. Her patience, caring personality, and intelligence helped me
become a better writer.
Last but not least, I extend my deepest appreciation to my family. My father, who I
believe is still around me and takes care of me all the time, and my mom, who shows me what
unconditional love for a daughter means, gave me the strength to complete this journey. My
sister always inspired me and gave me confidence in myself. My family gave me more than I can
describe with words and sentences. I hope there will be a way to return them the care, love, and
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support I received from them and let them feel what I feel now.
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TABLE OF CONTENTS
Page
ACKNOWLEDGEMENTS………………………………………………………………………iv
LIST OF TABLES………….…...……………….…………………………………………….…ix
LIST OF FIGURES………….……………..…….……………………………………………...xii
CHAPTER
1. INTRODUCTION………….…………………………………………………………..1
Readiness for Change…………………………………………………………………..3
Framework for Understanding the Conditions for High Levels of Readiness for
Change……………...…………………...…………...………………………………...5
Two Approaches to Organizational Change and Their Impact on Readiness for
Change……………………………………...…………...……………………………..7
Statement of the Problem…………...………...………………………………………11
Purpose of the Study…………………………...……………………………………..13
Significance of Study…………….……………...……………………………………13
2. REVIEW OF THE LITERATURE……………..……...……………………………..16
Readiness for Change………………..………………………………………………..16
Change Strategies of Planned Organizational Changes…………...……………...…..34
Organizational Learning Culture…………….………………………...……………..68
Individual Job Level Impact of Change…………...……………………………...…..89
Summary of the Chapter…………………………...………..………………………..96
3. RESEARCH DESIGN AND METHODS…………………….......…………………100
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Design of the Study………………...………………………………………………..100
Key Variables and Conceptual Framework……………...…...……………………..102
Instrumentation…………………..………………………...………………………..106
Sample Selection…………………..………….……………………………………..111
Data Collection…………………….………………………………………………..115
Data Preparation and Data Screening…………………...…………………………..116
Reliability and Validity…………………………….………………………………..122
Data Analysis……………..…………......…………………………………………..131
Delimitations of the Study……………….…………………...……………………..136
Summary of the Chapter…………………..………...…..…………………………..137
4. RESULTS………….....................…………..………………….....…………………138
Descriptive Statistics and Preliminary Analyses…………………..…...………...…138
Research Question 1: Change Strategies and Readiness for Change………..………141
Research Question 2: Learning Culture and Readiness for Change……………...…157
Research Question 3: Change Impact and Readiness for Change…..………………173
Comparing the Importance of Change Strategies, Learning Culture, and Change
Impact…………………………….……………...…………………………………..189
Summary of the Chapter…………………………………...………………………..195
5. CONCLUSION……...…………………...…………………………………………..197
Summary of the Findings…………...……………………...………………………..197
Discussion of the Findings…………………………………………………………..203
Implications for Research……………………………..……………...……………..210
Implications for Practice………………………………………………...…………..217
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Limitations of the Study…………………………………...……………….………..220
Suggestions for Future Research………………………...…………………………..224
Summary of the Chapter………………………………………...…………………..226
REFERENCES……………………..…………………………………………………………..227
APPENDIX
A. Informed Consent and Questionnaire……………………………………………….257
B. Recruiting Letter…………………..………………………..……………………….269
C. Measurement Models……………………..……….…………………..…………….272
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LIST OF TABLES
Page
Table 2.1: Comparison of the Constructs………………………...…………….………………..27
Table 2.2: Definitions of Readiness for Change……………………..…………………………..29
Table 2.3: Examples of Strategies of Each Group in Chin and Benne’s (1985) Typology……...41
Table 2.4: Key Characteristics of the Change Models……………………………...…………...53
Table 2.5: Definitions of Organizational Culture………………………………………………..70
Table 2.6: Definitions of Organizational Learning……………………………………………....75
Table 3.1: Overview of the Survey Instrument……………………………………..…………..110
Table 3.2: Multicollinearity Diagnostics for Independent Variables…….……………………..119
Table 3.3: Tests of Normality of Residuals…………………………...………………………..120
Table 3.4: Demographic Information of the Respondents.…………………..…..……….…….121
Table 3.5: Reliability Estimates of the Measures………………………………………………124
Table 3.6: Fit Indices and Cut-Off Values…………………...…………………………………126
Table 3.7: Fit Indices for the Measurement Models……………………………………………131
Table 4.1: Descriptive Statistics and Intercorrelations between Study Variables………...……139
Table 4.2: Partial Correlations between Change Strategies and Readiness for Change…….…142
Table 4.3: Readiness for Change Regressed on Change Strategies………………….…………143
Table 4.4: Relative Importance of Change Strategies: Overall Readiness for Change…...……146
Table 4.5: Relative Importance of Change Strategies: Change-Specific Efficacy (R1).….……146
Table 4.6: Relative Importance of Change Strategies: Appropriateness of the Change (R2).…147
Table 4.7: Relative Importance of Change Strategies: Management Support for the Change
(R3)…….….………………………………………….……………………………147
Table 4.8: Relative Importance of Change Strategies: Personal Benefit of the Change (R4)….148
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Table 4.9: Relative Importance of Change Strategies: Dominance Matrices….….….….….….149
Table 4.10: Moderating Effect of NR on the relationship between PC and Readiness for
Change……………………………………………………………………………152
Table 4.11: Moderating Effect of NR on the Relationship between ER and Readiness for
Change…………….………………...……………………………………………154
Table 4.12: Partial Correlations between Learning Culture and Readiness for Change……….158
Table 4.13: Readiness for Change Regressed on Overall Learning Culture………...…………160
Table 4.14: Moderating Effect of Overall Learning Culture on the Relationship between NR and
Readiness for Change………………………………….…………………………162
Table 4.15: Moderating Effect of Creating Continuous Learning Opportunities (LC1) on the
Relationship between NR and Readiness for Change………………....…………163
Table 4.16: Moderating Effect of Promoting Inquiry and Dialogue (LC2) on the Relationship
between NR and Readiness for Change………………………….………………164
Table 4.17: Moderating Effect of Encouraging Collaboration and Team Learning (LC3) on the
Relationship between NR and Readiness for Change……………....……………165
Table 4.18: Moderating Effect of Empowering People toward a Collective Vision (LC4) on the
Relationship between NR and Readiness for Change……………………………166
Table 4.19: Moderating Effect of Establishing Systems to Capture and Share Learning (LC5) on
the Relationship between NR and Readiness for Change………………..………167
Table 4.20: Moderating Effect of Connecting the Organization to Its Environment (LC6) on the
Relationship between NR and Readiness for Change…………………....………168
Table 4.21: Moderating Effect of Providing Strategic Leadership for Learning (LC7) on the
Relationship between NR and Readiness for Change………………..……..……169
Table 4.22: Partial Correlations between Change Impact and Readiness for Change…….……174
Table 4.23: Readiness for Change Regressed on Change Impact…………………...…………175
Table 4.24: Moderating Effect of Change Impact on the Relationship between NR and Readiness
for Change………………………..…………………….……………...…………178
Table 4.25: Moderating Effect of Change Impact on the Relationship between Overall Learning
Culture and Readiness for Change……..………..…………..…………...………179
Table 4.26: Moderating Effect of Change Impact on the Relationship between Creating
Continuous Learning Opportunities (LC1) and Readiness for Change……….…180
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Table 4.27: Moderating Effect of Change Impact on the Relationship between Promoting Inquiry
and Dialogue (LC2) and Readiness for Change…………..………...……………181
Table 4.28: Moderating Effect of Change Impact on the Relationship between Encouraging
Collaboration and Team Learning (LC3) and Readiness for Change……………182
Table 4.29: Moderating Effect of Change Impact on the Relationship between Empowering
People toward a Collective Vision (LC4) and Readiness for Change………...…183
Table 4.30: Moderating Effect of Change Impact on the Relationship between Establishing
Systems to Capture and Share Learning (LC5) and Readiness for Change..…….184
Table 4.31: Moderating Effect of Change Impact on the Relationship between Connecting the
Organization to Its Environment (LC6) and Readiness for Change………….….185
Table 4.32: Moderating Effect of Change Impact on the Relationship between Providing
Strategic Leadership for Learning (LC7) and Readiness for Change………..…..186
Table 4.33: Relative Importance of Study Variables: Overall Readiness for Change………….191
Table 4.34: Relative Importance of Study Variables: Change-Specific Efficacy (R1)……..….192
Table 4.35: Relative Importance of Study Variables: Appropriateness of the Change (R2)…...192
Table 4.36: Relative Importance of Study Variables: Management Support for the Change
(R3)……..………...………..……...………..……..………..………..………...…193
Table 4.37: Relative Importance of Study Variables: Personal Benefit of the Change
(R4)……….……….……….………….….……….……….………....……….….193
Table 4.38: Relative Importance of Study Variables: Dominance Matrices….…….………….195
Table 4.39: Summary of Tests on Hypotheses……………..………….…...……………..……196
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LIST OF FIGURES
Page
Figure 2.1: Normative-reeducative change strategies and individual readiness for organizational
change……..……………………………………………………...…………………67
Figure 3.1: Conceptual framework of the study…………..……………………...….…………106
Figure 4.1: Moderating effect of the normative-reeducative strategy (NR) on the relationship
between the power-coercive strategy (PC) and change-specific efficacy (R1)…....153
Figure 4.2: Moderating effect of the normative-reeducative strategy (NR) on the relationship
between the empirical-rational strategy (ER) and overall readiness for change…..155
Figure 4.3: Moderating effect of the normative-reeducative strategy (NR) on the relationship
between the empirical-rational strategy (ER) and change-specific efficacy (R1)....156
Figure 4.4: Moderating effect of the normative-reeducative strategy (NR) on the relationship
between the empirical rational strategy (ER) and appropriateness of the change
(R2)…………..…………………………..…………….………………...…...……156
Figure 4.5: Moderating effect of the normative-reeducative strategy (NR) on the relationship
between the empirical-rational strategy (ER) and management support for the change
(R3).……………………….…………..……...……..……...…………...…………156
Figure 4.6: Moderating effect of the normative-reeducative strategy (NR) on the relationship
between the empirical-rational strategy (ER) and personal benefit of the change
(R4).…..…………..…………..……...……………..……...……………..………..156
Figure 4.7: Moderating effect of overall learning culture on the relationship between the
normative-reeducative strategy (NR) and change-specific efficacy (R1)…………171
Figure 4.8: Moderating effect of creating continuous learning opportunities (LC1) on the
relationship between the normative-reeducative strategy (NR) and change-specific
efficacy (R1)……….…………..…………..……...………...…………..…………171
Figure 4.9: Moderating effect of promoting inquiry and dialogue (LC2) on the relationship
between the normative-reeducative strategy (NR) and change-specific efficacy
(R1)……….……………………………………………………………..…………171
Figure 4.10: Moderating effect of promoting inquiry and dialogue (LC2) on the relationship
between the normative-reeducative strategy (NR) and personal benefit of the
change (R4)……...………...………………………...………...…………………171
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Figure 4.11: Moderating effect of encouraging collaboration and team learning (LC3) on the
relationship between the normative-reeducative strategy (NR) and overall readiness
for change…...………...…....………...………………...………...………………172
Figure 4.12: Moderating effect of encouraging collaboration and team learning (LC3) on the
relationship between the normative-reeducative strategy (NR) and change-specific
efficacy (R1).....…....………...………………...………...…………….…………172
Figure 4.13: Moderating effect of empowering people toward a collective vision (LC4) on the
relationship between the normative-reeducative strategy (NR) and change-specific
efficacy (R1)..…....………...………………...………...…………….…...………172
Figure 4.14: Moderating effect of establishing systems to capture and share learning (LC5) on
the relationship between the normative-reeducative strategy (NR) and overall
readiness for change….…....………...……………………….……......…………172
Figure 4.15: Moderating effect of establishing systems to capture and share learning (LC5) on
the relationship between the normative-reeducative strategy (NR) and change-
specific efficacy (R1)…...………...……………………….……......……………173
Figure 4.16: Moderating effect of establishing systems to capture and share learning (LC5) on
the relationship between the normative-reeducative strategy (NR) and management
support for the change (R3)……………...……………….......……......…………173
Figure 4.17: Moderating effect of change impact (CI) on the relationship between the normative-
reeducative strategy (NR) and personal benefit of the change (R4)……..………187
Figure 4.18: Moderating effect of change impact (CI) on the relationship between overall
learning culture and personal benefit of the change (R4)…………………….….187
Figure 4.19: Moderating effect of change impact (CI) on the relationship between creating
continuous learning opportunities (LC1) and personal benefit of the change
(R4)….…...……………...………………….......……......………….......……......188
Figure 4.20: Moderating effect of change impact (CI) on the relationship between promoting
inquiry and dialogue (LC2) and personal benefit of the change (R4)……………188
Figure 4.21: Moderating effect of change impact (CI) on the relationship between establishing
systems to capture and share learning (LC5) and personal benefit of the change
(R4).…………………………………………………..………..…………………188
Figure 4.22: Moderating effect of change impact (CI) on the relationship between providing
strategic leadership for learning (LC7) and personal benefit of the change (R4)..188
Figure 6.1: CFA for change strategies…………….………………...…….……………………273
Figure 6.2: First-order CFA for the dimensions of a learning culture……….……....…………274
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Figure 6.3: First-order CFA for overall learning culture...….….…………...….………………275
Figure 6.4: Hierarchical CFA for a learning culture….….……………….....….………………276
Figure 6.5: First-order CFA for the dimensions of readiness for change………………………277
Figure 6.6: First-order CFA for overall readiness for change…………….…………….…...…278
Figure 6.7: Hierarchical CFA for readiness for change…….…………….……………...…..…279
Figure 6.8: CFA for change impact…….…………………………..……..………....…...….…280
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CHAPTER ONE
INTRODUCTION
One feature that characterizes contemporary organizations is change. Generally, change
is the way people talk about an event in which something appears to become, or turn into,
something else, where the something else is seen as a result or outcome (Ford & Ford, 1994). In
reference to organizations, change is defined somewhat differently depending on the perspectives
researchers take (Beer & Nohria, 2000b; Quinn, Kahn, & Mandl, 1994). For example,
researchers with the strategic management perspective regard organizational change as a process
of implementing corporate strategy made by organizational leaders and decision makers (Child,
1972; Dunphy, 2000). On the other hand, those who take the organizational development (OD)
perspective regard change as intentional efforts to make differences in the organizational work
setting for the purpose of enhancing individual development and improving organizational
performance (Porras & Robertson, 1992). These two perspectives are the most fundamental ones
in the organizational change literature (Beer & Nohria, 2000a, 2000b).
While the types or magnitude of change may be different (Burke, 2008; Van de Ven &
Poole, 1995; Weick & Quinn, 1999), it is now commonly accepted that all organizations are
under the influence of multiple changes. Furthermore, current scholars, especially the proponents
of complexity theories, have begun to view change as a condition of possibility for organizations
(S. L. Brown & Eisenhardt, 1997; Burnes, 2004a; Stacey, Griffiin, & Shaw, 2002; Styhre, 2002;
Tetenbaum, 1998). According to these scholars, change is not ―an exceptional effect, produced
only under specific circumstances by certain people‖ (Tsoukas & Chia, 2002, p. 569). Rather,
change is inherent in human action and necessarily occurs in a context of human social
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interactions (Ford & Ford, 1995). Considering that organizations are sites of continuously
evolving human action, it is no exaggeration to say that change is ―ontologically prior to
organization‖ (Tsoukas & Chia, 2002, p. 570). If we agree with this argument, we must conclude
that organizations are in a continuous state of change and, in order to survive, they must develop
the ability to continuously change themselves incrementally and, in many cases, in a
fundamental manner (Burnes, 2004b).
Organizational leaders are, thus, continually charged with introducing and implementing
various initiatives to change their organizations. However, in reality, many change efforts do not
result in their intended aims and do not foster sustained change. Specifically, researchers like
Burke and Biggart (1997) and Beer and Nohria (2000a, 2000b) estimated that about two-thirds of
change projects fail, and Burnes (2004c) suggested that the failure rate may be even higher. The
cause of many organizations’ inability to achieve the intended aims of their change efforts is
often considered as an implementation failure, rather than flaws innate in the change initiative
itself (K. J. Klein & Sorra, 1996). In particular, the failures are often attributed to the
organization’s inability to provide for an effective unfreezing process (Lewin, 1947/1997b)
before attempting a change induction (Kotter, 1995, 1996; Schein, 1987b, 1999b). Unfreezing in
the context of organizational change includes the process by which organizational members’
beliefs and attitudes about a change are altered so that they perceive the changes as both
necessary and likely to be successful. Generally, most organizational change models
acknowledge the importance of the unfreezing step through such phases as building momentum,
warm-up or defrosting activities, gaining buy-in to the change effort, or attitude training
(Armenakis, Harris, & Mossholder, 1993; Kotter, 1996; Schein, 1987b, 1999a).
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Readiness for Change
In response to the frequent failure of organizational change implementations, many
researchers have proposed frameworks to understand organizational change and analyze the
causes of failure. In the organizational change literature published during the 1990s, Armenakis
and Bedeian (1999) identified four major themes: change content, change context, change
process, and change criterion issues. As they explained, changes at the organizational level have
often been considered with a macro, systems-oriented focus (Judge, Thoresen, Pucik, &
Welbourne, 1999).
However, at the same time, a number of researchers have also adopted a micro-level
perspective on change and have put more emphasis on the role of individuals in implementing
changes (Armenakis et al., 1993; George & Jones, 2001; Greenhalgh, Robert, Macfarlane, Bate,
& Kyriakidou, 2004; Hall & Hord, 1987; Isabella, 1990; Lau & Woodman, 1995; Porras &
Robertson, 1992; Tetenbaum, 1998). The main idea underlying this approach is that ―change in
the individual organizational member’s behavior is at the core of organizational change‖ (Porras
& Robertson, 1992, p. 724). According to the researchers, organizations only change and act
through their members, and successful change will persist over the long term only when
individuals alter their on-the-job behaviors in appropriate ways (George & Jones, 2001; Porras &
Robertson, 1992). They also argue that many change efforts fail because change leaders often
underestimate the central role individuals play in the change process. To support the idea, these
researchers have empirically demonstrated that individuals are not passive recipients of
organizational change but actors who actively interpret and respond to what is happening in their
environments (Greenhalgh et al., 2004; Hall & Hord, 1987; Isabella, 1990; Lowstedt, 1993).
Furthermore, some recent research studies also have shown that employees’ attitudes toward
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organizational change influence their behavioral support for a change such that those who had
positive attitudes toward organizational change were more likely to change their behavior and
champion the change initiatives (e.g., Jones, Jimmieson, & Griffiths, 2005; J. P. Meyer, Srinivas,
Lal, & Topolnytsky, 2007). As evidenced by these studies, individuals’ attitudes toward
organizational change have real impact on change implementation and, therefore, are certainly
critical for any change initiatives to be successful.
Individual readiness for organizational change (henceforth, ―readiness for change‖),
which is the focus of this study, is increasingly important in this context. It has been defined as
the extent to which an individual believes that a change is needed and that he/she has the
capacity for the change. As previous researchers noted, readiness for change is conceptually
grounded in the unfreezing step of Lewin’s model (Armenakis et al., 1993; Eby, Adams, Russell,
& Gaby, 2000). Given that unfreezing in organizational change includes the process by which
organizational members’ beliefs and attitudes about a change are altered, readiness for change
can be understood as an indicator of the extent to which unfreezing is effectively achieved. In
this regard, just as unfreezing is important (Armenakis et al., 1993; Kotter, 1996; Schein, 1987b,
1999a), readiness for change is also critical to the success of change initiatives.
Even though readiness for change is an intuitively appealing construct, so far only a small
number of empirical studies have dealt with this phenomenon (e.g., C. E. Cunningham et al.,
2002; Eby et al., 2000; Hanpachern, Morgan, & Griego, 1998; Jones et al., 2005; Madsen, Miller,
& John, 2005; McNabb & Sepic, 1995; Weeks, Roberts, Chonko, & Jones, 2004). Moreover,
when assessing readiness for change, previous research studies tend to focus only on a single
aspect, such as perception of personal benefit from the change (Jones et al., 2005) or evaluation
of an organization’s capacity for making successful changes (Weeks et al., 2004). As a result,
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they have failed to capture the multifaceted nature of readiness for change. Considering the
importance of readiness for change, we still need more studies that investigate how to foster it in
organizations and that are conducted with measures which effectively capture the nature of the
construct of readiness for change.
Framework for Understanding the Conditions for High Levels of Readiness for Change
In order to examine the conditions under which employees can be more ready for change,
this study needs a framework illustrating the dimensions of organizational change the study
should focus on. Among the organizational models that explain organizational functioning and
performance (e.g., Burke & Litwin, 1992; Galbraith, 1977; Peters & Waterman, 1982), Pettigrew
and Whipp’s (1991) model offers a simple yet powerful framework for studying a phenomenon
in the context of organizational change. While developing their model of strategic change,
Pettigrew and Whipp maintained that organizational change is a complex, situation dependent,
and continuous process and must be understood in terms of process, context (both internal and
external), and content. Specifically, change process is described as the ―how‖ of change and
refers to actions and interactions of the various stakeholders as they negotiate proposals for
change. Change context is about the ―why and when‖ of change. External context refers to facts
such as prevailing economic circumstances and social and political environments, while internal
context is concerned with internal influences such as resources, capabilities, structure, culture,
and politics. Finally, change content is defined as the ―what‖ of change and is concerned with the
areas of transformation. As Armenakis and Bedeian (1999) summarized in their literature review,
researchers of organizational change usually focus on any of the three dimensions as their key
areas of interest.
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With a few exceptions (e.g., Devos, Buelens, & Bouckenooghe, 2007; Self, Armenakis,
& Schraeder, 2007), researchers have rarely assessed the three aspects simultaneously as they
relate to organizational change and tend to focus on a single dimension in each study (e.g.,
Wanberg & Banas, 2000; Wanous, Reichers, & Austin, 2000). However, given the
interconnectedness among the dimensions is critical, this tendency can be problematic. As
Pettigrew and Whipp (1991) emphasized, just as every single dimension is important in
understanding organizational change, the interaction between change process, context, and
content is also important. Therefore, in order to have a comprehensive picture of the conditions
that foster readiness for change, the three dimensions need to be examined simultaneously.
As a framework for understanding the conditions for fostering individual readiness for
organizational change, the three core dimensions can be better represented in terms of how they
are seen or experienced by individuals. Aspects of a change initiative are likely to have
significantly different impact for different work groups throughout the organization and,
ultimately, different implications for individuals within these groups (Judge et al., 1999; Lau &
Woodman, 1995; Mohrman, Mohrman, & Ledford, 1989). Therefore, it can be argued that
individuals’ reactions to change are expected to be based on their experience of the more
immediate change situation, rather than on the master plan established by the leaders or on the
label attached to the initiative. Furthermore, researchers have shown that individuals may hold
different perceptions even when they are within the same organizational context and experience
the same objective reality (Spreitzer, 1996, 2007) and that individual employees’ behaviors and
attitudes are determined more by their perceptions of reality than by objective reality (Rentsch,
1990; Spreitzer, 1996). Therefore, in studies dealing with individual attitudinal constructs like
readiness for change, the three core dimensions of change—change process, change context, and
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change content—need to be defined and assessed in terms of the way individuals perceive and
evaluate them.
Two Approaches to Organizational Change and Their Impact on Readiness for Change
As mentioned above, change process, change context, and change content need to be
examined in order to understand the conditions that foster readiness for change. The approaches
that leaders and agents of an organization take to implement change directly affect change
process, change context, and change content in the organization. Specifically, as Beer and Nohria
(2000a, 2000b) illustrate, if leaders of an organization assume that people are social and active in
nature and believe in the value of developing individual and organizational capabilities in
attaining the organization’s goal, they are more likely to focus on developing corporate culture
and human capability through individual and organizational learning. When it comes to
organizational change, these leaders emphasize the process of changing, obtaining feedback,
reflecting on the feedback, and making further changes. On the other hand, if leaders of an
organization assume that people are passive and complacent and have a singular focus on
maximizing immediate value, they are likely to take top-down, structure-focused, programmatic,
and knowledge-driven approaches to organizational change. In this regard, depending on the
approaches used, change process, change context, and change content in an organization will
take different forms and, consequently, will have different implications for individual readiness
for change.
In order to differentiate approaches to organizational change, this study will distinguish
between OD approaches and strategic management approaches. What follows is a brief
description of the two approaches and a discussion on their effectiveness in fostering readiness
for change.
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OD Approaches to Organizational Change
In the OD tradition, the aims of organizational change efforts are regarded as a deliberate
decision to increase an organization’s effectiveness and capability to change itself (Cummings &
Worley, 2005). In this perspective, organizational change initiatives usually take participative
and emergent forms. Also, they are process-driven and culture-focused (Beer & Nohria, 2000b).
In OD approaches, the change process is mainly based on normative-reeducative
strategies among the Chin and Benne’s (1985) typology of change strategies. As will be
illustrated in Chapter Two, normative-reeducative strategies assume that people are inherently
active and social and that, if organizational changes are to occur, individual members should not
only undergo rational informational processing, but should also reconsider their attitudes, values,
normative orientations, institutionalized roles and relationships, and cognitive and perceptual
orientations (Chin & Benne, 1985; Quinn & Sonenshein, 2008). As changes in these non-
cognitive determinants of behavior are possible only through mutual persuasion within
collaborative relationships, the organizational change procedures should involve collaboration
between change agents and organizational members. Therefore, under these assumptions,
employee participation is both an ethical imperative and a key source of energy for change
(Burnes, 2004b; Dunphy, 2000; Sashkin, 1986).
In addition, in OD approaches, the development of individual and organizational
capabilities is highly valued and considered to be the source of sustainable competitive
advantage (Senge, 2000). Therefore, organizations with a strong orientation to OD approaches
tend to emphasize the learning culture—a set of shared beliefs and values (Schein, 2004)
supporting organizational learning. These organizations facilitate organizational learning through
various institutionalized practices, such as creating continuous learning opportunities, promoting
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inquiry and dialogue, and encouraging collaboration and team learning (Lundberg, 1995;
Watkins & Marsick, 1993).
Strategic Management Approaches to Organizational Change
Strategic management approaches define organizational change as a process of
implementing corporate strategy (Dunphy, 2000). Under this view, CEOs and the top executive
team are seen to have the perspective, knowledge, and power to reposition the organization
strategically to take advantage of its dynamic environment, while other employees are seen as a
potential source of error, inadequacy, and special interest pleading (Conger, 2000; Dunphy,
2000). Therefore, to ensure that a change initiative generated by the top team is not subverted, it
is vital that other organizational members ―faithfully carry out the initiatives generated from the
top of the organization‖ (Dunphy, 2000, p. 126). Consequently, the change process is driven by a
small group of people with the leadership roles, and they must apply directive and coercive
actions to force change recipients to comply with the proposed change goals (Huy, 2001). The
stress on managerial control of the change process (Dunphy, 2000) is mainly based on power-
coercive strategies (Chin & Benne, 1985) which emphasize political, economic, and moral
sanctions for lack of compliance with a proposed change. It is also based on empirical-rational
strategies (Chin & Benne, 1985) which assume that people will follow their rational self-interest
once it is revealed to them. Strategic management approaches put much emphasis on formal
organizational arrangements and managerial levers like structure and systems since they can
readily be changed from the top down to yield quick results (Beer & Nohria, 2000b; Galbraith,
2000). Also, the approaches are characterized by prescient and comprehensive planning before
the initiation of change, motivating people through financial incentives, and heavy reliance on
external consultants to analyze problems and shape solutions (Beer & Nohria, 2000a, 2000b).
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Impact of Approaches to Change on Readiness for Change
As briefly reviewed above, change process, change context, and change content take
different forms depending on the approaches used. In particular, concerning the change process,
what distinguishes between OD approaches and strategic management approaches is the change
strategies adopted by organizations. Also, when it comes to the change context, the two
approaches differ in their emphases on a learning culture.
Organizational change can be understood as a situation that interrupts the normal patterns
of an organization (Ford, Ford, & D'Amelio, 2008). During the change, individuals are involved
in information seeking, meaning ascription, and assumption making about the change process in
order to make sense of the new environment and to draw conclusions about its possible outcomes
(Ford et al., 2008; Gioia, Thomas, Clark, & Chittipeddi, 1994). This includes extracting
particular behaviors and communications specific to the organizational change, interpreting them,
and acting on the resulting interpretation (Ford et al., 2008). In this respect, different change
strategies used by leaders or agents of an organization can influence readiness for change in
different ways, either by facilitating individuals’ learning of new attitudes, values, and norms
required in the new environment or by hindering individuals from adapting to them.
Furthermore, in an organization with a strong learning culture, individual and
organizational learning is facilitated through institutionalized practice (Lundberg, 1995; Watkins
& Marsick, 1993). Also, by developing individual and organizational capabilities, a learning
culture enhances organizational capacity to make successful changes. Therefore, employees in an
organization with a strong learning culture may have higher capabilities to implement change
and, at the same time, may have formed impressions that the organization can thrive under
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changing organizational conditions. Consequently, individuals in such an organization are likely
to have higher levels of readiness for change.
In addition, change strategies and the learning culture may have different influences on
readiness for change depending on the content of change. The content of change is usually
understood in terms of change type or substance. However, in studies dealing with individual
attitudinal constructs like readiness for change, the content of a specific change can be best
represented by the impact the change has on individuals’ jobs, rather than by the organizational
level initiative itself. As researchers have suggested (e.g., Caldwell, Herold, & Fedor, 2004;
Fedor, Caldwell, & Herold, 2006), the impact a change has on individuals’ jobs provide a
context within which organizational factors contribute to shaping individuals’ reactions to the
change. For example, in a situation where a change initiative accompanies huge impact on an
individual’s job, the influence of a certain change strategy on individual readiness for change can
increase. Likewise, in such a situation, a learning culture may be even more critical in fostering
readiness for change. Therefore, in investigating the roles of change strategies and a learning
culture in fostering readiness for change, we also need to examine the impact a change has on
individuals’ jobs.
Statement of the Problem
While there are many reasons why change fails, many researchers are focusing on the
organizations’ inability to provide for an effective unfreezing process before attempting a change
induction (Kotter, 1995, 1996; Schein, 1987b, 1999b). Readiness for change, which is
conceptually grounded in the unfreezing step of Lewin’s model, is critical to the success of
change initiatives. Even though readiness for change is an intuitively appealing construct, so far
only a small number of empirical studies have dealt with this phenomenon (e.g., Eby et al., 2000;
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Jones et al., 2005; Madsen et al., 2005). Considering the importance of readiness for change, we
need more studies that investigate how to foster it in organizations.
How can we understand the conditions where employees can be more ready for change?
As a framework for understanding these conditions, this study adopts Pettigrew and Whipp’s
(1991) model of organizational change. The model stresses that three dimensions of
organizational change—change process, change context, and change content—are critical in
understanding any change efforts. To overcome the limitations of previous studies which have
focused only on a single dimension and to gain a more comprehensive understanding of
organizational change, this study will examine change process, change context, and change
content simultaneously.
Depending on the approaches that leaders and agents of an organization take, the
dimensions can take different forms and, consequently, will have different implications for
individual readiness for change. This study distinguishes between OD approaches and strategic
management approaches, which are two primary archetypes of change implementation (Beer &
Nohria, 2000a, 2000b). As is briefly reviewed above, concerning the change process, what
distinguishes between OD approaches and strategic management approaches is the change
strategies adopted by organizations. Different change strategies can influence readiness for
change in different ways, either by facilitating individuals’ learning of new attitudes, values, and
norms required in the new environment or by hindering individuals from adapting to them. In
addition, when it comes to the change context, the two approaches differ in their emphases on the
learning culture. An organization with a strong emphasis on the learning culture develops
individual and organizational capabilities through institutionalized practices (Lundberg, 1995;
Watkins & Marsick, 1993) and, consequently, is likely to foster readiness for change. In light of
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the discussion thus far, this study will focus on change strategies and a learning culture and
examine how they influence readiness for change.
Furthermore, depending on the content of change, change strategies and the learning
culture may have different influences on readiness for change. Following the previous
researchers (e.g., Lau & Woodman, 1995; Novelli, Kirkman, & Shapiro, 1995), this study
assumes that the content of a specific change experienced by individuals can be better
represented by the impact the change has on individuals’ jobs, rather than by the labels attached
to change initiatives at the organizational level. Based on the assumption, this study will examine
how change strategies and the learning culture have different influences on readiness for change
depending on the impact a change has on individuals’ jobs.
Purpose of the Study
The purpose of this study was to examine the conditions that foster readiness for change.
The research questions guiding this study were as follows:
1. What is the relationship between the change strategy perceived by those responding
to a planned change and their readiness for change?
2. What is the relationship between the learning culture perceived by those responding
to a planned change and their readiness for change?
3. How does the impact of the change on individuals’ jobs affect the two relationships
presented in the first two research questions?
Significance of Study
The goal of OD is to bring about planned organizational change, which is a ―conscious,
deliberate, and intended‖ (Chin & Benne, 1985, p. 22) decision to increase an organization’s
effectiveness and capability to change itself (Cummings & Worley, 2005). As McLagan (1989)
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depicted with the Human Resources (HR) wheel, which specifies the core components of HR
function in organizations, OD and organizational change are within legitimate realm of Human
Resource Development (HRD) in improving individual, group, and organizational effectiveness.
Furthermore, it is increasingly understood that the HRD process is required to be more strategic
from both inside and outside of its profession (Christensen, 2006; Gilley & Maycunich, 2002;
Ruona & Gibson, 2004; Torraco & Swanson, 1995; Ulrich & Brockbank, 2005). Consequently,
HRD must concern itself with efforts which potentially add value to the organization and,
therefore, embrace the topic of OD and organizational change. Supporting this argument, Ruona
and Gibson (2004) illustrate using examples from real organizational settings that Human
Resource Management (HRM), HRD, and OD are increasingly required to coordinate, partner,
and think innovatively about how they are related and how their works impact organizations in
order to contribute to organizations strategically. In this respect, understanding the conditions for
successful organizational change is a valid and important topic to advance the field of HRD, and
HRD has important insights to contribute to the knowledge around OD and change.
As a number of influential contemporary theorists contend in the book Creaking the Code
of Change (Beer & Nohria, 2000c), both OD approaches and strategic management approaches
to organizational change have their own validity. However, in reality, while strategic
management approaches to change are very popular among corporate leaders, OD approaches
are relatively neglected and regarded as less important (Beer & Nohria, 2000a). As researchers in
the OD field assert, this tendency causes such costs as losing organizational capabilities,
particularly the capability of employees to become involved in identifying and solving work-
related problems, and the partnership, trust, and commitment which are vital for long-term
performance improvements and sustained change (Bennis, 2000; Senge, 2000; Weick, 2000).
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This study is an effort to explore the effectiveness of OD approaches to organizational
change. Specifically, this study focuses on the following two key features of OD as the
conditions that are expected to foster individual readiness for change: (1) OD approaches to
change implementation which are based on the normative-reeducative change strategies (Burke,
2008; Chin & Benne, 1985) and (2) OD approaches as an ongoing organizational effort to
enhance organizational health and capability through fostering organizational learning culture
(Watkins & Golembiewski, 1995). By showing the effectiveness of OD approaches to change
implementation in fostering readiness for change, this study produces evidence of whether OD
approaches to organizational change increase the likelihood of successful organizational changes.
In addition, by examining the relationship between a learning culture and readiness for change,
this study also demonstrates whether ongoing OD efforts to foster the learning culture in
organizations help to enhance organizational change efforts. The findings of this study can
broaden our understanding of how OD approaches can contribute to increasing the ability of
organizations to make successful changes.
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CHAPTER TWO
REVIEW OF THE LITERATURE
This chapter aims to make connections between multiple bodies of literature and
knowledge bases and, ultimately, to make claims concerning the three research questions posited
in Chapter One. Specifically, this chapter includes four major sections. The first section is a
review of the literature on readiness for change. Readiness for change will be defined and its
implications will be discussed. In the second section, I will review the literature on change
strategies. The effectiveness of different change strategies will be discussed in terms of their
influence on readiness for change. The third section will focus on organizational learning culture.
Specifically, based on a review of the literature on organizational culture, organizational learning,
and the learning organization, the way organizational learning culture can foster readiness for
change will be discussed. Lastly, the fourth section will focus on how change strategies and the
learning culture have different influences on readiness for change depending on the impact of
change experienced by individuals. In each section, based on the literature review and discussion,
hypotheses regarding the conditions for fostering readiness for change are proposed.
Readiness for Change
Traditionally, employees’ attitudes toward organizational change have been
conceptualized as ―resistance to change.‖ In addition, these attitudes have tended to be regarded
as an obstacle employees present to change initiatives and as something that must be overcome.
However, the traditional view on employees’ attitudes toward organizational change has been
challenged. In this section, based on a critical review of the traditional view, I will propose the
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use of another construct, readiness for change, and discuss its implications for organizational
change research.
Interest in the Role of Individuals in Organizational Change
Studies on organizational change have traditionally taken a macro-approach. For example,
in a review of change literature, Quinn, Kahn, and Mandl (1994) noted that research in the field
of organizational change and development has evolved from four major paradigms: OD, strategic
choice, resource dependence-institutional theory, and population ecology. Similarly, in the
organizational change literature published during the 1990s, Armenakis and Bedeian (1999)
identified four major themes: change content, change context, change process, and change
criterion issues. As these two seminal articles suggest, changes at the organizational level have
often been considered with a macro, systems-oriented focus (Judge et al., 1999).
However, at the same time, a number of researchers have also adopted a micro-level
perspective on change and have put more emphasis on the role of individuals in implementing
changes (Armenakis et al., 1993; George & Jones, 2001; Greenhalgh et al., 2004; Hall & Hord,
1987; Isabella, 1990; Lau & Woodman, 1995; Lowstedt, 1993; Porras & Robertson, 1992;
Tetenbaum, 1998). The main idea underlying this approach is that ―change in the individual
organizational member’s behavior is at the core of organizational change‖ (Porras & Robertson,
1992, p. 724). According to the researchers, organizations only change and act through their
members, and successful change will persist over the long term only when employees alter their
on-the-job behaviors in appropriate ways (George & Jones, 2001; Porras & Robertson, 1992).
They also argue that many change efforts fail because change leaders often underestimate the
central role individuals play in the change process.
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To support the idea, these researchers have empirically demonstrated that individual
employees are not passive recipients of the organizational level change but actors who actively
interpret and respond to what is happening in their environments. For example, based on in-depth
interviews within an organization going through a change, Isabella (1990) showed that
organizational members construe key events linked to the process of change as unfolding in four
distinctive stages: anticipation, confirmation, culmination, and aftermath. Similarly, Hall and
Hord (1987) showed that, when faced with change, people develop concerns of varying intensity
across stages—awareness, informational, personal, management, consequences, collaboration,
and refocusing—at different points in the change process. As this line of studies has shown,
individuals make assumptions about change processes, evaluate them, find meaning in them, and
develop feelings about them. These studies are meaningful in that they not only identify the
construed reality of each interpretive stage, but also describe processes that impel change
recipients between stages as change occurs (Armenakis & Bedeian, 1999).
Furthermore, some recent research studies have also shown that employees’ attitudes
toward organizational change influence their behavioral support for a change (C. E. Cunningham
et al., 2002; Jones et al., 2005; J. P. Meyer et al., 2007; Weeks et al., 2004). For example, by
using a temporal research design, Jones et al.’s (2005) study showed that the employees who had
demonstrated a higher level of readiness for change in the early stage of a change
implementation were more likely to change their behaviors to support a change initiative in the
post-implementation stage. Similarly, Meyer et al. (2007) showed that employees’ normative and
affective commitment to change were positively related to supportive behaviors such as
cooperation and championing. The findings show that employees’ attitudes toward
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organizational change have real impact on change implementation and, therefore, are certainly
critical for any organizational change to be successful.
Challenges to the Concept of Resistance to Change
Traditionally, individuals’ attitudes toward organizational change have often been
conceptualized as resistance to change, which has long been considered as a barrier to
organizational change attempts (Dent & Goldberg, 1999a; Jermier, Knights, & Nord, 1994).
However, some recent researchers have begun to criticize the prevalent view on resistance and
suggest a need for a more multifaceted perspective on employees’ attitudes toward
organizational change. In the following sub-sections, I will review the three most researched
topics on this issue: the positive aspect of resistance, the situational causes of resistance, and
resistance created by change agents.
Positive Aspect of Resistance
Resistance to change has been viewed as an obstacle employees present to change
initiatives and as something that must be overcome. What is implicit in this view is that
management is right and employees are wrong when it comes to change.
However, some researchers have argued that employees’ reactions to change are not
necessarily dysfunctional obstacles or liabilities to successful change. Rather, according to the
researchers, resistance can raise awareness and add momentum for change (Ford et al., 2008),
provide a feedback mechanism vital to the change process (D. Klein, 1985), and serve as a
source of information for developing more effective change efforts (Knowles & Linn, 2004;
Piderit, 2000; Waddell & Sohal, 1998). From this point of view, resistance to change can serve
as an asset and a resource in the implementation and successful accomplishment of change, and
we need to carefully examine it, rather than take it as given or ignore it.
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Situational Causes of Resistance
As Knowles and Linn (2004) noted, depending on the context, the source of
psychological resistance can be attributed either to the person or to the situation. Organizational
researchers showed that resistance in the context of organizational change is more often
attributed to the situation than to the person. For example, Kotter (1995) showed that employees
often understand the new vision and want to make it happen when organizations attempt a major
change. However, according to him, obstacles to change often reside in the organization’s
structure or in its system—for example, performance evaluation, compensation, succession
planning which are not aligned with the desired new behavior—and, thus, forces people to
―choose between the new vision and their own self-interest‖ (Kotter, 1995, p. 64). At least two
lines of research have supported the idea that resistance in the context of organizational change is
often attributed to the situation specific to a change.
Some researchers stress that resistance to change comes from experiencing lack of choice
(i.e. the imposition of change) or being forced to move to some new state of being and acting
(Burke, 2008). The concept of reactance helps to explain this human phenomenon. Psychological
reactance theory says that when a person senses that someone else is limiting his or her freedom
to choose or act, an uncomfortable state of reactance arises, creating motivation to reassert that
freedom (Brehm & Brehm, 1981). The more important the freedoms threatened and the more
arbitrary (i.e. not legitimate), blatant, direct, and demanding the threats, the greater the reactance
will be (Fuegen & Brehm, 2004; Knowles & Linn, 2004). In sum, according to these researchers,
individuals are not simply and naturally resistant to change—rather, they resist the imposition of
change, or the way change is imposed on them.
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In addition, empirical studies on various constructs related to employees’ attitudes toward
organizational change, such as readiness for change (e.g., Eby et al., 2000), commitment to
change (e.g., Herscovitch & Meyer, 2002), openness to change (e.g., Wanberg & Banas, 2000),
and cynicism about organizational change (e.g., Wanous et al., 2000), have shown that the
constructs are influenced by various factors that are specific to a given situation. In particular,
researchers reported that contextual factors—for example, justice perception (Bernerth,
Armenakis, Feild, & Walker, 2007; Caldwell et al., 2004; Fedor et al., 2006), participation in
change process (M. Brown & Cregan, 2008; Devos et al., 2007; Reichers, Wanous, & Austin,
1997; Wanberg & Banas, 2000; Wanous et al., 2000), information sharing (M. Brown & Cregan,
2008; Wanberg & Banas, 2000), trust in management (Devos et al., 2007), and experience with
previous change projects (Devos et al., 2007; Wanous et al., 2000)—greatly influence the
attitudinal reactions to organizational change. As the findings show, employees’ attitudes toward
organizational change are not a personality-based predisposition. Rather, they are a learned
response, shaped by the specific context.
Resistance Created by Change Agents
Some researchers with a social constructionist viewpoint challenge the idea that
resistance represents objective phenomena which exist independent of change agents. Rather,
they contend that change agents create resistance by expecting resistance (Dent & Goldberg,
1999a; Ford et al., 2008; Ford, Ford, & McNamara, 2002). According to them, change is a
situation that requires both change agents and change recipients to engage in sensemaking
(Weick, 1995). In this situation, change agents try to determine ―how will this get accomplished?‖
while change recipients try to determine ―what will happen to me?‖ (Ford et al., 2008; Gioia et
al., 1994). If change agents expect that resistance to change is natural and inevitable, then a self-
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fulfilling prophecy may emerge. By shaping the very phenomenon to which they are paying
attention, change agents’ expectation predisposes them to look for resistance and to make sense
of others’ actions in such a way as to confirm their expectation, thereby sustaining the received
truth that employees resist change (Dent & Goldberg, 1999a; Ford et al., 2008). In sum, if
change agents go into a change expecting resistance, they are likely to find it since their actions
to overcome the assumed resistance can lead to the appearance of the very resistance they hope
to avoid.
Reevaluation of the Concept of Resistance
Kurt Lewin’s idea of resistance is helpful for us to reevaluate the common use of the term
resistance to change and reconceptualize employees’ attitudes toward organizational change.
Lewin (1947/1997b) conceived resistance as a restraining force moving in the direction of
maintaining the status quo. In this respect, his conception of resistance is a systemic phenomenon
rather than an individual predisposition. However, since Lewin’s conceptualization, resistance
has come to be seen largely as a psychological phenomenon located ―over there‖ in change
recipients and is often used to justify organizations’ failings by blaming individuals for the
unsatisfactory results of change efforts (Dent & Goldberg, 1999a, 1999b; Ford et al., 2008; Ford
et al., 2002; Krantz, 1999; Maurer, 2006). In this respect, it is not an exaggeration to say that
leaders or agents of an organization have been assigning resistance because of a desire to provide
themselves with greater degrees of freedom in the ways they deal with change recipients.
Furthermore, as Piderit (2000) noted, by simply labeling their response as resistance, we can
easily dismiss potentially valid individual concerns about a proposed change.
As I elaborated thus far, resistance is not a personality-based predisposition. When
confronted with the possibility of change, most of us are likely to be ambivalent (Burke, 2008;
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Piderit, 2000), and our attitudes are shaped based on the contextual factors specific to a given
situation. These attitudes may contain rich information concerning the change implementation.
Furthermore, recent research even urges us to reconsider the role change agents play in creating
the resistance. Therefore, it is necessary for us to shift our attention to the overall system of
change and to make a more valid conceptualization of employees’ attitudes toward change.
Reconceptualizing Employees’ Attitudes toward Organizational Change
After reviewing the criticism of the traditional view of resistance to change, the following
question arose: Is there another way to understand employees’ attitudes toward organizational
change? While the tenets of resistance to change have been challenged, some researchers have
begun stressing other constructs such as readiness for change (e.g., Eby et al., 2000),
commitment to change (e.g., Herscovitch & Meyer, 2002), openness to change (e.g., Wanberg &
Banas, 2000), and cynicism about organizational change (e.g., Wanous et al., 2000). This study
focuses on one of these constructs, readiness for change, as it is comprehensive and captures
Lewin’s (1947/1997b) idea of unfreezing well. In the following sub-sections, readiness for
change will be defined and its implications for organizational change research will be discussed.
Lewin’s Idea of the Unfreezing Step
According to Lewin (1947/1997b), a particular set of behaviors is the result of two
groups of forces: those striving to maintain the status quo and those pushing for change. When
both sets of forces are equal, current behaviors are maintained in a state he called quasi-
stationary equilibrium supported by a large force field of driving and restraining forces. To
change the behaviors (i.e., to discard an old behavior and to adopt a new behavior successfully),
one needs to unfreeze the equilibrium between the two sets of forces, either by increasing the
forces pushing for change and/or by decreasing those forces maintaining the current state.
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Building on Lewin’s idea of unfreezing, Schein (1996/1999a) identified three processes
necessary to achieve unfreezing: disconfirmation of the validity of the status quo, the induction
of survival anxiety, and the creation of psychological safety. Disconfirmation functions as a
primary driving force and is a prerequisite for adaptation to new environmental circumstances or
for creative and generative learning. However, we can ignore the disconfirming information or
deny its validity, unless it arouses survival anxiety—the feeling that if we do not change, we will
fail to meet our needs or fail to achieve some goals or ideals that we have set for ourselves. In
addition, creating psychological safety is even more critical in that ―unless sufficient
psychological safety is created, the disconfirming information will be denied or in other ways
defended against, no survival anxiety will be felt, and consequently, no change will take place‖
(Schein, 1999a, p. 61). In fact, the goals of various activities for change management lie in the
various kinds of tactics that change agents employ to create psychological safety (Schein, 1999a).
In sum, in order to unfreeze the equilibrium, it is necessary to balance the amount of threat
produced by disconfirming data with enough psychological safety to allow the change recipient
to accept the information, feel the survival anxiety, and become motivated to change. Through
the processes, organizational members’ beliefs and attitudes about a change can be altered, and
they may perceive the changes as necessary and likely to be successful (Armenakis et al., 1993).
While Lewin (1947/1997b) thought that all three steps of unfreezing, moving, and
refreezing were critical to a successful change project, the reason why so many change efforts
fail is often attributed to the organizations’ inability to provide for an effective unfreezing
process before attempting a change induction (Kotter, 1995, 1996; Schein, 1987b, 1999b). In fact,
most organizational change models suggest that phases such as building momentum, warm-up or
defrosting activities, or gaining buy-in to the change effort (Armenakis et al., 1993; Kotter, 1996;
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Schein, 1987b, 1999a), which ultimately aim to increase driving forces and/or decrease
restraining forces, are critical components for any successful change initiative.
Unfreezing Step and Employees’ Attitudes toward Organizational Change
Attitude refers to a person’s overall evaluation of persons, objects, and issues. More
specifically, it refers to how favorably or unfavorably or how positively or negatively in general
one views some object of judgment (Petty & Wegener, 1998). Therefore, attitudes toward an
organizational change can be defined as an individual’s overall favorable/positive or
unfavorable/negative evaluative judgment of a change initiative implemented by an organization
(Lines, 2005).
As is widely acknowledged, it is important to separate general attitudes from specific
attitudes (Fisher, 1980). In organizations, a person may have a general attitude toward change
but at the same time possess different attitudes about particular changes. While the former may
be more directed by personality, the latter tends to be determined largely by the context (Katz &
Kahn, 1978; Lau & Woodman, 1995). In other words, even though a person is supportive of and
open to organizational changes in general, his/her attitudes about a specific change being
undertaken may vary depending on how he/she evaluates the contexts and the issues involved.
As Schein (1996/1999a) explained in his model of unfreezing, employees will form their
attitudes toward a change based on the disconfirming information, survival anxiety, and
psychological safety created in a situation specific to the change. In this respect, individuals’
attitudes toward a specific organization change can be a measure to assess how effectively an
organization has achieved the unfreezing process.
Recently, researchers have proposed several constructs reflecting this notion of
unfreezing, including commitment to change, openness to change, cynicism about organizational
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change, and readiness for change. Commitment to change is defined as ―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, p. 475). Openness to change has been defined as both
willingness to support the change and positive affect about the potential consequences of change
(Miller, Johnson, & Grau, 1994; Wanberg & Banas, 2000). Researchers define cynicism about
organizational change as ―a pessimistic viewpoint about change efforts being successful because
those responsible for making changes are blamed for being unmotivated, incompetent, or both‖
(Wanous et al., 2000, p. 133). Lastly, readiness for change is defined as organizational members’
belief in the organization’s capacity for making a successful change, the extent to which the
change is needed, and the benefits the organization as well as its members can gain from the
change (Armenakis et al., 1993). Table 2.1 shows the often-cited definition and focuses of each
of the constructs. These constructs are similar in that they all reflect an individual’s overall
positive or negative evaluative judgment of a specific change initiative. In addition, they are
defined as the cognitive precursor to the behavioral support for a change effort.
Despite their commonalities, however, these four constructs focus on slightly different
aspects of individuals’ attitudes toward organizational change and differ in the range of
phenomena they capture. For example, the construct of commitment to change is defined as ―a
mind-set,‖ but the definition does not show specific facets that determine the mind-set. Also,
cynicism about organizational change focuses particularly on management support for a change.
Among the constructs, readiness for change is the most comprehensive in that it captures various
aspects of individuals’ attitudes toward organizational change, including their belief in the
change-specific efficacy, appropriateness of a change, management support for a change, and
personal benefit from a change. Therefore, this study focuses on readiness for change.
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Table 2.1
Comparison of the Constructs
Construct Definition Focus of concept
Commitment
to 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; J. P. Meyer
et al., 2007)
Belief in the inherent benefits of the
change
Sense of obligation to provide
support for the change
Recognition of the costs associated
with failure to support the change
Openness to
change Willingness to support the change and
positive affect about the potential
consequences of change (Miller et al.,
1994; Wanberg & Banas, 2000)
The extent to which individuals are
looking forward to changes in their
work role
The extent to which individuals
expect the change to be for the better
particularly in relation to how they
do their job
Cynicism
about
organizational
change
A pessimistic viewpoint about change
efforts being successful because those
responsible for making changes are
blamed for being unmotivated,
incompetent, or both (Bernerth et al.,
2007; Bommer, Rich, & Rubin, 2005;
Reichers et al., 1997; Wanous et al.,
2000)
Pessimism about future change
being successful or futile
Blaming those responsible—usually
management—for one’s pessimism
Readiness for
change Evaluation of the individual and
organizational capacity for making a
successful change, the need for a change,
and the benefits the organization and its
members can gain from a change
(Armenakis et al., 1993; Holt, Armenakis,
Feild, & Harris, 2007)
Change-specific efficacy
Appropriateness of the change
Management support for the change
Personal benefit of the change
Defining Readiness for Change
Initially, studies on readiness were published primarily in the health and medical
literature (e.g., Block & Keller, 1998; Joe, Simpson, & Broome, 1998; Morera et al., 1998;
Prochaska, Redding, & Evers, 1997). These studies usually focused on ceasing harmful health
behaviors such as smoking and drug abuse and starting positive ones such as exercise, weight
management, and eating nutritional meals. Readiness in this context is concerned with the extent
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to which an individual perceives a change as needed and whether he/she has the capacity for the
change.
Although readiness is an individual-level construct, it requires a consideration of the
organizational context when the concept is applied to the organizational settings (Jansen, 2000).
Organizational change is a situation that interrupts the normal patterns of an organization. In the
situation, in order to make sense of the new environment and to draw conclusions about its
possible outcomes, individuals try to determine ―what will happen to me?‖ by being actively
involved in information seeking, meaning ascription, and assumption making about the change
process (Ford et al., 2008; Gioia et al., 1994). As a result, individuals form assumptions,
expectations, and impressions about the change, which comprise readiness for change in the
organizational change context.
As Table 2.2 shows, researchers have defined individual readiness for organizational
change in slightly different ways. For example, Armenakis et al. (1993) and Jansen (2000)
defined the concept in terms of the necessity of a specific change initiative and the organizational
capacity to implement it successfully. Similarly, Eby et al. (2000) contended that individual
readiness for organizational change is about the belief that the changes are ―both necessary and
likely to be successful‖ (p. 422). On the other hand, Jones et al. (2005) also emphasized
employees’ belief in the benefits from the change. Nevertheless, the researchers all agree that
individual readiness for organizational change involves an individual’s evaluation of the
individual and organizational capacity for making a successful change, the need for a change,
and the benefits the organization and its members may gain from a change (Armenakis et al.,
1993; Eby et al., 2000; Holt et al., 2007; Jansen, 2000).
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Table 2.2
Definitions of Readiness for Change
Source Definition
Armenakis et al. (1993) Organizational members’ beliefs, attitudes, and intentions regarding the
extent to which changes are needed and the organization’s capacity to
successfully make those changes. The cognitive precursor to the behaviors of
either resistance to, or support for, a change effort
Eby et al. (2000) An individual’s perception of the extent to which the organization is
perceived to be ready to take on large-scale change
Jansen (2000) An organization’s capacity for making change and the extent to which
individuals perceive the change as needed
Jones et al. (2005) The extent to which employees hold positive views about the need for
organizational change, as well as the extent to which employees believe that
such changes are likely to have positive implications for themselves and the
wider organization
Holt et al. (2007) The extent to which employees believe that (a) they are capable of
implementing a proposed change (change-specific efficacy), (b) the
proposed change is appropriate for the organization (appropriateness), (c) the
leaders are committed to the proposed change (management support), and
(d) the proposed change is beneficial to organizational members (personal
benefit)
Recently, through a scale development study, Holt et al. (2007) more clearly defined the
concept as a multifaceted construct with four dimensions: individuals’ belief in the change-
specific efficacy, appropriateness of the change, management support for the change, and
personal benefit of the change. Since Holt et al. proposed the most comprehensive
conceptualization of the construct of readiness for change, their definition of readiness for
change is used in this study.
As is widely acknowledged, it is important to separate general attitudes from specific
attitudes (Eagly & Chaiken, 1993; Fisher, 1980; Katz & Kahn, 1978). In an organization, a
person may have a general attitude toward change but, at the same time, the person can possess
different attitudes about particular change initiatives. While the former may depend more on
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personal needs and values, the latter is determined largely by one’s experience within the
organizational context (Katz & Kahn, 1978; Lau & Woodman, 1995). For example, even though
a person is supportive of organizational change in general, his/her attitudes about a specific
change initiative being undertaken may vary depending on how he/she evaluates the issues
involved in the change implementation. Readiness for change, as defined and used in this study,
should be understood as attitudes about a specific change, not as general attitudes toward change.
The definitions summarized in Table 2.2, especially those of Armenakis and Bedeian (1999),
Jansen (2000), and Holt et al., clearly show that the construct is directed at a specific change
initiative and has been conceptualized as attitudes toward a specific change.
As the definitions summarized in Table 2.2 indicate, individual readiness for
organizational change as is defined in this study is clearly an individual level concept.
Individuals in the same unit may have similar readiness for organizational change; however, we
cannot assume the similarity of readiness among the people at any level above that of the
individual (Dean, Brandes, & Dharwadkar, 1998). In this respect, individual readiness for
organizational change is conceptually distinct from organizational readiness for change, defined
and assessed in terms of an organization’s key infrastructure. For example, Preskill and Torres
(1999a, 1999b, 2001) defined organizational readiness in terms of key elements of organizational
infrastructure—culture, leadership, communication, and systems and structures—and argued that
these elements form the foundation based on which efforts for organizational learning can be
undertaken and sustained. As Preskill and Torres elaborated, the concept of organizational
readiness focuses on organizational infrastructure. Similarly, individuals’ evaluation concerning
how organizational infrastructure can facilitate and sustain organizational change efforts is a key
component of individual readiness for change (Armenakis et al., 1993; Eby et al., 2000; Holt et
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al., 2007; Jansen, 2000). In addition, other individual-level concerns, including the change-
specific efficacy and personal benefit of the change (Holt et al., 2007; Jones et al., 2005), are
critical for individuals to be ready for a specific organizational change initiative.
Research on Readiness for Change
The idea underlying the concept of readiness for change can be found in the previous
literature. As some researchers have noted, the definitions of readiness for change are
conceptually similar to Lewin’s (1947/1997b) notion of the unfreezing step (Armenakis et al.,
1993; Eby et al., 2000). The unfreezing step in the organizational change context includes the
process by which organizational members’ attitudes about a change initiative are altered in a way
that they perceive the change as necessary and likely to be successful. In this respect, when
individuals become ready for a change initiative, this indicates that the unfreezing step has been
successful.
In a similar vein, Rogers (1983, 2003) also endorsed the importance of readiness for
change through the innovation-decision process model. According to the model, individuals
develop a favorable or unfavorable attitude toward an innovation in the persuasion stage based
on the prior conditions (previous practice, felt needs/problems, innovativeness, norms of the
social systems) as well as on the knowledge they gained through the previous stage (knowledge
stage). Rogers stressed that individuals’ attitudes toward an innovation formed in the persuasion
stage affect the decision, implementation, and confirmation of the adoption of an innovation. By
explaining the formation of individuals’ attitudes toward an innovation and emphasizing their
role in innovation adoption, Rogers’ model also supports the importance and relevance of
individual readiness in the context of organizational change.
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In addition, in the concern-based adoption model, Hall and Hord (1987) also dealt with
the core ideas of individual readiness for organizational change. The main premise underlying
this model is that a change initiative can be more successful if the concerns of those affected by
it are considered. Concerns in their model are defined as ―the composite representation of the
feelings, preoccupation, thought, and consideration given to a particular issue or task‖ (Hall &
Hord, 1987, p. 59) and develop through the stages including awareness, informational, personal,
and consequence. These stages of concerns in Hall and Hord’s model are similar to the
components of the concept of individual readiness for change summarized in Table 2.2.
Some researchers have conducted empirical studies on individual readiness for
organizational change. The studies were usually concerned with the factors that contribute to
increasing the level of readiness for change. Specifically, the studies showed that employees’
belief in organizational ability to accommodate changing situations (Eby et al., 2000; Jones et al.,
2005), policies supporting change (Eby et al., 2000; McNabb & Sepic, 1995; Rafferty & Simons,
2006), social relationships within the division (Hanpachern et al., 1998; Jones et al., 2005;
Madsen et al., 2005), trust in peers and leaders (Rafferty & Simons, 2006), and participation at
work (Eby et al., 2000; Jones et al., 2005) could increase individual readiness for organizational
change. In addition, individual-level variables such as change self-efficacy (C. E. Cunningham et
al., 2002; Kwahk & Lee, 2008; Rafferty & Simons, 2006), organizational commitment (Kwahk
& Kim, 2008; Kwahk & Lee, 2008; Madsen et al., 2005), perceived personal competence
(Kwahk & Kim, 2008), and job satisfaction (McNabb & Sepic, 1995) were reported to increase
individual readiness for change. The studies also showed that job characteristics such as high
decision latitude and control over challenging tasks (C. E. Cunningham et al., 2002) would
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increase readiness for change. As the studies illustrated, readiness for change is shaped by
various contextual factors in a given situation.
Furthermore, some longitudinal studies showed that readiness for change actually
increased support for or participation in change implementation. For example, Cunningham et al.
(2002) showed that employees with higher scores of readiness for change at the early stage of a
change initiative actually participated in more activities at later stages than those with lower
scores. Similarly, Jones et al. (2005) showed that employees who reported higher levels of
readiness for change at the pre-implementation stage actually contributed more to the success of
change implementation at the implementation and post-implementation stages.
In sum, the findings reviewed above show that individual readiness for organizational
change is shaped by situational variables. For example, the more employees regard the
organization as having the ability to accommodate changing situations and the more they trust
peers and leaders, the more likely they are to be ready for a change initiative. As individual
readiness for organizational change is based on specific organizational experiences, it is likely to
change over time as individuals’ experiences change. In this respect, the concept of individual
readiness for change can be better conceptualized as states, rather than personality traits.
Summary of the Section on Readiness for Change
Readiness for change in the organizational change context involves individuals’ belief in
the individual and organizational capacity for making a successful change, the need for a change,
and the benefits the organization and its members can gain from a change (Armenakis & Bedeian,
1999; Armenakis et al., 1993; Eby et al., 2000; Holt et al., 2007; Jansen, 2000). The use of the
construct of individual readiness for organizational change gives us advantages over the common
use of resistance to change. Often, resistance to change is viewed as ―a reactive process where
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agents embedded in power relations actively oppose initiatives by other agents‖ (Jermier et al.,
1994, p. 9). By using the term, leaders and change agents commonly fail to notice the potentially
positive intentions that may motivate negative responses to change. On the other hand, the
concept of readiness for change assumes that individuals’ concerns over change are natural and
there must be reasons for the concerns. Furthermore, it is also assumed that change can be more
successful if the concerns of change recipients are considered. In this respect, the concept of
readiness for change helps us pay attention to the situational causes of such concerns—for
example, individuals’ perception of poor management support for and a lack of organizational
capability to cope with a specific change initiative (Eby et al., 2000; Holt et al., 2007).
Furthermore, research studies have shown that employees with higher levels of readiness for
change are more likely to support the proposed change and commit to its implementation (C. E.
Cunningham et al., 2002; Jones et al., 2005; J. P. Meyer et al., 2007; Weeks et al., 2004). In this
regard, readiness for change is a more valid and useful concept for understanding employees’
attitudes toward organizational change than resistance to change.
In the following sections, the conditions to foster readiness for change will be reviewed.
As discussed in Chapter One, when examining the conditions, I will focus on change strategies,
the learning culture, and the individual job level impact of change.
Change Strategies of Planned Organizational Changes
Based on Beer and Nohria’s (2000a, 2000b) idea that there are distinct archetypes of
change implementation, this study distinguishes between OD approaches and strategic
management approaches to change, which are based on quite different change strategies. In this
section, I will review the change strategies underlying the two groups of approaches. In addition,
I will discuss the implications of different change strategies for readiness for change.
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To understand change strategies and their implications, we first need to understand what
change models and change strategies mean. Simply put, change models prescribe the major
procedures that should be carried out to implement change. In this regard, actual change
implementation is directly related to change models. On the other hand, change strategies, which
underlie change models, are foundations that allow us to understand and compare change models.
Organizational researchers have long been interested in theories of changing (Bennis,
1966), which explain what must be done and in what general order, to trigger changes in
organizations. Porras and Robertson (1992) categorized theories of changing into two types:
procedure theories and strategy theories. By outlining the actual procedures and major steps that
should be carried out, procedure theories provide recommendations for how best to implement
change (e.g., Burke, 1994; Cummings & Worley, 2005; Kotter, 1996; Schein, 1987b). On the
other hand, strategy theories focus on broad strategies for implementing change and provide
general guidance for change activities (e.g., Beer & Nohria, 2000a, 2000b; Chin & Benne, 1985;
Hornstein, Bunker, Burke, Gindes, & Lewicki, 1971; Quinn & Sonenshein, 2008; Rajagopalan &
Spreitzer, 1997). They also provide methods for categorizing approaches to change or activities
that change agents might use to bring about change (Porras & Robertson, 1992).
The distinction between change models and change strategies in this study is based on
Porras and Robertson’s (1992) idea of strategy theories and procedure theories. As mentioned
above, change models provide specific descriptions of the major procedures and steps that should
be carried out to implement change. In this respect, procedure theories that are concerned with
the actual implementation of change in organizations (Porras & Robertson, 1992) deal with
change models. On the other hand, change strategies represent different archetypes of change
based on different assumptions about why and how changes should be made and, therefore, are
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concerned with strategy theories (Porras & Robertson, 1992). Thus, as strategy theories provide
methods for categorizing approaches to change, change strategies can be a foundation for
understanding and comparing the underlying assumptions of change models. In order to set the
framework to compare representative change models, I will review change strategies in the
following sub-section. Specifically, Chin and Benne’s (1985) work, which was first published in
1961, is reviewed as it provides the most comprehensive and integrative grounds for
understanding approaches to change and change strategies (Burke, 2008; Quinn & Sonenshein,
2008; Szabla, 2007). Additionally, based on that understanding, the key principles of change
models commonly used in organizational settings are reviewed and compared.
Chin and Benne’s Typology of Change Strategies
Following Burke (2008), this study defines change strategies as the way ―change is
implemented‖ (p. 158). As implementation means ―the process of gaining targeted employees’
appropriate and committed use of an innovation‖ (K. J. Klein & Sorra, 1996, p. 1055), change
strategies can be understood as the process of gaining change recipients’ support for and
commitment to a change.
Many researchers have used various terms to describe and define different strategies for
change implementation in organizations. For example, Greiner (1967) used the distinctions
between unilateral action, sharing of power, and delegated authority. Similarly, Zaltman and
Duncan (1977) contrasted facilitative, persuasive, reeducative, and power strategies, and Dunphy
and Stace (1988) contrasted participation and coercion strategies for change. Among this line of
works, Chin and Benne’s work (1985) is considered the most comprehensive and integrative one
(Burke, 2008; Quinn & Sonenshein, 2008; Szabla, 2007). Based on the sociological and
psychological roots of strategies of planned change, Chin and Benne (1985) classified the
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strategies into three categories: empirical-rational, power-coercive, and normative-reeducative.
What follows is a brief review of the three categories of change strategies.
Empirical-Rational Change Strategies
The fundamental assumptions underlying empirical-rational change strategies are that
people are rational and that they will follow their rational self-interest once it is revealed to them.
Therefore, under these assumptions an organization member will adopt a proposed change if it
can be rationally justified and if it can be shown that he or she will gain by the change (Chin &
Benne, 1985). Also, as ignorance is assumed to block change, scientific investigation, research,
and education to disseminate knowledge are regarded as the chief ways of facilitating changes.
While there are variations in this group of strategies, typically experts, either internal or
external to the client system, are contracted to analyze the system with the goal of making it
more efficient. Change agents, often aided by experts, try to modify change recipients’ behaviors
with reason and logic. The main strategies of this group include dissemination of knowledge
through general education, personnel selection and replacement, and employing systems analysts
as consultants, to name a few (Chin & Benne, 1985). In addition, other tactics and strategies such
as persuasion with reasoning (Zaltman & Duncan, 1977), negotiation (Kotter & Schlesinger,
1979), exchange (Falbe & Yukl, 1992), presenting the benefits of change (Nutt, 1996), rational
appeals of experts (Nutt, 1998; Yukl & Falbe, 1990), engineering intervention (Huy, 2001),
education and communication (Kotter & Schlesinger, 1979), and telling strategy (Quinn &
Sonenshein, 2008) are also based on empirical-rational approaches.
Normative-Reeducative Change Strategies
Like empirical-rational strategies, normative-reeducative strategies assume that people
are rationally self-interested. However, at the same time, these strategies also assume that people
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are inherently social—they conform to and are committed to socially funded and communicated
meanings, norms, and institutions (Chin & Benne, 1985). Therefore, if organizational changes
are to occur, individual members not only need to undergo rational informational processing but
also should reconsider their attitudes, values, normative orientations, institutionalized roles and
relationships, and cognitive and perceptual orientations (Chin & Benne, 1985; Quinn &
Sonenshein, 2008). As changes in these non-cognitive determinants of behavior need to be
exercised through mutual persuasion within collaborative relationships, change processes
required in this group of strategies are fundamentally different from transmitting information or
exercising force. Under this view, as Lewin (1947/1997b) emphasized, change occurs only when
individuals participate in their own reeducation (Chin & Benne, 1985). In addition, the
proponents of normative-reeducative strategies also assume that participation is essential for
building the partnership, trust, and commitment that are thought to be vital for long-term
performance improvements (Bennis, 2000).
Normative-reeducative strategies have the following features in common (Chin & Benne,
1985): all emphasize the client system and its involvement in the change process; the problem
confronting the client system is assumed to lie in the attitudes, values, norms, and the external
and internal relationships, rather than being one that can be met by providing more adequate
technical information; nonconscious elements that impede problem resolution must be brought
into consciousness and publicly examined and reconstructed; and the methods and concepts of
the behavioral sciences are resources which change agents and clients use to deal with problems.
The main strategies of this group include (a) improving the problem-solving capabilities of a
system and (b) fostering growth in the persons who make up the system to be changed (Chin &
Benne, 1985). As noted by researchers, OD is the major representation of this group of strategies
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(Burke, 2008; Burnes, 2004b). In addition, such strategies as delegated authority (Greiner, 1967),
involvement of target (Kotter & Schlesinger, 1979; Zaltman & Duncan, 1977), collaboration
(Dunphy & Stace, 1988), inspirational appeals (Falbe & Yukl, 1992; Yukl & Falbe, 1990), soft
approach (Beer & Nohria, 2000a), teaching intervention (Huy, 2001), analytical and guided
learning approach (Huy, 2001), shared methods (Powell & Posner, 1980; Waldersee & Griffiths,
2004), and participating strategy (Kotter & Schlesinger, 1979; Quinn & Sonenshein, 2008) are
also based on normative-reeducative strategies.
Power-Coercive Change Strategies
Power is an ingredient of all strategies, and strategies are differentiated by the nature of
power upon which each strategy depends and the ways each strategy generates and applies power
in the process of effecting changes. Specifically, empirical-rational strategies depend on
knowledge as a major ingredient of power and regard people with knowledge as legitimate
sources of power. Similarly, normative-reeducative strategies also admit the importance of
knowledge as a source of power, though they tend to redress the imbalance between different
types of knowledge used in effecting changes (Chin & Benne, 1985). On the other hand, power-
coercive strategies are characterized by their emphasis on political and economic sanctions for
lack of compliance with a proposed change or on utilization of moral power playing upon
sentiments of guilt and shame (Chin & Benne, 1985). Under this group of strategies, more
powerful people within an organizational hierarchy impose their will on the less powerful to
exact their compliance. Chin and Benne (1985) regard the use of political institutions and
manipulation of power elites as the main strategies of this group. In addition, other strategies and
tactics commonly associated with this approach are unilateral action (Greiner, 1967; Waldersee
& Griffiths, 2004), power (Zaltman & Duncan, 1977), authoritative direction and coercion
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(Dunphy & Stace, 1988; Kotter & Schlesinger, 1979), pressure (Yukl & Falbe, 1990),
manipulation and co-optation/coalition (Falbe & Yukl, 1992; Kotter & Schlesinger, 1979), edict
(Nutt, 1998), hard approach (Beer & Nohria, 2000a), commanding (Huy, 2001), and forcing
strategy (Quinn & Sonenshein, 2008).
Thus far, I have reviewed the three groups of change strategies synthesized by Chin and
Benne (1985). Table 2.3 shows the summary of the characteristics of each group of change
strategies and the examples which have been proposed by researchers. In reality, change
implementations in organizations are typically a combination of different groups of strategies.
However, one group of strategies usually dominates and affects how other groups of strategies
are implemented and/or whether or not the secondary or tertiary groups of strategies are
experienced as they are intended.
Summary: Chin and Benne’s Typology of Change Strategies
While different researchers have used different terms to define and categorize change
strategies, Chin and Benne’s (1985) typology of change strategies is considered to be the most
comprehensive and integrative one. Based on the sociological and psychological roots of
strategies of planned change, Chin and Benne classified the strategies into three categories:
empirical-rational, normative-reeducative, and power-coercive. While change implementations
in organizations can be understood as a combination of multiple strategies, one group of
strategies may dominate and affect how the other groups of strategies are implemented.
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Table 2.3
Examples of Strategies of Each Group in Chin and Benne’s (1985) Typology
Characteristics according to
Chin and Benne (1985) Other Examples
Empirical-
rational
strategies
Dissemination of
knowledge through
general education
Personnel selection and
replacement
Employing systems
analysts as consultants
Persuasion with reasoning (Zaltman & Duncan, 1977),
negotiation (Kotter & Schlesinger, 1979), exchange (Falbe
& Yukl, 1992), presenting the benefits of change (Nutt,
1996), rational appeals of experts (Nutt, 1998; Yukl &
Falbe, 1990), engineering intervention (Huy, 2001),
education and communication (Kotter & Schlesinger, 1979),
telling strategy (Quinn & Sonenshein, 2008)
Normative-
reeducative
strategies
Improving the problem-
solving capabilities of a
system
Fostering growth in the
persons who make up the
system to be changed
Delegated authority (Greiner, 1967), involvement of target
(Kotter & Schlesinger, 1979; Zaltman & Duncan, 1977),
collaboration (Dunphy & Stace, 1988), inspirational appeals
(Falbe & Yukl, 1992; Yukl & Falbe, 1990), soft approach
(Beer & Nohria, 2000a), teaching intervention (Huy, 2001),
analytical and guided learning approach (Huy, 2001), shared
methods (Powell & Posner, 1980; Waldersee & Griffiths,
2004), participating strategy (Kotter & Schlesinger, 1979;
Quinn & Sonenshein, 2008)
Power-
coercive
strategies
Use of political
institutions
Manipulation of power
elites
Unilateral action (Greiner, 1967; Waldersee & Griffiths,
2004), power (Zaltman & Duncan, 1977), authoritative
direction and coercion (Dunphy & Stace, 1988; Kotter &
Schlesinger, 1979), pressure (Yukl & Falbe, 1990),
manipulation and co-optation/coalition (Falbe & Yukl, 1992;
Kotter & Schlesinger, 1979), edict (Nutt, 1998), hard
approach (Beer & Nohria, 2000a), commanding (Huy,
2001), forcing strategy (Quinn & Sonenshein, 2008)
Change Models and Underlying Change Strategies
As mentioned above, change models prescribe the actual procedures and activities to
implement change. A comprehensive review of the change models is not the main purpose of this
dissertation. However, to understand the change strategies underlying OD approaches and
strategic management approaches, I will briefly review the basic tenets of the key change models
of both OD and strategic management approaches.
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OD Change Models
The key OD change models frequently introduced in OD textbooks include Lewin’s
three-step change model, the action research model, and the positive model of planned change.
These change models are not exclusive of each other since they share the same assumptions
about human nature and organizations. In addition, even though many OD textbooks describe
Lewin’s three-step model as separate from the action research model, it should be noted that
Lewin regarded action research and the three-step change model, together with field theory and
group dynamics, as forming an integrated approach to understanding and bringing about change
(Burnes, 2004b). Arguably, the three-step change model underlies all OD change models,
including the action research model. Therefore, even though Lewin’s three-step model and the
action research model are described separately in this section, it should be noted that the former
provides the basis for the latter and that the two need to be understood as forming one approach.
Lewin’s three-step model. Based on his work on field theory and group dynamics, Lewin
(1947/1997b) proposed a change model composed of three steps: unfreezing, moving, and
refreezing. According to the model, equilibrium between two groups of forces—those striving to
maintain the status quo and those pushing for change—needs to be unfrozen by increasing the
forces pushing for change and/or by decreasing the forces maintaining the current state in order
to change a particular set of behaviors. This is the goal of unfreezing. The second step, moving,
is to take actions that will shift the client system from its original set of behaviors to a new set.
The actions could be any of what OD researchers and practitioners call interventions (Burke,
1994). The last step, refreezing, aims to stabilize the new set of behaviors at a new quasi-
stationary equilibrium in order to ensure that the new behaviors are relatively safe from
regression. This step usually accompanies the use of supporting mechanisms, such as norms,
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policies, and structures that reinforce the new organizational state. Since Lewin, researchers have
put forth considerable effort to elaborate this three-step model. In 1958, Lippitt, Watson, and
Westely elaborated Lewin’s model into five phases: development of a need for change,
establishment of a change relationship, working toward change, generalization and stabilization
of change, and achieving a terminal relationship (Burke, 2008). Later, Schein (1987; 1999a) also
elaborated the model with more detailed steps: disconfirmation, induction of guilt or survival
anxiety, creation of psychological safety or overcoming of learning anxiety, cognitive
redefinition, imitation and positive or defensive identification with a role model, scanning the
new environment for new and relevant information, and personal and relational refreezing.
Lewin’s three-step change model provides a general framework underlying most of the
efforts to implement organizational change. In fact, it is no exaggeration to say, ―Scratch any
account of creating and managing change and the idea that change is a three-stage process which
necessarily begins with a process of unfreezing will not be far below the surface. Indeed it has
been said that the whole theory of change is reducible to this one idea of Kurt Lewin’s‖ (Hendry,
1996, p. 624).
Action research model. Action research is an outgrowth of the tradition of John Dewey
and Kurt Lewin (Argyris, Putnam, & Smith, 1985). Criticizing the traditional separation of
knowledge and action, Dewey articulated a theory of inquiry to integrate science and practice
(Dewey, 1929, 1933 in Argyris et al., 1985). Following this tradition, Lewin was committed to
combining theory building with research on practical problems through action research. Lewin
(1946/1997a) defined action research as proceeding in a spiral of steps each of which is
composed of a circle of planning, action, and fact-finding about the results of the action.
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Action research challenges the view that researchers must remain objective and value-
free in order to be credible. Instead, action researchers embrace the notion that knowledge is
socially constructed and regard all research as embedded within a system of values (Brydon-
Miller, Greenwood, & Maguire, 2003; Checkland & Holwell, 2007). In order to offer solutions
to problems and to lead to new behaviors, action researchers approach the client system in
naturally-occurring settings about which they have little knowledge and work collaboratively
with the clients as co-learners (J. B. Cunningham, 1993; Dickens & Watkins, 2006). Therefore,
the relationship between the researchers and the client system affects the direction of the research.
In addition, the main principles of action research include the following (Argyris et al., 1985): (a)
action research involves change experiments on real problems in social systems; (b) the intended
change is typically at the level of norms and values expressed in action and typically involves
reeducation (i.e. changing patterns of thinking and acting that are presently well established in
individuals and groups); and (c) action research challenges the status quo from the perspective of
democratic values.
While many different models are used by action researchers (J. B. Cunningham, 1993),
most models consist of cycles of planning, acting, reflecting or evaluating, and then taking
further action (Dickens & Watkins, 2006). More detailed models include the following steps
(Cummings & Worley, 2005): problem identification, consultation with a behavioral science
expert, data gathering and preliminary diagnosis, feedback to key clients or groups, joint
diagnosis of the problem, joint action planning, action, and data gathering after action. Even
though the action research model is one of the earliest models of planned change, it still
underlies most current approaches to planned change (Cummings & Worley, 2005)—such as
process consultation (Schein, 1987b) and action technologies including action science, action
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inquiry, and action learning (Raelin, 2006)—and is used to describe a spectrum of activities to
foster change (J. B. Cunningham, 1993; Dickens & Watkins, 2006).
Positive model of planned change. The two OD change models described above are
primarily problem-focused and deficit-based in that they focus on organizational problems. In
contrast, the positive model of planned change focuses on what an organization is doing right or
what is working (Cooperrider & Sekerka, 2006; Cummings & Worley, 2005). The model is
consistent with a growing movement in social sciences called positive organizational scholarship
(Cameron, Dutton, & Quinn, 2003), which focuses on positive dynamics in organizations that
give rise to extraordinary outcomes. The positive model of planned change involves three stages:
elevation of inquiry, fusion of strengths, and activation of energy (Cooperrider & Sekerka, 2006).
Through the stages, members of an organization create a shared vision about the organization’s
positive potential, clarify the common good or higher purpose, and embrace it. The increase in
moral power distorts the existing system and gives rise to an emergent system that is full of
committed people doing what needs to be done, when it needs to be done (Quinn & Sonenshein,
2008). Additionally, it encourages a positive orientation to how change is conceived and
managed (Cummings & Worley, 2005). The positive model of planned change is conceived as an
alternative to traditional action research and problem-solving approaches which, according to the
proponents of the positive model, result in recreating the process being studied, rather than
leading to new knowledge (Bushe & Kassam, 2005; Quinn & Sonenshein, 2008).
This positive model of planned change has been applied to planned organizational change
primarily through a process called appreciative inquiry (Cooperrider & Srivastva, 1987). Simply
put, appreciative inquiry is an approach for guiding organizational change based on previous
successes and peak performance. It arose from the realization that ―inquiry itself can be an
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intervention‖ (Cooperrider & Sekerka, 2006, p. 227) as it involves agenda setting, language
shaping, affect creation, and knowledge generation. The inquirers here are not outside
consultants but those within the organization; in this respect, appreciative inquiry promotes
broad member involvement. It is also assumed that designing a future state based on the best of
the past can serve as a source of learning and power for future organizational growth
(Cooperrider & Whitney, 2005; Whitney & Trosten-Bloom, 2003). When organizational
members collaborate to realize the life-giving image capturing peak moments, positive
principles—well illustrated by the Pygmalion effect or the self-fulfilling prophecy—can work in
organization, and the organization becomes able to construct a more desirable future
(Cooperrider & Sekerka, 2006; Whitney & Trosten-Bloom, 2003). Since its original conception,
appreciative inquiry has been applied to a wide range of activities, including strategic planning,
group culture change, team building, leadership development, and coaching (Quinn &
Sonenshein, 2008; Skinner & Kelley, 2006). It is now widely acknowledged that appreciative
inquiry is an exceptional tool for engaging participants in a collective process of reframing and
generating a possible future.
Strategic Management Change Models
The strategic management literature defines organizational change as a process of
implementing corporate strategy (Dunphy, 2000). In the literature, decisions are made based on
shareholder value, which is regarded as the only legitimate measure of corporate success (Beer &
Nohria, 2000a, 2000b). The following two change models—Theory E models (Beer & Nohria,
2000c) and John Kotter’s (1995, 1996) change process model—are the examples of strategic
management change models.
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Theory E models. Based on the review of changes in the real world, Beer and Nohria
(2000b) named the change models based on strategic management approaches ―Theory E‖
models, which encompasses the strategic management change models in general. In the modes,
CEOs and the top executive team are viewed as having the perspective, knowledge, and power to
reposition the organization strategically to take advantage of its dynamic environment; in
contrast, other individuals are seen as a potential source of error, inadequacy, and special interest
pleading (Conger, 2000; Dunphy, 2000). Therefore, to ensure that a change initiative generated
by the top team is not subverted, it is vital that other organizational members ―faithfully carry out
the initiatives generated from the top of the organization‖ (Dunphy, 2000, p. 126). Consequently,
the change process is driven by a small group of people with leadership roles, and they must
apply directive and coercive actions to force change recipients to comply with the proposed
change goals (Huy, 2001). For this purpose, leaders usually announce visible crises and try to
hold subordinates accountable for achieving the change goals. Also, the use of external
consultants who apply generic analytical frameworks is legitimized as prescient and
comprehensive planning before radical change is assumed to be possible (Beer & Nohria, 2000a;
Huy, 2001).
Another characteristic of Theory E models is the heavy use of economic incentive (Beer
& Nohria, 2000a). The models assume that financial incentives must play a leading and central
role in motivating change (Wruck, 2000) because they are believed to overcome organizational
inertia and opposition to change. This perspective on the use of financial incentive is in contrast
to the view that it should come after the consensus about strategy and other interventions to
motivate required behaviors (Ledford & Heneman, 2000).
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Kotter’s change process model. The strategic management literature has provided
corporate leaders with many recommendations for implementing organizational change, and
John Kotter’s work is one notable exemplar. Based on close observation of many organizations,
Kotter (1995, 1996) proposed a change process model composed of the following eight stages: (a)
creating a sense of urgency, (b) creating the guiding coalition, (c) developing a vision and
strategy, (d) communicating the change vision, (e) empowering broad-based action, (f)
generating short-term wins, (g) consolidating gains and producing more change, and (h)
anchoring new approaches in the culture. The eight stages can be grouped into three distinct
processes, which can compare to Lewin’s ideas of unfreezing, moving, and refreezing,
respectively. Specifically, the first four stages are the transformation process which helps defrost
a status quo; the fifth to seventh stages introduce many new practices; and the last stage grounds
the changes in the corporate culture and helps make them stick.
According to Kotter (1996), the first stage, creating a sense of urgency, is the most
critical in that ―by far the biggest mistake people make when trying to change organizations is to
plunge ahead without establishing a high enough sense of urgency‖ (Kotter, 1996, p. 4). To
create a sense of urgency, Kotter stressed that leaders need to identify visible crises, or even
create artificial ones, and communicate them to change recipients. He also emphasized the
importance of forming a guiding coalition composed of leaders with position power, expertise,
credibility, and leadership. Based on the sense of urgency, the guiding coalition is to create the
necessary vision, communicate the vision widely, empower a broad base of people to take action,
ensure credibility, build short-term wins, lead/manage different change projects, and anchor the
new approaches in the organization’s culture.
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Some of the ideas presented in the model appear to be similar to those stressed in the OD
models. For example, the model acknowledges that leaders should facilitate two-way
communication about the change visions, that empowered employees are the key drivers of
successful change implementation, and that providing ―the right kind of experience‖ (Kotter,
1996, p. 109) through skill and attitude training is critical. Also, Kotter emphasizes that in many
cases, individuals do not resist a change initiative itself; rather, individuals are often
disempowered or discouraged to support it due to barriers that lie in structures, skills, systems,
and supervisors. However, the basic assumptions underlying this model include the belief that (a)
comprehensive planning is possible before initiating change (Beer & Nohria, 2000a; Huy, 2001),
(b) the guiding coalition composed of CEOs and the top executive team, rather than others
involved in and affected by the change initiative, has the qualities to initiate and lead it (Conger,
2000; Dunphy, 2000), and (c) other organizational members are supposed to take rather passive
roles, to comply with the proposed change goals, and to faithfully carry out the initiative from
the guiding coalition (Dunphy, 2000; Huy, 2001). These assumptions, as well as the values
underlying the assumptions, are distinct from those driving OD change models that are described
earlier in this sub-section. Kotter’s (1996) work well exemplifies the strategic management
perspective on planned change that is popular among corporate leaders and management.
Change Strategies Underlying OD Change Models and Strategic Management Change Models
Change models prescribe the actual procedures and activities that should be carried out to
implement change. On the other hand, change strategies underlie change models and are
foundations upon which we can understand and compare change models. Based on the
discussion thus far, I will review the underlying change strategies of the key change models of
OD approaches and strategic management approaches.
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Change strategies underlying OD change models. In OD approaches to change, the aims
of organizational change efforts are regarded as a deliberate decision to increase an
organization’s effectiveness and capability to change itself (Cummings & Worley, 2005). As
reviewed above, in the OD change models, involvement of the members of a client system is
more than an ethical consideration. Action researchers assume that, as the members are
―grounded in the context‖ (Dickens & Watkins, 2006, p. 191) and ―best positioned to understand
the processes‖ (Brydon-Miller et al., 2003, p. 25), they know the subtle characteristics of the
situation that enable or hinder effective implementation of a plan. Consequently, research that is
conducted without a collaborative relationship with the members is likely to be incompetent
and/or irrelevant. Therefore, it needs to be the members who identify and prioritize issues of
concern and co-create a change strategy and comprehensive action plan.
Furthermore, in OD approaches to change, learning is viewed as a normal part of
leadership and management, and individuals are provided opportunities to reflect on and gain
new insights into their situation and to learn and transform their perspectives by being involved
in the process (Burnes, 2004b). Consequently, individuals are expected to become able to
contribute to the decision-making process and to express themselves and achieve personal
fulfillment through membership. The proponents of appreciative inquiry further advance these
assumptions. Appreciative inquiry is based on the idea that the best intervention might be for a
member to be ―an inquirer, seeking to understand organizational life and to create a spirit of
inquiry that invites others to collaboratively do the same‖ (Cooperrider & Sekerka, 2006, p. 227)
and, therefore, promotes broad member involvement. By being involved in the process,
individuals are expected to alter their underlying paradigm or meaning system, change their
behaviors, and ultimately create new structures and processes (Quinn & Sonenshein, 2008). In
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this respect, in the OD change models, involvement and improvement are part of each other. As
Cummings and Worley (2005) observed, contemporary applications of OD principles have
substantially increased the degree of member involvement in the change process.
The three OD change models reviewed above assume that people are inherently active
and social and that the organizational change procedures should involve collaboration between
change agents and organizational members in order to alter the members’ beliefs, values, and
norms. Some researchers, including Huy (2001) and Burke (2008), classified the action research
model as based on empirical-rational strategies in that the model uses scientific research methods
in the service of promoting change. However, in my point of view, what drives action research is
more akin to the core assumptions of normative-reeducative strategies. What matters is not
which methods are used but how and for what purposes they are used. In action research, the
scientific methods are used to increase the involvement of the members of a client system, to
facilitate co-learning between researchers and the members, and to reeducate the norms and
values of the members. In this respect, the action research model, just like Lewin’s three-step
change model and the positive model of organizational change, is based on normative-
reeducative strategies. The goal of change in the OD change models is to develop individual and
organizational capabilities and effectiveness through the process of changing, obtaining feedback,
reflecting on the feedback, and making further changes (Beer & Nohria, 2000a, 2000b).
Consequently, organizational change initiatives primarily take participative and emergent forms.
In addition, employee participation and involvement are regarded as a key source of energy for
change (Burnes, 2004b; Dunphy, 2000; Sashkin, 1986). In sum, as some researchers have
already suggested (Burke, 2008; Chin & Benne, 1985; Huy, 2001), the OD change models are
mainly based on normative-reeducative strategies.
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Change strategies underlying strategic management change models. In the strategic
management change models reviewed above, change recipients are assumed to be passive and
complacent, which justifies change agents’ control of the change process (Dunphy, 2000) and the
imposition of political or economic sanctions on change recipients for lack of compliance with
the proposed change. The models are characterized by initiating and managing change from the
top down, emphasis on structure and systems (rather than corporate culture and employees’
behavior and attitudes), prescient and comprehensive planning before the initiation of change
(compared to emergent, evolving forms of planning), motivating people through financial
incentives (rather than through commitment), and heavy reliance on external consultants to
analyze problems and shape solutions (Beer & Nohria, 2000a, 2000b). In this respect, these
models are primarily based on both power-coercive strategies and empirical-rational strategies
(Chin & Benne, 1985).
Summary: Change Models and Underlying Change Strategies
In this sub-section, with the examples of key change models, I reviewed the change
strategies upon which OD approaches and strategic management approaches are based. As
reviewed above, OD approaches to change are mainly based on normative-reeducative change
strategies. On the other hand, strategic management approaches are primarily based on power-
coercive and empirical-rational strategies. The change strategies represent different assumptions
about why and how changes should be made. Table 2.4 summarizes some differences among the
change models reviewed in this sub-section and shows which change strategies provide the basis
for OD approaches and strategic management approaches, respectively.
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Table 2.4
Key Characteristics of the Change Models
OD Approaches Strategic Management Approaches
Key change
model Lewin’s three-step model /
Action research model
Positive model /
Appreciative inquiry Theory E models Kotter’s change process
model
Typical identity
of main change
agents
Consultants with process
expertise
Action researchers
Organizational
members Top executives and a group of
leaders
External consultants with
generic analytical knowledge
Top executives and a group
of leaders
Guiding coalition
Role of change
agents Researchers and
practitioners
Teachers or facilitators
Inquirers
Facilitators
Analysts / Factual information
providers
Commanders
Analysts / Factual
information providers
Relationship
between change
agents and
change
recipients
Collaborative
Co-learning
No distinction between
change agents and
recipients
Information providers versus
recipients
Hierarchical
Information providers
versus recipients
Typical change
actions Planning, acting, reflecting/
evaluating
Inquiry
Teaching
Inquiring, questioning
Self-changing
Conducting comprehensive
planning and analysis before
change
Demanding strict compliance
Providing financial incentives
Conducting comprehensive
planning and analysis before
change
Providing new knowledge
and information
Assumptions
about change
recipients
Rational and social
Inherently active
Rational and social
Inherently active
Rational
Passive / Seeking for
compliance
Rational
Passive
Outcomes Emerging in the process
Changes in beliefs, values,
and norms
Enhanced understanding of
the situation
Potentially transformative
Emerging in the process
Changes in paradigm
Potentially
transformative
Change recipients’ compliance
Incremental
Change recipients’
compliance
Incremental
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Change Strategies and Readiness for Change
How do the change strategies reviewed above influence readiness for change? Which
change strategy is most effective when it comes to fostering readiness for change? In the
following sub-sections, I will discuss the effectiveness of the change strategies generally and
review what the literature has evidenced about the effectiveness of each strategy as related to
fostering readiness for change.
Comparing the Effectiveness of Change Strategies
The effectiveness of the three categories of change strategies (Chin & Benne, 1985)—
power-coercive, empirical-rational, and normative-reeducative strategies—can be reviewed
focusing on the profoundness of the goals pursued, the lasting effects of change, and the
enhanced capability for continuous transformation.
Profoundness of the goals. Strategic management approaches have received widespread
support and it is thought that they can deliver results relatively rapidly (Beer & Nohria, 2000a;
Huy, 2001). Change agents following these approaches, which are based on power-coercive and
empirical-rational strategies, determine the desired state—often superior economic performance
(Beer & Nohria, 2000a)—and push change recipients to conform to their expectations with a set
of authorities or with logical arguments. In addition, change recipients are expected to comply
with the goals even without reflecting on their beliefs and values, which is likely to result in only
incremental changes within the underlying paradigm (Quinn & Sonenshein, 2008; Weick, 2000).
However, conformity demonstrated as a response to a directive from a higher authority or
social pressure should not be confused with commitment which implies a personal decision to
participate at an intellectual and emotional level (Henderson, 2002). The three OD models,
which are based on normative-reeducative strategies, focus more on commitment than
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conformity and regard employee participation and involvement as both an ethical imperative and
the key source of energy for change (Burnes, 2004b; Dunphy, 2000; Sashkin, 1986). In the
models, participation and involvement are expected to accompany alteration in the underlying
paradigm and meaning, which can lead to transformational changes in the long run (George &
Jones, 2001; Huy, 2001; Porras & Robertson, 1992). For example, appreciative inquiry, one of
the most recent movements in the field of OD, demonstrates that the appreciation generated
through positive questions becomes a form of power that attracts people into a transformational
state (Cooperrider & Whitney, 2005; Whitney & Trosten-Bloom, 2003). The success cases of
appreciative inquiry show that when organizational members collaborate to work on changing
the organization, the organization becomes able to construct a more desirable future (Bushe &
Kassam, 2005; Cooperrider & Sekerka, 2006; Whitney & Trosten-Bloom, 2003).
Lasting effects of change. Leaders or change agents tend to believe that they are in
control of the change process when they follow the strategic management change models.
However, as Quinn and Sonenshein (2008) pointed out, change agents with this perspective have
little actual control since they focus only on changes in observed behavior, not on those in basic
beliefs or values (Huy, 2001). Moreover, power-coercive strategies often result in damaging
relationships and destroying trust while forfeiting voluntary commitment (Beer & Nohria, 2000a;
Quinn & Sonenshein, 2008). Consequently, as soon as monitoring ceases, compliance and new
behaviors are likely to disappear.
In contrast, normative-reeducative strategies focus on changes in recipients’ attitudes,
values, and normative orientations (Chin & Benne, 1985; Quinn & Sonenshein, 2008) which can
result in lasting changes in behavior (Weick, 2000). Supporting this argument, Chin and Benne
(1985) recommended that even when political-coercive strategies are used, change agents still
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need to adopt normative-reeducative strategies as those who are to conduct themselves in new
ways need to be reeducated to have new knowledge, new skills, new attitudes, and new value
orientations. Moreover, contrary to power-coercive strategies, normative-reeducative strategies
can contribute to building the partnership, trust, and commitment (Bennis, 2000) which are vital
for long-term performance improvements. These arguments stress the long lasting effects of
normative-reeducative strategies as well as those of the OD change models based on such
strategies.
Capability for continuous transformation. Lastly, while the strategic management
approaches rest on the assumption that prescient and comprehensive planning before radical
change is possible (Beer & Nohria, 2000a; Huy, 2001; Ledford & Heneman, 2000; Rajagopalan
& Spreitzer, 1997), the OD change models usually do not assume that change agents can know
the answer or desired outcome. Rather, change agents following the OD models are engaged in a
mutual process with the change recipients and assume that the desired future emerges over time
during the process (Quinn & Sonenshein, 2008; Weick, 2000).
Recently, some researchers, especially complexity theorists, have challenged the
assumption held by the strategic management approaches, arguing that it is impossible to predict
the outcomes of change and to plan, control, and manage change in a rational, top-down, and
linear fashion (Burnes, 2004a; Stacey et al., 2002; Styhre, 2002; Tetenbaum, 1998). According to
these theorists, organizations are complex systems which are ―radically unpredictable and where
even small changes can have massive and unanticipated effects‖ (Burnes, 2004a, p. 318).
Organizations as complex systems transform themselves by being constantly poised at the ―edge
of chaos‖ (S. L. Brown & Eisenhardt, 1997, p. 29). The presence of appropriate order-generating
rules, which permits self-organization to take place, allows some systems to remain at the edge
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of chaos even under changing environmental conditions, while others fall over the edge (Burnes,
2004a; Stacey et al., 2002). Unless employees have the freedom to act as they see fit, self-
organization will be blocked and organizations will not be able to achieve continuous and
beneficial change (Burnes, 2004a). Therefore, to promote change, it is critical for organizations
to let the members have the freedom to self-organize (Burnes, 2004a).
This idea coincides with Senge’s (2000) argument that organizations are nonlinear
dynamic systems in which there are many unintended consequences when direct linear action is
taken. Consequently, under this view, the ability to predict the consequences of any action is
fundamentally limited, and the causal theories that guide our actions may be inadequate in
complex situations (Senge, 2000). He further contends that if organizational goals are set at the
top, management may actually prevent the organization from discovering the factors that may be
critical to its economic health and that it is organizational capability to learn that matters in the
long run. In sum, these theorists and researchers support the idea that, among the three
approaches described by Chin and Benne (1985), only normative-reeducative strategies enable
organizations to transform themselves continuously and successfully (Quinn & Sonenshein,
2008).
In conclusion, as reviewed thus far, OD approaches and strategic management
approaches are based on different change strategies. In reality, few organizations subscribe to
just one strategy, and the success of change implementation may hinge on the use of multiple
change strategies (Beer & Nohria, 2000a; Huy, 2001). While multiple change strategies may be
employed in a single change initiative, one of the three groups of strategies usually dominates
and affects whether or not other strategies are experienced as they are intended. Change
implementation primarily based on power-coercive and empirical-rational strategies is likely to
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have many of the critical limitations described above. The change models which are grounded in
normative-reeducative strategies can be more effective in the long run since the models can bring
about changes in beliefs, values, and norms, and ultimately result in fundamental and long
lasting changes in organizations.
Effectiveness of Change Strategies in Fostering Readiness for Change
As researchers with a social constructionist viewpoint contend, organizational change is a
situation that interrupts normal patterns of organization (Ford et al., 2008) and requires both
change agents and change recipients to engage in sensemaking (Weick, 1995). When faced with
organizational change, employees are actively involved in information seeking, meaning
ascription, and assumption making about the change process to make sense of the new
environment and to draw conclusions about its possible outcomes (Ford et al., 2008; Gioia et al.,
1994). This includes extracting particular behaviors and communications specific to the
organizational change out of streams of ongoing events, interpreting them, and acting on the
resulting interpretation (Ford et al., 2008). In this respect, the change strategies used by leaders
or agents of an organization are critical in change recipients’ sensemaking (Weick, 1995) as well
as the development of their readiness for change.
How do the change strategies reviewed above influence readiness for change? Which
group of strategies, then, is the most effective in fostering readiness for change? Each of the
three categories of change strategies has its own advantages (Beer & Nohria, 2000a, 2000b) and
may contribute to fostering readiness for change to some extent. In addition to the advantages
discussed in the previous sub-section, however, normative-reeducative strategies are arguably
more effective in fostering readiness for change than the other change strategies. This argument
can be supported by the following aspects of organizational change.
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Power-coercive vs. normative–reeducative change strategies. To some degree, power-
coercive strategies can possibly contribute to fostering individuals’ readiness for change. As
Schein (1996/1999a) noted, the threat and survival anxiety produced by disconfirming data may
facilitate the unfreezing process in the organizational context.
However, power-coercive strategies alone are ineffective and insufficient for fostering
individual readiness for change. As discussed above, change can be understood as a situation that
interrupts normal patterns of organization. In the situation, change recipients are required to
make sense of the new environment and determine ―what will happen to me?‖ (Ford et al., 2008;
Gioia et al., 1994). If we agree with this idea, we must conclude that individuals are required to
reconsider their beliefs, values, and normative orientations during organizational change to make
sense of the new environment (Ford et al., 2008; Gioia et al., 1994; Preskill & Torres, 1999a).
Changes in these non-cognitive determinants of behavior need reeducation (Lewin, 1946/1997a)
so that patterns of thinking and acting that are presently well-established can change. As Lewin
(1946/1997a) emphasized, reeducation is not possible through coercion or pressure and should
be distinguished from conformity.
One of the biggest differences between normative-reeducative strategies and power-
coercive strategies is that the former focus on commitment and the latter focus on conformity.
Under power-coercive strategies, change recipients are forced to comply with the goals and, as a
response, may conform to the direction without reflecting on their beliefs and values (Huy, 2001;
Quinn & Sonenshein, 2008). On the other hand, under normative-reeducative strategies,
organizational members are given occasions for participation in the decision-making process,
thereby having a choice to contribute by offering an opinion and potentially to shape the process
(Anderson, 2009). For example, in the action research model, which reflects the core idea of
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normative-reeducative strategies, those affected by problems must be actively involved in
diagnosis, action planning, action taking, and evaluating the effects of action. Through the
experiences, individuals have more control and autonomy over their work (Skelley, 1989),
achieve personal fulfillment through membership (Anderson, 2009), come to fully understand
their situation (Burnes, 2004b), and contribute to generation and dissemination of new
knowledge (Freedman, 2006). Furthermore, these experiences also help individuals have high
levels of emotional investment in and commitment to supporting planned change (Beckhard,
1969 ; Wooten & White, 1999). Under these conditions, individuals have the potential to view
the change as necessary and valuable and/or to provide feedback to the organizational system
about the change in ways that can enhance the change implementation. This fosters the
meaningful engagement of individuals and their commitment to and support for the change at an
intellectual and emotional level (Freedman, 2006; Huy, 2001; Porras & Robertson, 1992). As
discussed above, individual perception of the necessity and value of a change are significant
aspects of readiness for change (Armenakis et al., 1993; Eby et al., 2000; Holt et al., 2007;
Jansen, 2000) and can facilitate the adoption of the change (Rogers, 2003).
In light of the discussion in this subsection, it can be argued that power-coercive change
strategies may correlate negatively with readiness for change (Hypotheses 1a). On the other hand,
normative-reeducative change strategies may contribute to fostering readiness for change
(Hypotheses 1b).
Hypothesis 1a: The power-coercive change strategy will be negatively related to
readiness for change.
Hypothesis 1b: The normative-reeducative change strategy will be positively related to
readiness for change.
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In reality, few organizations subscribe to just one strategy, and change implementations
in organizations are typically a combination of these strategies (Beer & Nohria, 2000a; Huy,
2001). As discussed above, when power-coercive strategies are used, normative-reeducative
change strategies should be combined to help employees become ready for organizational change;
in other words, normative-reeducative change strategies can mitigate the negative relationship
between power-coercive strategies and readiness for change (Hypothesis 3a).
Hypothesis 3a: The normative-reeducative change strategy will moderate the relationship
between the power-coercive change strategy and readiness for change. Specifically, the
stronger the normative-reeducative change strategy is, the weaker the negative
relationship between the power-coercive change strategy and readiness for change will be.
Normative–reeducative vs. empirical-rational change strategies. In some respects,
empirical-rational change strategies can be effective in fostering readiness for change. The
strategies are based on the idea that people follow their rational self-interest; therefore, when
these strategies are adopted, information, facts, and rationales regarding the change
implementation, often provided by external consultants or technical experts, play an important
role. Also, the benefits individuals can obtain as a result of a change initiative, including the
financial incentives (Beer & Nohria, 2000a, 2000b), are stressed. By providing individuals with
information and letting them know the benefits of a change initiative, empirical-rational change
strategies may contribute to fostering individual readiness for change to some degree.
However, some researchers have shown that empirical-rational strategies may not work
well in implementing organizational change and can be less effective than normative-reeducative
strategies in fostering readiness for change. Specifically, the researchers criticize the idea that
adoption of new ideas or innovation is driven by their merits. Through a review of more than
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4000 studies on diffusion of innovations, Rogers (1983, 2003) explained how an individual’s
predisposition—such as interests, needs, and existing attitudes—influences the effects of
knowledge concerning an innovation. According to him, individuals have tendencies to attend to
communication messages that are consistent with their existing attitudes and beliefs (selective
exposure) and to interpret communication messages in terms of their existing attitudes and
beliefs (selective perception). Due to these tendencies, even if individuals are exposed to new
knowledge concerning an innovation, such exposure will have little effect on them unless the
innovation is perceived as relevant to their needs and as consistent with the individual’s attitudes
and beliefs (Hassinger, 1959; Rogers, 2003). Therefore, empirical-rational strategies may not
work without normative-reeducative efforts to alter change recipients’ beliefs, values, and
attitudes (Chin & Benne, 1985). Furthermore, the researchers with a constructionist viewpoint
(and who would align with the normative-reeducative approaches) contend that the diffusion of
new practices depends more on the change recipients’ beliefs in the benefits of the new practices
than on the actual benefits, and that the beliefs are shaped and promoted by the interaction
between change agents and change recipients (Barett, Thomas, & Hocevar, 1995; Ford et al.,
2008; Ford et al., 2002; Green, 2004). In other words, the individuals’ adoption of any change or
innovation depends more on the interaction between change agents and change recipients than on
the objective merits of ideas and products themselves.
Change models with the normative-reeducative orientation engage change recipients in a
mutual process with change agents and provide each group (or multiple groups) with
opportunities to reexamine their present attitudes, values, and knowledge (Quinn & Sonenshein,
2008; Weick, 2000). This is partly based on the idea that research conducted without a
collaborative relationship with the relevant stakeholders (i.e. in organizational change, individual
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members of an organization) is likely to result in incompetent solutions. For example, in the
action research model, those affected by change are viewed as knowing the subtle characteristics
of the situation that enable or hinder effective implementation of a plan (Brydon-Miller et al.,
2003; Dickens & Watkins, 2006). Therefore, in the model, the benefits are assumed to be created
by combining expert knowledge and local knowledge within the collaborative relationship
throughout the reiterative cyclical process. As the solutions resulting from action research are
based on the local knowledge of organizational members, they are likely to be more relevant and
appropriate from the perspective of organizational members than other approaches which
emphasize objectivity, distance, and controls. As researchers noted, individuals’ evaluation of
the appropriateness of a change initiative is a significant component of their readiness for
organizational change (Holt et al., 2007; Jansen, 2000).
Furthermore, by facilitating the interaction between change agents and recipients,
normative-reeducative strategies provide more opportunities for change recipients to develop the
knowledge they need to believe in the benefits of a change (Freedman, 2006), which can
facilitate the adoption of the change (Ford et al., 2008; Green, 2004; Rogers, 2003). Through the
experiences of co-learning and co-creation, individuals gain the competencies needed to apply
the action research methods and become able to plan and take effective actions for and by
themselves in the future. Thus, they become increasingly self-reliant and less dependent upon
experts, consultants, or authority structures (Freedman, 2006). As discussed above, change-
specific efficacy and belief in the benefits of a change are significant components of the
construct of readiness for change (Armenakis et al., 1993; Holt et al., 2007; Jansen, 2000).
In light of the discussion in this subsection, it can be argued both normative-reeducative
change strategies and empirical-rational change strategies, to some degree, contribute to
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fostering employees’ readiness for change (Hypotheses 1b, 1c). However, normative-reeducative
change strategies are expected to be more effective than empirical-rational change strategies in
fostering readiness for change (Hypothesis 2).
Hypothesis 1b: The normative-reeducative change strategy will be positively related to
readiness for change.
Hypothesis 1c: The empirical-rational change strategy will be positively related to
readiness for change
Hypothesis 2: The normative-reeducative change strategy will be more effective than the
empirical-rational change strategy in fostering readiness for change.
As mentioned above, in reality, change implementations in organizations are typically a
combination of these strategies (Beer & Nohria, 2000a; Huy, 2001), and one of the three groups
of strategies usually dominates and affects whether or not other groups of strategies are
experienced as they are intended. As discussed thus far, when empirical-rational change
strategies are used, normative-reeducative change strategies should be combined to help
employees become ready for organizational change (Chin & Benne, 1985); in other words,
empirical-rational change strategies can be more effective in a situation with a stronger emphasis
on normative-reeducative change strategies (Hypothesis 3b).
Hypothesis 3b: The normative-reeducative change strategy will moderate the relationship
between the empirical-rational change strategy and readiness for change. Specifically, the
stronger the normative-reeducative change strategy is, the stronger the positive
relationship between the empirical-rational change strategy and readiness for change will
be.
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Empirical evidence supporting the effectiveness of normative-reeducative change
strategies in fostering readiness for change. Many empirical studies have demonstrated the
effectiveness of normative-reeducative strategies in fostering readiness for change. In his classic
work on changing food preference, Lewin (1948/1997c) demonstrated that participative
discussion is more effective than a lecture. Similarly, Coch and French’s (1948) study, which is
often regarded as the first one to investigate the causes of individuals’ resistance to
organizational change (Dent & Goldberg, 1999a), showed that people are more likely to accept
and learn new methods if they participated in planning and developing the change.
Following this tradition, many researchers have examined the relative effectiveness of
participation in the change project or change decision making. For example, Zaltman and
Duncan (1977), Falbe and Yukl (1992), and Nutt (1998) showed that facilitative and reeducative
strategies are more effective than strategies using persuasion, pressure, and edict. Recent studies
dealing with employees’ attitudes toward organizational change also support the effectiveness of
normative-reeducative strategies in fostering readiness for change. According to the studies, such
factors as participation in change projects and/or in training (Devos, Vanderheyden, & Van den
Broeck, 2001; Shum, Bove, & Auh, 2008), participation in the decision process (M. Brown &
Cregan, 2008; Ertürk, 2008; Wanberg & Banas, 2000; Wanous et al., 2000), procedural justice or
fairness of the change process (Bernerth et al., 2007; M. Brown & Cregan, 2008; Caldwell et al.,
2004; Fedor et al., 2006; Foster, 2010), interactional justice of the change process (Bernerth et al.,
2007; Cindy, Neubert, & Xiang, 2007; Foster, 2010), and sharing information (the vision, the
progress, and likely consequences of the intended change, etc.) during change implementation
(M. Brown & Cregan, 2008; Miller et al., 1994; Qian & Daniels, 2008; Shum et al., 2008;
Stanley, Meyer, & Topolnytsky, 2005; Wanberg & Banas, 2000) contribute to employees’
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positive attitudinal reactions to organizational change. Szabla’s (2007) study is also notable in
that it showed that normative-reeducative strategies are more effective than the other groups of
strategies in eliciting positive cognitive, emotional, and intentional responses to organizational
change. As the findings show, aspects of change implementation based on normative-reeducative
strategies positively influence employees’ attitudes toward organizational change. Figure 2.1
summarizes how the core values or characteristics of normative-reeducative strategies (Anderson,
2009; Jamieson & Gellermann, 2006) can potentially foster each dimension of individual
readiness for change proposed by Holt et al. (2007).
In sum, as proposed by the hypotheses above, normative-reeducative change strategies
are effective in fostering readiness for change (Hypothesis 1b). Furthermore, normative-
reeducative change strategies may mitigate the negative relationship between power-coercive
change and readiness for change (Hypothesis 3a). Also, the effectiveness of empirical-rational
change strategies can be enhanced when they are combined with normative-reeducative change
strategies (Hypotheses 3b).
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Figure 2.1. Normative-reeducative change strategies and individual readiness for organizational
change
Some core values/characteristics of
normative-reeducative strategies
Authenticity, congruence, responsibility,
openness, and trust
Leaders gives employees information,
explain organizational directions, and
allow them to make decisions.
Leaders are straightforward, genuine,
honest, and truthful about their plans,
opinions, and motivations
Participation, involvement, and empowerment
Individuals are empowered to identify and
prioritize issues of concern and co-create a
change strategy and action plan
Individuals become able to contribute
to the decision-making process
Individuals have more control and
autonomy over their work
Individuals are able to express
themselves and achieve personal
fulfillment through membership
Dialogue and collaboration
Interventions seek to bring conflict to light
where they can be addressed in a healthy
manner
Change is used as space that would foster
creativity and new ways to do things
Growth, development, and learning
Learning is viewed as a normal part of
leadership and management
Individuals are provided opportunities to
learn about the change and transform their
perspectives
Individuals gain competencies to plan and
take effective action in the future / become
self-reliant and less dependent upon
technical expert
Change self-efficacy
Appropriateness of the change
Management support for the
change
Personal benefit of the change
Components of individual
readiness for change
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Summary: Change Strategies and Readiness for Change
Normative-reeducative change strategies are more effective than either power-coercive or
empirical-rational strategies in terms of the profoundness of the goals pursued, the lasting effects
of change, and the enhanced capability for continuous transformation. When it comes to
fostering readiness for change, normative-reeducative change strategies are expected to be more
effective since they enhance the potential for change recipients to view the change as necessary
and valuable, to be meaningfully engaged in and committed to the change at an intellectual and
emotional level, to become self-reliant and competent for future change, and to develop the
knowledge they need to believe in the benefits of a change. Also, for these reasons, the
effectiveness of power-coercive and empirical-rational change strategies can be enhanced when
they are combined with normative-reeducative change strategies.
Summary of the Section on Change Strategies of Planned Changes
The OD change models reviewed in this section are based on normative-reeducative
strategies. The strategic management models reviewed above are primarily based on both power-
coercive and empirical-rational change strategies. As discussed in this section, normative-
reeducative strategies are expected to be more effective in fostering individual readiness for
change than either power-coercive or empirical-rational change strategies. Also, even when other
groups of change strategies are primarily used, the strategies can be more effective when they are
combined with normative-reeducative change strategies.
Organizational Learning Culture
Organizational change is not separate from an organization’s history or from other
circumstances from which the change emerges. Rather, it should be regarded as a continuous
process which occurs in the historical, cultural, and political context of the organization
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(Pettigrew & Whipp, 1991). Supporting this idea, researchers have examined the irrefutable roles
of contextual factors such as culture, climate, and leadership in sustaining organizational change
(e.g., Jones et al., 2005; A. D. Meyer, 1982a, 1982b; Schein, 2004; Schneider, Brief, & Guzzo,
1996). In particular, many organizational researchers have stressed the importance of a learning
culture (Schein, 2004; Senge, 1990, 2000; Watkins & Marsick, 1993). For example, Schein
(2004) argues that in a world of turbulent change organizations have to learn faster, which calls
for a learning culture that favors ―perpetual learning‖ (p. 394). Similarly, Watkins and Marsick
(1993) pointed out that an organization needs a ―culture that is learning oriented, with beliefs,
values, and policies that support learning‖ (p. 166). Other researchers have also stressed the
importance of cultures of inquiry and generativity in facilitating organizational learning and
change (Argyris & Schön, 1996; Senge, 1990).
In this section, I will briefly review the literature on organizational culture and
organizational learning. In addition, I will also review the literature on the learning organization
which describes the organizational conditions for organizational learning in detail. Finally, based
on a review of the literature, I will discuss how a learning culture may foster individual readiness
for change.
Organizational Culture
Organizational culture has been a popular topic in various disciplines over the past few
decades. However, as it is extremely broad and inclusive in scope, there is still a lack of
consensus as to what the term organizational culture really means (Martin, 2002; Smircich, 1983;
Trice & Beyer, 1993). In the following sub-sections, I will review the definitions and core
elements of organizational culture which will serve as a basis for understanding a learning
culture.
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Definitions of Organizational Culture
Some of the most often-cited definitions of organizational culture are summarized in
Table 2.5. Among the many definitions of organizational culture, Schein’s (2004) definition of
organizational culture as ―a pattern of shared basic assumptions‖ (p. 17) is the most widely
accepted and well-known (Cameron & Quinn, 2006; Harris & Ogbonna, 2002). Through
collective experience and repeated social interactions, over time a group of people forms shared
assumptions (Schein, 2004) or certain ideologies (Trice & Beyer, 1993) about the way that the
world surrounding them works and the methods for problem solving that are effective in that
world. In this respect, organizational culture is the accumulated shared learning of a given group
(Schein, 2004) functioning as a means to ―channel people’s actions so that most of the time
[people] repeat apparently successful patterns of behavior‖ (Trice & Beyer, 1993, p. 2).
Table 2.5
Definitions of Organizational Culture
Source Definition
Sathe (1985) ―the set of important understandings (often unstated) that members of a community
share in common‖ (p. 6)
Louis (1985) ―a set of understandings or meanings shared by a group of people. The meanings are
largely tacit among the members, are clearly relevant to a particular group, and are
distinctive to the group‖ (p. 74)
Trice and Beyer
(1984) Culture has ―two basic components: (1) its substance, or the networks of meanings
contained in its ideologies, norms, and values; and (2) its forms, or the practices
whereby these meanings are expressed, affirmed, and communicated to members‖ (p.
654)
Schein (1985) ―a pattern of shared basic assumptions that was learned by a group as it solved its
problems of external adaptation and internal integration, that has worked well enough
to be considered valid and, therefore, to be taught to new members as the correct way
to perceive, think, and feel in relation to those problems‖ (2004, p. 17).
Barney (1986) ―a complex set of values, beliefs, assumptions, and symbols that define the way in
which a firm conducts its business‖ (p. 657)
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Core Elements of Organizational Culture
Schein’s conceptualization of organizational culture is the most widely accepted, in part
because it reflects the wide variety of approaches to organizational culture. Schein (2004)
distinguishes three levels of depth in organizational culture: artifacts, espoused beliefs and values,
and basic underlying assumptions.
Artifacts and espoused beliefs and values are explicit layers of organizational culture.
Specifically, artifacts are all the phenomena that one sees, hears, and feels when one encounters a
new or an unfamiliar group. According to Schein (2004), artifacts like the physical environment,
language, stories, and rituals are easy to observe but superficial and difficult to decipher.
Espoused beliefs and values provide the day-to-day operating principles by which the members
of a group guide their actions and tend to be elicited when one asks about observed behavior or
other artifacts. However, espoused beliefs and values are not always congruent with the
underlying assumptions—rather, they can represent what they ideally would like those reasons to
be and what are often their rationalizations for their behavior. In this sense, espoused beliefs and
values reflect what Argyris and Schön (1978, 1996) have called espoused theories. If espoused
beliefs and values are based on prior learning and if the actions based on them continue to be
successful over time, they can be transformed into shared assumptions.
Schein (2004) saw the essence of a culture as lying in a set of basic underlying
assumptions, which are so taken for granted that one finds little variation within a social unit.
Culture as a set of basic assumptions tells us ―what to pay attention to, what things mean, how to
react emotionally to what is going on, and what actions to take in various kinds of situations‖
(Schein, 2004, p. 32). In this sense, basic assumptions are similar to what Argyris and Schön
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(1978, 1996) have identified as theories-in-use in that both of them actually guide group
members’ behavior.
Trice and Beyer (1993) considered that the substance of a culture resides in its ideologies,
which they defined as shared, interrelated sets of beliefs, values, and norms. According to them,
ideologies explain and justify existing social systems in ways that make them seem natural,
logically compelling, and morally acceptable. Whereas ideologies defined by Trice and Beyer
seem to be similar to what Schein meant by basic underlying assumptions, Schein (2004) clearly
distinguished ideologies from basic assumptions, arguing that an organization’s ideology ―can be
any of several things‖ (p. 132) among the various elements of organizational culture—it can be
the conscious component of the total set of assumptions; a list of espoused values; or an
expression of ideals and future aspirations, which is a cultural artifact. In this respect, only some
ideologies, with the passage of time, may be taken for granted as an inevitable part of everyday
life and become sets of shared assumptions.
Roles of Explicit Layers of Organizational Culture
Not all researchers regard explicit layers of organizational culture as superficial as Schein
(2004) did. In particular, Trice and Beyer (1984, 1993) stressed the functions of the cultural
forms in expressing, affirming, and communicating cultural substances—the network of
meanings contained in ideologies, norms, and values—to organizational members. According to
them, cultural forms make ideologies tangible and concrete. Therefore, cultural forms contribute
to the processes through which people make sense of their situations (Weick, 1995) and,
ultimately, to the persistence of cultural ideologies.
From this point of view, artifacts or cultural forms do more than simply reflect deeply
held, unconscious assumptions (Martin, 2002). They provide organizational members with the
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ways to collectively express, affirm, and communicate meanings (Trice & Beyer, 1993).
Furthermore, they also serve as ―generative processes that yield and shape meanings and that are
fundamental to the very existence of [an] organization‖ (Smircich, 1983, p. 353). HRD and OD
activities in organizations, including familiar ones like formal training and development
programs, informal learning opportunities, knowledge management system, and mentoring and
coaching programs, are examples of the explicit layers of organizational culture which make the
organizational culture tangible and persistent over time and which express its meanings to the
members.
Researchers differ in their choice of the level they examine when they study
organizational culture. As each of Schein’s levels of culture is amenable to a different research
method, the appropriate means of assessment depends on the cultural level to be examined
(Ashkanasy, Broadfoot, & Falkus, 2000). As Schein (2004) defined culture as shared underlying
assumptions, for him the best way to gain understanding of a culture is to enter a discussion with
cultural members, using the interview techniques of a clinical psychologist to tap unconscious
and preconscious assumptions (Schein, 1987a). However, unlike Schein, other researchers,
including Trice and Beyer (1993), argue that explicit layers of organizational culture are not
necessarily more superficial than deeply held assumptions and that they provide rich texts which
can be used to read a culture (Ashkanasy et al., 2000; Martin, 2002; Trice & Beyer, 1993). These
researchers examine more explicit layers of culture, including espoused beliefs and values, with
a structured and quantitative approach. In this study, I accept Schein’s conceptualization of three
levels of organizational culture. At the same time, however, following Martin’s (2002) and Trice
and Beyer’s (1993) views, I assume that not only underlying assumptions but also observable
and accessible manifestations of cultures—as represented by espoused beliefs and values and
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artifacts/cultural forms–are the core elements of organizational culture. This assumption justifies
the quantitative approach to organizational culture employed in this study.
Furthermore, organizational behavior researchers have shown that individuals may hold
different perceptions even when they are within the same organizational context (Spreitzer, 1996,
2007) and that an individual’s behaviors and attitudes are determined more by his/her
perceptions of reality than by objective reality (Rentsch, 1990; Spreitzer, 1996). In this respect, it
is useful to focus on the individual perception of organizational variables in order to study
individual attitudes and behaviors. Following these organizational behavior researchers’
arguments, this study relies on individuals’ perceptions of the explicit layers of culture, including
espoused beliefs and values, as a source of data that can be used to understand and assess
organizational culture.
Summary: Organizational Culture
Organizational culture is the accumulated shared learning of a given group which tells us
―what to pay attention to, what things mean, how to react emotionally to what is going on, and
what actions to take in various kinds of situations‖ (Schein, 2004, p. 32). As noted by researchers
like Trice and Beyer (1993) and Martin (2002), not only the underlying assumptions, but also
more explicit manifestations of cultures—espoused beliefs and values and artifacts/cultural
forms—are important elements of culture in that they express, affirm, and communicate the
underlying assumptions to the members and, thus, make the assumptions persistent over time.
Organizational Learning
To complete the understanding of organizational learning culture, I will review the
definitions and core processes of organizational learning in this section.
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Definitions of Organizational Learning
Like organizational culture, organizational learning is a very elusive concept. In order to
understand the concept of organizational learning, researchers often start with these questions:
Can organizations actually learn? Or is it a metaphor for the cumulative learning of the
individuals of the organization? As many organizational learning theorists have elaborated, while
organizations learn through the experience and actions of individuals, organizational learning is
more than the sum total of each individual’s learning (Argyris & Schön, 1978, 1996; Fiol &
Lyles, 1985; Hedberg, 1981; Huber, 1991; Shrivastava, 1983; Watkins, 1996). In other words,
according to organizational learning theorists, organizations actually learn.
Table 2.6
Definitions of Organizational Learning
Source Definition
Argyris (1977) ―a process of detecting and correcting error‖ (p. 116)
Argyris and Schön (1978, 1996) ―inquiry that leads to a change in theory-in-use‖ (1996, p. 19)
Fiol and Lyles (1985) ―the process of improving actions through better knowledge and
understanding‖ (p. 803).
Levitt and March (1988) Organizations learn when they ―encode inferences from history into
routines that guide behavior‖ (p. 319).
Huber (1991) ―An entity learns if , through its processing of information, the range
of its potential behaviors is changed‖ (p. 89).
Senge (1990) ―a continuous testing of experience and its transformation into
knowledge available to whole organization and relevant to their
mission‖ (p. 6).
Dodgson (1993) ―the ways firms build, supplement, and organize knowledge and
routines around their activities and within their cultures and adapt and
develop organizational efficiency by improving the use of the broad
skills of their workforces‖ (p. 377)
Watkins and Marsick (1993) ―Organizational learning is changed organizational capacity for doing
something new‖ (p. 152).
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Table 2.6 shows some of the often-cited definitions of organizational learning. As
Lundberg (1995) summarized, its definitions have some commonalities: (a) organizational
learning is not simply the sum of each member’s learning; (b) organizational learning is a form
of meta-learning—for example, double-loop learning (Argyris & Schön, 1978), generative
learning (Senge, 1990), and transformational learning (Kofman & Senge, 1993; Watkins &
Marsick, 1993)—that requires the rethinking of the patterns that connect and relate the pieces of
an organization and also relates the patterns to the relevant environment; and (c) organizational
learning embraces both cognitive elements (e.g., knowledge) and repetitive organizational
activities (e.g., routines).
Core Processes of Organizational Learning
Many researchers have elaborated the key processes through which organizations learn.
Among the theories, Argyris and Schön’s one is noteworthy in that their theory focuses on the
roles of individuals in organizational learning and, therefore, provides knowledge useful to HRD
and OD practitioners. The following two processes are critical in their theory (Watkins &
Marsick, 1993).
Changes in theories-in-use. Argyris and Schön (1978, 1996) provided a detailed
explanation of the organizational learning process by focusing on the interpersonal inquiry and
the way such inquiry interacts with processes occurring at higher levels of aggregation such as
teams, departments, and organizations. According to them, when an individual within an
organization experiences a problematic situation and inquires into it on the organization’s behalf
(i.e., acting as agents for the organization), the inquiry becomes an organizational inquiry.
However, not every organizational inquiry results in organizational learning, even when it
produces changes in the design of organizational practices. The outcomes of inquiry qualify as
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products of organizational learning when individuals ―modify their images of organization or
their understandings of organizational phenomena and restructure their activities‖ (Argyris &
Schön, 1996, p. 16), thereby changing organizational theories-in-use. In short, organizational
learning occurs when organizational theories-in-use are changed through organizational inquiries.
Changes in organizational memory. As discussed above, changes in organizational
theories-in-use lead to organizational learning. However, at the same time, the organization
should be able to integrate the learning into its processes and make the knowledge accessible to
others within the organization by storing it in the organizational environment (Argyris & Schön,
1996), or in the structures, technologies, and systems that hold and coordinate routines (M. D.
Cohen, 1991; Lundberg, 1995). The stored information from an organization’s history, such as
knowledge about what worked in the past when certain types of problem occurred (Watkins,
1996), composes organizational memory. In this respect, organizational learning accompanies
changes in organizational memory (Levitt & March, 1988) through capturing, storing, and
sharing new knowledge in organizations. Many theorists have emphasized storing and sharing
learning outcomes as an important condition for organizational learning (M. D. Cohen, 1991;
Fiol & Lyles, 1985; Huber, 1991; Levitt & March, 1988; Lundberg, 1995).
Besides the two elements of organizational learning reviewed above, researchers have
stressed several other processes and conditions of organizational learning including a better
system for error detection and correction (Argyris & Schön, 1996; Watkins & Marsick, 1997b),
cultures of inquiry and generativity (Argyris & Schön, 1996; Senge, 1990; Watkins & Marsick,
1997b), and extracting and building knowledge (Nonaka, 1994; Shrivastava, 1983; Watkins &
Marsick, 1997b).
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Summary: Organizational Learning
Among the diverse ways to explain organizational learning, Argyris and Schön’s one is
adopted in this study because it provides knowledge useful to HRD and OD professionals.
According to Argyris and Schön, organizational learning happens when an individual within an
organization experiences a problematic situation, inquires into it on the organization’s behalf,
and changes organizational theories-in-use. In addition, the new learning should be integrated
into relevant processes of the organization and be made accessible to others within the
organization.
Learning Organization
Organizational researchers have paid much attention to the conditions that support
organizational learning. In particular, researchers of the learning organization have made
significant contributions to enhancing our understanding of a learning culture. To complete the
understanding of a learning culture and its dimensions, the literature on the learning organization
is reviewed in this section.
Definitions of the Learning Organization
Simply put, a learning organization is one that purposefully enhances (Dodgson, 1993;
Watkins & Marsick, 1993) or one that is good at (Lundberg, 1995; Tsang, 1997) organizational
learning. Therefore, it makes conceptual sense to say that a learning organization has a strong
emphasis on a learning culture, or a set of shared beliefs and values (Schein, 2004) that supports
organizational learning. Researchers of learning organizations have offered prescriptions of
organizational conditions that may function as enablers of organizational learning. By
investigating the conditions and enablers, they have uncovered the cultural forms, beliefs, and
values that constitute a learning culture.
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Due to the variety of perspectives, no common description of learning organizations
appears to exist. Senge (1990) described a learning organization as a place ―where people
continually expand their capacity to create the results they truly desire, where new and expansive
patterns of thinking are nurtured, where collective aspiration is set free, and where people are
continually learning how to learn together‖ (Senge, 1990, p. 1) and suggested the use of five
disciplines—shared vision, personal mastery, changing mental models, team learning, and
systemic thinking—that are required to achieve it. Also, Kofman and Senge (1993) defined
foundations of learning organizations as ―(1) a culture based on transcendent human values of
love, wonder, humility, and compassion; (2) a set of practices for generative conversation and
coordinated action; and (3) a capacity to see and work with the flow of life as a system‖ (p. 16).
Focusing more on the knowledge creation process, Nonaka (1991) characterized knowledge-
creation companies as places where ―inventing new knowledge is not a specialized activity… It
is a way of behaving, indeed a way of being, in which everyone is a knowledge worker‖ (p. 97).
Criticizing Senge’s (1990) and Nonaka’s (1991) definitions for lack of practicality,
Garvin (1993) defined a learning organization as one that is ―skilled at creating, acquiring, and
transferring knowledge, and at modifying its behavior to reflect new knowledge and insights‖ (p.
80). Also from a strategic perspective, Goh (1998) proposed more specific components of
learning organizations, including clarity and support for mission and vision, shared leadership
and involvement, a culture that encourages experimentation, ability to transfer knowledge across
organizational boundaries, and teamwork and cooperation. While Garvin’s (1993) and Goh’s
(1998) strategic perspectives of learning organizations provide practical guidelines for building
learning organizations, their conceptualizations have limitations in that they neglect the
importance of individual learning (Yang, Watkins, & Marsick, 2004).
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On the other hand, based on the integration of adult learning theories and organizational
learning theories, Watkins and Marsick (1993, 1996) proposed that in a learning organization
learning and change must take place at every level, including individuals, groups, and
organizations. They contended that a learning organization is one in which learning is continuous,
strategically used, integrated with work, and ultimately results in increased organizational
capacity for innovation and growth. In addition, a learning organization has embedded systems
or mechanisms to capture and share learning (Watkins & Marsick, 1993).
Among the various perspectives, Watkins and Marsick’s conceptualization of the
learning organization is regarded as the most integrative one (Ortenbiad, 2002; Redding, 1997;
Yang et al., 2004). In addition, Watkins and Marsick’s works on the learning organization have
focused primarily on the cultural aspects of organizations (Yang et al., 2004). Therefore, the
characteristics attributed to the learning organization in their framework reflect a learning culture.
In light of this, this study focuses on Watkins and Marsick’s framework to understand the
elements of a learning culture.
Dimensions of the Learning Organization: Watkins and Marsick’s Framework
Through a series of works, Watkins and Marsick have identified the dimensions of the
learning organization (Marsick & Watkins, 1999, 2003; Watkins & Marsick, 1993, 1996, 1997a;
Yang et al., 2004). What follows is a brief description of the seven dimensions of the learning
organization. The first three dimensions are at the individual and group levels and the remaining
four are at the organizational level.
Creating continuous learning opportunities. In learning organizations, work is designed
in such a way that people can stop and learn from problems, challenges, and mistakes while on
the job. Also, practices such as planning for learning, teaching managers to be facilitators and
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coaches, and providing incentives to support formal and informal learning are encouraged
(Watkins & Marsick, 1993).
Promoting inquiry and dialogue. Learning organizations promote skills that are needed to
learn more effectively from others. Specifically, dialogue, which calls for ―open minds and open
communication‖ (Watkins & Marsick, 1993, p. 13), and inquiry, which involves questioning that
―simultaneously challenges assumptions and yet does not attack the individual‖ (p.14), are
encouraged. These are the core activities to initiate interpersonal inquiry which leads to
organizational learning (Argyris & Schön, 1978, 1996).
Encouraging collaboration and team learning. In learning organizations, teams are
conceived to be ―the medium for moving new knowledge throughout the learning organization‖
(Watkins & Marsick, 1993, p. 14), and collaboration is believed to offer ―avenues for exchange
of new ways of working‖ (p. 14). Therefore, continuous and collaborative learning within groups
is emphasized.
Creating systems to capture and share learning. Learning organizations systematically
work to capture and embed new learning. They facilitate widespread dissemination of the
learning both for others already in the organization who would benefit from this knowledge and
for future employees (Watkins, 1996).
Empowering people toward a collective vision. In learning organizations, everyone has
an idea of what the whole picture looks like and knows how to get something done in the
organization. This collective vision cannot be developed and implemented without
empowerment. Empowerment creates reserves in human capacity by increasing freedom of
decision making and movement, and by freeing people to experiment, take risks, and learn from
results and mistakes (Marsick & Watkins, 1999).
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Providing strategic leadership for learning. In learning organizations, leaders are
encouraged to model and champion learning. Furthermore, they are required to ―think
strategically about how to use learning to create change and to move the organization in new
directions or new markets‖ (Watkins & Marsick, 1996, p. 7).
Connecting the organization to its environment. Learning organizations are responsive to
both ―members of the organization and their work-life needs‖ (Watkins & Marsick, 1993, p. 18)
and ―external customers whose needs influence all members of an organization‖ (p. 18).
The seven dimensions of the learning organization can be understood as the action
imperatives to foster a learning culture in organizations. As Watkins and Golembiewski (1995)
argued, the concepts of the learning organization and organizational learning culture are a
reaffirmation of long-standing beliefs of OD.
Dimensions of the Learning Organization as Characteristics of a Learning Culture
The dimensions of the learning organization identified above are observable
characteristics (Yang et al., 2004). More specifically, among the core elements of organizational
culture, the dimensions can be compared to the beliefs and values of organizational members.
Also, the set of dimensions identified above can be compared to the ideologies which Trice and
Beyer (1993) defined as shared, interrelated sets of beliefs, values, and norms. The beliefs and
values express themselves through artifacts (Schein, 2004) or cultural forms (Trice & Beyer,
1993) which include practices such as mentoring and coaching, incentives for formal and
informal learning, and knowledge sharing systems. These practices make the beliefs and values
tangible and persistent over time.
As beliefs and values, the dimensions of a learning culture specified above define what is
important in an organization (Watkins & Marsick, 1993) and provide operating principles by
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which its members guide their actions (Schein, 2004; Trice & Beyer, 1993). If individual-,
group-, and organizational-level learning activities based on the beliefs and values work well and
continue to be successful over time, they may become taken for granted and transformed into
assumptions. However, if they are not based on prior learning, the beliefs and values represented
in the dimensions specified above may show only what individuals or management would like
the ideal reason for their behaviors to be. Therefore, depending on the organizational context, the
dimensions of a learning culture identified above can be consistent with the organization’s
underlying assumptions or distinct from them. Learning organizations are places where the
beliefs and values represented in the dimensions of a learning culture are consistent with their
basic underlying assumptions.
Summary: Learning Organization
A learning organization has a strong emphasis on a learning culture, or a set of shared
beliefs and values (Schein, 2004), that supports organizational learning. To understand the
elements of a learning culture, this study adopts Watkins and Marsick’s (1993, 1996) framework
of the learning organization as it provides the most integrative framework and focuses primarily
on the cultural aspects. The seven dimensions of the framework show the cultural forms, beliefs,
and values of a learning culture.
Learning Culture and Readiness for Change
A learning culture can be defined as a set of shared beliefs and values (Schein, 2004) that
supports organizational learning. In order to understand the influences of a learning culture on
readiness for change, I will discuss how a learning culture facilitates organizational change and
influences individuals.
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Learning Culture and Organizational Change
The idea that change always involves learning (Beckhard & Pritchard, 1992; A. D. Meyer,
1982a) is one of the basic assumptions shared by HRD and OD researchers (Swanson & Holton,
2001). More clearly, Watkins and Marsick (1993) explained the relationship between change and
learning by defining change as ―a cyclical process of creating knowledge (the change or
innovation), disseminating it, implementing the change, and then institutionalizing what is
learned by making it part of the organization’s routines‖ (p. 21). Other organizational learning
theorists have also argued that organizational learning is a prerequisite for successful
organizational change (Baker & Sinkula, 1999; Garvin, 1993; Lundberg, 1995; Ulrich, Von
Glinow, & Jick, 1993).
Meyer’s (1982a) study on how organizations learn as a response to a dramatic
environmental change showed that an organization’s learning process and outcomes are more
consistent with its own culture than with the objective realities imposed by its environment. As
the study demonstrated, organizational culture guides and shapes organizational responses (A. D.
Meyer, 1982b; Smircich, 1983) and ultimately supports organizational learning and change.
Meyer’s argument is consistent with the basic premise of the learning organization literature that
a learning culture helps an organization learn and change (Garvin, 1993; Huber, 1991; Watkins
& Marsick, 1993, 1996). By purposefully supporting individual learning and inquiry and sharing
and embedding what is learned, the beliefs and values of a learning culture facilitate changes in
organizational theories-in-use and in organizational memory and, thereby, facilitating
organizational learning and change (Garvin, 1993; Huber, 1991; A. D. Meyer, 1982a; Watkins &
Marsick, 1993, 1996).
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Learning Culture and Individuals
How does a learning culture influence individuals? The impact of culture on individuals
has long been a topic of interest among researchers (Fuller & Clarke, 1994; Martin, 2002; A. D.
Meyer, 1982a; Schein, 2004; Trice & Beyer, 1993). As is widely acknowledged, individuals are
embedded in organizational culture which is created by their actions yet, at the same time, the
culture has an objective existence independent of the actions of any individual (Schein, 2004;
Trice & Beyer, 1993). Each member of an organization constructs his or her own representation
of the culture or of organizational theories-in-use (Argyris et al., 1985; A. D. Meyer, 1982b). In
this sense, individuals carry within them a microcosmic portrait of the organization (Argyris &
Schön, 1996). As reviewed above, Argyris and Schön’s organizational learning theory teaches us
that through organizational inquiry individuals ―modify their images of organization or their
understandings of organizational phenomena and restructure their activities‖ (Argyris & Schön,
1996, p. 16) and, therefore, change organizational theories-in-use. In other words, the alterations
individuals make in their image of the organization during an organizational inquiry give rise to
new organizational practices, which guide the socialization of individuals with particular
theories-in-use (Argyris et al., 1985). In addition, the new practices create conditions where
particular theories-in-use are effective, thereby reinforcing the theories-in-use. In this respect, as
Argyris and Schön (1996) put it, organizational theories-in-use are ―dependent on the ways in
which its members represent it‖ (p. 16).
In an organization which embodies a learning culture, organizational routines and shared
beliefs are regularly modified as a matter of institutionalized practice (Lundberg, 1995), and
individuals are encouraged to undertake organizational inquiries in various ways (Preskill &
Torres, 1999b; Watkins & Marsick, 1993, 1996). Therefore, in such an organization, individuals
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have more opportunities to be engaged in organizational inquiry as well as to capture and share
what has been learned by others. Through these opportunities, individuals are encouraged to
continuously modify their own image of the organization, to restructure their activities, to give
rise to new practices, and, ultimately to change organizational theories-in-use (Argyris & Schön,
1978, 1996). In this way, the learning culture enables individuals to be the agents learning on
behalf of their organization and to be ready for organizational changes.
In addition, as reviewed above, organizations with a strong emphasis on a learning
culture are good at creating, acquiring and transferring knowledge, and modifying behavior to
reflect new knowledge and insight and, therefore, tend to be more apt to learn and change
(Garvin, 1993; Huber, 1991; Watkins & Marsick, 1993, 1996). As a consequence, employees in
an organization with a strong emphasis on a learning culture may have learned that the
organization is likely to thrive under changing organizational conditions, which will also result in
a higher level of readiness for change.
In conclusion, a learning culture not only encourages individuals to be engaged in
organizational learning but also enhances organizational capacity to make successful changes
(Watkins & Marsick, 1993). Therefore, employees who perceive their work environment to have
characteristics associated with a learning culture are more likely to have higher levels of
readiness for organizational change. In light of the discussion thus far, I propose the following
hypothesis.
Hypothesis 4a: Learning culture will be positively related to readiness for change.
Combined Influence of Change Strategies and a Learning Culture on Readiness for Change
The issue of whether change is best developed with the active involvement of
organizational members or under the direction of leaders is one of the most debated issues in the
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field of organizational change. In particular, OD approaches to planned change which represent
normative-reeducative change strategies (Chin & Benne, 1985) have supported widespread
involvement and participation by organizational members in bringing about organizational
change. Under these approaches, employee involvement and participation are not only an ethical
imperative, but also a key source of energy for change since organizational members have the
knowledge and capabilities to contribute effectively to organizational decision making around
change (Bennis, 2000; Brydon-Miller et al., 2003; Burnes, 2004b; Dickens & Watkins, 2006;
Lawler, 1986; Sashkin, 1986; Wagner, Leana, Locke, & Schweiger, 1997). According to this
view, employees ―know more about their jobs than supervisors‖ (Wagner et al., 1997, p. 50) and
―can develop the knowledge to make important decisions about the management of their work
activities‖ (Lawler, 1986, p. 193). To the contrary, as I reviewed above, the proponents of
strategic management approaches contend that the impetus for change should be in the hands of
a team of leaders alone, as only the leaders have ―the perspective, the knowledge, and the power
to reposition the organization strategically‖ (Dunphy, 2000, p. 124). Also, they tend to be
skeptical about organizational members’ capabilities to contribute to the success of change
initiatives (Conger, 2000; Dunphy, 2000; Locke, Schweiger, & Latham, 1986).
What underlies the debate is the difference in the view on organizational members’
capability. As those in the strategic management school point out, organizational members do
not necessarily have the capability to participate effectively in the change process. In order for
their involvement and participation in the change process to have successful outcomes,
organizational members must be knowledgeable, capable, and motivated to make a genuine
contribution. As Dunphy (2000) summarized, ―participation by knowledgeable, skilled, and
motivated members of the organization does enhance a change project; participation by
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uninformed, unskilled, and unmotivated members of the workforce does not‖ (p. 133). Therefore,
normative-reeducative strategies to a specific change initiative can be effective especially when
organizational members have the capability to effectively participate in and make a genuine
contribution to the change process. In other words, OD approaches to planned change can be
further justified when organizational members have the capability to contribute to change
implementation.
Under what circumstances, then, are organizational members more likely to be capable of
contributing to the success of a change initiative? Organizational members’ capabilities to
contribute to change are something that can be learned through their experiences in organizations.
As I reviewed above, a learning culture develops the capability of employees to identify and
solve work-related problems by supporting organizational learning—more specifically, by
creating continuous learning opportunities, encouraging collaboration and team learning,
creating systems to capture and share learning, and empowering people (Watkins & Marsick,
1993).
In this respect, it can be argued that a learning culture is one of the prerequisites for OD
approaches to planned change, or normative-reeducative strategies (Chin & Benne, 1985), to be
successful. Specifically, organizational members who have worked in an environment with a
stronger emphasis on a learning culture are more likely to be capable of making genuine
contributions to change than those who have not. Therefore, OD approaches to planned change
can be more effective in a situation with a stronger emphasis on a learning culture.
Based on the discussion thus far, I propose the following hypothesis.
Hypothesis 4b: Learning culture will moderate the relationship between the normative-
reeducative change strategy and readiness for change. Specifically, the stronger the
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learning culture is, the stronger the positive relationship between the normative-
reeducative change strategy and readiness for change will be.
Summary: Learning Culture and Readiness for Change
The learning culture not only encourages individuals to be engaged in organizational
learning but also enhances organizational capacity to make successful changes. In this respect, it
can be argued that employees who have worked in an environment with a strong emphasis on a
learning culture are more likely to be ready for change than those who have not (Hypothesis 4a).
In addition, a learning culture enhances individual capabilities and enables individuals to be
capable of making genuine contributions to changes. In this regard, normative-reeducative
strategies are likely to be more effective in a situation with a stronger emphasis on a learning
culture (Hypothesis 4b).
Summary of the Section on Learning Culture
A learning culture can be defined as a set of shared beliefs and values that supports
organizational learning. Watkins and Marsick’s (1993, 1996) framework of the learning
organization shows the cultural forms, beliefs, and values of a learning culture. A learning
culture fosters individual readiness for change by encouraging individuals to be engaged in
individual and organizational inquiries and by enhancing organizational capacity to change. In
addition, by developing individual capabilities to make genuine contributions to change, a
learning culture also provides conditions where normative-reeducative change strategies can be
more effective.
Individual Job Level Impact of Change
Some researchers argue that the applicability of OD approaches to change is limited in
reality where abrupt and radical organizational changes are frequent. They say that, given the
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transformative nature of changes such as takeovers, mergers, and closures, which often involve
massive restructuring and layoffs, OD approaches are ―extremely limited and value based‖
(Dunphy & Stace, 1988, p. 317). According to this view, OD approaches are simply a managerial
technique that is appropriate in certain circumstances (Conger, 2000; Locke et al., 1986), and
directive and coercive strategies are generally more effective in bringing about change. Some of
these researchers take the contingency approach, arguing that different change models are
required to bring about different types of changes (e.g., Dunphy & Stace, 1988; Huy, 2001;
Kotter & Schlesinger, 1979; Stace & Dunphy, 1991; Waldersee & Griffiths, 2004). However, as
Dunphy and Stace (1988) noted, other researchers, especially those associated with large
consulting firms, go further and attempt to implement planned changes primarily through
designing and installing control systems regardless of their types or the contexts.
This section examines whether the effectiveness of normative-reeducative strategies and
the learning culture is limited to certain types of change or applies to across different types of
change. To examine the topic, I will first discuss why the content or type of a change needs to be
conceptualized in terms of the impact the change has on individual’s job when studying
readiness for change. Based on the discussion, I will examine how change strategies and the
learning culture have different influences on readiness for change depending on the impact the
change has on individuals’ jobs.
Types of Change
Researchers have classified types of change in various ways. First of all, in terms of the
ultimate goal of change, many researchers have distinguished between transformational change
and transactional change. The distinction between transformational and transactional change is
primarily based on Burke and Litwin’s (1992) model of organizational change. In the model,
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mission and strategy, leadership, and culture are the transformational factors that most
immediately and directly respond to external environmental dynamics; and structure, systems,
management practices, work unit climate, individual needs and values, task requirements and
individual skills and abilities, and motivation are transactional factors which are more concerned
with the day-to-day operations of the organization (Burke, 2008; Burke & Litwin, 1992).
Changes in transformational factors require significantly new behavior from organizational
members, tend to affect most features and levels of the organization, and are discontinuous and
revolutionary in nature. On the other hand, changes in transactional factors involve fine-tuning
the organization and limited levels of the organization, and we use terms such as continuous
improvement, incremental, developmental, evolutionary, and selective to describe them (Burke,
2008; Burke & Litwin, 1992; Cummings & Worley, 2005). Even though the word
―transformational‖ is generally used to refer to the targets or contents of change, it is also
associated with change strategies by some researchers. For example, Dunphy and Stace (Dunphy
& Stace, 1988; Stace & Dunphy, 1991) used ―transformative change strategies‖ in such a way
that they include both charismatic and dictatorial transformation strategies.
Some researchers classified types of change in terms of orders of change. Specifically,
they distinguished between first-order change and second-order change (Bartunek & Moch, 1987,
1994; Porras & Robertson, 1992; Porras & Silvers, 1991). First-order change refers to small-
scale and less drastic changes that help the organization overcome stagnation and enhance
efficiency by fine-tuning the organization. This type of change consists of alterations or
modifications in existing system characteristics without effecting its core (Porras & Robertson,
1992). Second-order change, on the other hand, refers to ―changes in cognitive frameworks
underlying the organization’s activities, changes in the deep structure or shared schemata that
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generate and give meaning to these activities‖ (Bartunek & Moch, 1994, p. 24) and involves a
fundamental shift of the existing system (Porras & Robertson, 1992). In this respect, first-order
change involves what is referred to as continuous improvement, and evolutionary and
transactional change; and second-order change is concerned with radical, revolutionary, and
transformational change (Burke, 2008).
Beer and Nohria (2000a, 2000b) proposed another important distinction among different
types of change: (a) changes for the creation of economic value and (b) changes to develop
organizational capabilities. The former type of change focuses on change strategies, structure,
and systems, which are elements that can readily be changed from the top down to yield quick
financial results. On the other hand, the latter type of change focuses on culture, behavior, and
attitudes in order to develop organizational capabilities, particularly the capability of employees
to become involved in identifying and solving work-related problems. Under this perspective, an
organization can enhance its economic value by focusing on the effectiveness and efficiency
with which work is carried out at every level.
Lastly, planned change needs to be distinguished from unplanned change. The former is a
―conscious, deliberate, and intended‖ (Chin & Benne, 1985, p. 22) decision to increase an
organization’s effectiveness and capability to change itself (Cummings & Worley, 2005).
Unplanned change is a change ―whose impetus originates outside the organizational system‖
(Porras & Robertson, 1992, p. 721). In a similar vein, changes are also differentiated as
anticipated change, emergent change, and opportunity-based change (Orlikowski & Hofman,
1997). Anticipated changes are those that are planned ahead of time and occur as intended.
Emergent changes are those that arise spontaneously from local innovation and that are not
originally anticipated or intended. Opportunity-based changes are those that are not anticipated
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ahead of time but are introduced purposefully and intentionally during the change process in
response to an unexpected opportunity, event, or breakdown (Orlikowski & Hofman, 1997).
Even though ways to define types of changes are diverse, they are not exclusive of each other.
Different labels can be used together to describe and define a change.
Change as Experienced by Individuals
While the change literature usually conceptualizes the content of change in terms of
broad initiatives, some researchers focus on the content of change as seen or experienced by
individuals (e.g., Caldwell et al., 2004; Devos et al., 2007; Fedor et al., 2006; Herold, Fedor, &
Caldwell, 2007; Judge et al., 1999; Lau & Woodman, 1995; Novelli et al., 1995). As these
researchers argue, the organization-level impact of a specific change, such as implementation of
Total Quality Management (TQM) or of Enterprise Resource Planning (ERP), can be somewhat
independent of the impact the change may have on work groups or on the individuals within the
groups (Fedor et al., 2006). Even though a change at the organizational level is clearly important,
it often has significantly different impact for different work groups throughout the organization
and, ultimately, different implications for individuals within these groups. In this respect, the
content of a specific change experienced by individual employees are likely to be best
represented by the impact the change has on individuals’ jobs rather than by the organizational
level initiative itself. In addition, it can be argued that individuals’ reactions to change, such as
their readiness for change, are expected to be based on their experience of the more immediate
change situation, rather than the labels attached to the organizational level initiative.
Several researchers support this argument. For example, Lau and Woodman (1995)
concluded that individual employees were concerned more about the impact a change had on
their immediate work environment, such as adjustments in work processes and routines, than
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about the meaning of the organizational-level change. Novelli et al. (1995) noted that positive
outcomes of a change from individual perspectives, rather than from the organizational
perspective, increased employees’ commitment to the change. More recently, Caldwell et al.
(2004) and Fedor et al. (2006) showed that impact of a change at the individual levels affected
person-job fit and individuals’ commitment to the change. These arguments support the idea that
individuals assess the personal impact of a change by considering the more immediate aspects of
the change that have filtered down in the form of adjustments in work processes or routines
(Burke & Litwin, 1992).
Attitudinal reactions to organizational change are thought to be driven, in part, by
feelings of uncertainty, loss of familiar routines, fear of failure, lack of choice, and threats to
individual sensemaking engendered by a change event (Brehm & Brehm, 1981; Burke, 2008;
Ledford, Mohrman, Mohrman, & Lawler, 1989; Oreg, 2003). The impact of a change on
individual jobs affects the degree of such feelings and, therefore, provides a context within which
change strategies and a learning culture contribute to shaping individuals’ responses to the
change. For example, if a change has huge impact on an individual’s job, it would evoke more
individual concerns over the change, such as uncertainty, fear of failure, loss of control, and
disruption in sensemaking than would one with small impact do. Under such conditions, the
benefits of a change itself, which is a significant component of readiness for change (Holt et al.,
2007), may be lessened from the individual’s standpoints. Therefore, under these conditions,
individuals are expected to feel less ready for the change. In addition, one might expect that,
under conditions of high amounts of individual job changes, change strategies used in the
situation and a learning culture in the work environment will become more salient and their
effects on readiness for change may be amplified.
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In light of the discussion in this section, I present the following three hypotheses.
Hypothesis 5a: The magnitude of individual job level impact will be negatively related to
readiness for change.
Hypothesis 5b: The magnitude of individual job level impact will moderate the
relationship between the normative-reeducative change strategy and readiness for change.
Specifically, the stronger the individual job level impact is, the stronger the positive
relationship between the normative-reeducative change strategy and readiness for change
will be.
Hypothesis 5c: The magnitude of individual job level impact will moderate the
relationship between learning culture and readiness for change. Specifically, the stronger
the individual job level impact is, the stronger the relationship between learning culture
and readiness for change will be.
Summary of the Section on Individual Job Level Impact of Change
While types of change are differentiated in various ways, the content of change
experienced by individual employees is likely to be best represented by the impact a specific
change has on individuals’ jobs rather than by the labels attached to the change initiative at the
organizational level. Under conditions of high individual job changes, which evoke more
individual concerns over the change, the benefits of the change itself may be lessened from the
individual’s standpoint, and, therefore, individual readiness for change is expected to be low. In
addition, under the aforementioned conditions, change strategies used in the situation and a
learning culture in the work environment will become more important in fostering readiness for
change.
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Summary of the Chapter
In the first section, I reviewed the literature on readiness for change. The construct of
readiness for change is composed of individuals’ belief in the extent to which (a) they are
capable of making a successful change, (b) the change is appropriate for the organization, (c) the
leaders and management are committed to the change, and (d) the proposed change is beneficial
to organizational members. Second, I reviewed the literature on change strategies. Based on the
review of the principles and characteristics of different changes strategies, I discussed why
normative-reeducative change strategies, on which OD approaches to organizational change are
based, are more effective than any other change strategies in fostering readiness for change. In
the third section, based on a review of the literature on organizational culture, organizational
learning, and the learning organization, I discussed how organizational learning culture can
foster readiness for change. Finally, I discussed how the impact a change has on individuals’ jobs
provides a context within which change strategies and the learning culture contribute to shaping
individuals’ readiness for change. Specifically, I argued that under conditions of high amounts of
individual job changes, change strategies used in the situation and the learning culture in the
work environment will become more important in fostering readiness for change.
Based on the review of the literature, I proposed hypotheses to address the research
questions of this study. Research Question 1 was ―What is the relationship between the change
strategy perceived by those responding to a planned change and their readiness for change?‖ To
address this research question, the following seven hypotheses were proposed. First of all, I
argued that power-coercive change strategies may decrease readiness for change; on the other
hand, empirical-rational change strategies and normative-reeducative change strategies are
expected to contribute to fostering readiness for change.
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Hypothesis 1a: The power-coercive change strategy will be negatively related to
readiness for change
Hypothesis 1b: The normative-reeducative change strategy will be positively related to
readiness for change.
Hypothesis 1c: The empirical-rational change strategy will be positively related to
readiness for change
Even though Hypotheses 1b and 1c posit that both normative-reeducative change
strategies and empirical-rational change strategies may contribute to fostering readiness for
change, normative-reeducative change strategies are expected to be more effective than
empirical-rational change strategies.
Hypothesis 2: The normative-reeducative change strategy will be more effective than the
empirical-rational change strategy in fostering readiness for change.
Change implementations in organizations in reality are typically a combination of these
strategies (Beer & Nohria, 2000a; Huy, 2001). Even when other groups of change strategies are
used, normative-reeducative change strategies need to be combined with the main change
strategies to help employees become ready for organizational change. Specifically, normative-
reeducative change strategies may mitigate the negative relationship between power-coercive
change strategies and readiness for change. In addition, empirical-rational change strategies may
be more effective in a situation with a stronger emphasis on normative-reeducative change
strategies.
Hypothesis 3a: The normative-reeducative change strategy will moderate the relationship
between the power-coercive change strategy and readiness for change. Specifically, the
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stronger the normative-reeducative change strategy is, the weaker the negative
relationship between the power-coercive change strategy and readiness for change will be.
Hypothesis 3b: The normative-reeducative change strategy will moderate the relationship
between the empirical-rational change strategy and readiness for change. Specifically, the
stronger the normative-reeducative change strategy is, the stronger the positive
relationship between the empirical-rational change strategy and readiness for change will
be.
Research Question 2 was ―What is the relationship between the learning culture
perceived by those responding to a planned change and their readiness for change?‖ In Chapter 2,
to address this research question, two hypotheses were proposed. Specifically, I argued that the
learning culture fosters readiness for change by encouraging individuals to be engaged in
organizational learning and enhancing organizational capacity to make successful changes.
Hypothesis 4a: Learning culture will be positively related to readiness for change.
Furthermore, normative-reeducative strategies for a specific change initiative can be
effective especially when organizational members have the capability to effectively participate in
and make a genuine contribution to the change process. A learning culture enhances the
development of employees’ capability to identify and solve work-related problems by supporting
organizational learning. Therefore, normative-reeducative strategies can be more effective in a
situation with a stronger emphasis on a learning culture.
Hypothesis 4b: Learning culture will moderate the relationship between the normative-
reeducative change strategy and readiness for change. Specifically, the stronger the
learning culture is, the stronger the positive relationship between the normative-
reeducative change strategy and readiness for change will be.
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Finally, Research Question 3 was ―How does the impact of the change on individuals’
jobs affect the two relationships presented in the first two research questions?‖ Three hypotheses
were proposed to address this research question. Specifically, under conditions of high individual
job changes, which evoke more individual concerns over the change, the benefits of the change
itself may be lessened from the individual’s standpoint, and therefore, individual readiness for
change is expected to be low. Based on the idea, I posited the following hypothesis.
Hypothesis 5a: The magnitude of individual job level impact will be negatively related to
readiness for change.
In addition, under conditions of high individual job changes, change strategies used in the
situation and a learning culture in the work environment will become more important in fostering
readiness for change.
Hypothesis 5b: The magnitude of individual job level impact will moderate the
relationship between the normative-reeducative change strategy and readiness for change.
Specifically, the stronger the individual job level impact is, the stronger the positive
relationship between the normative-reeducative change strategy and readiness for change
will be.
Hypothesis 5c: The magnitude of individual job level impact will moderate the
relationship between learning culture and readiness for change. Specifically, the stronger
the individual job level impact is, the stronger the relationship between learning culture
and readiness for change will be.
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CHAPTER THREE
RESEARCH DESIGN AND METHODS
The purpose of this study was to examine the conditions conducive to individual
readiness for organizational change. The following three research questions guided this study.
1. What is the relationship between the change strategy perceived by those responding
to a planned change and their readiness for change?
2. What is the relationship between the learning culture perceived by those responding
to a planned change and their readiness for change?
3. How does the impact of change on individuals’ jobs affect the two relationships
presented in the first two research questions?
This chapter describes the research design and methods used in this study. Specifically,
this chapter is organized into nine sections: research design, conceptual framework,
instrumentation, sample selection, data collection, data preparation and screening, reliability and
validity, data analysis, and delimitations of this study.
Design of the Study
This study adopted a descriptive research design to provide systematic description of the
characteristics of a given area of interest (i.e., individual readiness for organizational change)
without manipulating variables or controlling the environment in which the study took place
(Merriam & Simpson, 2000). Specifically, to answer the research questions, this study employed
a survey design which provides a description of attitudes or opinions of a population by studying
a sample of that population (Creswell, 2003).
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As a method of data collection, the quantitative survey, a method used to gather self-
report descriptive information (Rosenfeld, Edwards, & Thomas, 1995), was selected for the
following reasons. First of all, the method allowed me to obtain a standardized measurement that
was consistent across all respondents and to conduct statistical tests with key variables of the
study. Second, the quantitative survey method is particularly strong at studying large groups of
people and can be used to draw conclusions beyond the group being studied (Holton & Burnett,
2005). Considering the potential practical implications of this study, attempts to apply the
findings from the sample being studied to broader groups should be valued. For this reason, the
quantitative survey method has been frequently used in organization research, to collect
information from organizational members on some set of organizationally relevant constructs
(Bartlett, 2005).
As this study was based on data collected through self-report surveys, organizational
level variables included in this study (e.g., change strategies and learning culture) were actually
individuals’ perception of the variables. This approach can be justified for the following reasons.
First of all, it can be argued that aspects of a change are likely to have significantly different
impacts for different work groups throughout the organization and, ultimately, different
implications for individuals within these groups (Judge et al., 1999; Lau & Woodman, 1995;
Mohrman et al., 1989). In this situation, individuals’ readiness for organizational change is
expected to be based on their experience of the more immediate change situation, rather than on
the master plan established by the leaders or on the label attached to the initiative. Therefore, the
key variables of this study, which are organizational level variables, need to be defined and
assessed in terms of how individuals evaluate or experience the variables.
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In addition, in organizational research, studying individuals’ self-report perception of
organizational aspects has some advantages. Organizational behavior researchers have shown
that individuals may hold different perceptions even when they are within the same
organizational context (Spreitzer, 1996, 2007) and that an individual’s behaviors and attitudes
are determined more by his/her perceptions of reality than by objective reality (Rentsch, 1990;
Spreitzer, 1996). In this respect, in order to study individuals’ attitudes and behaviors, it is useful
to focus on their perception of organizational variables. Additionally, from the OD practitioners’
standpoint, self-report measures offer internal credibility to organizational members (Ashkanasy
et al., 2000) and, therefore, can increase the likelihood that members would accept the results of
the survey.
Key Variables and Conceptual Framework
The purpose of this study was to examine the conditions conducive to individual
readiness for organizational change. Specifically, this study focused on the influences of change
strategies and learning culture on individual readiness for organizational change. In addition, this
study examined how the impact a change has on individuals’ jobs works as a context within
which change strategies and learning culture contribute to shaping individuals’ readiness for
organizational change. What follows is the description of the key variables of this study.
Independent Variables
The independent variables of this study include the following: change strategies, learning
culture, and individual job level impact of change.
First, as discussed in Chapter Two, this study defines change strategies as the way change
is implemented (Burke, 2008). Following Chin and Benne’s (1985) classic work, this study
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differentiates among three change strategies: the power-coercive change strategy, the normative-
reeducative change strategy, and the empirical-rational change the strategy.
Second, based on Schein’s (2004) idea of organizational culture and Watkins and
Marsick’s (1993) idea of the learning organization, I define a learning culture as a set of beliefs
and values about the functioning of an organization that supports organizational learning (see
Chapter Two). In this study, Watkins and Marsick’s (1993, 1996) framework of the dimensions
of the learning organization is used as a basis for assessing the learning culture of an
organization.
Third, in this study, individual job level impact of change represents the content of
change. As discussed in Chapter Two, individuals’ reactions to change, such as their readiness
for organizational change, are based on their experience of the more immediate aspects of the
change that have filtered down in the form of adjustments in work processes and routines (Burke
& Litwin, 1992). Similar to previous research (e.g., Caldwell et al., 2004; Fedor et al., 2006), this
study assumes that the content of a change experienced by individuals can be represented by the
impact the change has on individuals’ jobs.
Dependent Variables
In this study, following Holt et al.’s (2007) construct validation study, individual
readiness for organizational change (henceforth, readiness for change) is defined and
operationalized as a multifaceted construct with four dimensions: the extent to which employees
believe that (a) they are capable of implementing a proposed change (change-specific efficacy),
(b) the proposed change is appropriate for the organization (appropriateness of the change), (c)
the leaders are committed to the proposed change (management support for the change), and (d)
the proposed change is beneficial to organizational members (personal benefit of the change).
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Control Variables: Individual Differences
Given the nature of readiness for change, it may be influenced by individual differences.
Therefore, in addition to the four key variables of interest reviewed above, additional variables
related to individual differences were included in this study. Specifically, one personality
variable—negative affectivity (Watson, Clark, & Tellegen, 1988)—and a few selected
demographic variables were included. With these variables, I examined whether there was an
individual-level systematic variance that was not represented by the key study variables. Also, in
testing the hypothesized relationships among the key study variables, I controlled for the effects
of these variables related to individual differences.
Negative affectivity. Negative affectivity is a general dimension of subjective distress and
unpleasurable engagement that subsumes a variety of aversive mood states, including anger,
contempt, disgust, guilt, fear, and nervousness (Watson et al., 1988). People with high negative
affectivity have high levels of subjective distress, nervousness, and anxiety and are more prone
to feelings of anger, contempt, disgust, and fear. As summarized by Watson et al.(1988),
psychologists have considered negative affectivity to be related to self-reported stress as well as
to frequency of unpleasant events.
Some leaders and managers tend to believe that some individuals are negative about
everything, not just change and, therefore, resist change regardless of organizational efforts to
facilitate change. I included negative affectivity in this study to examine whether some
individuals are predisposed to having low levels of readiness for change to the extent that they
are generally negative. In addition, as negative affectivity may contaminate true relationships
among the key variables of this study, its inclusion also enabled me to control for the probable
effect on readiness for change.
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Demographic variables. A few demographic variables—age, gender, educational level,
and organizational tenure—were included in the analysis so that their effects on readiness for
change could be examined and controlled for. Previous research studies have shown mixed
results about the relationships between demographic characteristics and individuals’ attitudes
toward change. Regarding the effect of age, for example, Kanfer and Ackerman (2004)
suggested that age-related declines in intellectual abilities and in openness to change may make it
more difficult for older workers to increase efforts as a way of overcoming high demands for
novel information processing or new skill learning which often occur during organizational
change. However, it is also possible that the increased experience of older workers provides them
with the resources and resiliency to adapt to change. The research evidence on this issue is rare,
with a few studies providing contradictory findings concerning the effects of age on employees’
success at adapting to change (Caldwell et al., 2004). Organizational tenure, the total years of
employment in the current organization, was also considered because individuals who have
worked in the organization longer are likely to have more difficulties in adapting to the changes.
Conceptual Framework
The research questions that guided this study were:
1. What is the relationship between the change strategy perceived by those responding
to a planned change and their readiness for change?
2. What is the relationship between the learning culture perceived by those responding
to a planned change and their readiness for change?
3. How does the impact of the change on individuals’ jobs affect the two relationships
presented in the first two research questions?
Figure 3.1 presents the conceptual framework of this study.
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Figure 3.1. Conceptual framework of the study
Instrumentation
What follows is a description of the construction of the survey instrument of this study.
Measures
The survey instrument of this study was composed of several existing measures,
including the perception of change leadership strategy scale (Szabla, 2007), the dimensions of
the learning organization questionnaire (DLOQ; Marsick & Watkins, 2003), the readiness for
change scale (Holt et al., 2007), and the negative portion of the positive and negative affects
schedule scales (PANAS Scales; Watson et al., 1988). The measures were originally developed
using various response formats. For example, the DLOQ was developed with a 6-point scale
Change Strategies
(change process)
Power-coercive
Normative-reeducative
Empirical-rational
Readiness for Change
Change-specific
efficacy
Appropriateness
Management support
Personal benefit
Change Impact
(change content)
Hypotheses 1a, 1b, 1c, 2, 3a, 3b
Hypothesis 4a
Hypothesis 5a
Hy
po
thesis 4
b
Hy
po
thesis 5
b
Hy
po
thesis 5
c
Learning Culture
(change context)
Creating continuous learning
opportunities
Promoting inquiry and dialogue
Encouraging collaboration and
team learning
Empowering people toward a
collective vision
Establishing systems to capture
and share learning
Connecting the organization to
its environment
Providing strategic leadership
for learning
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ranging from 1 (almost never) to 6 (almost always) with no middle anchor; the readiness for
change scale used a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree); and
the PANAS Scales used a 5-point scale ranging from 1 (very slightly or not at all) to 5
(extremely). To avoid confusing the respondents, all measures used a five-point Likert-type scale
ranging from 1 (strongly disagree or almost never) to 5 (strongly agree or almost always).
Internal consistency is independent of the number of choices employed in the rating format, and,
therefore, minor alterations to response formats like this do not affect the reliability of the
instrument (Gable & Wolf, 1993). What follows is a brief description of each of the measures.
Change strategy. To assess individuals’ perception of change strategies, the perception of
change leadership strategy scale developed by Szabla (2007) was used. Following Spector’s
(1992) idea that survey respondents can easily fail to recognize negative constructions and
respond negatively when their intended response is actually positive, some of the items on the
scale that had included negative constructions were rephrased. Sample items of the scale include
―those leading this change are focusing on the facts and promoting the benefits of this change‖
and ―the relationship between those leading this change and those responsible for carrying out
this change is collaborative.‖ The responses were measured on a five-point Likert-type scale (1 =
strongly disagree; 5 = strongly agree).
Learning culture. To measure perception of the learning culture, the DLOQ was used.
Originally developed by Watkins and Marsick (1997a) to assess ―shifts in an organization’s
climate, culture, systems, and structures that influence whether individuals learn‖ (Marsick &
Watkins, 2003, p. 133), the DLOQ captures individuals’ perception of various aspects of the
learning culture. For this study, the shortened version of the DLOQ with 21 items (Marsick &
Watkins, 2003; Yang, 2003) was adopted. The DLOQ has been widely used in a variety of
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contexts and is accepted as a valid and reliable instrument in many empirical studies. Sample
items include ―in my organization, people give open and honest feedback to each other‖ and ―my
organization makes its lessons learned available to all employees.‖ The responses were measured
on a five-point Likert-type scale (1 = almost never; 5 = almost always).
Change impact. In order to measure the individual job level impact of change, six items
from Caldwell et al. (2004) and Fedor et al.’s (2006) studies, which capture the extent to which
individuals’ jobs are impacted by a change, were used. The six items are concerned with the
changes in job demands, expectations, and responsibilities. Sample items include ―as a result of
this change, the nature of my work has changed‖ and ―as a result of this change, my job
responsibilities have changed.‖ (see Appendix A) The items were rated on a five-point Likert-
type scale, ranging from 1 (strongly disagree) to 5 (strongly agree).
Readiness for change. In order to measure readiness for change, the readiness for change
scale developed by Holt et al. (2007) was used. Using a systematic scale development process,
Holt et al. identified four dimensions of readiness for change—change-specific efficacy,
appropriateness of the change, management support for the change, and personal benefit of the
change—and developed a scale with 25 items. Following Spector’s (1992) idea mentioned above,
a few items on the scale that had included negative constructions were rephrased. Sample items
of the scale include ―I think that the organization will benefit from this change‖ and ―I have the
skills that are needed to make this change work.‖ The responses were measured on a five-point
Likert-type scale, from 1 (strongly disagree) to 5 (strongly agree).
Negative affectivity. The negative portion of PANAS scales (Watson et al., 1988) was
used to measure negative affectivity. It contains items presenting negative feelings, such as being
scared, upset, guilty, and nervous and asks respondents to indicate the extent to which they have
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experienced these feelings. The PANAS scales can be administered with various instructional
sets reflecting different time frames and can measure either a state or a trait (Ford & Ford, 1994;
Watson et al., 1988). By using long-term instructions, this study defined negative affectivity as
relatively stable individual differences in general affective level (i.e., a trait) rather than transient
fluctuations in mood over a time frame (i.e., a state). Specifically, the respondents of this study
were asked to respond to the items on the basis of how they felt in general. The responses were
measured on a five-point scale, from 1 (very slightly or not at all) to 5 (extremely).
Demographic information. In order to examine and control for the probable effects of
demographic characteristics on readiness for change, questions regarding age, gender,
educational level, and organizational tenure were included in the survey instrument.
Pilot Testing the Survey Instrument
A pilot study was conducted to find initial support for the reliability of the instrument.
Questionnaires were distributed to a convenience sample of 57 employees who worked in an
organization which had just launched an organization-wide change initiative. In order to ensure
similarity between the pilot respondents and the population of this study, all the pilot respondents
needed to meet the following two criteria: (a) he/she was full-time employees in the organization
and (b) he/she was aware of the organizational change initiative that was underway in their
organization at the time the pilot study was conducted.
Based on the 57 responses, Cronbach’s alphas, a measure of internal consistency, were
calculated. The coefficients ranged from a low of .701 for items measuring power-coercive
change strategy to a high of .926 for items measuring the appropriateness dimension of readiness
for change. (See Table 3.5 for Cronbach’s alphas resulting from the pilot study.) Overall,
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Cronbach’s alphas resulting from the pilot study exceeded .7, indicating an acceptable level of
internal consistency (Nunnally, 1978).
Table 3.1
Overview of the Survey Instrument
Section Dimensions Number of items
Section I. Change strategies Empirical-rational strategies 5
Power-coercive strategies 5
Normative-reeducative strategies 5
Section II. Learning culture Creating continuous learning 3
Promoting inquiry and dialogue 3
Team learning 3
Empowering people 3
Shared systems 3
System connectedness 3
Provide leadership 3
Section III. Impact of change Individual job level impact 6
Section IV. Readiness for change
Change-specific efficacy 10
Appropriateness 6
Management support 6
Personal benefit 3
Section V. Individual differences Negative Affectivity 10
Gender 1
Age 1
Educational level 1
Organizational tenure 1
Work area/unit 1
Staff position 1
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Summary of the Survey Instrument
Before constructing the survey instrument, permission from the authors of the perception
of change leadership strategy scale (Szabla, 2007), the DLOQ (Watkins & Marsick, 1997a), and
the readiness for change scale (Holt et al., 2007) for inclusion of the scales in the survey
instrument was obtained. Table 3.1 shows the overview of the survey instrument. It was
composed of five sections, and the total number of items was 83. (See Appendix A for a copy of
the survey instrument used in the study.)
Sample Selection
In this study, the sample selection took place at both the organization level and the
individual level. What follows is a brief description of how the organization and individuals were
selected for this study.
Selecting the Organization
Many research studies dealing with employees’ attitudes toward organizational change
involve a single organization (e.g., M. Brown & Cregan, 2008; Eby et al., 2000; Elias, 2009;
Szabla, 2007). Collecting data from one organization has some advantages. In particular, it
enables me to control for the confounding effects of contextual factors, such as HR policies
supportive of change and history of change attempts, which may cause organizational-level
systematic variance in readiness for change. Due to this advantage, the data for this study were
collected from one organization.
The participating organization was selected through convenience sampling. A flyer to
solicit participation of organizations was sent out to current part-time graduate students and
graduates of the Human Resource and Organizational Development (HROD) program at the
University of Georgia and to other relevant groups (see Appendix B for the flyer). Among the
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organizations which responded, one organization was selected for this study as it met the
following conditions which were noted in the recruitment flyer.
A planned change intervention, which met the following criteria, should be underway at
the time the study was conducted: (a) an intentional effort that alters (b) key
organizational target variables that then impact (c) organizational members and their on-
the-job behaviors resulting in changes in (d) organizational outcomes (Chin & Benne,
1985; Porras & Silvers, 1991).
The organizational change initiative was so significant that it affected as many levels of
the organization as possible.
The selected organization is a large nonprofit healthcare provider in the Southeastern
region of the United States. It is a family of hospitals, urgent care centers, a nursing home, and a
residential hospice. The organization has about 10,000 employees, including about 400
physicians. Its services range from primary care (e.g., family practice, OB/GYN) to specialty
care (e.g., cardiology, neurosurgery). The total revenues exceeded 1 billion in 2009.
An organization-wide assessment conducted in 2007 showed that the rate of serious
safety events at its hospitals had shown an increasing trend for a few consecutive years. Also,
injury and illness rates of employees and physicians had been significantly higher than the
average rates in healthcare. Based on the assessment, in 2009, the organization embarked on a
change initiative which affected all its hospitals. The purpose of the initiative was to reduce the
organization’s serious safety event rate by 80% over three years and, ultimately, to improve the
quality of patient care. The vision of the initiative was to create a highly reliable environment for
safe practices and to establish safety as a core value of the organization. The organization created
a master plan which included the use of advanced technology and innovation, constant practice
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of safety principles, vigilance in understanding errors, and providing feedback to the patients and
customers.
To implement the change initiative, first of all, core values expressed in the organization
have changed. Safety became the first agenda on every meeting. When a decision is made, the
question ―how does this decision impact safety?‖ should be answered. Also, acts to prevent harm
were publicly recognized and praised. Specific behavior expectations aligned with safe practices
were set and communicated through various ways. Furthermore, to disseminate the core values
and promote expected behaviors for safe practices, the organization provided extensive training
sessions for its members. At the time the study was conducted, a majority of team members had
completed human error prevention training and safety training.
In addition, as a part of leadership development programs, front line managers and
directors had been specially trained as safety coaches by the time the study was conducted. Their
roles as safety coaches included training and coaching employees as well as measuring and
reporting safe practices. They were using department meetings, walk rounds, group feedback
sessions, and daily check-ins for the purpose of training and communicating safety to employees.
They were also observing the performance of groups and individual employees to determine if
practice met the safe behavior expectations and to reveal safety problems before they became
events that result in harm. Based on these observations, managers and directors provided real
time feedback to reinforce good practices and to correct unsafe practices.
Also, the organization has put forth effort to capture and share lessons learned within the
organization. For example, it established a web page on Intranet to share success stories and
critical lessons across the hospitals. Once a hospital team posted success stories and critical
safety lessons learned through practices, they were disseminated to all the other team members
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across the hospitals within 24 hours through the Intranet system. Also, every quarter the stories
and lessons were integrated into a safety coaching guide which was used by safety coaches to
update their knowledge and to make suggestions for effective interaction with employees.
The change initiative implemented in the organization can be defined in various ways.
First of all, the initiative was a planned change which is based on a ―conscious, deliberate, and
intended‖ (Chin & Benne, 1985, p. 22) decision to increase an organization’s effectiveness and
capability to change itself (Cummings & Worley, 2005). Also, the initiative was an anticipated
change (Orlikowski & Hofman, 1997), rather than either an emergent change or opportunity-
based change, in that it was planned ahead of time and occurred as intended. In addition, the goal
of the change initiative was to establish a culture of safety with values and beliefs supporting
safe practices. As the change initiative affected most features and levels of the organization,
modified an established framework or method of operating, and involved new behavior from
organizational members, the initiative could be described as transformational, gamma, and
second-order change (Bartunek & Moch, 1987; Burke, 2008; Burke & Litwin, 1992), rather than
transactional, alpha, and first-order change.
Selecting the Individuals
The full-time employees of the hospitals who worked in the units that were affected by
the change initiative comprised the population of this study. They include physicians, nursing
staffs (e.g., RN, LVN/LPN), clinical ancillary staffs (e.g., radiology technicians, laboratory
technicians, pharmacists), support services staffs (e.g., facility services staffs, food services staff),
and administration and management staffs. To get access to as many individuals as possible in
the organization, non-probability sampling was used. The invitations to participate and link to
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the on-line survey were sent to the population, and those who voluntarily participated in the
survey comprised the sample of this study.
Data Collection
Before collecting data, the following activities were completed: (a) permission from the
organization to distribute the questionnaires to their employees and (b) permission from the
Institution Review Board and Human Subjects Office of the University of Georgia to conduct the
research (Project 2010-10323-2). These activities were conducted after the permission of
dissertation committee members in December, 2009.
In addition, parts of the questionnaire were customized to make them appropriate for the
situation in the organizations. To provide a common change referent for the respondents, a brief
description of the change initiative was given in the introduction of the questionnaire. Also,
reminders were provided in the instructions for each section throughout the questionnaire. Based
on the description, the respondents were expected to have the same change initiative in mind
while they were completing the questionnaire.
The questionnaire of this study was included as a part of an organization-wide survey on
quality culture which was conducted in October, 2010. The survey invitation email with a link to
the informed consent form and the online survey was internally disseminated to 948 employees
who worked in the units that were directly affected by the change initiative (see Appendix A for
the consent form and the questionnaire). Employees were allowed to take part in the survey
during work hours.
In this study, the subject of organizational change could be perceived as sensitive and,
therefore, might motivate respondents to respond in socially desirable ways. To decrease the risk
of response error caused by social desirability (Dillman, Smyth, & Christian, 2008), the
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questionnaire was accompanied by an information letter clarifying the objectives of the study
and ensuring the confidentiality of the data collected. In addition, the respondents who were not
comfortable with the level of confidentiality provided by the Internet were encouraged to print
out a copy of the survey, fill it out by hand, and mail it to the researchers at the address given in
the informed consent form, with no identifiers or return address on the envelope.
Furthermore, to minimize nonresponse error, Dillman et al.’s (2008) suggestions were
utilized in this study. Specifically, information about how the survey results would be used to
benefit the potential respondents and others in the organization was provided; the survey was
designed to be as easy as possible for people to complete; positive regard and respect were
shown through the survey; sponsorship by legitimate authority in the organizations was noted;
and confidentiality and security of information was ensured. In addition, two follow up messages
were sent to potential respondents. In all, 160 completed questionnaires were returned, with a
response rate of 17 percent. Chapter Five includes potential issues concerning the response rate
of this study.
Data Preparation and Data Screening
Before either a raw data file or a matrix summary of the data was created, the original
data were carefully prepared and screened for potential problems.
Data Preparation
Following a previous study (Caldwell et al., 2004), the six items measuring the impact of
change scale which formed Section I of the survey instrument were coded into one dimension.
The 15 items of the perception of change leadership strategy scale, which formed Section II,
were coded into the three categories of change strategies following the original scale developed
by Szabla (2007). The 25 items of the readiness for change scale which formed Section III of the
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survey instrument were coded into the four dimensions suggested by Holt et al. (2007). The 21
items of the DLOQ which formed Section IV were coded into seven dimensions following the
framework provided by Marsick and Watkins (2003). Some of the items in Section II and
Section III were reverse-coded. The mean scores of the items measuring each dimension were
used in the analysis.
In addition to the measures of the study variables, the survey instrument included several
variables related to individual differences: negative affectivity, age, gender, educational level,
and organizational tenure. The 10 items measuring negative affectivity were coded following the
instructions given by Watson et al. (1988), and the mean score of the 10 items of negative
affectivity was used in the analysis. Age and organizational tenure were coded in years. Gender
was coded 1 for male and 0 for female. Educational level was coded with 1 to 5 indicating
degree from low to high: high school graduate, associate’s degree, bachelor’s degree, master’s
and professional degree, and doctoral degree.
Data Screening
As will be explained in detail below, multiple regression analysis was the primary
statistical technique used to test the hypotheses of this study. Prior to analysis, the collected data
were examined to see whether they met the assumptions of multiple regression: the assumptions
of normality, linearity, and homoscedasticity of residuals (Kline, 2005; Pedhazur, 1997).
Additionally, I examined whether there were outliers or multicollinearity in the data.
Absence of outliers. In order to examine the existence of univariate outliers, standardized
scores were examined. The common rule of thumb is that scores more than three standard
deviations beyond the mean may be outliers (Kline, 2005). There were 7 cases that had extreme
Z scores (above ±3.00) in the data. These cases were deleted from the dataset.
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In addition, multivariate outliers were identified by examining the Mahalanobis distance
statistic (Mahalanobis D2), which indicates the distance in standard deviation units between a set
of scores for an individual case and the sample means for all variables. A conservative level of
statistical significance has been recommended for this test (Kline, 2005). There were 2 cases that
had the Mahalanobis distance values with a probability less than .001. These cases were deleted
from the dataset.
Absence of multicollinearity. Multicollinearity occurs when intercorrelations among some
variables are high because what appear to be separate variables actually measure the same thing.
Particularly in this study, there could be problems with multicollinearity in testing interaction
effects because an interaction term (obtained by multiplying a moderator variable by an
independent variable) is highly correlated with the moderator variable and the independent
variable. To avoid possible problems with multicollinearity and to increase interpretability of
interactions, all the variables involved in the interaction effects were centered following the
procedure outlined by Aiken and West (1991).
Multicollinearity can be detected by tolerance and variance inflation factors (VIFs).
Tolerance indicates the proportion of total standardized variance that is not explained by other
variables. VIF is the ratio of the total standardized variance to unique variance. Tolerance values
less than .10 or VIF values higher than 10 imply that there might be multicollinearity (Kline,
2005). As reported in Table 3.2, the tolerance and VIF values of the independent variables
indicate no occurrence of multicollinearity in the data.
Normality, linearity, and homoscedasticity of residuals. Histograms, normal probability
plots, and scatterplots of standardized residuals were examined to test the assumptions of
normality, linearity, and homoscedasticity of residuals. The visual inspection of the charts and
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plots indicated that the residuals were normally distributed about the predicted score, the
residuals had a linear relationship with predicted scores, and the variances of residuals were
homogeneous for predicted scores.
Table 3.2
Multicollinearity Diagnostics for Independent Variables
Variable Tolerance VIF
Power-coercive strategy .463 2.161
Empirical-rational strategy .397 2.518
Normative-reeducative strategy .386 2.590
Power-coercive strategy × Normative-reeducative strategy .371 2.693
Empirical-rational strategy × Normative-reeducative strategy .446 2.243
Learning culture (overall) .721 1.388
Normative-reeducative strategy × Learning culture (overall) .596 1.678
Change impact .856 1.168
Normative-reeducative strategy × Change impact .683 1.464
Learning culture (overall) × Change impact .695 1.438
Age .788 1.269
Gender .865 1.156
Education .812 1.231
Organizational tenure .844 1.186
Negative affectivity .810 1.235
Note. All independent variables involved in the interaction effects were centered.
As a further check, the Kolmogorov-Smirnov test and the Shapiro-Wilk test were
conducted with a null hypothesis that the residuals come from a normal distribution (Table 3.3).
With the exception of the fourth dimension of readiness for change, the tests failed to reject the
null hypothesis, providing further evidence of normality of the residual terms. As for the last
dimension (R4), the two tests provided conflicting results: the Kolmogorov-Smirnov test failed
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to reject the null hypothesis whereas the Shapiro-Wilk test rejected the null hypothesis at the .05
level of significance. Since the Kolmogorov-Smirnov test and the visual inspection of the plot
provided support for the normality of the residuals, I continued with the analysis assuming that
the regression residuals in predicting the personal benefit of the change dimension of readiness
for change (R4) were normally distributed.
Table 3.3
Tests of Normality of Residuals
Dependent variable Kolmogorov-Smirnov
statistic (p-value)
Shapiro-Wilk
statistic (p-value)
Overall readiness for change .071 (.074) .984 (.093)
Change-specific efficacy (R1) .072 (.063) .983 (.068)
Appropriateness of the change (R2) .059 (.200*) .993 (.653)
Management support for the change (R3) .039 (.200*) .993 (.682)
Personal benefit of the change (R4) .068 (.200*) .979 (.029)
Note. * This is a lower bound of the true significance
As a result of data screening, the respondent group was reduced to 151. Table 3.4
presents the composition of the respondents. Power analyses were conducted separately for each
hypothesis of this study with the program and procedure developed by Faul, Erdfelder, Buchner,
and Lang (2009). The analyses indicated power levels above .095, suggesting that the sample
size was appropriate for minimizing Type II errors in testing the hypotheses of this study
(Dattalo, 2008).
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Table 3.4
Demographic Information of the Respondents
Variable Mean SD Frequency Percent
Gender
Male 36 23.84
Female 115 76.16
Age 49.14 10.788
20-29 8 5.41
30-39 26 16.89
40-49 34 22.30
50-59 57 37.84
Older than 60 27 17.57
Educational level
High school graduate 11 7.38
Associate's degree 22 14.77
Bachelor's degree 44 28.90
Professional or master’s degree 67 44.30
Doctoral degree 7 4.70
Tenure in the organization 7.72 6.964
Less than 5 68 44.90
5-9 40 26.53
10-14 16 10.88
15-19 13 8.84
20-24 9 6.12
More than 25 4 2.72
The average age of respondents was 49.14 years; 76.16 percent were women, and the
median level of education was bachelor’s degree (the range was from high school graduate to
doctoral degree). Average tenure within the studied organization was 7.72 years. The
composition of the respondents appears to be typical considering the characteristics of the
workforce in the healthcare industry. Specifically, given that hospitals are often characterized by
a workforce composed mostly of women (Konovsky & Pugh, 1994), the ratio of female and male
respondents of this study appears to be normal. In addition, even though health diagnosing and
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treating practitioners (e.g., physicians) are highly educated and usually have advanced degrees,
most workers (e.g., health technologists and technicians, service workers) have jobs that require
less than 4 years of college education (Bureau of Labor Statistics, 2010). So the fact that the
educational level of respondents from the hospitals covers a wide range, with bachelor’s degree
in the median, appears to reflect the industry norm.
Reliability and Validity
In a quantitative study, reliability concerns the degree to which the scores are free from
random measurement error. Validity concerns the degree to which the scores measure what they
are supposed to measure and do not measure what they are not supposed to measure (Kline,
2005). What follows is a description of the steps taken to ensure the reliability and validity of the
measures used in this study.
Reliability
Among several types of reliability, internal consistency reliability, an indicator of how
well the individual items of a scale reflect a common underlying construct (Spector, 1992), is
often used to test the reliability of a survey instrument. If internal consistency reliability is low, it
means that the content of the items may be so heterogeneous that the total score is not the best
possible unit of analysis for the measure (Kline, 2005). Cronbach’s alpha is a statistic most often
used to assess internal consistency.
Concerning the perception of change leadership strategy scale, Szabla’s (2007) study
showed that Cronbach’s alphas for the three categories of change strategies ranged from .73
to .81, which indicated high reliability of the scale. Cronbach’s alphas for the three categories of
change strategies resulting from the current study ranged from .741 to .869, also indicating high
reliability of the scale (Table 3.5).
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The shortened version of the DLOQ (Marsick & Watkins, 2003; Yang, 2003) has been
used in a wide variety of settings and has shown high to moderate reliability. For example, in
two of the previous studies, Cronbach’s alphas for the seven dimensions ranged from .68 to .83,
and Cronbach’s alpha for the 21-item scale was .93 (Yang, 2003; Yang et al., 2004). Cronbach’s
alphas for the seven dimensions resulting from the current study ranged from .812 to .900 and
that for overall learning culture (21 items) was .959 (Table 3.5).
Concerning the readiness for change scale, Holt et al.’s (2007) study showed high to
moderate reliability with Cronbach’s alphas for the four dimensions ranging from .66 to .94.
Current study showed that Cronbach’s alphas for the four dimensions ranged from .816 to .933
and that for overall readiness for change (25 items) was .950, indicating high reliability of the
scale (Table 3.5).
In previous studies, the six items to measure individual job level impact of a change also
showed high reliability with Cronbach’s alphas of .81 (Caldwell et al., 2004) and .75 (Fedor et
al., 2006). In the current study, Cronbach’s alpha of the six-item measure of individual job level
impact change was .887 (Table 3.5).
Finally, previous studies using the negative portion of PANAS Scales showed high
reliability with Cronbach’s alphas ranging from .87 to .91 (Folger & Konovsky, 1989; Wanous et
al., 2000; Watson et al., 1988). The reliability estimate resulting from the current study was .837
(Table 3.5).
In all, the reliability estimates of the measures used in this study met the criteria
suggested by Nunnally (1978), which is .7. Consistent with the previous studies, this study
reported high to moderate levels of reliability of the measures included in the survey instrument
of this study.
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Table 3.5
Reliability Estimates of the Measures
Measure
Pilot Study Current Study
Cronbach’s
alpha
Cronbach’s alpha
on standardized
items
Cronbach’s
alpha
Cronbach’s alpha
on standardized
items
Change strategy
Power-coercive strategy .701 .703 .742 .741
Empirical-rational strategy .774 .774 .866 .869
Normative-reeducative strategy .777 .780 .765 .777
Learning culture
Creating continuous learning .864 .874 .802 .812
Promoting inquiry and dialogue .858 .859 .883 .883
Team learning .822 .831 .875 .879
Empowering people .868 .869 .825 .826
Shared systems .890 .890 .820 .821
System connectedness .772 .774 .799 .800
Provide leadership .911 .912 .898 .900
Individual job level impact of change .803 .805 .886 .887
Readiness for change
Appropriateness .926 .928 .930 .933
Management support .924 .924 .905 .907
Change-specific efficacy .836 .848 .825 .837
Personal benefit .708 .717 .815 .816
Negative affectivity .839 .826 .828 .837
Validity
Most forms of score validity are subsumed under the concept of construct validity, which
represents the degree to which scores on the items measure the hypothetical construct the
researcher believes they do. Content validity, which is a facet of construct validity, particularly
concerns the extent to which items on a scale are representative of the domain they are supposed
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to measure (Kline, 2005). To examine and improve the content validity of the survey instrument
of this study, a group of experts reviewed the items on the survey instrument. The experts
included two professors on the dissertation committee, two doctoral students in the HROD
program, and 16 practitioners in the fields of HROD and adult education recruited from a pool of
part-time graduate students and graduates of the HROD program at the University of Georgia.
Feedback from the group was used to refine the survey instrument by rephrasing instructions and
items as necessary.
To further examine the construct validity of the measures included in the instrument,
confirmatory factor analysis (CFA) was conducted. CFA estimates the quality of the factor
structure and designated factor loadings by statistically testing the fit between a proposed
measurement model and the data (Kline, 2005). The CFAs for this study were conducted using
LISREL version 8.70 (Jöreskog & Sörbom, 2004).
Although no single criterion for assessing goodness of fit has been established, several
authors recommended sets of criteria (e.g., Hu & Bentler, 1998, 1999, 1995; Quintana &
Maxwell, 1999; Weston & Gore, 2006). Using Hu and Bentler’s (1998, 1995) recommendations,
the following fit indices were examined in this study: χ2, standardized root mean square residual
(SRMR), root mean square error of approximation (RMSEA), comparative fit index (CFI), non-
normed fit index (NNFI), and incremental fit index (IFI). The first three indices are stand-alone
fit indices which assess how well the tested model reproduces the original data, without
consulting a reference model. The other three indices are incremental fit indices which measure
improvement in fit by comparing the tested model with a baseline model (Hu & Bentler, 1995;
Kline, 2005). The characteristics of these fit indices and their cut-off values suggested by
researchers are summarized in Table 3.6.
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Table 3.6
Fit Indices and Cut-Off Values
Fit index Characteristics Cut-off value
2 Assessing the magnitude of discrepancy between the
original and the model-implied covariance matrices
and, therefore, directly testing how well a model fits
the observed data
The smaller, the better fit
SRMR Standardized value of an average of the residuals
between individual observed and estimated covariance
and variance terms
Being sensitive to the simple misspecified model
.08 or lower (Hu & Bentler, 1999)
RMSEA Assessing how well a model fits a population not just a
sample used for estimation
A standardized measure of the lack of fit that corrects
for model complexity
Being very sensitive to misspecified factor loadings
.06 or lower (Hu & Bentler, 1998)
.10 or lower (Quintana &
Maxwell, 1999)
CFI Assessing the degree of fit between the hypothesized
and null measurement models (Making a comparison
of the tested and baseline model non-centrality
parameters)
Being very sensitive to misspecified factor loadings
.95 or higher (Hu & Bentler,
1998, 1999)
NNFI A relative fit index that compares the model being
tested to a baseline model (null model), taking into
account the degree of freedom (Considering the
complexity of the model by using the degrees of
freedom for the baseline and tested model)
.95 or higher (Hu & Bentler,
1998, 1999)
IFI Comparing the difference in fit of the baseline and
tested models to the difference in the fit of the baseline
model and the ideal fit of the tested model
.95 or higher (Hu & Bentler,
1998, 1999)
Change strategies. A series of CFAs was conducted to examine the measurement models
(see Table 3.7 for the summary). The first CFA examined the measurement model of change
strategies. The standardized factor loadings between the latent variables (three change strategies)
and their indicators ranged from .45 to .84, indicating that each item was a good to moderately
acceptable indicator of the latent variables. The chi-square value for the current model indicated
a poor fit (χ2=161.85, df=87, p<.001). However, researchers have noted that chi-square
has some
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limitations, including the possibility of rejecting the model even when it reproduces the original
data well (Hu & Bentler, 1995; Weston & Gore, 2006) and that it needs to be supplemented with
additional fit indices. Among the fit indices examined in this study, chi-square was the only one
that indicated a poor fit. The SRMR, RMSEA, CFI, NNFI, and IFI values indicated a good
model fit (SRMR =.068, RMSEA=.078, CFI=.97, NNFI=.96, IFI=.97). Thus, I concluded that
this measurement model of change strategies adequately reproduced the data collected from the
sample.
Learning culture. To examine the measurement model of the learning culture, three CFAs
were conducted. Specifically, the first CFA examined whether the 21 items measured the seven
dimensions of the learning culture (i.e., whether each item loaded best on the dimension it was
supposed to do). The standardized factor loadings between the latent variables (i.e., the seven
dimensions of learning culture) and their indicators ranged from .72 to .94, indicating that each
item was an adequate indicator of the latent variables. The chi-square value resulting from this
CFA indicated a poor fit (χ2=297.56, df=168, p<.001). However, the SRMR, RMSEA, CFI,
NNFI, and IFI values from the analysis indicated a good model fit (SRMR =.043, RMSEA=.073,
CFI=.99, NNFI=.98, IFI=.99). Thus, I concluded that the measurement model of the learning
culture with 7 factors and 21 items presented a good fit to the data collected from the sample.
The second CFA examined whether the 21 items measured one variable, overall learning
culture (i.e., whether all the items loaded on one latent variable). The standardized factor
loadings between the latent variable and their indicators ranged from .58 to .86. The fit indices
showed mixed results. Specifically, both the chi-square value and the RMSEA value resulting
from the second CFA indicated a poor fit (χ2=662.48, df=189, p<.001; RMSEA=.13). On the
other hand, the SRMR, CFI, NNFI, and IFI values from the analysis indicated a good model fit
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(SRMR =.06, CFI=.96, NNFI=.96, IFI=.96). The difference in the chi-square values of the first
and the second CFAs (∆χ2=364.92. ∆df=21) was significant at the .001 level, indicating that the
first measurement model provided a better fit to the data than the second measurement model. In
other words, the measurement model of learning culture with seven factors (seven dimensions of
the learning culture) reproduced the data better than the model with one factor (overall learning
culture). The values of other fit indices, which were discussed above, provided additional
evidence supporting this conclusion.
In Watkins and Marsick’s (1993) framework, learning culture is considered to subsume
or affect the seven dimensions (factors) included in the previous CFA model. In this respect, the
DLOQ has a hierarchical structure—that is, the seven dimensions are the first-order factors and
the learning culture is the second-order factor. To examine the measurement model with a
second-order factor (the learning culture) in addition to the first-order factors (the seven
dimensions) and their indicators (21 items), hierarchical CFA (Kline, 2005) was conducted. The
standardized factor loadings between the second-order factor and the seven first-order factors
ranged from .79 to .97, and those between the seven first-order factors and the 21 indicators
ranged from .73 to .94. The chi-square value indicated a poor fit (χ2=359.22, df=182, p<.001).
However, the SRMR, RMSEA, CFI, NNFI, and IFI values from the analysis indicated a good
model fit (SRMR=.051, RMSEA=.083, CFI=.98, NNFI=.98, IFI=.98). Thus, I concluded that the
hierarchical CFA model also presented a good fit to the data collected from the sample. Based on
this result, in this study the learning culture (overall learning culture) was measured by averaging
the scores on the seven dimensions.
Readiness for change. The same procedure was applied to examine the measurement
model of readiness for change. The first CFA was conducted to examine whether the 25 items
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measured the four dimensions of readiness for change (i.e., whether each item loaded best on the
dimension it was supposed to do). The standardized factor loadings between the four dimensions
and their indicators ranged from .44 to .86. The chi-square value resulting from the first CFA
indicated a poor fit (χ2=588.84, df=269, p<.001). Additionally, the SRMR value indicated a
marginally acceptable fit (SRMR =.081). However, the RMSEA, CFI, NNFI, and IFI values
from the analysis indicated a good model fit (RMSEA=.091, CFI=.96, NNFI=.95, IFI=.96).
Given the limitations of the chi-square (Hu & Bentler, 1995; Weston & Gore, 2006) and the fact
that the RMSEA, CFI, NNFI, and IFI values from the analysis indicated a good fit, I assumed
that the measurement model of readiness for change with 4 factors and 25 items presented a good
fit to the data collected from the sample.
The second CFA examined whether the 25 items measured one variable, overall
readiness for change (i.e., whether all the items loaded on one latent variable). The standardized
factor loadings between the latent variable and their indicators ranged from .36 to .82. The fit
indices showed mixed results. Specifically, all the fit indices resulting from this second CFA
indicated a poor fit (χ2=1466.18, df=275, p<.001; SRMR =.11; RMSEA=.174; CFI=.89;
NNFI=.88; IFI=.89). The difference in the chi-square values of the first and the second CFAs
(∆χ2=877.34. ∆df=6) was significant at the .001 level, indicating that the first measurement
model provided a better fit to the data than the second measurement model. In sum, the
measurement model of readiness for change with four factors (four dimensions of readiness for
change) reproduced the data better than the model with one factor (overall readiness for change).
Additionally, in Holt et al.’s (2007) model, readiness for change is supposed to subsume
all four dimensions (change-specific efficacy, appropriateness of the change, management
support for the change, and personal benefit of the change). That is, the four dimensions are the
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first-order factors and readiness for change is the second-order factor in the measurement model
of readiness for change. To examine the measurement model, hierarchical CFA was conducted.
The standardized factor loadings between the second-order factor and the four first-order factors
ranged from .63 to .95, and those between the four first-order factors and the 25 indicators
ranged from .44 to .86. The chi-square value resulting from this second CFA indicated a poor fit
(χ2=592.57, df=271, p<.001). However, the SRMR, RMSEA, CFI, NNFI, and IFI values from
the analysis indicated an acceptable to good model fit (SRMR =.081, RMSEA=.091, CFI=.96,
NNFI=.95, IFI=.96). Thus, I concluded that the hierarchical CFA model also presented a good fit
to the data collected from the sample. Based on this result, in this study overall readiness for
change was measured by averaging the scores on the four dimensions.
Change impact. Finally, CFA was conducted to examine the measurement model of
change impact. The standardized factor loadings between the latent variable (change impact) and
the indicators ranged from .48 to .89. All the fit indices resulting from the first CFA indicated a
good model fit (χ2= 2.52, df=5, p=.28; SRMR=.018; RMSEA=.043; CFI=1.00; NNFI=.99;
IFI=1.00).
The results of CFAs discussed in this section are summarized in Table 3.7. Figures with
the standardized factor loadings of the measurement models are presented in Appendix C.
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Table 3.7
Fit Indices for the Measurement Models
Measurement model 2 SRMR RMSEA CFI NNFI IFI
Model
fit
Change strategies 161.85
(df=87, p<.001) .068 .078 .97 .96 .97 Good
Learning culture: First-order
CFA (seven factors)
297.56
(df=168, p<.001) .043 .073 .99 .98 .99 Good
Learning culture: Hierarchical
CFA (seven first-order factors
and one second-order factor)
359.22
(df=182, p<.001) .051 .083 .98 .98 .98 Good
Readiness for change: First-
order CFA (four factors)
588.84
(df=269, p<.001) .081 .091 .96 .95 .96 Good
Readiness for change:
Hierarchical CFA (four first-
order factors and one second-
order factor)
592.57
(df=271, p<.001) .081 .091 .96 .95 .96 Good
Change impact 2.52
(df=5, p=.28) .018 .043 1.00 .99 1.00
Good
Data Analysis
In Chapter 2, several hypotheses were proposed to address the three research questions of
this study. Research Question 1 was ―What is the relationship between the change strategy
perceived by those responding to a planned change and their readiness for change?‖ Following
six hypotheses were proposed to address this research question.
Hypothesis 1a: The power-coercive change strategy will be negatively related to
readiness for change
Hypothesis 1b: The normative-reeducative change strategy will be positively related to
readiness for change.
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Hypothesis 1c: The empirical-rational change strategy will be positively related to
readiness for change
Hypothesis 2: The normative-reeducative change strategy will be more effective than the
empirical-rational change strategy in fostering readiness for change.
Hypothesis 3a: The normative-reeducative change strategy will moderate the relationship
between the power-coercive change strategy and readiness for change. Specifically, the
stronger the normative-reeducative change strategy is, the weaker the negative
relationship between the power-coercive change strategy and readiness for change will be.
Hypothesis 3b: The normative-reeducative change strategy will moderate the relationship
between the empirical-rational change strategy and readiness for change. Specifically, the
stronger the normative-reeducative change strategy is, the stronger the positive
relationship between the empirical-rational change strategy and readiness for change will
be.
Research question 2 of this study was ―What is the relationship between the learning
culture perceived by those responding to a planned change and their readiness for change?‖ To
address this research question, following two hypotheses were proposed.
Hypothesis 4a: Learning culture will be positively related to readiness for change.
Hypothesis 4b: Learning culture will moderate the relationship between the normative-
reeducative change strategy and readiness for change. Specifically, the stronger the
learning culture is, the stronger the positive relationship between the normative-
reeducative change strategy and readiness for change will be.
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Research Question 3 was ―How does the impact of the change on individuals’ jobs affect
the two relationships presented in the first two research questions?‖ Three hypotheses concerning
the role of individual job level impact were proposed to address this research question.
Hypothesis 5a: The magnitude of individual job level impact will be negatively related to
readiness for change.
Hypothesis 5b: The magnitude of individual job level impact will moderate the
relationship between the normative-reeducative change strategy and readiness for change.
Specifically, the stronger the individual job level impact is, the stronger the positive
relationship between the normative-reeducative change strategy and readiness for change
will be.
Hypothesis 5c: The magnitude of individual job level impact will moderate the
relationship between learning culture and readiness for change. Specifically, the stronger
the individual job level impact is, the stronger the relationship between learning culture
and readiness for change will be.
As these hypotheses illustrate, this study included a set of independent variables and
aimed to examine their influences on a dependent variable. Therefore, multiple regression
analysis, a multivariate technique which is suited for analyzing collective and separate effects of
two or more independent variables on a single dependent variable (Pedhazur, 1997), was selected
as the primary technique to test the hypotheses. Hierarchical regression framework was used
when necessary.
Hierarchical Regression Analysis
With hierarchical regression, which is also called incremental partitioning of variance
(Pedhazur, 1997) or sequential multiple regression (Keith, 2006), the variables are entered into
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the regression equation in some order determined in advance. The order of entry of independent
variables in the regression model is crucial and should be determined by causal priority (a theory
about the pattern of relations among the variables under study) or by the need to remove
confounding or spurious relationships (P. Cohen, Cohen, West, & Aiken, 2003; Pedhazur, 1997).
Generally, potentially confounding variables or nuisance variables that need to be controlled for
are entered in the first and subsequent steps; and the variables of main interest are entered in the
final step. In this study, following Cohen et al.’s instructions, variables related to individual
differences (age, gender, educational level, organizational tenure, negative affectivity) were
entered in step 1 as they were not of central interest to this study and, in fact, were nuisance
variables that needed to be controlled for. Independent variables of each hypothesis were entered
in step 2. To test Hypotheses 1a, 1b, 1c, 4a, and 5a, these first two steps were used.
Among the hypotheses proposed in Chapter Two, Hypotheses 3a, 3b, 4b, 5b, and 5c were
concerned with the role of a moderator. A moderator affects the relationship between an
independent and a dependent variable, so that the direction and/or strength of the relationship
vary according to the level or value of the moderator (Baron & Kenny, 1986; Holmbeck, 1997).
Hierarchical regression analysis has been advocated as the method of choice for testing
interactive effects when the moderator is continuous (P. Cohen et al., 2003). When testing these
hypotheses involving moderators, the interaction term obtained by multiplying a moderator
variable by an independent variable was entered in step 3, following step 1 and step 2 as
explained above. The interaction term should be entered after the independent variables because
interaction effects are meaningful only after the main effects are partialled out (P. Cohen et al.,
2003). The moderating effect was indicated by a significant increase in the squared multiple
correlation coefficient (∆R2) from step 2 to step 3.
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In addition, to further explore the nature of the moderating effects, separate regression
lines of the dependent variable on the independent variable were generated for the high and low
levels of the moderator. One standard deviation above the mean and one standard deviation
below the mean were designated as the values for the high and low levels of the moderator,
respectively (Aiken & West, 1991; P. Cohen et al., 2003). This comparison of regression lines
was conducted only when a statistically significant interaction was found and was used as an aid
to probing the nature of this interaction.
Dominance Analysis
Multiple regression, including the hierarchical approach, uses a residualization approach
to variance partitioning. Therefore, shared variance among variables is assigned to the variable
entered first in the hierarchical sequence (Pedhazur, 1997). As a consequence, the importance of
a variable is dependent upon its unique contribution to prediction after partialling out any
variance shared with variables entered previously in the hierarchical sequence. Thus,
standardized regression coefficients (beta weights) are not the most appropriate gauge of the
unique value of and the relative importance of a variable, especially in the presence of
multicollinearity (Budescu, 1993; J. W. Johnson, 2000).
Hypothesis 2 deals with the relative importance of one variable over another. To test the
hypothesis, an approach called dominance analysis (Azen & Budescu, 2003; Budescu, 1993) was
used in this study. While conducted within a hierarchical regression framework, dominance
analysis is an alternative analytic strategy that assesses the relative importance of more than one
variable to prediction. Instead of taking residualization approach to variance partitioning,
dominance analysis computes the average variance accounted for by each variable by examining
all possible combinations of variables in a regression sequence. Through the process, each
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variable’s direct effect, total effect, and partial effect are assessed (Budescu, 1993). These three
effects are then averaged together into an index, M(Cxi), which then can be used to compare the
relative importance among variables. Dominance analysis has been widely used to accurately
determine the relative importance of variables (e.g., Eby et al., 2000; Eby, Butts, & Lockwood,
2003).
Delimitations of the Study
This study is based on data collected through self-report surveys. The key variables of
this study, which are organizational level variables (i.e. change strategies and learning culture),
were defined and assessed in terms of how they were evaluated or experienced by individuals.
Based on previous researchers’ arguments (Judge et al., 1999; Lau & Woodman, 1995; Mohrman
et al., 1989; Rentsch, 1990; Spreitzer, 1996, 2007), I justified this approach and highlighted its
benefits in the early part of this chapter. Measuring components of readiness for change at the
organizational level (Preskill & Torres, 1999a, 1999b, 2001), as useful as that might be, is
beyond the scope of this study.
This study did not attempt to evaluate the effectiveness of the specific change efforts
examined in this study. Instead, the study focused only on the relationships among the variables
of interest. In addition, this study took a cross-sectional approach (Merriam & Simpson, 2000)
and measured how individuals perceived the change strategies, the learning culture, and the
impact of a certain change on their jobs, and how much they felt ready for the change at a single
point in time. That is, the study did not measure how individuals perceive the factors over time.
Finally, considering that readiness for change may be a complex and emotionally loaded
response to organizational change, more in-depth, exploratory qualitative approaches would also
be useful. Rather than focusing on interpretation and in-depth analysis of the responses, however,
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this study focused on examining the relationships among the variables of interest which were
derived from the relevant literature.
Summary of the Chapter
This chapter included a detailed description of the research design, conceptual framework,
instrumentation, sample selection, data collection, data preparation and screening, reliability and
validity, data analysis, and delimitations of this study. This descriptive study employed a survey
design, and a quantitative survey was used as the method of data collection. Data were collected
in a healthcare organization where an organization-wide change initiative was underway at the
time the study was conducted. Prior to the analysis, reliability and validity of the measures were
examined and assumptions of multiple regression analysis were checked with the collected data.
To test the hypotheses proposed in Chapter Two, a series of hierarchical multiple regression
analyses and dominance analyses was conducted.
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CHAPTER FOUR
RESULTS
This chapter presents the results of the statistical analyses described in Chapter Three.
The findings are organized in relation to each of the three research questions of this study.
Descriptive Statistics and Preliminary Analyses
Table 4.1 shows the descriptive statistics and zero-order correlations among study
variables. The pattern of correlations in Table 4.1 provides initial support for several hypotheses.
As it shows, the power-coercive change strategy (henceforth, PC), the normative-reeducative
change strategy (henceforth, NR), and the empirical-rational change strategy (henceforth, ER)
were all related to readiness for change in the expected direction. In addition, the seven
dimensions of learning culture and change impact were also related to readiness for change in the
expected direction. The dimensions of learning culture were all significantly intercorrelated, and
the dimensions of readiness for change were also significantly intercorrelated.
Among the individual difference variables included in this study (age, gender,
organizational tenure, educational level, and negative affectivity), age and gender were
significantly related to readiness for change. Specifically, age was negatively related to overall
readiness for change (r=-.189, p<.05); among the survey respondents, men tended to be more
ready for change than women (t=3.190, p<.01). On the other hand, as Table 4.1 shows,
organizational tenure, educational level, and negative affectivity (NA) were not significantly
related to readiness for change.
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Table 4.1
Descriptive Statistics and Intercorrelations between Study Variables
M SD 1 2 3 4 5 6 7 8 9 10
1. R1 4.00 .581
2. R2 3.79 .608 .653**
3. R3 3.65 .643 .532**
.648**
4. R4 3.77 .817 .549**
.668**
.414**
5. R (O) 3.80 .536 .810**
.932**
.796**
.748**
6. PC 2.55 .631 -.515**
-.519**
-.442**
-.559**
-.599**
7. ER 3.64 .611 .439**
.569**
.575**
.381**
.608**
-.518**
8. NR 3.21 .676 .300**
.440**
.531**
.324**
.490**
-.537**
.687**
9. LC1 3.85 .719 .269**
.213**
.212**
.204* .265
** -.397
** .272
** .315
**
10. LC2 3.61 .805 .134 .087 .099 .133 .127 -.319**
.194* .273
** .816
**
11. LC3 3.54 .777 .249**
.268**
.279**
.233**
.309**
-.436**
.341**
.423**
.760**
.771**
12 LC4 3.50 .752 .317**
.366**
.322**
.248**
.386**
-.316**
.249**
.305**
.567**
.479**
13. LC5 3.40 .796 .278**
.258**
.230**
.250**
.301**
-.408**
.238**
.348**
.712**
.645**
14. LC6 3.71 .752 .245**
.275**
.312**
.239**
.323**
-.404**
.379**
.409**
.711**
.684**
15. LC7 3.72 .783 .200* .270
** .211
** .181
* .268
** -.368
** .313
** .356
** .691
** .691
**
16. LC (O) 3.62 .654 .284**
.292**
.280**
.250**
.333**
-.445**
.334**
.408**
.882**
.857**
17. CI 3.12 .854 -.195* -.155 -.100 -.292
** -.203
* .205
* -.164
* -.125 -.031 .006
18. AGE 49.14 10.788 -.189* -.209
* -.246
** -.149 -.242
** .043 -.083 -.061 .040 .056
19. GEN .24 .429 -.198* -.245
** -.193
* -.202
* -.255
** .154 -.179
* -.095 -.116 -.021
20. TEN 7.72 6.964 -.040 -.047 .009 .010 -.027 -.054 .030 .048 .052 .023
21. EDU 3.24 1.011 -.011 -.096 -.074 -.007 -.069 -.079 -.018 .017 .056 .019
22. NA 1.27 .393 -.103 -.033 .103 -.082 -.027 .142 -.080 -.125 -.182* -.183
*
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Table 4.1
Descriptive Statistics and Intercorrelations between Study Variables (cont’d)
Note. R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal benefit of the change;
R(O): overall readiness for change; PC: power-coercive strategy; ER: empirical-rational strategy; NR: normative-reeducative strategy; LC1:
creating continuous learning opportunities; LC2: promoting inquiry and dialogue; LC3: encouraging collaboration and team learning; LC4:
empowering people toward a collective vision; LC5: establishing systems to capture and share learning; LC6: connecting the organization to its
environment; LC7: providing strategic leadership for learning; LC (O): overall learning culture; CI: change impact on an individual’s job; GEN:
gender; TEN: organizational tenure; EDU: educational level; NA: negative affectivity. †p<.10, *p<.05, **p<.01, ***p<.001.
11 12 13 14 15 16 17 18 19 20 21
1. R1
2. R2
3. R3
4. R4
5. R (O)
6. PC
7. ER
8. NR
9. LC1
10. LC2
11. LC3
12 LC4 .621**
13. LC5 .740**
.622**
14. LC6 .742**
.586**
.688**
15. LC7 .694**
.556**
.653**
.771**
16. LC (O) .897**
.743**
.851**
.869**
.850**
17. CI -.093 -.069 -.001 .026 .037 -.022
18. AGE .037 -.127 .054 -.026 .078 .018 .119
19. GEN .013 -.062 -.025 -.116 -.039 -.060 .100 .002
20. TEN -.016 -.054 .027 -.037 -.061 -.010 -.018 .219**
.062
21. EDU .100 .036 .107 .004 .046 .061 .143 .193* .191
* -.070
22. NA -.212**
-.051 -.160 -.120 -.179* -.182
* .131 -.163
* .044 .119 -.036
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Research Question 1: Change Strategies and Readiness for Change
Research Question 1 is ―What is the relationship between the change strategy perceived
by those responding to a planned change and their readiness for change?‖ The findings related to
Research Question 1 are organized into three themes: (a) the relationship between each of the
change strategies and readiness for change, (b) the relative importance of the change strategies in
understanding readiness for change, and (c) the moderating effects of the normative-reeducative
change strategy.
Relationship between Change Strategies and Readiness for Change
Table 4.2 presents the relationship between each of the three change strategies and
readiness for change partialling out gender, age, educational level, organizational tenure, and NA.
When these individual difference variables were controlled for, PC was negatively related to
overall readiness for change (r=-.592, p<.001). Also, PC was negatively related to all four
dimensions of readiness for change: change-specific efficacy (r=-.487, p<.001), appropriateness
of the change (r=-.509, p<.001), management support for the change (r=-.443, p<.001), and
personal benefit of the change (r=-.532, p<.001). Therefore, Hypothesis 1a was supported.
In addition, NR was positively related to overall readiness for change (r=.478, p<.001).
NR was also positively related to all four dimensions of readiness for change: change-specific
efficacy (r=.265, p<.01), appropriateness of the change (r=.426, p<.001), management support
for the change (r=.541, p<.001), and personal benefit of the change (r=.290, p<.001). Therefore,
Hypothesis 1b was supported.
Finally, ER was positively related to overall readiness for change (r=.586, p<.01). ER
was also positively related to all four dimensions of readiness for change: change-specific
efficacy (r=.402, p<.001), appropriateness of the change (r=.545, p<.001), management support
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for the change (r=.567, p<.001), and personal benefit of the change (r=.339, p<.001). Therefore,
Hypothesis 1c was supported.
Table 4.2
Partial Correlations between Change Strategies and Readiness for Change
R(O) R1 R2 R3 R4
PC -.592*** -.487*** -.509*** -.443*** -.532***
NR .478*** .265** .426*** .541*** .290***
ER .586** .402*** .545*** .567*** .339***
Note. Gender, age, educational level, organizational tenure, and NA were partialled out from all
correlations. PC: power-coercive strategy; NR: normative-reeducative strategy; ER: empirical-rational
strategy; R(O): overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the
change; R3: management support for the change; R4: personal benefit of the change. **p<.01, ***p<.001.
To investigate the influence of each change strategy on readiness for change, hierarchical
regression analysis was conducted (Table 4.3). Across all the regression equations, the control
variables were entered in step 1, and each of the change strategies was added in step 2. As Table
4.3 reports, change strategies accounted for a significant amount of the variance in overall
readiness for change and in all its four dimensions. Specifically, beyond the explanation
provided by the individual differences variables, PC accounted for an additional 32.8% of the
variance in overall readiness for change (p<.001) and an additional 20.1 % to 25.9 % of the
variance in the four dimension of readiness for change (p<.001). Beyond the contributions of
individual differences, NR explained an additional 23.1% of the variance in overall readiness for
change (p<.001) and an additional 8.0 % to 28.2 % of the variance in the four dimensions of
readiness for change (p<.001). Finally, ER accounted for an additional 32.5% of the variance in
overall readiness for change (p<.001) and an additional 12.3 % to 29.9 % of the variance in the
four dimension of readiness for change (p<.001).
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Table 4.3
Readiness for Change Regressed on Change Strategies
R(O) R1 R2 R3 R4
Step 1
GEN -.144* -.206** -.187* -.114 -.175* -.129† -.135† -.190* -.134† -.108 -.140* -.093 -.118 -.183* -.151†
AGE -.177* -.176* -.008* -.157* -.170* -.157† -.140† -.139† -.128† -.177* -.155* -.156* -.116 -.129 -.127
EDU -.061 .001 .003 -.001 .054 .055 -.093 -.038 -.035 -.060 -.020 -.012 -.004 .054 .059
TEN -.010 -.003 .000 -.015 .003 -.001 -.037 -.031 -.031 .022 .009 .021 .023 .040 .045
NA .034 .018 .004 -.053 -.083 -.085 .028 .014 .003 .141† .153* .127† -.028 -.058 -.071
Step 2
PC -.596*** -.480*** -.530*** -.467*** -.518***
NR .493*** .290*** .438*** .544*** .329***
ER .509*** .413*** .550*** .563*** .361***
∆R2 .328 .231 .325 .213 .080 .161 .259 .183 .285 .201 .282 .299 .248 .103 .123
∆F 81.037
***
48.622
***
80.023
***
41.638
***
13.143
***
29.289
***
55.142
***
34.761
***
63.375
***
39.279
***
62.208
***
67.883
***
50.198
***
17.267
***
21.072
***
R2 .446 .349 .443 .300 .167 .248 .357 .280 .383 .299 .379 .396 .324 .180 .199
Note. Table entries are standardized regression coefficients. GEN: gender; EDU: educational level; TEN: organizational tenure; NA: negative
affectivity; PC: power-coercive strategy; NR: normative-reeducative strategy; ER: empirical-rational strategy. †p<.10, *p<.05, **p<.01,
***p<.001.
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In sum, Hypothesis 1a, Hypothesis 1b, and Hypothesis 1c were fully supported. As
expected, PC was negatively related to readiness for change and both ER and NR were positively
related to it (Tables 4.2 and 4.3). In addition, each change strategy accounted for a significant
portion of the variance in readiness for change (Table 4.3).
Relative Importance of the Change Strategies in Understanding Readiness for Change
Hypothesis 2 is concerned with the relative importance of the change strategies in
understanding readiness for change. To determine the relative importance of the change
strategies (PC, NR, and ER), dominance analysis (Azen & Budescu, 2003; Budescu, 1993) was
conducted.
Step 1 of the dominance analysis consists of computing separate regression equations
based on each possible ordering of variables. Based on the results, a qualitative assessment of
dominance is determined by comparing each pair of variables across all rows for which both
variables are not empty (Azen & Budescu, 2003; Budescu, 1993). Step 2 of the dominance
analysis involves a quantitative assessment of the relative importance of each variable (Azen &
Budescu, 2003; Budescu, 1993). In this step, an index, M(Cxi), which represents the average R2
for each variable across all possible orderings of variables—i.e., the average of the direct effect,
the average of the partial effects, and the total effect—is obtained.
To test Hypothesis 2, five dominance analyses were conducted: one for overall readiness
for change (Table 4.4) and four for the dimensions of readiness for change (Tables 4.5 through
4.8). The control variables—gender, age, educational level, organizational tenure, and NA—
were included in all regression equations.
Table 4.4 shows the results of step 1 of the dominance analysis for overall readiness for
change. Row 1 reports each of the three change strategies’ independent contributions to R2 (i.e.,
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the direct effect of each change strategy on overall readiness for change). Rows 2 through 4
report the effect of each of the remaining change strategies after one other change strategy is
already accounted for in the model (i.e., the partial effects of each change strategy on overall
readiness for change). Rows 5 through 7 show the incremental impact of each change strategy on
a regression equation already containing all of the other change strategies (i.e., the total effect of
each change strategy on overall readiness for change). The last row shows the maximum
explained R2
(.543). As row 1 in Table 4.4 shows, the contribution of PC was greater than those
of NR and ER. Data from rows 3 and 4 confirm this assertion: Row 3 shows that the contribution
of PC was greater than that of ER, and row 4 shows that the contribution of PC was greater than
that of NR. Regarding the dominance of NR versus ER, rows 1 and 2 show that the contribution
of ER was greater than that of NR.
Tables 4.5 through 4.8 report the results of step 1 of the dominance analysis for the four
dimensions of readiness for change. Consistent with the dominance analysis for overall readiness
for change (Table 4.4), the analysis for the change-specific efficacy dimension of readiness for
change (henceforth, R1) revealed that PC was dominant to both NR and ER and that ER was
dominant to NR (Table 4.5). The analysis for the personal benefit dimension of readiness for
change (henceforth, R4) showed the same pattern of dominance (Table 4.8). On the other hand,
the dominance analyses for the other two dimensions of readiness for change–the
appropriateness of the change dimension (henceforth, R2) and the management support for the
change dimension (henceforth, R3)–showed different patterns of dominance. The analysis for R2
showed that ER was dominant to both PC and NR and that PC was dominant to NR (Table 4.6).
The analysis for R3 showed that ER was dominant to both PC and NR and that NR was
dominant to PC (Table 4.7).
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Table 4.4.
Relative Importance of Change Strategies: Overall Readiness for Change
Variables already
in the equation
R2 accounted for by variables
already in the equation
Additional contribution of
PC NR ER
— .446 .349 .443
PC .446 — .033 .097
NR .349 .130 — .111
ER .443 .100 .017 —
PC, NR .478 — — .065
PC, ER .543 — .000 —
NR, ER .460 .083 — —
PC, NR, ER .543 — — —
Note. Control variables were included in all regression equations. PC: power-coercive strategy; NR:
normative-reeducative strategy; ER: empirical-rational strategy.
Table 4.5
Relative Importance of Change Strategies: Change-Specific Efficacy (R1)
Variables already
in the equation
R2 accounted for by variables
already in the equation
Additional contribution of
PC NR ER
— .300 .167 .248
PC .300 — .000 .033
NR .167 .133 — .081
ER .248 .085 .000 —
PC, NR .300 — — .041
PC, ER .333 — .008 —
NR, ER .248 .093 — —
PC, NR, ER .341 — — —
Note. Control variables were included in all regression equations. PC: power-coercive strategy; NR:
normative-reeducative strategy; ER: empirical-rational strategy.
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Table 4.6
Relative Importance of Change Strategies: Appropriateness of the Change (R2)
Variables already
in the equation
R2 accounted for by variables
already in the equation
Additional contribution of
PC NR ER
— .357 .280 .383
PC .357 — .026 .096
NR .280 .102 — .111
ER .383 .069 .008 —
PC, NR .382 — — .070
PC, ER .452 — .000 —
NR, ER .391 .061 — —
PC, NR, ER .452 — — —
Note. Control variables were included in all regression equations. PC: power-coercive strategy; NR:
normative-reeducative strategy; ER: empirical-rational strategy.
Table 4.7
Relative Importance of Change Strategies: Management Support for the Change (R3)
Variables already
in the equation
R2 accounted for by variables
already in the equation
Additional contribution of
PC NR ER
— .299 .379 .396
PC .299 — .110 .132
NR .379 .029 — .066
ER .396 .034 .049 —
PC, NR .409 — — .049
PC, ER .430 — .028 —
NR, ER .445 .013 — —
PC, NR, ER .458 — — —
Note. Control variables were included in all regression equations. PC: power-coercive strategy; NR:
normative-reeducative strategy; ER: empirical-rational strategy.
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Table 4.8
Relative Importance of Change Strategies: Personal Benefit of the Change (R4)
Variables already
in the equation
R2 accounted for by variables
already in the equation
Additional contribution of
PC NR ER
— .324 .180 .199
PC .324 — .002 .010
NR .180 .146 — .033
ER .199 .134 .013 —
PC, NR .325 — — .009
PC, ER .334 — .000 —
NR, ER .213 .121 — —
PC, NR, ER .334 — — —
Note. Control variables were included in all regression equations. PC: power-coercive strategy; NR:
normative-reeducative strategy; ER: empirical-rational strategy.
Table 4.9 summarizes the results of step 2 of the dominance analysis. Of the variance in
overall readiness for change, PC, NR, and ER accounted for 21.5%, 12.5%, and 20.4 %,
respectively. Of the total variance in overall readiness for change that could be attributed to the
three change strategies combined (R2=.544), PC made the most contribution (39.5%), followed
by ER (37.5%) and then by NR (23.0%). As Table 4.9 shows, the relative importance of PC, NR,
and ER varied across the dimensions of readiness for change. As for R1 and R4, change
strategies showed the same pattern of dominance: PC was the most important (49.1%, 58.2%),
followed by ER (33.8%, 23.0%) and then by NR (17.1%, 18.8%). On the other hand, for R2, ER
made the most contribution (41.1%), followed by PC (37.1%) and then NR (21.9%). For R3, ER
made the most contribution (39.5%), followed by NR (35.4%) and then PC (25.1%).
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Table 4.9
Relative Importance of Change Strategies: Dominance Matrices
PC NR ER
R (O) Direct effect (k=0) .446 .349 .443
Average of partial effect (k=1) .115 .025 .104
Total effect (k=2) .083 .000 .065
M (Cxi) .215 .125 .204
Relative percentage (Rank) 39.5% (1) 23.0% (3) 37.5% (2)
R1 Direct effect (k=0) .300 .167 .248
Average of partial effect (k=1) .109 .000 .057
Total effect (k=2) .093 .008 .041
M (Cxi) .167 .058 .115
Relative percentage (Rank) 49.1% (1) 17.1% (3) 33.8% (2)
R2 Direct effect (k=0) .357 .280 .383
Average of partial effect (k=1) .086 .017 .104
Total effect (k=2) .061 .000 .070
M (Cxi) .168 .099 .186
Relative percentage (Rank) 37.1% (2) 21.9% (3) 41.1% (1)
R3 Direct effect (k=0) .299 .379 .396
Average of partial effect (k=1) .032 .080 .099
Total effect (k=2) .013 .028 .049
M (Cxi) .115 .162 .181
Relative percentage (Rank) 25.1% (3) 35.4% (2) 39.5% (1)
R4 Direct effect (k=0) .324 .180 .199
Average of partial effect (k=1) .140 .008 .022
Total effect (k=2) .121 .000 .009
M (Cxi) .195 .063 .077
Relative percentage (Rank) 58.2% (1) 18.8% (3) 23.0% (2)
Note. k=the number of additional variables taken into account. Relative percentage indicates the relative
importance of each variable to overall prediction. PC: power-coercive strategy; NR: normative-
reeducative strategy; ER: empirical-rational strategy; R(O): overall readiness for change; R1: change-
specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4:
personal benefit of the change.
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Hypothesis 2 proposes that NR is more important than ER in fostering readiness for
change. According to the results of dominance analyses described in this section, ER was
consistently more important than NR in understanding overall readiness for change as well as its
four dimensions. Therefore, Hypothesis 2 was not supported. Even though Hypothesis 2 was not
supported, the dominance analysis results provide potentially significant implications. According
to the results, all three change strategies—PC, NR, and ER—made significant contributions to
the variance in readiness for change and, therefore, were all important in understanding readiness
for change. Furthermore, the analysis results showed that among the three change strategies PC,
which had a negative effect on readiness for change (Tables 4.2 and 4.3), made the most
contribution to prediction of overall readiness for change (Table 4.9). Therefore, in addition to
creating an environment in which employees experience ER and NR, making conditions to
minimize experiences related to PC is also critical in fostering readiness for change. The
implication of these findings will be discussed in Chapter Five in more detail.
Moderating Effects of the Normative-Reeducative Change Strategy
In Hypotheses 3a and 3b, NR is proposed as a moderator that specifies the conditions
under which the direction or strength of an effect varies. Specifically, Hypothesis 3a concerns the
moderating effect of NR on the relationship between PC and readiness for change. Hypothesis 3b
deals with the moderating effect of NR on the relationship between ER and readiness for change.
As explained in Chapter Three, hierarchical regression analyses were conducted to test
the moderating effect. The variables related to individual differences (age, gender, educational
level, organizational tenure, negative affectivity) were entered in step 1 as they were not of
central interest to this study and, in fact, were nuisance variables that needed to be controlled for.
To avoid possible problems with multicollinearity and to increase interpretability of interactions,
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all independent variables involved in the interaction effects were centered before they were
added to the regression equations (Aiken & West, 1991; P. Cohen et al., 2003). After being
centered, the independent variables were entered in step 2. Finally, the interaction term obtained
by multiplying the two independent variables was entered in step 3. The moderating effect was
indicated by a significant increase in the squared multiple correlation coefficient (∆R
2) when the
interaction term was added.
As Hypothesis 1a was supported, a target for testing the moderating effect of NR on the
relationship between PC and readiness for change was set up. Table 4.10 illustrates the procedure
and results of the test on Hypothesis 3a. The control variables were added in step 1; two
independent variables (PC and NR) were added in step 2; and finally the interaction term (PC ×
NR) was added in step 3. As Table 4.10 shows, NR had no significant moderating effect on the
relationship between PC and overall readiness for change or on the relationship between PC and
three of the four dimensions of readiness for change. The interaction was significant only for R1
(∆R2=.033, p<.05), indicating that NR significantly moderated the negative relationship between
PC and R1.
To further investigate the nature of the moderating effect of NR on the relationship
between PC and R1, separate regression lines of R1 on PC were generated for the high and low
levels of NR. One standard deviation above the mean and one standard deviation below the mean
were designated as the values for the high and low levels of NR, respectively (Aiken & West,
1991; P. Cohen et al., 2003). Figure 4.1 presents the regression lines of R1 on PC for the high
and low levels of NR. The regression lines suggest that NR acted as a moderator in the
relationship between PC and R1 such that the negative relationship was stronger at the higher
level of NR.
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Table 4.10
Moderating Effect of NR on the Relationship between PC and Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.153* -.141* -.132† -.110 -.143* -.135† -.099 -.098 -.133† -.120
AGE -.158* -.167* -.144† -.160* -.123† -.128† -.159* -.160* -.104 -.113
EDU -.056 -.061 -.006 -.016 -.089 -.092 -.042 -.042 -.007 -.013
TEN -.021 -.028 -.014 -.026 -.047 -.051 -.001 -.002 .022 .015
NA .046 .044 -.065 -.068 .037 .036 .179* .179* -.035 -.037
Step 2
PC -.459*** -.507*** -.411*** -.501*** -.404*** -.436*** -.295*** -.299*** -.451*** -.503***
NR .272*** .212** .106 -.006 .246** .207* .384*** .380*** .117 .053
Step 3
PC × NR -.116 -.216* -.077 -.008 -.124
∆R2 .360 .010 .201 .033 .284 .004 .305 .000 .243 .011
∆F 46.868*** 2.537 19.218*** 6.646* 31.202*** .919 34.658*** .012 24.278*** 2.216
R2 .477 .487 .288 .322 .381 .385 .403 .403 .318 .329
Note. Table entries are standardized regression coefficients. PC: power-coercive strategy; NR: normative-reeducative strategy; R(O): overall
readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal
benefit of the change.
†p<.10, *p<.05, **p<.01, ***p<.001.
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Figure 4.1. Moderating effect of the normative-reeducative strategy (NR) on the relationship
between the power-coercive strategy (PC) and change-specific efficacy (R1)
To conclude, NR did not moderate the relationship between PC and overall readiness for
change. Among the four dimensions of readiness for change, the interaction between PC and NR
was significant for only one dimension, R1 (Table 4.10). Even though NR significantly
moderated the negative relationship between PC and R1, the nature of the moderation was
opposite to what was proposed in Hypothesis 3a. Contrary to expectation, the negative
relationship between PC and R1 was stronger when NR was higher (Figure 4.1). In sum, NR
either did not affect the negative relationship between PC and readiness for change (overall
readiness for change, R2, R3, R4) or even strengthened the negative relationship between PC and
readiness for change (R1). Therefore, Hypothesis 3a, which proposed that NR would mitigate the
negative effect of PC on readiness for change, was not supported.
To test Hypothesis 3b, which deals with the moderating effect of NR on the relationship
between ER and readiness for change, hierarchical regression analyses were conducted. Table
4.11 illustrates the procedure and result of the test on Hypothesis 3b.
1
2
3
4
5
1 2 3 4 5
low NR
high NR
R1
PC
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Table 4.11
Moderating Effect of NR on the Relationship between ER and Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.147* -.154* -.126 -.131† -.132† -.137† -.092 -.099 -.150† -.155†
AGE -.208** -.151* -.188* -.151† -.166* -.115 -.191** -.137† -.154† -.111
EDU .044 .004 .083 .057 .001 -.036 .023 -.016 .085 .055
TEN -.005 -.020 .001 -.009 -.034 -.047 .009 -.006 .040 .029
NA .039 .013 -.071 -.088 .032 .009 .175* .150* -.044 -.064
Step 2
ER .406*** .478*** .369*** .416*** .417*** .482*** .286** .355*** .205† .259*
NR .166† .187* .007 .021 .111 .130 .299** .318** .152 .167
Step 3
ER × NR .305*** .200* .277*** .294*** .230**
∆R2 .268 .079 .129 .034 .233 .065 .272 .074 .102 .045
∆F 29.650*** 19.960*** 11.175*** 6.091* 23.667*** 14.533*** 29.400*** 17.853*** 8.388*** 7.763**
R2 .385 .464 .216 .250 .330 .395 .370 .444 .177 .221
Note. Table entries are standardized regression coefficients. ER: empirical-rational strategy; NR: normative-reeducative strategy; R(O): overall
readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal
benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Again, all independent variables involved in the interaction effects were centered (Aiken
& West, 1991). The control variables were entered in step 1; two independent variables (ER and
NR) were added in step 2; and finally the interaction term (ER × NR) was added in step 3. As
Table 4.11 shows, NR moderated the positive relationship between ER and overall readiness for
change (∆R2=.079, p<.001). Also, NR moderated the positive relationship between ER and R1
(∆R2=.034, p<.05), between ER and R2 (∆R
2=.065, p<.001), between ER and R3 (∆R
2=.074,
p<.001), and between ER and R4 (∆R2=.045, p<.01).
To further investigate the nature of the moderating effect of NR on the relationship
between ER and readiness for change, separate regression lines of readiness for change on ER
were generated for the high and low levels of NR (Figures 4.2 through 4.6). One standard
deviation above the mean and one standard deviation below the mean were designated as the
values for the high and low levels of NR, respectively (Aiken & West, 1991; P. Cohen et al.,
2003).
Figure 4.2. Moderating effect of the normative-reeducative strategy (NR) on the relationship
between the empirical-rational strategy (ER) and overall readiness for change
3
4
5
6
7
1 2 3 4 5
low NR
high NR
ER
R (O)
5
4
3
2
1
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Figure 4.3. Moderating effect of the
normative-reeducative strategy (NR) on the
relationship between the empirical-rational
strategy (ER) and change-specific efficacy
(R1)
Figure 4.4. Moderating effect of the
normative-reeducative strategy (NR) on the
relationship between the empirical-rational
strategy (ER) and appropriateness of the
change (R2)
Figure 4.5. Moderating effect of the
normative-reeducative strategy (NR) on the
relationship between the empirical-rational
strategy (ER) and management support for the
change (R3)
Figure 4.6. Moderating effect of the
normative-reeducative strategy (NR) on the
relationship between the empirical-rational
strategy (ER) and personal benefit of the
change (R4)
3
4
5
6
7
1 2 3 4 5
low NR high NR
3
4
5
6
7
1 2 3 4 5
low NR high NR
3
4
5
6
7
1 2 3 4 5
low NR high NR
3
4
5
6
7
1 2 3 4 5
low NR high NR
ER ER
ER ER
R1 R2
R3 R4
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
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Figure 4.2 presents the regression lines of overall readiness for change on ER for the high
and low levels of NR. Comparison of the two regression lines reveals that the positive
relationship between ER and overall readiness for change was stronger when NR was higher.
That is, NR moderated the relationship between ER and overall readiness for change (∆R2=.079,
p<.001) such that the positive relationship was stronger at the higher level of NR (Figure 4.2).
Figures 4.3 through 4.6 present the regression lines of the four dimensions of readiness
for change on ER for the high and low levels of NR. Comparison of the regression lines
consistently shows that the positive relationship between ER and each dimension of readiness for
change was stronger when NR was higher.
In sum, ER had differential effects on readiness for change depending on the level of NR.
That is, NR moderated the relationship between ER and readiness for change (Table 4.11) such
that the positive relationship was stronger at the higher level of NR (Figures 4.2 through 4.6).
Therefore, Hypothesis 3b was fully supported.
Research Question 2: Learning Culture and Readiness for Change
Research question 2 is ―What is the relationship between the learning culture perceived
by those responding to a planned change and their readiness for change?‖ The findings related to
Research Question 2 are organized into two themes: (a) the relationship between learning culture
and readiness for change and (b) the moderating effect of learning culture on the relationship
between NR and readiness for change.
Relationship between Learning Culture and Readiness for Change
Table 4.12 presents the relationship between the dimensions of learning culture and the
dimensions of readiness for change partialling out gender, age, educational level, organizational
tenure, and NA. As it shows, when the variables related to individual difference were controlled
for, overall learning culture was positively related to overall readiness for change (r=.338,
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p<.001) and to the four dimensions of readiness for change (.231≤ r ≤.306, p<.01). Six out of the
seven dimensions of learning culture (LC1, LC3, LC4, LC5, LC6, and LC7) were positively
related to overall readiness for change (.252≤ r ≤.364, p<.01) and to each of the four dimensions
of readiness for change (.170≤ r ≤.345, p<.05).
Table 4.12
Partial Correlations between Learning Culture and Readiness for Change
R(O) R1 R2 R3 R4
LC(O) .338*** .266*** .293*** .306*** .231**
LC1 .252** .242** .198* .223** .170*
LC2 .134 .124 .089 .128 .123
LC3 .337*** .244** .290*** .329*** .228**
LC4 .364*** .285*** .345*** .305*** .218**
LC5 .321*** .274*** .275*** .264** .242**
LC6 .304*** .214* .252** .314*** .210*
LC7 .295*** .199* .290*** .257** .180*
Note. Gender, age, educational level, organizational tenure, and NA were partialled out from all
correlations. LC (O): overall learning culture; LC1: creating continuous learning opportunities; LC2:
promoting inquiry and dialogue; LC3: encouraging collaboration and team learning; LC4: empowering
people toward a collective vision; LC5: establishing systems to capture and share learning; LC6:
connecting the organization to its environment; LC7: providing strategic leadership for learning; R(O):
overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3:
management support for the change; R4: personal benefit of the change. *p<.05, **p<.01, ***p<.001.
To further investigate the relationship between learning culture and readiness for change,
regression analyses were conducted. Table 4.13 shows that the addition of learning culture
(measured by all 21 items) accounted for an additional 10.4 percent of the variance in overall
readiness for change beyond the explanation provided by individual difference variables
(∆R2=.104, p<.001). Learning culture also accounted for a significant amount of the variance in
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each of the four dimensions of readiness for change beyond the contribution of individual
difference variables: an additional 6.6% of the variance in R1 (∆R2=.066, p<.001), 8.0% of the
variance in R2 (∆R2=.080, p<.001), 8.5 % of the variance in R3 (∆R
2=.085, p<.001), and 5.2 %
of the variance in R4 (∆R2=.052, p<.01).
In sum, as expected, learning culture was positively related to readiness for change
(Tables 4.12). In addition, learning culture accounted for a significant portion of the variance in
readiness for change (Table 4.13). Thus, Hypothesis 4a, which proposes a positive relationship
between learning culture and readiness for change, was supported.
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Table 4.13
Readiness for Change Regressed on Overall Learning Culture
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.259** -.236** -.207* -.189* -.237** -.218** -.196* -.176* -.216* -.200*
AGE -.248** -.236** -.212* -.203* -.202* -.192* -.234** -.224** -.179* -.171*
EDU .033 .009 .073 .054 -.011 -.032 .015 -.006 .079 .063
TEN .052 .042 .036 .027 .018 .009 .070 .061 .077 .069
NA -.056 .005 -.129 -.080 -.054 .000 .073 .128 -.105 -.062
Step 2
LC(O) .329*** .263*** .289*** .298*** .233**
∆R2 .117 .104 .087 .066 .097 .080 .098 .085 .075 .052
∆F 3.680** 18.410*** 2.650* 10.837*** 2.988* 13.428*** 3.022* 14.390*** 2.254† 8.232**
R2 .117 .221 .087 .154 .097 .177 .098 .183 .075 .127
Note. Table entries are standardized regression coefficients. LC (O): overall learning culture; R(O): overall readiness for change; R1: change-
specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal benefit of the change. †p<.10, *p<.05,
**p<.01, ***p<.001.
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Moderating Effect of Learning Culture
In Hypothesis 4b, learning culture is proposed as a moderator. Specifically, it is proposed
that the nature of the effect of NR on readiness for change varies according to the level of
learning culture. As the test on Hypothesis 1b supported a positive relationship between NR and
readiness for change, a target for testing the moderating effect of learning culture was set up. To
test Hypothesis 4b, separate hierarchical regression analyses were conducted for overall learning
culture and for the seven dimensions of learning culture. Tables 4.14 through 4.21 illustrate the
procedure and results of the analyses for Hypothesis 4b. As the tables show, the variables were
entered into the regression equations in three steps. The control variables were entered in step 1.
After being centered (Aiken & West, 1991), NR and learning culture were added in step 2.
Finally, the interaction term (NR × learning culture) was added in step 3.
Table 4.14 reports the results of regression analysis for testing the moderating effect of
overall learning culture. As it shows, overall learning culture moderated the relationship between
NR and R1 (∆R2=.034, p<.05). Tables 4.15 through 4.21 show the results of the hierarchical
regression analyses to investigate the moderating effect of each dimension of learning culture on
the relationship between NR and readiness for change. As the tables present, LC1 moderated the
relationship between NR and R1 (∆R2=.017, p<.10); LC2 moderated the relationships between
NR and R1 (∆R2=.021, p<.10) and between NR and R4 (∆R
2=.017, p<.10); LC3 moderated the
relationship between NR and R(O) (∆R2=.016, p<.10) and between NR and R1 (∆R
2=.029,
p<.05); LC4 moderated the relationship between NR and R1 (∆R2=.030, p<.05); and LC5
moderated the relationships between NR and R (O) (∆R2=.026, p<.05), between NR and R1
(∆R2=.045, p<.01), and between NR and R3 (∆R
2=.014, p<.10).
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Table 4.14
Moderating Effect of Overall Learning Culture on the Relationship between NR and Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.191** -.176* -.166* -.140† -.177* -.170* -.123† -.118 -.172* -.154†
AGE -.209** -.194* -.189* -.163† -.167* -.160* -.192* -.187* -.154† -.136
EDU .019 -.005 .059 .018 -.023 -.035 .005 -.003 .069 .041
TEN .001 -.006 .006 -.005 -.028 -.031 .013 .011 .043 .036
NA .056 .035 -.054 -.090 .045 .035 .187* .180* -.030 -.055
Step 2
NR .386*** .374*** .200* .180* .347*** .341*** .452*** .448*** .244** .231**
LC(O) .193* .179* .193* .169* .166* .159* .138† .134† .147† .131
Step 3
NR × LC (O) .114 .198* .058 .039 .134
∆R2 .225 .011 .099 .034 .178 .003 .252 .001 .101 .016
∆F 23.302*** 2.369 8.278*** 5.972* 16.754*** .545 26.328*** .284 8.318*** 2.651
R2 .342 .354 .186 .221 .276 .278 .350 .351 .176 .192
Note. Table entries are standardized regression coefficients. NR: normative-reeducative strategy; LC (O): overall learning culture; R(O): overall
readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal
benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.15
Moderating Effect of Creating Continuous Learning Opportunities (LC1) on the Relationship between NR and Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.179* -.172* -.150† -.131 -.169* -.171* -.115 -.115 -.163* -.147†
AGE -.209** -.204** -.189* -.174* -.167* -.169* -.192* -.192* -.154† -.141†
EDU .020 .014 .057 .040 -.020 -.019 .006 .006 .070 .056
TEN -.011 -.013 -.008 -.013 -.037 -.036 .005 .005 .035 .030
NA .054 .046 -.050 -.071 .041 .043 .186* .186* -.032 -.049
Step 2
NR .419*** .414*** .224** .209* .381*** .382*** .476*** .476*** .271*** .259**
LC1 .150* .149* .188* .186* .109 .109 .107 .107 .109 .108
Step 3
NR × LC1 .050 .135† -.012 -.001 .113
∆R2 .214 .002 .099 .017 .166 .000 .246 .000 .093 .012
∆F 21.750*** .470 8.294*** 2.861† 15.295*** .025 25.487*** .000 7.635*** 1.965
R2 .331 .333 .186 .203 .263 .263 .344 .344 .168 .180
Note. Table entries are standardized regression coefficients. NR: normative-reeducative strategy; LC1: creating continuous learning opportunities;
R(O): overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4:
personal benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.16
Moderating Effect of Promoting Inquiry and Dialogue (LC2) on the Relationship between NR and Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.195** -.181* -.171* -.148† -.180* -.174* -.126† -.121 -.175* -.155†
AGE -.211** -.198* -.192* -.170* -.168* -.162* -.193* -.188* -.156† -.137
EDU .032 .013 .072 .040 -.011 -.020 .015 .008 .079 .050
TEN -.002 -.005 .003 -.002 -.029 -.031 .012 .011 .041 .036
NA .037 .020 -.066 -.093 .025 .018 .172* .165* -.039 -.064
Step 2
NR .448*** .458*** .250** .265** .410*** .414*** .501*** .504*** .281*** .295***
LC2 .028 .015 .074 .054 -.008 -.014 .003 -.001 .061 .043
Step 3
NR × LC2 .094 .154† .042 .034 .139†
∆R2 .195 .008 .073 .021 .155 .002 .236 .001 .086 .017
∆F 19.259*** 1.566 5.899** 3.478† 14.137*** .280 24.059*** .206 6.988*** 2.836†
R2 .312 .320 .160 .181 .252 .254 .334 .335 .161 .178
Note. Table entries are standardized regression coefficients. NR: normative-reeducative strategy; LC2: promoting inquiry and dialogue; R(O):
overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4:
personal benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.17
Moderating Effect of Encouraging Collaboration and Team Learning (LC3) on the Relationship between NR and Readiness for
Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.205** -.186* -.179* -.154† -.189* -.174* -.135† -.126† -.182* -.166*
AGE -.209** -.191* -.189* -.165* -.167* -.153† -.192* -.183* -.154† -.138
EDU .014 -.012 .057 .022 -.027 -.048 -.001 -.013 .065 .043
TEN .002 -.003 .007 .001 -.027 -.030 .014 .012 .044 .040
NA .063 .042 -.050 -.078 .052 .035 .197** .187* -.025 -.042
Step 2
NR .383*** .362*** .206* .179* .345*** .329*** .439*** .430*** .243** .226*
LC3 .196* .203** .170* .179* .167* .173* .168* .171* .146† .152†
Step 3
NR × LC3 .133† .178* .105 .061 .114
∆R2 .226 .016 .092 .029 .178 .010 .259 .003 .100 .012
∆F 23.322*** 3.338† 7.587*** 4.856* 16.711*** 1.881 27.353*** .712 8.260*** 1.940
R2 .342 .358 .179 .207 .275 .285 .357 .360 .175 .187
Note. Table entries are standardized regression coefficients. NR: normative-reeducative strategy; LC3: encouraging collaboration and team
learning; R(O): overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the
change; R4: personal benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.18
Moderating Effect of Empowering People toward a Collective Vision (LC4) on the Relationship between NR and Readiness for
Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.186** -.175* -.162* -.144 -.172* -.164* -.120† -.115 -.169* -.160*
AGE -.178* -.164* -.161† -.138 -.137† -.127 -.170* -.164* -.135 -.123
EDU .015 -.008 .056 .020 -.029 -.044 .002 -.008 .068 .050
TEN .007 -.001 .011 .000 -.022 -.027 .017 .014 .047 .041
NA .037 .020 -.072 -.099 .030 .018 .174* .167* -.045 -.058
Step 2
NR .390*** .357*** .210* .157† .343*** .321*** .455*** .441*** .257** .231**
LC4 .254*** .238*** .231** .206* .247*** .236** .180* .173* .158† .145†
Step 3
NR × LC4 .119 .190* .082 .052 .093
∆R2 .253 .012 .117 .030 .211 .006 .265 .002 .105 .007
∆F 27.266*** 2.526 9.956*** 5.203* 20.704*** 1.088 28.311*** .468 8.752*** 1.187
R2 .370 .381 .204 .233 .308 .313 .363 .365 .180 .188
Note. Table entries are standardized regression coefficients. NR: normative-reeducative strategy; LC4: empowering people toward a collective
vision; R(O): overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the
change; R4: personal benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.19
Moderating Effect of Establishing Systems to Capture and Share Learning (LC5) on the Relationship between NR and Readiness for
Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.196** -.177* -.171* -.146† -.181* -.167* -.126† -.113 -.175* -.163*
AGE -.213** -.195* -.193* -.170* -.171* -.157* -.194* -.181* -.157† -.146†
EDU .012 -.025 .050 .001 -.029 -.056 .004 -.024 .062 .037
TEN -.006 -.014 -.001 -.011 -.034 -.039 .009 .003 .037 .033
NA .052 .026 -.055 -.089 .042 .023 .182* .163* -.031 -.047
Step 2
NR .396*** .401*** .204* .211* .356*** .360*** .468*** .472*** .246** .249**
LC5 .184* .146† .204* .154† .157* .129 .104 .076 .160† .135
Step 3
NR × LC5 .173* .226** .127 .125† .111
∆R2 .223 .026 .104 .045 .177 .014 .245 .014 .105 .011
∆F 23.034*** 5.618* 8.720*** 7.911** 16.541*** 2.694 25.368*** 2.879† 8.693*** 1.823
R2 .340 .367 .191 .236 .274 .288 .343 .357 .180 .191
Note. Table entries are standardized regression coefficients. NR: normative-reeducative strategy; LC5: establishing systems to capture and share
learning; R(O): overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the
change; R4: personal benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.20
Moderating Effect of Connecting the Organization to Its Environment (LC6) on the Relationship between NR and Readiness for
Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.185* -.183* -.162* -.155† -.173* -.173* -.117 -.117 -.167* -.162*
AGE -.208** -.201** -.188* -.172* -.166* -.167* -.190* -.190* -.153† -.139
EDU .029 .018 .069 .044 -.014 -.014 .011 .010 .076 .054
TEN .005 -.001 .010 -.005 -.024 -.024 .018 .017 .047 .034
NA .040 .034 -.070 -.083 .031 .032 .178* .177* -.042 -.053
Step 2
NR .401*** .079 .222* -.546 .366*** .388 .450*** .407 .255** -.411
LC6 .145† .133† .127 .098 .112 .113 .138† .137† .113 .087
Step 3
NR × LC6 .332 .791 -.023 .045 .687
∆R2 .212 .003 .082 .019 .166 .000 .252 .000 .094 .014
∆F 21.476*** .664 6.679** 3.092† 15.312*** .003 26.342*** .012 7.647** 2.319
R2 .329 .332 .169 .187 .263 .263 .350 .350 .169 .183
Note. Table entries are standardized regression coefficients. NR: normative-reeducative strategy; LC6: connecting the organization to its
environment; R(O): overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for
the change; R4: personal benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.21
Moderating Effect of Providing Strategic Leadership for Learning (LC7) on the Relationship between NR and Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.196** -.192** -.170* -.157† -.181* -.182* -.126† -.131† -.175* -.165*
AGE -.225** -.222** -.201* -.191* -.184* -.184* -.202** -.205** -.164† -.157†
EDU .028 .024 .070 .054 -.016 -.015 .012 .017 .077 .066
TEN .013 .011 .015 .009 -.014 -.014 .021 .022 .050 .046
NA .048 .042 -.065 -.089 .043 .044 .181* .189* -.038 -.055
Step 2
NR .407*** .225 .233** -.427 .354*** .389 .470*** .675† .267** -.202
LC7 .157* .153* .116 .104 .172* .173* .103 .107 .098 .089
Step 3
NR × LC7 .186 .676 -.036 -.210 .480
∆R2 .216 .001 .080 .018 .181 .000 .245 .002 .091 .009
∆F 21.955*** .279 6.508** 3.022† 17.068*** .010 25.351*** .362 7.430*** 1.508
R2 .332 .334 .167 .185 .278 .278 .343 .345 .166 .175
Note. Table entries are standardized regression coefficients. NR: normative-reeducative strategy; LC7: providing strategic leadership for learning;
R(O): overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4:
personal benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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To further explore the nature of the moderating effect of learning culture, separate
regression lines were generated for the high and low levels of learning culture only for those
cases where a statistically significant interaction between NR and learning culture was found
(Figures 4.7 through 4.16). One standard deviation above the mean and one standard deviation
below the mean were designated as the values for the high and low levels of overall learning
culture, respectively (Aiken & West, 1991; P. Cohen et al., 2003).
The two regression lines presented in Figure 4.7 suggest that overall learning culture
moderated the relationship between NR and R1 such that the positive relationship was stronger at
the higher level of overall learning culture. In addition, Figures 4.8 through 4.16, which present
the regression lines of readiness for change on the dimensions of learning culture, indicate the
same pattern of moderation. The comparison between the regression lines in each figure
indicates that the positive relationship between NR and readiness for change was stronger when
the dimension of learning culture was higher.
In sum, NR had differential effects on readiness for change depending on the level of
learning culture. Specifically, learning culture moderated the relationship between NR and
readiness for change (Tables 4.14 through 4.21) such that the positive relationship between the
two was stronger when learning culture was higher (Figures 4.7 through 4.16). Thus, Hypothesis
4b was supported.
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Figure 4.7. Moderating effect of overall
learning culture on the relationship between the
normative-reeducative strategy (NR) and
change-specific efficacy (R1)
Figure 4.8. Moderating effect of creating
continuous learning opportunities (LC1) on the
relationship between the normative-reeducative
strategy (NR) and change-specific efficacy
(R1)
Figure 4.9. Moderating effect of promoting
inquiry and dialogue (LC2) on the relationship
between the normative-reeducative strategy
(NR) and change-specific efficacy (R1)
Figure 4.10. Moderating effect of promoting
inquiry and dialogue (LC2) on the relationship
between the normative-reeducative strategy
(NR) and personal benefit of the change (R4)
3
4
5
6
7
1 2 3 4 5
low LC(O) high LC(O)
2
3
4
5
6
7
1 2 3 4 5
low LC1 high LC1
2
3
4
5
6
7
1 2 3 4 5
low LC2 high LC2
2
3
4
5
6
7
1 2 3 4 5
low LC2 high LC2
NR NR
NR NR
R1 R1
5
4
3
2
1
5
4
3
2
1
R1 R4
5
4
3
2
1
5
4
3
2
1
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172
Figure 4.11. Moderating effect of encouraging
collaboration and team learning (LC3) on the
relationship between the normative-reeducative
strategy (NR) and overall readiness for change
Figure 4.12. Moderating effect of encouraging
collaboration and team learning (LC3) on the
relationship between the normative-reeducative
strategy (NR) and change-specific efficacy
(R1)
Figure 4.13. Moderating effect of empowering
people toward a collective vision (LC4) on the
relationship between the normative-reeducative
strategy (NR) and change-specific efficacy
(R1)
Figure 4.14. Moderating effect of establishing
systems to capture and share learning (LC5) on
the relationship between the normative-
reeducative strategy (NR) and overall readiness
for change
2
3
4
5
6
7
1 2 3 4 5
low LC3 high LC3
2
3
4
5
6
7
1 2 3 4 5
low LC3 high LC3
2
3
4
5
6
7
1 2 3 4 5
low LC4 high LC4
2
3
4
5
6
7
1 2 3 4 5
low LC5 high LC5
NR NR
NR NR
R(O) R1
R1 R(O)
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
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Figure 4.15. Moderating effect of establishing
systems to capture and share learning (LC5) on
the relationship between the normative-
reeducative strategy (NR) and change-specific
efficacy (R1)
Figure 4.16. Moderating effect of establishing
systems to capture and share learning (LC5) on
the relationship between the normative-
reeducative strategy (NR) and management
support for the change (R3)
Research Question 3: Change Impact and Readiness for Change
Research Question 3 is ―How does the impact of the change on individuals’ jobs affect
the two relationships presented in the first two research questions?‖ The findings related to
Research Question 3 are organized into two themes: (a) the relationship between change impact
and readiness for change and (b) the moderating effects of change impact.
Relationship between Change Impact and Readiness for Change
Hypothesis 5a proposes that the magnitude of individual job level impact is negatively
related to readiness for change. Table 4.22 presents the relationship between change impact and
readiness for change partialling out gender, age, educational level, organizational tenure, and NA.
As it shows, when the variables related to individual difference were controlled for, change
2
3
4
5
6
7
1 2 3 4 5
low LC5 high LC5
2
3
4
5
6
7
1 2 3 4 5
low LC5 high LC5
NR NR
R1 R3
5
4
3
2
1
5
4
3
2
1
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impact was negatively related to overall readiness for change (r=-.155, p<.10). Among the
dimensions of readiness for change, change impact was negatively related to R1 (r=-.150, p<.10)
and R4 (r=-.259, p<.01).
Table 4.22
Partial Correlations between Change Impact and Readiness for Change
R(O) R1 R2 R3 R4
Change Impact -.155† -.150† -.103 -.065 -.259**
Note. Gender, age, educational level, organizational tenure, and NA were partialled out from all
correlations. R(O): overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the
change; R3: management support for the change; R4: personal benefit of the change. †p<.10, *p<.05,
**p<.01, ***p<.001.
To further examine the influence of change impact on readiness for change, hierarchical
regression analysis was conducted. As reported in Table 4.23, change impact accounted for a
significant amount of the variance in R4 beyond the contribution of individual difference
variables (∆R2=.056,
p<.001).
In sum, change impact was negatively related to overall readiness for change (Table 4.22).
In particular, among the four dimensions of readiness for change, change impact accounted for a
significant amount of the variance in R4 (Table 4.23). Thus, Hypothesis 5a was supported.
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Table 4.23
Readiness for Change Regressed on Change Impact
Variables R(O) R1 R2 R3 R4
Step 1
GEN -.263** -.252** -.213* -.203* -.239** -.233** -.198* -.194* -.224** -.205*
AGE -.263** -.243** -.235** -.215* -.208* -.195* -.238** -.230* -.211* -.174*
EDU .030 .044 .069 .082 -.013 -.003 .014 .019 .074 .099
TEN .072 .061 .064 .053 .028 .021 .077 .073 .113 .093
NA -.067 -.043 -.143† -.120 -.059 -.043 .068 .078 -.124 -.081
Step 2
CI -.135 -.132 -.089 -.054 -.246**
∆R2 .123 .017 .096 .016 .098 .007 .098 .003 .088 .056
∆F 3.867** 2.717 2.924* 2.502 3.008* 1.141 3.011* .414 2.674* 9.048**
R2 .123 .140 .096 .112 .098 .106 .098 .101 .088 .145
Note. Table entries are standardized regression coefficients. CI: change impact; R(O): overall readiness for change; R1: change-specific efficacy;
R2: appropriateness of the change; R3: management support for the change; R4: personal benefit of the change. †p<.10, *p<.05, **p<.01,
***p<.001.
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Moderating Effects of Change Impact
Hypothesis 5b deals with the moderating effect of change impact on the relationship
between NR and readiness for change. The test on Hypothesis 1a showed that NR was positively
related to readiness for change, so a target for testing the moderating effect of change impact on
the relationship between NR and readiness for change was set up.
To test Hypothesis 5b, hierarchical regression analysis was conducted (Table 4.24). The
control variables were entered in step 1. After being centered (Aiken & West, 1991), two
independent variables (change impact and NR) were added in step 2; and finally the interaction
term (change impact × NR) was added in step 3. As presented in Table 4.24, change impact
significantly, but marginally, moderated the relationship between NR and R4 (∆R2=.020, p<. 10).
To further explore the nature of the moderating effect of change impact, separate
regression lines of R4 on NR were generated for the high and low levels of change impact
(Figure 4.17). One standard deviation above the mean and one standard deviation below the
mean were designated as the values for the high and low levels of change impact, respectively
(Aiken & West, 1991; P. Cohen et al., 2003). The two regression lines in Figure 4.17 suggest
that the positive relationship between NR and R4 was stronger at the higher level of change
impact. In sum, change impact moderated the relationship between NR and R4 (Table 4.24) such
that the positive relationship between the two was stronger when change impact was higher
(Figure 4.17). As the moderating effect was limited only to the relationship between NR and R4
and did not affect overall readiness for change, Hypothesis 5b was partially supported.
Hypothesis 5c concerns the moderating effect of change impact on the relationship
between learning culture and readiness for change. As supported by the test on Hypothesis 4a,
learning culture was positively related to readiness for change. Therefore, a target for testing the
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moderating effect of change impact on the relationship between learning culture and readiness
for change was set up. To test Hypothesis 5c, separate hierarchical regression analyses were
conducted for overall learning culture and for the dimensions of learning culture (Table 4.25
through 4.32). Across all the analyses, the control variables were entered in step 1; after being
centered (Aiken & West, 1991), two independent variables (change impact and learning culture)
were added in step 2; and finally the interaction term (change impact × learning culture) was
added in step 3.
As presented in Table 4.25, change impact moderated the relationship between overall
learning culture and R4 (∆R2=.024, p<.05). In addition, as reported in Tables 4.26 through 4.32,
change impact moderated the relationship between LC1 and R4 (∆R2=.027, p<.05), the
relationship between LC2 and R4 (∆R2=.020, p<.10), the relationship between LC5 and R4
(∆R2=.027, p<.05), and the relationship between LC7 and R4 (∆R
2=.036, p<.05).
To further examine the nature of the moderating effects, separate regression lines were
generated for the high and low levels of change impact only for those cases where a statistically
significant interaction between learning culture and change impact was found (Figures 4.18
through 4.22). One standard deviation above the mean and one standard deviation below the
mean were designated as the values for the high and low levels of change impact, respectively
(Aiken & West, 1991; P. Cohen et al., 2003).
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Table 4.24
Moderating Effect of Change Impact on the Relationship between NR and Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.187* -.189* -.162* -.161† -.176* -.179* -.124† -.130† -.159* -.150†
AGE -.192* -.192* -.172* -.173* -.157† -.155† -.189* -.186* -.117 -.121
EDU .043 .044 .083 .081 -.005 -.001 .017 .025 .100 .089
TEN -.014 -.012 -.008 -.011 -.037 -.033 .009 .019 .015 .000
NA .051 .049 -.058 -.056 .037 .033 .175* .166* -.010 .004
Step 2
CI -.092 -.092 -.092 -.092 -.059 -.058 -.021 -.019 -.194* -.198*
NR .451*** .449*** .265*** .267*** .405*** .400*** .501*** .492*** .288*** .302***
Step 3
NR × CI -.018 .024 -.048 -.098 .144†
∆R2 .202 .000 .076 .001 .158 .002 .236 .009 .117 .020
∆F 20.150*** .061 6.136** .089 14.476*** .400 24.113*** 1.918 9.835*** 3.453†
R2 .319 .319 .163 .163 .256 .258 .334 .343 .192 .212
Note. Table entries are standardized regression coefficients. CI: change impact; NR: normative-reeducative change strategy; R(O): overall
readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal
benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.25
Moderating Effect of Change Impact on the Relationship between Overall Learning Culture and Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.226** -.227** -.180* -.185* -.211** -.217** -.172* -.172* -.182* -.164*
AGE -.213* -.212* -.182* -.177* -.175* -.169* -.214* -.213* -.129 -.147†
EDU .021 .022 .065 .068 -.023 -.020 -.001 -.001 .085 .076
TEN .025 .024 .012 .009 -.003 -.007 .054 .054 .039 .051
NA .029 .029 -.058 -.058 .017 .017 .138† .138† -.020 -.020
Step 2
CI -.118 -.117 -.107 -.106 -.082 -.081 -.049 -.049 -.211* -.214**
LC(O) .330*** .330*** .264*** .263*** .290*** .288*** .298*** .298*** .235** .241**
Step 3
LC (O) × CI -.010 -.045 -.056 -.005 .159*
∆R2 .116 .000 .077 .002 .086 .003 .087 .000 .092 .024
∆F 10.328*** .016 6.250** .312 7.169*** .500 7.289*** .003 7.534*** 4.080*
R2 .233 .233 .164 .166 .183 .186 .185 .185 .167 .192
Note. Table entries are standardized regression coefficients. CI: change impact; LC(O): overall learning culture; R(O): overall readiness for change;
R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal benefit of the change.
†p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.26
Moderating Effect of Change Impact on the Relationship between Creating Continuous Learning Opportunities (LC1) and Readiness
for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.215** -.217** -.165* -.169* -.203* -.209* -.162† -.165* -.174* -.164*
AGE -.218* -.213* -.185* -.177* -.180* -.168† -.218* -.213* -.132 -.155†
EDU .024 .026 .064 .068 -.019 -.014 .001 .004 .087 .076
TEN .012 .008 -.002 -.007 -.012 -.021 .043 .039 .030 .046
NA .014 .015 -.062 -.061 .000 .002 .124 .125 -.031 -.034
Step 2
CI -.116 -.114 -.106 -.103 -.080 -.076 -.047 -.045 -.210* -.218**
LC1 .252** .250** .243** .240** .202* .198* .223** .221** .176* .184*
Step 3
LC1 × CI -.035 -.053 -.087 -.041 .166*
∆R2 .072 .001 .065 .003 .044 .007 .049 .002 .069 .027
∆F 6.006** .197 5.247** .430 3.481* 1.141 3.895* .262 5.444** 4.326*
R2 .189 .190 .152 .155 .141 .148 .147 .149 .144 .170
Note. Table entries are standardized regression coefficients. CI: change impact; LC1: creating continuous learning opportunities; R(O): overall
readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal
benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.27
Moderating Effect of Change Impact on the Relationship between Promoting Inquiry and Dialogue (LC2) and Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.246** -.247** -.196* -.196* -.229** -.234** -.190* -.192* -.195* -.187*
AGE -.224* -.219* -.191* -.188* -.185* -.168† -.224* -.217* -.137 -.166†
EDU .043 .045 .082 .083 -.004 .002 .018 .021 .100 .089
TEN .028 .024 .013 .012 .002 -.011 .057 .052 .040 .060
NA -.005 -.005 -.081 -.081 -.019 -.018 .108 .108 -.037 -.040
Step 2
CI -.117 -.115 -.107 -.106 -.081 -.074 -.048 -.046 -.211* -.222**
LC2 .146† .145† .140† .140† .099 .098 .134 .133 .138† .139†
Step 3
LC2 × CI -.028 -.014 -.089 -.037 .147†
∆R2 .032 .001 .029 .000 .015 .007 .019 .001 .058 .020
∆F 2.582† .118 2.218 .028 1.160 1.121 1.476 .196 4.517* 3.176†
R2 .149 .150 .116 .116 .112 .119 .117 .118 .133 .153
Note. Table entries are standardized regression coefficients. CI: change impact; LC2: promoting inquiry and dialogue; R(O): overall readiness for
change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal benefit of the
change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.28
Moderating Effect of Change Impact on the Relationship between Encouraging Collaboration and Team Learning (LC3) and
Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.251** -.254** -.200* -.204* -.232** -.237** -.194* -.196* -.200* -.195*
AGE -.216** -.211* -.185* -.178* -.178* -.171* -.216* -.213* -.131 -.138
EDU .011 .012 .060 .061 -.032 -.031 -.014 -.013 .079 .077
TEN .028 .027 .016 .013 .001 -.002 .056 .055 .042 .045
NA .038 .037 -.056 -.058 .025 .022 .153† .152† -.015 -.013
Step 2
CI -.099 -.097 -.093 -.091 -.065 -.063 -.031 -.030 -.198* -.200*
LC3 .333*** .335*** .242** .246** .292*** .296*** .329*** .330*** .227** .222**
Step 3
LC3 × CI -.042 -.064 -.066 -.024 .066
∆R2 .116 .002 .065 .004 .086 .004 .104 .001 .088 .004
∆F 10.278*** .304 5.220** .637 7.122*** .712 8.821*** .097 7.126*** .686
R2 .233 .235 .152 .156 .183 .187 .202 .202 .163 .167
Note. Table entries are standardized regression coefficients. CI: change impact; LC3: encouraging collaboration and team learning; R(O): overall
readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal
benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.29
Moderating Effect of Change Impact on the Relationship between Empowering People toward a Collective Vision (LC4) and
Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.226** -.224** -.180* -.181* -.209** -.207** -.173* -.172* -.185* -.180*
AGE -.177* -.179* -.153† -.152† -.141† -.143† -.185* -.186* -.108 -.113
EDU .018 .016 .062 .063 -.028 -.030 -.003 -.004 .085 .081
TEN .039 .038 .023 .024 .010 .009 .066 .066 .049 .046
NA -.014 -.012 -.092 -.093 -.019 -.017 .098 .099 -.052 -.047
Step 2
CI -.097 -.099 -.090 -.089 -.062 -.065 -.031 -.032 -.198* -.204*
LC4 .346*** .344*** .279*** .280*** .329*** .327*** .292*** .290*** .212** .206*
Step 3
LC4 × CI .038 -.018 .043 .024 .091
∆R2 .128 .001 .085 .000 .111 .002 .085 .001 .083 .008
∆F 11.545*** .256 7.023*** .054 9.529*** .311 7.039*** .090 6.712** 1.303
R2 .245 .246 .173 .173 .208 .210 .183 .183 .158 .166
Note. Table entries are standardized regression coefficients. CI: change impact; LC4: empowering people toward a collective vision; R(O): overall
readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal
benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.30
Moderating Effect of Change Impact on the Relationship between Establishing Systems to Capture and Share Learning (LC5) and
Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.236** -.233** -.187* -.188* -.220** -.220** -.182* -.178* -.188* -.177*
AGE -.220** -.222** -.187* -.187* -.181* -.181* -.221* -.224** -.134 -.143†
EDU .011 .009 .054 .055 -.033 -.032 -.008 -.010 .075 .068
TEN .014 .017 .002 .002 -.012 -.012 .046 .051 .030 .041
NA .020 .018 -.062 -.062 .008 .009 .125 .122 -.023 -.030
Step 2
CI -.121 -.118 -.110 -.110 -.085 -.085 -.051 -.048 -.214** -.204*
LC5 .312*** .315*** .270*** .270*** .272*** .271*** .253** .258** .242** .255**
Step 3
LC5 × CI .044 -.001 -.008 .062 .166*
∆R2 .105 .002 .080 .000 .076 .000 .063 .004 .095 .027
∆F 9.182*** .330 6.528** .000 6.289** .010 5.141** .602 7.823*** 4.531*
R2 .222 .224 .167 .167 .173 .174 .161 .165 .170 .197
Note. Table entries are standardized regression coefficients. CI: change impact; LC5: establishing systems to capture and share learning; R(O):
overall readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4:
personal benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.31
Moderating Effect of Change Impact on the Relationship between Connecting the Organization to Its Environment (LC6) and
Readiness for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.213** -.219** -.173* -.188* -.201* -.214* -.156† -.158† -.172* -.145†
AGE -.207* -.207* -.178* -.178* -.171* -.171* -.206* -.206* -.124 -.124
EDU .039 .040 .080 .084 -.008 -.004 .013 .014 .097 .090
TEN .033 .033 .019 .018 .005 .004 .061 .061 .045 .047
NA .006 .007 -.079 -.078 -.005 -.004 .122 .122 -.035 -.036
Step 2
CI -.136† -.135† -.120 -.119 -.097 -.096 -.067 -.067 -.224** -.226**
LC6 .298*** .293*** .215** .201* .250** .238** .304*** .303*** .219** .243**
Step 3
LC6 × CI -.029 -.077 -.065 -.010 .130
∆R2 .098 .001 .055 .006 .066 .004 .092 .000 .086 .016
∆F 8.472*** .134 4.324* .876 5.362** .640 7.686*** .015 6.950*** 2.589
R2 .215 .216 .142 .147 .163 .167 .190 .190 .161 .177
Note. Table entries are standardized regression coefficients. CI: change impact; LC6: connecting the organization to its environment; R(O): overall
readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal
benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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Table 4.32
Moderating Effect of Change Impact on the Relationship between Providing Strategic Leadership for Learning (LC7) and Readiness
for Change
Variables R (O) R1 R2 R3 R4
Step 1
GEN -.237** -.239** -.191* -.200* -.219** -.232** -.182* -.183* -.191* -.155†
AGE -.241** -.239** -.202* -.195* -.202* -.192* -.239** -.238** -.148† -.176*
EDU .038 .039 .080 .081 -.009 -.008 .014 .014 .097 .094
TEN .049 .048 .030 .024 .020 .012 .075 .075 .056 .079
NA .014 .015 -.076 -.075 .009 .011 .123 .123 -.032 -.037
Step 2
CI -.128 -.128 -.114 -.116 -.092 -.095 -.058 -.058 -.218* -.210*
LC7 .286*** .285*** .192* .189* .284*** .279*** .248** .248** .188* .201*
Step 3
LC7 × CI -.011 -.049 -.070 -.005 .197*
∆R2 .090 .000 .045 .002 .083 .005 .061 .000 .073 .036
∆F 7.717*** .018 3.543* .357 6.862*** .753 4.923** .004 5.853** 6.001*
R2 .207 .207 .132 .135 .180 .184 .159 .159 .148 .185
Note. Table entries are standardized regression coefficients. CI: change impact; LC7: providing strategic leadership for learning; R(O): overall
readiness for change; R1: change-specific efficacy; R2: appropriateness of the change; R3: management support for the change; R4: personal
benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.
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The regression lines in Figure 4.18 suggest that change impact moderated the relationship
between overall learning culture and R4 (∆R2=.024, p<.05) such that the positive relationship
was stronger at the higher level of change impact. Figures 4.19 through 4.22 present the
regression lines of readiness for change on the relevant dimensions of learning culture for the
high and low levels of change impact. Comparison of the regression lines in those figures
consistently shows that the positive relationship between learning culture and readiness for
change was stronger when change impact was high than when change impact was low. In sum,
as expected in Hypothesis 5c, change impact acted as a moderator in the relationship between
learning culture and readiness for change (Tables 4.25 through 4.32) such that the positive
relationship between the two was stronger when change impact was higher (Figures 4.18 through
4.22). As the moderating effects were limited to the relationship between certain dimensions of
learning culture and readiness for change, Hypothesis 5c was partially supported.
Figure 4.17. Moderating effect of change
impact (CI) on the relationship between the
normative-reeducative strategy (NR) and
personal benefit of the change (R4)
Figure 4.18. Moderating effect of change
impact (CI) on the relationship between overall
learning culture and personal benefit of the
change (R4)
3
4
5
6
7
1 2 3 4 5
low CI high CI
3
4
5
6
7
1 2 3 4 5
low CI high CI
R4
NR
R4
LC(O)
5
4
3
2
1
5
4
3
2
1
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Figure 4.19. Moderating effect of change
impact (CI) on the relationship between
creating continuous learning opportunities
(LC1) and personal benefit of the change (R4)
Figure 4.20. Moderating effect of change
impact (CI) on the relationship between
promoting inquiry and dialogue (LC2) and
personal benefit of the change (R4)
Figure 4.21. Moderating effect of change
impact (CI) on the relationship between
establishing systems to capture and share
learning (LC5) and personal benefit of the
change (R4)
Figure 4.22. Moderating effect of change
impact (CI) on the relationship between
providing strategic leadership for learning
(LC7) and personal benefit of the change (R4)
3
4
5
6
7
1 2 3 4 5
low CI high CI
3
4
5
6
7
1 2 3 4 5
low CI high CI
3
4
5
6
7
1 2 3 4 5
low CI high CI
3
4
5
6
7
1 2 3 4 5
low CI high CI
LC7
LC1 LC2
LC5
R4 R4
5
4
3
2
1
5
4
3
2
1
R4 R4
5
4
3
2
1
5
4
3
2
1
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Comparing the Importance of Change Strategies, Learning Culture, and Change Impact
Determining the relative importance of the key variables of this study was not one of the
research questions of this study. However, understanding which aspect of change is most
instrumental in understanding individual readiness for organizational change can provide
potentially useful scholarly and practical implications.
The study variables were grouped into four sets. Set A consisted of change strategies (PC,
NR, and ER). Set B included the seven dimensions of learning culture. Set C included one
variable, change impact. Finally, Set D included the variables related to individual differences:
age, gender, educational level, organizational tenure, and NA. To examine the relative
importance of these four sets of variables, dominance analysis (Azen & Budescu, 2003; Budescu,
1993) was conducted. Specifically, one dominance analysis was conducted for overall readiness
for change (Table 4.33) and additional four analyses were conducted for the four dimensions of
readiness for change (Tables 4.34 through 4.37).
As described above, in step 1 of the dominance analysis, the unique contribution of each
set of variables was assessed, holding all other possible orderings of sets constant (Azen &
Budescu, 2003; Budescu, 1993). Table 4.33 shows the results of step1 of dominance analysis for
overall readiness for change. Row 1 reports the direct effect of each set of variables on overall
readiness for change. Rows 2 through 11 assess the partial effects of each set of variables. Rows
12 through 15 assess the total effect of each set of variables. Pairwise dominance of each set of
variables was determined by comparing each pair of sets across all rows for which both sets were
non-empty. For example, row 1 shows that the contribution of Set A (.480) was greater than the
contributions of Set B (.215), Set C (.041), and Set D (.131). Rows 3 through 5 and rows 9
through 11 also show that the contribution of Set A was greater than the contributions of Set B,
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Set D, and Set C. Likewise, rows through 12 to 15 also indicate that the contribution of Set A
was greater than those of the other sets. These comparisons were continued for Set A, Set B, Set
C, and Set D respectively. The data in Table 4.33 consistently indicate that Set A was dominant
to Set B, Set C, and Set D; Set B was dominant to Set C and Set D; Set D was dominance to Set
C. The consistency of responses across all possible pairings is indicative of dominance (Eby et
al., 2000). Specifically, this consistent pattern of dominance suggests that the most useful
variables in understanding overall readiness for change were those included in Set A, followed
by the variables in Set B, then the variables in Set D, and then finally the variables in Set C.
Tables 4.34 through 4.37 report the results of the dominance analyses for the four
dimensions of readiness for change. The results of the dominance analysis for R1 and R2 (Tables
4.34 and 4.35) were consistent with those of the dominance analysis for overall readiness for
change (Table 4.33). Specifically, Tables 4.34 and 4.35 show that Set A was dominant to Set B,
Set C, and Set D; Set B was dominant to Set C and Set D; Set D was dominance to Set C. This
pattern of dominance suggests that the most useful variables in understanding R1 and R2 were
those included in Set A, followed by the variables in Set B, then the variables in Set D, and then
finally the variables in Set C.
On the other hand, the analysis for R3 and R4 showed different patterns of dominance.
Table 4.36 presents the dominance analysis result for R3. Row 1 shows that Set A was dominant
to other sets of variables. Data from other rows confirm this pattern. Also, Set C was consistently
the least dominant to the other sets of variables. However, there was no clear pattern of
dominance between Set B and Set D. Specifically, rows 1 and 4 show that Set B was dominant to
Set D; however, rows 2, 7, 12, and 14 indicate that Set D was dominant to Set B. Table 4.37
presents the dominance analysis result for R4. Row 1 shows that Set A was dominant to the other
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sets. Data from other rows confirm this pattern. Set C was consistently dominant to Set D.
However, the results regarding the dominance of Set B over Set C and Set D were mixed. Rows
1, 4, and 5 show that Set B was dominant to Set C and to Set D. However, Rows 2, 7, and 8
show that Set C and Set D were dominant to Set B.
In step 2 of the dominance analysis, M(Cxi) was obtained by averaging the following
three pieces of information in Tables 4.33 through 4.37: the direct effect (reported in row 1), the
average of the partial effects (reported in rows 2 through 11), and the total effect (reported in
rows 12 through15). Table 4.38 summarizes the results of step 2 of the dominance analysis for
overall readiness for change and its four dimensions.
Table 4.33
Relative Importance of Study Variables: Overall Readiness for Change
Variables already in the
equation
R2 accounted for by
variables already in
the equation
Additional contribution of
Set A Set B Set C Set D
— .000 .480 .215 .041 .131
Set A .480 — .060 .003 .056
Set B .215 .324 — .029 .098
Set C .041 .442 .203 — .110
Set D .131 .405 .183 .021 —
Set A, Set B .540 — — .002 .044
Set A, Set C .483 — .058 — .053
Set A, Set D .536 — .048 .001 —
Set B, Set C .244 .298 — — .083
Set B, Set D .314 .270 — .013 —
Set C, Set D .151 .385 .175 — —
Set A, Set B, Set C .542 — — — .042
Set A, Set B, Set D .583 — — .000 —
Set A, Set C, Set D .536 — .047 — —
Set B, Set C, Set D .327 .257 — — —
Set A, Set B, Set C, Set D .584 — — — —
Note. Set A: change strategies (PC, NR, and ER); Set B: dimensions of learning culture; Set C: change
impact; Set D: age, gender, educational level, organizational tenure, and NA.
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Table 4.34
Relative Importance of Study Variables: Change-Specific Efficacy (R1)
Variables already in the
equation
R2 accounted for by
variables already in
the equation
Additional contribution of
Set A Set B Set C Set D
— .000 .317 .145 .038 .097
Set A .317 — .049 .006 .036
Set B .145 .221 — .028 .063
Set C .038 .284 .136 — .079
Set D .097 .256 .111 .020 —
Set A, Set B .366 — — .004 .028
Set A, Set C .322 — .048 — .033
Set A, Set D .353 — .041 .002 —
Set B, Set C .174 .197 — — .049
Set B, Set D .208 .186 — .015 —
Set C, Set D .117 .238 .106 — —
Set A, Set B, Set C .371 — — — .025
Set A, Set B, Set D .394 — — .002 —
Set A, Set C, Set D .355 — .041 — —
Set B, Set C, Set D .223 .173 — — —
Set A, Set B, Set C, Set D .396 — — — —
Note. Set A: change strategies (PC, NR, and ER); Set B: dimensions of learning culture; Set C: change
impact; Set D: age, gender, educational level, organizational tenure, and NA.
Table 4.35
Relative Importance of Study Variables: Appropriateness of the Change (R2)
Variables already in the
equation
R2 accounted for by
variables already in
the equation
Additional contribution of
Set A Set B Set C Set D
— .000 .393 .196 .024 .108
Set A .393 — .071 .001 .049
Set B .196 .267 — .015 .088
Set C .024 .369 .188 — .093
Set D .108 .334 .177 .009 —
Set A, Set B .463 — — .000 .043
Set A, Set C .393 — .070 — .048
Set A, Set D .441 — .065 .000 —
Set B, Set C .212 .252 — — .077
Set B, Set D .285 .221 — .004 —
Set C, Set D .117 .324 .172 — —
Set A, Set B, Set C .463 — — — .043
Set A, Set B, Set D .506 — — .000 —
Set A, Set C, Set D .441 — .065 — —
Set B, Set C, Set D .289 .217 — — —
Set A, Set B, Set C, Set D .507 — — — —
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Table 4.36
Relative Importance of Study Variables: Management Support for the Change (R3)
Variables already in the
equation
R2 accounted for by
variables already in
the equation
Additional contribution of
Set A Set B Set C Set D
— .000 .380 .181 .010 .107
Set A .380 — .047 .000 .071
Set B .181 .245 — .004 .088
Set C .010 .370 .176 — .101
Set D .107 .343 .162 .004 —
Set A, Set B .427 — — .001 .054
Set A, Set C .380 — .048 — .071
Set A, Set D .451 — .030 .001 —
Set B, Set C .186 .242 — — .085
Set B, Set D .269 .212 — .001 —
Set C, Set D .111 .340 .159 — —
Set A, Set B, Set C .428 — — — .055
Set A, Set B, Set D .481 — — .002 —
Set A, Set C, Set D .451 — .031 — —
Set B, Set C, Set D .270 .212 — — —
Set A, Set B, Set C, Set D .483 — — — —
Note. Set A: change strategies (PC, NR, and ER); Set B: dimensions of learning culture; Set C: change
impact; Set D: age, gender, educational level, organizational tenure, and NA.
Table 4.37
Relative Importance of Study Variables: Personal Benefit of the Change (R4)
Variables already in the
equation
R2 accounted for by
variables already in
the equation
Additional contribution of
Set A Set B Set C Set D
— .000 .325 .094 .085 .083
Set A .325 — .017 .030 .026
Set B .094 .248 — .078 .062
Set C .085 .270 .086 — .060
Set D .083 .268 .073 .062 —
Set A, Set B .342 — — .030 .021
Set A, Set C .355 — .016 — .019
Set A, Set D .351 — .012 .024 —
Set B, Set C .171 .201 — — .042
Set B, Set D .156 .207 — .057 —
Set C, Set D .145 .230 .069 — —
Set A, Set B, Set C .372 — — — .015
Set A, Set B, Set D .363 — — .023 —
Set A, Set C, Set D .375 — .012 — —
Set B, Set C, Set D .214 .173 — — —
Set A, Set B, Set C, Set D .387 — — — —
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As reported in Table 4.38, Set A, Set B, Set C, and Set D accounted for 36.4%, 12.8%,
1.8%, and 8.2% of the variance in overall readiness for change, respectively. Of the total
variance in overall readiness for change that could be attributed to the four sets of variables
combined, Set A made the most contribution (61.5%), followed by Set B (21.6%), Set D (13.9%),
and Set C (3.0%). The analysis results for R1, R2, and R3 also showed the same pattern of
dominance: Set A was the most important in understanding the dimension of readiness for
change, followed by Set B, then by Set D, and finally by Set C.
On the other hand, the analysis results for R4 presented a different pattern of dominance.
Of the total variance in R4 that could be attributed to the four sets of variables combined, Set A
made the most contribution, followed by Set C, Set B, and then Set D. It is intuitively
understandable that change impact (the impact of change on one’s job) will be more important in
understanding R4 (one’s belief in the personal benefit of the change) than it will be in
understanding other dimensions of readiness for change.
In sum, the variables included in Set A (change strategies) emerged as the most important
set of variables, accounting for the majority of the variance in readiness for change. Also, the
variables included in Set A (change strategies) and Set B (learning culture) together accounted
for over 80% of the variance that could be attributed to the all the variables included in this study.
These findings were consistent across three of the four dimensions of readiness for change: R1,
R2, and R3. For R4, on the other hand, the pattern of dominance was different. While Set A
emerged again as the most dominant; Set C was the second most important variable, followed by
those included in Set B, and then Set D.
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Table 4.38
Relative Importance of Study Variables: Dominance Matrices
Set A Set B Set C Set D
R (O) Direct Effect (k=0) .480 .215 .041 .131
Average of partial effect (k=1, 2) .354 .121 .012 .074
Total effect (k=3) .257 .047 .000 .042
M (Cxi) .364 .128 .018 .082
Relative percentage (Rank) 61.5% (1) 21.6% (2) 3.0% (4) 13.9% (3)
R1 Direct Effect (k=0) .317 .145 .038 .097
Average of partial effect (k=1, 2) .230 .082 .013 .048
Total effect (k=3) .173 .041 .002 .025
M (Cxi) .240 .089 .018 .057
Relative percentage (Rank) 59.5% (1) 22.1% (2) 4.4% (4) 14.0% (3)
R2 Direct Effect (k=0) .393 .196 .024 .108
Average of partial effect (k=1, 2) .295 .124 .005 .066
Total effect (k=3) .217 .065 .000 .043
M (Cxi) .302 .128 .010 .072
Relative percentage (Rank) 58.9% (1) 25.1% (2) 1.9% (4) 14.1% (3)
R3 Direct Effect (k=0) .380 .181 .010 .107
Average of partial effect (k=1, 2) .292 .104 .002 .078
Total effect (k=3) .212 .031 .002 .055
M (Cxi) .295 .105 .005 .080
Relative percentage (Rank) 60.8% (1) 21.7% (2) 1.0% (4) 16.5% (3)
R4 Direct Effect (k=0) .325 .094 .085 .083
Average of partial effect (k=1, 2) .237 .046 .047 .038
Total effect (k=3) .173 .012 .023 .015
M (Cxi) .245 .051 .052 .045
Relative percentage (Rank) 62.4% (1) 12.9% (3) 13.2% (2) 11.5% (4)
Note. k=the number of additional sets of variables taken into account. Relative percentage indicates the
relative importance of each set of variables to overall prediction.
Summary of the Chapter
This chapter presented the results of statistical analyses to test the hypotheses proposed in
Chapter Two. Table 4.39 summarizes the analyses conducted to test each hypothesis and the
results of those analyses.
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Additionally, dominance analysis was conducted to determine the relative importance of
the study variables. The analysis results indicated that among the study variables change
strategies were the most instrumental in understanding readiness for change. Furthermore, across
the dimensions of readiness for change, change strategies and learning culture explained 75.3 to
84 percent of the variance that could be attributed to the variables included in this study.
Table 4.39
Summary of Tests on Hypotheses
Research
Question
Hypothesis Analysis conducted Results
RQ1 Hypothesis 1a Partial correlation analysis
Hierarchical regression analysis
Supported
Hypothesis 1b Partial correlation analysis
Hierarchical regression analysis
Supported
Hypothesis 1c Partial correlation analysis
Hierarchical regression analysis
Supported
Hypothesis 2 Dominance analysis Not supported
Hypothesis 3a Hierarchical regression analysis
Comparison of regression lines
Not supported
Hypothesis 3b Hierarchical regression analysis
Comparison of regression lines
Supported
RQ2 Hypothesis 4a Partial correlation analysis
Hierarchical regression analysis
Supported
Hypothesis 4b Hierarchical regression analysis
Comparison of regression lines
Partially supported
RQ3 Hypothesis 5a Partial correlation analysis
Hierarchical regression analysis
Partially supported
Hypothesis 5b Hierarchical regression analysis
Comparison of regression lines
Partially supported
Hypothesis 5c Hierarchical regression analysis
Comparison of regression lines
Partially supported
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CHAPTER FIVE
CONCLUSION
This chapter includes the summary of key research findings, discussion of the findings,
implications for research and practice, limitations of the study, and suggestions for future
research.
Summary of the Findings
What follows is a summary of the findings described in the previous chapter. It is
organized according to the three research questions of this study.
Research Question 1
Research Question 1 was ―What is the relationship between the change strategy perceived
by those responding to a planned change and their readiness for change?‖ The following
hypotheses were proposed to address this research question.
Hypothesis 1a: The power-coercive change strategy will be negatively related to
readiness for change
Hypothesis 1b: The normative-reeducative change strategy will be positively
related to readiness for change.
Hypothesis 1c: The empirical-rational change strategy will be positively related to
readiness for change
Hypothesis 2: The normative-reeducative change strategy will be more effective
than the empirical-rational change strategy in fostering readiness for change.
Hypothesis 3a: The normative-reeducative change strategy will moderate the
relationship between the power-coercive change strategy and readiness for change.
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Specifically, the stronger the normative-reeducative change strategy is, the
weaker the negative relationship between the power-coercive change strategy and
readiness for change will be.
Hypothesis 3b: The normative-reeducative change strategy will moderate the
relationship between the empirical-rational change strategy and readiness for
change. Specifically, the stronger the normative-reeducative change strategy is,
the stronger the positive relationship between the empirical-rational change
strategy and readiness for change will be.
As Hypotheses 1a, 1b, and 1c proposed, the analysis results indicated that the power-
coercive change strategy was negatively related to readiness for change (overall readiness for
change as well as its four sub-dimensions); and both the normative-reeducative change strategy
and the empirical-rational change strategy were positively related to readiness for change
(overall readiness for change as well as its four dimensions). In addition, each change strategy
explained a significant amount of the variance in readiness for change.
The test on Hypothesis 2 (dominance analysis) showed that the empirical-rational change
strategy contributed more to the variance in readiness for change than the normative-reeducative
change strategy did. In other words, the empirical-rational change strategy was more important
than the normative-reeducative change strategy in understanding readiness for change. Thus,
Hypothesis 2 was not supported.
As the test on Hypothesis 3a showed, the normative-reeducative change strategy did not
moderate the relationship between the power-coercive changes strategy and overall readiness for
change. Further examination revealed that the normative-reeducative change strategy moderated
the negative relationship between the power-coercive change strategy and one of the dimensions
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of readiness for change—change-specific efficacy (R1). However, the nature of the moderating
effect was opposite to what was expected in Hypothesis 3a. The result showed that the
normative-reeducative change strategy did not mitigate the negative effect of the power-coercive
change strategy on change-specific efficacy (R1). Rather, the negative relationship between the
power-coercive change strategy and change-specific efficacy (R1) was stronger at the higher
level of normative-reeducative change strategy. Therefore, Hypothesis 3a was not supported.
The test on Hypothesis 3b showed that the normative-reeducative change strategy
moderated the relationship between the empirical-rational change strategy and readiness for
change (including all its four dimensions). As expected, the positive relationship between the
empirical-rational change strategy and all four dimensions of readiness for change was stronger
at the higher level of normative-reeducative change strategy. In other words, the empirical-
rational change strategy was more effective when combined with the higher level of normative-
reeducative change strategy than when combined with the lower level of normative-reeducative
change strategy. Therefore, Hypothesis 3b was supported.
Research Question 2
Research question 2 of this study was ―What is the relationship between the learning
culture perceived by those responding to a planned change and their readiness for change?‖ To
address this research question, the following two hypotheses were proposed.
Hypothesis 4a: Learning culture will be positively related to readiness for change.
Hypothesis 4b: Learning culture will moderate the relationship between the
normative-reeducative change strategy and readiness for change. Specifically, the
stronger the learning culture is, the stronger the positive relationship between the
normative-reeducative change strategy and readiness for change will be.
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The test on Hypothesis 4a showed that overall learning culture was positively related to
readiness for change. Also, it showed that every dimension of learning culture, with the
exception of promoting inquiry and dialogue (LC2), was positively related to all four dimensions
of readiness for change. Furthermore, learning culture explained a significant amount of the
variance in readiness for change. Thus, hypothesis 4a was supported.
The test on Hypothesis 4b showed that the normative-reeducative change strategy
moderated the relationship between learning culture and readiness for change (across all its four
dimensions). Specifically, two dimensions—encouraging collaboration and team learning (LC3)
and establishing systems to capture and share learning (LC5)—moderated the relationship
between the normative-reeducative change strategy and overall readiness for change. All seven
dimensions of learning culture moderated the relationship between the normative-reeducative
change strategy and change-specific efficacy (R1). One dimension, establishing systems to
capture and share learning (LC5), moderated the relationship between the normative-reeducative
change strategy and management support for the change (R3). Finally, the dimension of
promoting inquiry and dialogue (LC2) moderated the relationship between the normative-
reeducative change strategy and personal benefit of the change (R4). Further examination
revealed that, as expected, the positive relationship between the normative-reeducative change
strategy and readiness for change was stronger when the score on learning culture was higher.
Thus, Hypothesis 4b was supported. This result supports the argument that a learning culture
helps individuals be prepared to make genuine contributions to changes; therefore, normative-
reeducative change strategies are likely to be more effective in a situation with a stronger
emphasis on learning culture.
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Research Question 3
Research Questions 3 was ―How does the impact of the change on individuals’ jobs affect
the two relationships presented in the first two research questions?‖ In Chapter 2, three
hypotheses concerning the role of individual job level impact were proposed to address this
research question.
Hypothesis 5a: The magnitude of individual job level impact will be negatively
related to readiness for change.
Hypothesis 5b: The magnitude of individual job level impact will moderate the
relationship between the normative-reeducative change strategy and readiness for
change. Specifically, the stronger the individual job level impact is, the stronger
the positive relationship between the normative-reeducative change strategy and
readiness for change will be.
Hypothesis 5c: The magnitude of individual job level impact will moderate the
relationship between learning culture and readiness for change. Specifically, the
stronger the individual job level impact is, the stronger the relationship between
learning culture and readiness for change will be.
The test on Hypothesis 5a showed that change impact was negatively related to overall
readiness for change, but only marginally. Thus, Hypothesis 5a was marginally supported.
Among the four dimensions of readiness for change, change impact was negatively related to
change-specific efficacy (R1) and personal benefit of the change (R4). But it was not
significantly related to appropriateness of the change (R2) or management support for the change
(R3).
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The test on Hypothesis 5b indicated that change impact did not moderate the relationship
between the normative-reeducative change strategy and overall readiness for change. Further
investigation showed that, depending on the level of change impact, the normative-reeducative
change strategy had differential effects on one dimension of readiness for change–personal
benefit of the change (R4). Specifically, as expected, the positive relationship between the
normative-reeducative change strategy and personal benefit of the change (R4) was stronger
when the impact of the change was higher. As the interaction between change impact and the
normative-reeducative change strategy was limited only to personal benefit of the change (R4)
and did not affect overall readiness for change, Hypothesis 5b was partially supported.
Finally, the test on Hypothesis 5c showed that change impact did not moderate the
relationship between the normative-reeducative change strategy and overall readiness for change.
Further investigation showed that, depending on the level of change impact, learning culture had
differential effects on one of the dimensions of readiness for change—personal benefit of the
change (R4). The moderating effects occurred in a way that was expected in Hypothesis 5c:
learning culture was more effective in increasing individuals’ belief in the personal benefit of the
change (R4) when the impact of the change was higher. In addition, when examining each
dimension of learning culture, change impact also moderated the relationship between creating
continuous learning opportunities (LC1) and personal benefit of the change (R4), the relationship
between promoting inquiry and dialogue (LC2) and personal benefit of the change (R4), the
relationship between establishing systems to capture and share learning (LC5) and personal
benefit of the change (R4), and the relationship between providing strategic leadership for
learning (LC7) and personal benefit of the change (R4). As the interaction between change
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impact and learning culture was limited only to personal benefit of the change (R4) and did not
affect overall readiness for change, Hypothesis 5c was partially supported.
Relative Importance of Study Variables
The relative importance among the study variables was examined in addition to the three
main research questions. The dominance analysis results indicated that change strategies was the
most important set of variables, explaining the majority of the variance in overall readiness for
change. Furthermore, in four of the five analyses (one for overall readiness for change and four
for the dimensions of readiness for change), learning culture emerged as the second most
important factor in understanding readiness for change. Across the four dimensions of readiness
for change, change strategies and learning culture together explained 75.3 to 84 percent of the
variance that could be attributed to all the variables included in this study. On the other hand, the
individual differences variables altogether explained only 11.5 to 16.5 percent of the variance
accounted for by the study variables.
Discussion of the Findings
This section includes the discussion of the findings summarized above. It is organized
according to the key topics of this study.
Change Strategies and Readiness for Change
As researchers with a social constructionist viewpoint contend, organizational change is a
situation that interrupts normal patterns of organization (Ford et al., 2008). When faced with
organizational change, individuals are actively involved in information seeking, meaning
ascription, and assumption making about the change process to make sense of the new
environment and to draw conclusions about its possible outcomes (Ford et al., 2008; Gioia et al.,
1994). This includes extracting particular behaviors of leaders and communications specific to
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the organizational change out of streams of ongoing events, interpreting them, and acting on the
resulting interpretation (Ford et al., 2008). In this respect, the change strategies used by leaders
or agents of an organization are critical in the development of individuals’ readiness for change.
As the findings summarized above indicated, all three change strategies made significant
and unique contributions to readiness for change. Furthermore, as expected, the directions of the
relationship that each change strategy had with readiness for change were different. The power-
coercive change strategy had a negative effect on readiness for change and the empirical-rational
change strategy and the normative-reeducative change strategy had a positive effect on it.
Furthermore, both the dominance analysis results and hierarchical regression analysis results
indicated that the normative-reeducative change strategy did not mitigate the negative effect of
the power-coercive change strategy on readiness for change. Worse yet, when it comes to
change-specific efficacy (R1), the negative relationship between the power-coercive change
strategy and change-specific efficacy became even stronger (i.e., the negative effect of the
power-coercive change strategy became aggravated) at the higher level of normative-reeducative
change strategy. This findings suggest that change recipients may not perceive leaders’ or change
agents’ actions for the normative-reeducative change strategy as being authentic where the
power-coercive change strategy is the primary change strategy.
In addition, as the dominance analysis results indicated, when comparing the empirical-
rational change strategy with the normative-reeducative change strategy, the former contributed
more to the variance in readiness for change than the latter. However, this doesn’t mean that the
normative-reeducative change strategy is less effective than the empirical-rational change
strategy. As the hierarchical regression analysis results showed, the empirical-rational change
strategy interacted with the normative-reeducative change strategy such that the former was more
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effective when it was combined with a higher level of normative-reeducative change strategy.
Thus, to be more effective, the empirical-rational change strategy needs to be combined with the
normative-reeducative change strategy.
In sum, the findings of this study indicated that the power-coercive change strategy had
detrimental effects on readiness for change, which the normative-reeducative change strategy
would not be able to mitigate. Therefore, in addition to creating an environment in which
employees experience empirical-rational and normative-reeducative change strategies, making
conditions to minimize experiences related to power-coercive change strategies is also important
in fostering readiness for change. The analysis results also indicated that the organization needs
to combine normative-reeducative change strategies with empirical-rational change strategies to
further increase individuals’ readiness for change. The discussion summarized in this paragraph
resonates with Beer and Nohria’s (2000a) idea:
Clearly, if the objective is to build a company that can adapt, survive, and prosper over
the years, Theory E strategies must somehow be combined with Theory O strategies. But
unless they’re carefully handled, melding E and O is likely to bring the worst of both
theories and the benefits of neither. Indeed, the corporate changes we’ve studied that
arbitrarily and haphazardly mixed E and O techniques proved destabilizing to the
organizations in which they were imposed. (p. 138)
Learning Culture and Readiness for Change
As discussed in Chapter Two, in an organization which embodies a learning culture,
individuals have many opportunities to be engaged in organizational inquiry as well as to capture
and share what has been learned by others (Preskill & Torres, 1999b; Watkins & Marsick, 1993,
1996). Through these opportunities, learning culture enables individuals to be agents learning on
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behalf of their organization and to be ready for organizational changes. Furthermore, individuals
in an organization with a strong emphasis on learning culture may have learned that the
organization is likely to thrive under changing organizational conditions, which will also help
them be ready for change.
The findings of this study supported this argument. The correlation analysis results
indicated that learning culture had a positive relationship with readiness for change. Also, the
hierarchical regression analysis showed that learning culture explained a significant amount of
the variance in readiness for change.
Furthermore, learning culture contributes to shaping readiness for change by moderating
the relationship between normative-reeducative change strategies and readiness for change. As
argued in Chapter Two, one of the biggest differences between the proponents of the strategic
management approach and those of the OD approach is the view on organizational members’
capability. Hypothesis 4b was based on the idea that ―participation by knowledgeable, skilled,
and motivated members of the organization does enhance a change project; participation by
uninformed, unskilled, and unmotivated members of the workforce does not‖ (Dunphy, 2000, p.
133). In other words, organizational members must be knowledgeable, capable, and motivated to
make a genuine contribution in order for their involvement and participation in the change
process to have successful outcomes. As I reviewed in Chapter Two, learning culture, which is a
reaffirmation of long-standing beliefs of OD (Watkins & Golembiewski, 1995), would enhance
employees’ capability to identify and solve work-related problems (Watkins & Marsick, 1993).
In this respect, normative-reeducative change strategies could be effective especially when there
is a strong emphasis on learning culture.
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The findings of this study also supported this argument. The analysis showed that overall
learning culture moderated the positive relationship between the normative-reeducative change
strategy and readiness for change, particularly change-specific efficacy (R1), such that the
positive relationship between the two was stronger when the score on learning culture was higher.
Furthermore, the analysis showed that each of the seven dimensions of learning culture had
distinct effects on a different dimension of readiness for change. For example, when individuals
have experienced a stronger emphasis on encouraging collaboration and team learning (LC3)
and/or establishing systems to capture and share learning (LC5) in the organization, the
normative-reeducative change strategy is more effective in increasing their overall readiness for
change. When individuals have experienced a stronger emphasis on establishing systems to
capture and share learning (LC5) in the organization, the normative-reeducative change strategy
is more effective in increasing their beliefs in management support for the change (R3). Also,
when individuals have experienced a stronger emphasis on promoting inquiry and dialogue (LC2)
in the organization, the normative-reeducative change strategy is more effective in increasing
their beliefs in personal benefit of the change (R4).
As discussed above, the normative-reeducative change strategy can be more effective in a
situation in which there is an ongoing organizational effort to foster a learning culture and to
enhance organizational health and capability (Watkins & Golembiewski, 1995). The seven
dimensions of learning culture strengthen the positive relationship between the normative-
reeducative change strategy and more than one dimension of readiness for change. In sum, a
learning culture not only directly promotes an environment where individuals tend to be more
ready for change but also makes a condition where the normative-reeducative change strategy
approach to planned change can be more effective in fostering readiness for change.
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Change Impact and Readiness for Change
It is commonly accepted that individuals’ attitudinal reactions to organizational change
are driven, in part, by feelings of uncertainty, loss of familiar routines, and fear of failure
engendered by a change event (Brehm & Brehm, 1981; Burke, 2008; Ledford et al., 1989; Oreg,
2003). Therefore, individuals are thought to be more negative about a change initiative that has
larger impact on their jobs.
The findings of this study supported this argument, but only marginally. Change impact
and overall readiness for change were marginally correlated. Further examination showed that
change impact was negatively related to two dimensions of readiness for change: change-specific
efficacy (R1) and personal benefit of the change (R4). On the other hand, change impact did not
correlate with appropriateness of the change (R2) or with management support for the change
(R3). In sum, it can be argued that individuals may feel less ready for change when the change
impact is high than when it is low. Specifically, as individuals perceive the impact of a change
on their jobs to be higher, they tend to consider themselves as less capable of dealing with the
change and consider the change as less beneficial to themselves. However, overall, the negative
relationship between change impact and readiness for change is only marginal. Furthermore,
change impact appears not to affect individuals’ beliefs in the appropriateness of a change (R2)
or in management support for the change (R3).
In addition, in Chapter Two, it was proposed that change impact (the impact of a change
on individuals’ jobs) provides a context within which change strategies and a learning culture
contribute to shaping individuals’ responses to the change. Specifically, Hypotheses 5b and 5c
suggested that, under conditions of high amounts of individual job changes, change strategies
used in the situation and a learning culture in the work environment would become more salient
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and their effects on readiness for change would be amplified. The hierarchical regression
analysis results partially supported this argument. First of all, the analysis showed that the
normative-reeducative change strategy had differential effects on individuals’ beliefs in the
personal benefit of the change (R4) depending on the magnitude of change impact. Specifically,
the normative-reeducative change strategy was more effective when change impact was high
than when it was low. Similarly, learning culture also had differential effects on individuals’
beliefs in the personal benefit of the change (R4) depending on the magnitude of the change
impact. That is, learning culture was more effective when change impact was high than when it
was low.
In sum, individuals tend to be less ready for a change initiative that accompanies a larger
impact on their job. But, the findings suggest that the association between the two is only
marginal and is limited to certain aspects of readiness for change. Furthermore, both change
strategies and the learning culture have differential effects on readiness for change depending on
the magnitude of change impact. Specifically, at times of a change accompanying a huge impact
on individuals’ job, the normative-reeducative change strategy and learning culture would
become more effective in shaping readiness for change, particularly individuals’ beliefs in the
personal benefit of the change (R4).
Individual Differences and Readiness for Change
Whether individuals with certain characteristics tend to be more positive about
organizational change than others without those characteristics has been of interest to many
researchers. Research findings regarding the effects of demographic differences and personality
variables on individuals’ attitudes toward organizational change are not consistent. For example,
some research has reported a significant relationship between certain personality variables and
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individuals’ attitudes toward organizational change (e.g., Chen & Wang, 2007; Elias, 2009;
Wanberg & Banas, 2000). However, other research has indicated that personality-based
predispositions are of minor importance in determining individuals’ attitudes to change (e.g.,
Devos et al., 2007; Devos et al., 2001; Wanous et al., 2000).
The findings of this study suggest that individual differences have a relatively minor
importance in explaining individuals’ readiness for change. Among the five variables related to
individual differences (age, gender, organizational tenure, educational level, and negative
affectivity), only age and gender had a statistically significant relationship with readiness for
change. Furthermore, even though individual difference variables made contributions across the
dimensions of readiness for change, their importance was relatively small compared to that of
change strategies and the learning culture. This finding indicates that individuals’ readiness for
change can be more attributed to the situation than to the person (Devos et al., 2007; Devos et al.,
2001; Wanous et al., 2000). While personality may have an effect on attitudes toward change in
general, its effects are likely to become minor in a specific change context due to the decisive
effects of the situational variables.
Implications for Research
The findings of this study have substantial implications for research. In this section, the
implications are discussed focusing on the following three themes: (1) reconceptualizing
employees’ reactions to organizational change, (2) proposing a framework for HRD research on
organizational change, and (3) reaffirming organization development and change as a legitimate
realm of HRD.
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Reconceptualizing Employees’ Reactions to Organizational Change
As discussed in Chapter Two, the concept of individual readiness for change is found in
the influential works of Lewin (1947/1997b), Rogers (1983, 2003), and Hall and Hord (1987).
Furthermore, the importance of individual readiness for organizational change has been stressed
by most change models, ranging from Lewin’s three-step change model, which provides the
basis for almost all the OD change models, to Kotter’s change process model which exemplifies
the strategic management approach to organizational change.
The use of the construct of individual readiness for organizational change gives us
advantages over the common use of resistance to change. Oftentimes, resistance to change is
viewed as ―a reactive process where agents embedded in the power relations actively opposed
initiatives by other agents‖ (Jermier et al., 1994, p. 9). By using the term ―resistance to change,‖
leaders and change agents commonly fail to notice the potentially positive intentions that may
motivate negative responses to change. On the other hand, as discussed in Chapter Two, the
concept of readiness for change assumes that individuals’ concerns over change are natural and
there must be reasons for the concerns. Furthermore, it is also assumed that change can be more
successful if the concerns of change recipients are considered. Therefore, the concept of
readiness for change helps us pay attention to the key components of such concerns—for
example, as this study illustrated, individuals’ evaluation of management support for and
personal benefit of a specific change initiative. Also, it draws attention to the situational causes
of those concerns, such as those indicated by the findings of this study: the change strategies
employed by the leaders and the existence of ongoing efforts to foster the learning culture in the
organization. In this regard, readiness for change is a more valid and practical concept to
understand employees’ attitudes toward organizational change than resistance to change.
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Furthermore, by examining the relationship between negative affectivity and readiness
for change, this study addressed the basic issue of how a personality variable might predispose
some individuals to have low levels of readiness for change. As reviewed above, previous studies
have reported mixed results regarding the influence of personality variables on attitudes toward
organizational change. For example, some studies have suggested that personality variables such
as internal locus of control, internal work motivation, self-esteem, and optimism are significantly
related to attitudes toward organizational change (Chen & Wang, 2007; Elias, 2009; Judge et al.,
1999; Wanberg & Banas, 2000). On the other hand, other studies have indicated that personality
variables such as locus of control and negative affectivity do not have a significant relationship
with readiness for change (Devos et al., 2001; Wanous et al., 2000). The findings of this study
provided further support for the latter group of research, by suggesting that negative affectivity
does not correlate with readiness for change.
As is widely acknowledged, it is important to separate general attitudes from specific
attitudes (Eagly & Chaiken, 1993; Fisher, 1980; Katz & Kahn, 1978). In an organization, a
person may have a general attitude toward change but, at the same time, the person can possess
different attitudes about particular change initiatives. While the former may depend more on
personal needs and values, the latter is determined largely by one’s experience within the
organizational context (Katz & Kahn, 1978; Lau & Woodman, 1995). For example, even though
a person is supportive of organizational change in general, his/her attitudes about a specific
change initiative being undertaken may vary depending on how he/she evaluates the issues
involved in the change implementation. The findings of this study suggest that negative attitudes
toward particular organizational change, more specifically low levels of readiness for change, are
not simply the feelings that negative people (people with a high level of negative affectivity)
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bring into the organization; rather, the attitudes are more attributed to the situation, particularly
change strategies and learning culture. While personality has an effect on attitudes toward
change in general, its effect may become irrelevant in a specific change context due to the
decisive effects of the situational variables (Devos et al., 2001; Wanous et al., 2000). In this
respect, readiness for change is not a personality-based predisposition. It is ―shaped by
experiences in the work context‖ (J. L. Johnson & O'Leary-Kelly, 2003, pp. 640-641) and,
therefore, is likely to change as individuals’ experiences change. This conclusion supports the
idea that readiness for change is malleable by appropriate efforts at the organizational level
(Bommer et al., 2005).
Importance of OD Approaches in the Context of Organizational Change
In this study, I focused on two key features of OD as the conditions conducive to
fostering individual readiness for organizational change: (a) OD approaches to change
implementation which are based on the normative-reeducative change strategy (Chin & Benne,
1985) and (b) OD approaches as an ongoing organizational effort to enhance organizational
health and capability through fostering a learning culture (Watkins & Golembiewski, 1995).
Specifically, to discuss the effectiveness of OD approaches to change implementation in
fostering readiness for change, I compared OD approaches to change with strategic management
approaches to change. Based on the work of Chin and Benne, I highlighted the differences
among the key change models under the two approaches. Additionally, to examine the effects of
the learning culture on readiness for change, I introduced Watkins and Marsick’s (1993, 1996)
framework of the learning organization which integrates theories on organizational learning and
on organizational culture. Finally, I also examined whether the role of OD approaches to change
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implementation and the role of learning culture vary depending on the impact of a change
initiative.
As Beer and Nohria (2000a, 2000b) observed, both the OD and the strategic management
approaches to organizational change have their own validity, and change implementations in the
real world are usually a mixture of these two archetypical strategies. However, while the
strategic management approaches are very popular among corporate leaders in that they can
result in increased economic value in a relatively short period of time, OD approaches to change
implementation have been relatively neglected and regarded as less important. Worse yet, OD
approaches are often criticized as being ―extremely limited and value based‖ (Dunphy & Stace,
1988, p. 317) by the proponents of the strategic management approaches who claim that directive
and coercive strategies are generally more effective in bringing about change (Conger, 2000;
Locke et al., 1986).
Is the criticism of OD approaches valid? Are OD approaches limited and ineffective in
facilitating organizational change? As is reviewed above, readiness for change is critical in the
success of change initiatives. Given that many organizational changes do fail because of low
levels of individual readiness for change, it is worthwhile to examine which approaches to
organizational change are more effective in fostering readiness for change in organizations. This
study synthesized previous literature to support the effectiveness of OD approaches. Furthermore,
based on the synthesis, this study empirically showed that the two key features of OD—change
strategies based on the normative-reeducative change strategy and an ongoing effort to enhance
learning culture—are effective in fostering individuals’ readiness for organizational change.
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Framework for HRD Research on Organizational Change
Although researchers have stressed the relevance of change process, change context, and
change content in understanding organizational change (Armenakis & Bedeian, 1999; Pettigrew
& Whipp, 1991), few researchers have empirically studied their simultaneous effects. Previous
studies have usually focused on a single aspect of change: for example, Sta. Maria and Watkins
(2003) focused specifically on organizational culture, Bommer et al.(2005) dealt with issues
related to a specific type of leadership, and Wanberg and Banas (2000) examined individuals’
experience with change process in the context of organizational change. Even though the
findings of these studies were informative and enhanced our understanding to a great extent, a
more holistic picture is needed to capture the complexity and multidimensional character of
organizational change.
The purpose of this study was to examine the conditions that foster readiness for change.
For this purpose, I investigated the concurrent effects of change strategies (change process),
learning culture (change context), and impact of change (change content) on individuals’
readiness for change. In addition to their independent effects on readiness for change, this study
also dealt with how the three aspects of organizational change intersect with each other to impact
readiness for change. Specifically, this study examined how learning culture (change context)
interacts with change strategies (change process) to make an environment where individuals tend
to be more ready for change. I also investigated whether the role of change strategies (change
process) and learning culture (change context) would vary depending on the impact of a change
initiative (change content). The findings of this study revealed that change process, change
context, and change content not only have significant influences on individuals’ readiness for
change independent of each other but also interact with each other to impact readiness for change.
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The findings indicate the complexity and multidimensional character of change initiatives and
their impact on individuals.
By considering the impact of change process, change context, and change content all
together in examining the conditions conducive to individual readiness for change, this study
may add new insights into these areas where empirical work has been limited. Furthermore, the
framework used to empirically examine the hypothesized relationships among the key variables
of this study can be modified by other HRD researchers to examine the value of OD approaches
with different outcome criteria or dependent variables.
Organization Development and Change as a Legitimate Realm of HRD
As researchers have noted, the term HRD is used in many different contexts and is
concerned with a wide range of activities (Blake, 1995; Garavan, Costine, & Heraty, 1995;
McCracken & Wallace, 2000). Traditionally, the role of HRD has been seen as that of a deliverer
of training activities for improving individual employees’ skills and knowledge in response to
specific problems (Beer & Spector, 1985; Gilley & Maycunich, 2002). As a consequence,
organizational change had received much less attention compared to other areas of the traditional
HRD. A recent citation analysis study conducted on the major HRD journals—Human Resource
Development Quarterly, Human Resource Development Review, Human Resource Development
International, and Advances in Developing Human Resources—showed that OD, organizational
change, and change management have not been the major themes of the articles published during
the past two decades in the field of HRD (Jo, Jeung, Park, & Yoon, 2009).
Even though HRD and OD have evolved somewhat independently (Ruona & Gibson,
2004), it is widely acknowledged that the two are inseparable. The idea that change always
involves learning (Beckhard & Pritchard, 1992; A. D. Meyer, 1982a) is one of the basic
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assumptions shared by HRD and OD researchers (Swanson & Holton, 2001). More clearly,
Watkins and Marsick (1993) explained the relationship between change and learning by defining
change as ―a cyclical process of creating knowledge (the change or innovation), disseminating it,
implementing the change, and then institutionalizing what is learned by making it part of the
organization’s routines‖ (p. 21). Other organizational learning theorists have also argued that
organizational learning is a prerequisite for successful organizational change (Baker & Sinkula,
1999; Garvin, 1993; Lundberg, 1995; Ulrich et al., 1993). This fundamental relationship between
learning and change points out why change is one of the core constructs for the field of HRD
(Swanson & Holton, 2001). Furthermore, in reality, HRD has been increasingly required to help
the organization achieve its business results, improve its competitiveness, and enhance its
capability to achieve goals and solve problems (Christensen, 2006; Gilley & Maycunich, 2002;
Robinson & Robinson, 1989; Ruona & Gibson, 2004; Torraco & Swanson, 1995; Ulrich &
Brockbank, 2005). In fact, studies on HRD professionals’ roles have consistently emphasized
OD and organizational change as critical realms of their roles (ASTD, 2004; McLagan, 1989).
The findings of this study show that the values of human potential, participation, and
development embedded in the OD approaches, which are also embraced by HRD professionals,
can be effective in facilitating and sustaining organizational change. By doing so, this study
emphasized the potential contributions HRD professionals could make for facilitating and
sustaining organizational change with their insights in learning and change.
Implications for Practice
The role of HRD practitioners as change agents is becoming increasingly important
(Christensen, 2006; Ulrich & Brockbank, 2005). The practical implications of this study are
mainly concerned with the role of HRD in leading and facilitating change.
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Framing the Change Situation with the Construct of Readiness for Change
One of the basic premises of this study is that major successful organizational change
rarely happens unless individual members assist it. Change in organizations always involves
changing individuals through making new patterns of action, beliefs, and attitudes among the
individuals (Schein, 1996/1999a). This perspective of organizational change requires HRD to
move beyond training-oriented change interventions (Swanson & Holton, 2001) and to focus
more on the whole unfreezing process (Lewin, 1947/1997b). In Chapter Two, based on a review
of the literature, I proposed that the level of readiness for change can be a powerful measure to
assess how effectively an organization has achieved the unfreezing process.
As discussed in Chapter Two, the question of ―how to foster readiness for change‖ can
clearly bring about different perspective on the situation and produce different outcomes from
the question of ―how to overcome resistance to change.‖ The former question creates a more
dynamic, proactive, and systemic view of change than the latter. In addition, while the latter
question assumes that change agents’ role is that of monitors who react to signs of resistance, the
former question can enable change agents to take the role of coaches and champions for change
who design environments conducive to readiness for change in organizations (Jansen, 2000).
With precise understanding of the concept of readiness for change, HRD practitioners can
accurately capture the meanings and information attached to employees’ attitudes toward
organizational change and reveal problems in the change implementation. Also, they will be able
to better guide the unfreezing phase (Lewin, 1947/1997b) in organizations and make more
appropriate interventions for the organizational change implementation.
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Advocating and Advancing the HRD Practitioners’ Role in Organizational Change
Negative affectivity (Watson et al., 1988) is a personality variable that concerns an
individual’s general outlook on life. It was included in this study to address the basic issue of
whether a personality variable like negative affectivity might predispose some individuals to be
negative about change and to be less ready for it. More specifically, it was chosen for this study
to address the assumption often held by leaders and managers that some individuals are less
ready for any change initiative in the organization to the extent that they are generally negative
(Wanous et al., 2000). The findings of this study undermine this assumption. According to the
analysis results presented in Chapter Four, negative affectivity has no statistically significant
relationship with readiness for change. Furthermore, the individual difference variables including
demographic characteristics and negative affectivity only explained a relatively small portion of
the variance in readiness for change. As the findings of this study suggest, rather than individual
difference, situational causes play an important role in shaping employees’ attitudes toward
organizational change.
In this respect, one of the main lessons that this study may provide for HRD practitioners
is that individuals’ readiness for change can be shaped by appropriate efforts at the
organizational level. HRD practitioners should be concerned about creating an environment in
which individuals can be more ready for change. Specifically, as the findings of this study
indicate, they need to help individuals experience empirical-rational and normative-reeducative
change strategies in their work in times of change and be able to judiciously use the OD-oriented
approaches in a variety of ways. For example, they can take steps to enhance employees’
confidence in their own abilities to accommodate a particular change initiative. Also, their long-
term efforts to create the learning culture need to be understood as creating a range of training
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activities, developmental relationships, and a learning environment that respond to the need for
facilitating and sustaining organizational change. As the findings of this study illustrate, the
ongoing efforts to build a learning organization—such as creating continuous learning
opportunities, encouraging collaboration and team learning, establishing systems to capture and
share learning, and providing strategic leadership for learning (Watkins & Marsick, 1993)—have
beneficial effects on increasing individuals’ readiness for change in times of change.
Limitations of the Study
This study has limitations that need to be acknowledged. The major limitations are
concerned with the risk of nonresponse bias, the potential threat to construct validity, the use of a
single data source, limited generalizability of the findings, and the potential presence of
prochange biases.
Response Rate and Risk of Nonresponse Bias
As reported in Chapter Three, the survey invitations were sent to 948 individuals in the
organization. Among them, 160 returned completed responses, with a response rate of 17 percent.
Achieving a high response rate on physician surveys has been admitted to be a challenging task
(Delnevo, Abatemarco, & Steinberg, 2004). In particular, a recent experiment on physicians’
survey response behaviors revealed that the physicians’ response rate decreased dramatically (in
that study, to 16.7%) when the questionnaires were over 1,800 words in length (Jepson, Asch,
Hershey, & Ubel, 2005). Considering that the questionnaire of this study had 1,733 words, the
low participation of physicians in this study appears to be somewhat expected.
According to some researchers, little evidence has been found for a relationship between
response rate and nonresponse bias (Groves, 2006). For example, Keeter and the colleagues
(Keeter, Kennedy, Dimock, Best, & Craighill, 2006; Keeter, Miller, Kohut, Groves, & Presser,
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2000) showed that low response rates do not always results in high nonresponse bias. As a way
to check for nonresponse bias, it is recommended to conduct further analyses such as
respondent/nonrespondent analysis (Creswell, 2003). As discussed in Chapter Three, the
comparison between the respondents of this study and the data from the Bureau of Labor
Statistics (2010) showed that the composition of the respondents was largely consistent with that
of the workforce in the healthcare industry. However, the respondent/ nonrespondent analysis
specific to this study could not be conducted because detailed information concerning the
employees’ profile could not be disclosed by the organization due to confidentiality reasons. The
potential risk of nonresponse error could be a limitation of this study since the 160 individuals
who returned completed responses might be different from those who did not in a way that was
important to this study (Dillman et al., 2008; Spector, 1992).
Potential Threat to Construct Validity
One of the most conspicuous limitations of this study lies in the measurement models.
With the exception of the DLOQ, other measures were relatively new and validated by only a
few studies. Thus, this study needed to provide proof of the construct validity for those newer
measures. As discussed in Chapter Three, power analyses indicated that the sample size (N=151)
was appropriate for minimizing Type II errors in testing the hypotheses of this study. However,
CFA for the overall measurement model could not be conducted because the sample size of this
study was not large enough to meet the criteria concerning sample sizes required for CFA: ten
observations per each estimated parameter (Jackson, 2003). Even though the examination of the
individual measurement models provided initial support for construct validity of the measures
used in this study, CFA for the overall measurement model would have provided further
evidence of the construct validity if it could have been conducted.
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Furthermore, in the individual measurement models examined in Chapter Three, a few
standardized factor loadings were relatively low. For example, the factor loading from the
power-coercive change strategy to the first item measuring it (PC→PC1) was .48 (see Figure 6.1
in Appendix C) and that from change-specific efficacy to the second item measuring it
(R1→R1.2) was .44 (see Figure 6.5 in Appendix C). Even though the measurement models
provided an adequate fit to the data collected from the sample, the presence of indicators with a
low factor loading may have threatened the convergent validity of the measures, which can in
turn reduce the statistical power to detect interactions in multiple regression (Aiken & West,
1991).
Use of a Single Data Source
In addition, the data used in this study was collected through self-report surveys. As I
discussed in Chapters Three, the use of self-report data gave some advantages to this study.
However, the respondent providing the measure of independent and dependent variables was the
same person, which may result in inflated correlations between the study variables (Podsakoff,
MacKenzie, Lee, & Podsakoff, 2003). Thus, the use of self-report data in this study may pose the
threat of common method variance, which is one of the most frequently mentioned concerns
among social scientists in general including organizational researchers (Podsakoff et al., 2003;
Podsakoff & Organ, 1986).
Harman’s single-factor test was conducted to examine the presence of common method
variance in this dataset of this study. In this single-factor test, all of the items in a study are
subject to exploratory factor analysis (EFA). Common method variance is assumed to exist if (1)
a single factor emerges from unrotated factor solutions, or (2) a first factor explains the majority
of the variance in the variables (Podsakoff & Organ, 1986). Results of an EFA using principal
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components extraction did not support the presence of a method factor. Sixteen factors emerged
with eigenvalues greater than 1.0, and the first factor accounted for 25.711 percent of the total
variance. Thus, I concluded that no substantial common method variance exists in the dataset
used in this study.
Limited Generalizability
The fourth limitation of this study is concerned with the fact that this study used a dataset
collected from a single organization. As discussed in Chapter Three, collecting data from one
organization has advantages. In particular, it gives researchers some control over the
confounding effects which may present in cross-organizational research (Eby et al., 2000). If this
study had used datasets collected from multiple organizations, the differences in, for example,
HR policies and history of change attempts among organizations could have caused
organizational-level systematic variance in readiness for change.
Despite its advantage, however, collecting data from a single organization may limit the
generalizability of the study findings. As explained previously, the data to test the hypotheses of
this study were collected from a large healthcare organization, and the characteristics of the jobs
and work processes in the organization may have influenced the findings of this study.
Specifically, the individuals working in the hospitals are likely to have been trained to perform
effectively in an environment where empirical-rational change strategies are dominant compared
with those working in other industries. In this respect, attempts to generalize the findings of this
study to different organizational settings or to a situation where different types of change
initiatives are being implemented (e.g., a change initiative driven by the implementation of a new
technology) should be carefully guided.
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Issue of Prochange Biases
Researchers in the field of OD and change themselves have noted that prochange biases,
the presumption that changes will eventually benefit organizations, are prevalent in the
organizational change literature (Abrahamson, 1991; Kimberly, 1981; Rogers, 2003). Depending
on the intention of the person who uses the concept of readiness for change, it can also be used to
argue that individuals need to be ready for any change initiatives and, consequently, endorse
prochange biases. This can be an issue because change is not always good; change can result in a
less effective organization if it is ill conceived, poorly implemented, or not focused on desired
outcomes (Swanson & Holton, 2001).
However, the arguments developed and examined in this study can also help researchers
and practitioners overcome prochange biases. One of the potential implications of this study is
that certain situational causes do affect or shape individuals’ reactions to organizational change.
By examining these situational causes, organizations can improve change implementation, adopt
effective and efficient change efforts, and reject unproductive ones. In this respect, even though
the concept of readiness for change might be misused to endorse prochange biases, the
arguments presented in this study can help organization change professionals to overcome the
biases.
Suggestions for Future Research
As mentioned above, this study was conducted with a dataset collected from a single
organization. Therefore, the findings may be somewhat unique to the organization which
participated in this study and not applicable to other settings. Specifically, the pattern of
relationships among the variables included in this study may appear differently in studies
conducted with datasets collected in other organizations or in a situation where different types of
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change initiatives are going on. Conducting similar studies across diverse settings with different
organizational contexts and/or with different types of change initiatives will greatly enhance our
understanding as to the conditions that foster individuals’ readiness for change.
This study relied on a limited number of variables referring to change process (change
strategies), change context (learning culture), and change content (the impact of change on
individuals’ jobs). Future researchers need to explore a broader range of variables—for example,
communications specific to a change initiative and change history in the organization—so that
we can better understand the conditions that help individuals be ready for change. Furthermore,
the conceptual framework used to empirically examine the hypothesized relationships among the
key variables of this study can be modified by other HRD researchers to examine the value of
OD approaches with outcome criteria other than readiness for change.
Recently, a group of constructs representing individuals’ attitudes toward organizational
change has gained interests among researchers. Commitment to change (e.g., Herscovitch &
Meyer, 2002), openness to change (e.g., Wanberg & Banas, 2000), and cynicism about
organizational change (e.g., Wanous et al., 2000) are some examples. These constructs are
similar to readiness for change in that they all reflect an individual’s overall positive or negative
evaluative judgment of a specific change initiative. In addition, they are also defined as the
cognitive precursor to the behavioral support for a change effort. In this respect, like readiness
for change, these constructs can also be a measure to assess how effectively an organization has
achieved the unfreezing process. Future studies to explore how to use these constructs in the field
of HRD would be valuable to enhance the role of HRD in organizational change.
Finally, future research needs to be conducted to determine the effects of readiness for
change. Even though some of the previous research studies have shown a positive association
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between individuals’ attitudes toward organizational change and their actual behavioral support
for change initiatives (e.g., Herscovitch & Meyer, 2002; Jones et al., 2005; Kwahk & Lee, 2008;
J. P. Meyer et al., 2007; Michaelis, Stegmaier, & Sonntag, 2009; Parish, Cadwallader, & Busch,
2008; Rubin, Dierdorff, Bommer, & Baldwin, 2009; Shum et al., 2008; Stanley et al., 2005),
more empirical work needs to be done to explain this link with confidence. Research in this line
will eventually help HRD researchers and practitioners find better ways to improve organizations’
ability to increase organizational members’ acceptance of or support for change initiatives.
Summary of the Chapter
This chapter included the summary and discussion of key findings. Specifically, the
findings were discussed focusing on the major topics of this study: (a) change strategies and
readiness for change, (b) learning culture and readiness for change, (c) change impact and
readiness for change, and (d) individual differences and readiness for change. As discussed in the
implications for HRD research and practice section, this study can potentially contribute to the
field of HRD through its attempt to (a) reconceptualize employees’ reactions to organizational
change, (b) propose a framework for HRD research on organizational change, and (c) reaffirm
organization development and change as a legitimate realm of HRD. Furthermore, this study also
has potential implications for HRD practitioners, particularly in their role in leading and
facilitating change in the organization. Finally, the limitations of this study and suggestions for
future research were discussed.
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APPENDIX A
INFORMED CONSENT AND QUESTIONNAIRE
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Note. All the identifiers were removed to protect confidentiality.
Thank you for participating in [the annual organization-wide survey]. Your feedback is
invaluable as we continue our [the change initiative].
This year, as we continue our journey towards high reliability, we have the opportunity
to partner with the University of Georgia in evaluating our readiness for change as it
relates to [the change initiative]. We hope you will consider providing additional
feedback through a special survey designed to assess this key component of readiness
for change. This feedback will further inform us as we continue to improve our
processes. The survey will asks you about how much you feel you are and have been
prepared for [the change initiative], what has been your experience with the
implementation of [the change initiative], and how you perceive the learning culture in
general is at [the organization]. This survey is prepared in partnership with the Human
Resource and Organizational Development (HROD) program at the University of
Georgia.
This survey is optional. You can decide whether to take part in it or not. The survey is
part of a study being conducted by Ms. Myungweon Choi, a doctoral student at the
University of Georgia. Your participation in the survey allows us to better prepare for
our ongoing [the change initiative], while at the same time helping Ms. Choi and the
University of Georgia understand how to inform organizations about best practices for
change management. We hope you can help us by participating in this important
survey. It will take about 25 minutes for you to complete this optional survey and since
this is a research study for Ms. Choi, you will see next a detailed informed consent
outlining the voluntary nature of this study.
Thanks so much for all of your efforts in helping create a safe day every day at [the
organization]. You are making a difference in the lives of many.
Sincerely,
[The name of Senior Vice President]
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Informed Consent
Researchers: This study is conducted by Ms. Myungweon Choi, a doctoral student in the Human Resource and
Organizational Development program at the University of Georgia, under the supervision of Dr. Wendy Ruona.
Purpose and Procedures: This study aims to examine organizational conditions to foster readiness for change. If you
agree to take part in this survey, you will be asked to complete a questionnaire with 83 items. It will take about 25
minutes to complete the questionnaire.
Voluntariness: Your decision to be in this study is voluntary. You can stop at any time. You do not have to answer
any questions you do not want to answer. Refusal to take part in or withdrawing from this study will involve no
penalty or loss of benefits you would receive otherwise. You must be 18 years of age or older to take part in this
study.
Risks and Benefits: While responding to the survey, you may have concerns about whether your responses are
monitored by authorities in the organizations. By using secure sockets layer (SSL) encryption for the survey link and
survey pages during transmission, we will prevent it from happening and secure the collected data. In addition, if
you are not comfortable with the level of confidentiality provided by the Internet, you can also print out a copy of
the survey, fill it out by hand, and mail it to Myungweon Choi, 109 River's Crossing, 850 College Station Road,
Athens, GA 30602, with no identifiers and return address on the envelope.
You will not receive any direct benefits from participating in this study. But, you will have an opportunity to reflect
on a change initiative implemented in your organization. In addition, your participation in this study may help
elucidate important issues and improve our capacity as Human Resource Development (HRD) and Organizational
Development (OD) professionals to intervene on the factors and affect positive change more effectively in
organizations.
Confidentiality: Due to the technology itself, there is a limit to the confidentiality that can be guaranteed when it
comes to Internet communications. However, we will take multiple measures to keep your participation in this
survey confidential: (1) the IP addresses associated with the responses will not be collected; (2) even though the
email addresses of those who have responded and who have not will be collected, the information will be used only
for the purpose of sending new messages or reminders during the data collection period. The email addresses will be
removed from the data and destroyed by the researchers on or before August 31, 2010; and (3) no one else except
the researchers will have access to the data in any case.
Right to Ask Questions: Contact Myungweon Choi at [email protected] or (706) 614-3232 and Dr. Wendy Ruona
at [email protected] or (706) 542-4474 with questions, complaints, or concerns about the research. You can also call
this number if you feel this study has harmed you. Additional questions or problems regarding your rights as a
research participant should be addressed to The Chairperson, Institutional Review Board, University of Georgia, 612
Boyd Graduate Studies Research Center, Athens, Georgia 30602-7411; Telephone (706) 542-3199; E-Mail Address
[email protected]
Agreement: Completion and return of the survey implies that you have read the information in this form and consent
to take part in the study. If you agree to participate in this study, click on ―I Agree‖ button and you will proceed to
the survey on the next page. Your voluntary participation in the study would imply your informed consent to
participate. Please print a copy of this form for your records or future reference.
Thank you for your consideration.
Sincerely,
Myungweon Choi
Dr. Wendy Ruona
I agree [ ] I disagree [ ]
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Introduction
Section I. Impact of [the change initiative] on Your Job
This section asks about the impact of [the change initiative] on your job. Please provide your
opinion whether you agree or disagree with the following statements. When responding to the
statements, think of the situation specific to [the change initiative].
Question
Str
ong
ly
dis
agre
e
Dis
agre
e
Nei
ther
agre
e n
or
dis
agre
e
Ag
ree
Str
ong
ly
agre
e
1-1 With [the change initiative], the nature of my work
has changed.
1-2 With [the change initiative], I am expected to do
more work than I used to do.
1-3 With [the change initiative], my job responsibilities
have changed.
1-4 I find greater demands placed on me at work
because of [the change initiative].
1-5 I am experiencing more pressure at work because
of [the change initiative].
1-6 As a result of [the change initiative], the work
processes and procedures I use have changed.
This questionnaire has 83 items. There are six sections asking about (1) the impact of the
change on your job, (2) change strategies used in your organization, (3) your readiness for the
change, (4) the learning culture in your organization, (5) your personality, and (6) general
demographic information (age, gender, etc.). It will take about 25 minutes to complete the
survey.
You are asked to provide your opinion whether you agree or disagree with the statements. This
is a general survey asking for your opinions. It is not a test; thus, there are no right or wrong
answers. Please check the one response on each survey question that best reflects your
perception.
If you have any questions please contact Myungweon Choi ([email protected] ) or Dr. Wendy
Ruona ([email protected] ).
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Section II. Change Strategies
The term change strategies is concerned with the way change is implemented. This section asks
about the change strategies used in your organization. Please provide your opinion whether you
agree or disagree with the following statements. When responding to the statements, think of the
situation specific to [the change initiative].
Question
Str
ong
ly
dis
agre
e
Dis
agre
e
Nei
ther
agre
e n
or
dis
agre
e
Ag
ree
Str
ong
ly
agre
e
2-1
Those leading [the change initiative] have been
establishing links between themselves and key
individuals responsible for carrying out [the change
initiative].
2-2
Those leading [the change initiative] have been
focusing on the facts and promoting the benefits of
[the change initiative].
2-3
To get employees to change, those leading [the
change initiative] have been involving employees
from many levels of the organization.
2-4
The need for [the change initiative] was justified by
experts who are knowledgeable about [the change
initiative].
2-5
The relationship between those leading [the change
initiative] and those responsible for carrying out
[the change initiative] has been collaborative.
2-6
To get employees to change, those leading [the
change initiative] have been using logical
arguments and factual evidence to carry out [the
change initiative].
2-7
Those leading [the change initiative] have not been
focusing on how employees are accepting [the
change initiative].
2-8
To get employees to change, those leading [the
change initiative] have been using their positions of
power and using threats to implement [the change
initiative].
2-9
Decisions about [the change initiative] have been
made by experts who are extremely knowledgeable
about [the change initiative].
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2-10 Those leading [the change initiative] have been
playing the role of order giver.
2-11 I have a lot of authority to make decisions about
[the change initiative].
2-12
Those leading [the change initiative] have been
creating a division between themselves and those
responsible for carrying out [the change initiative].
2-13
Those leading [the change initiative] have been
spending a lot of time dealing with how [the change
initiative] is being accepted by employees.
2-14
Decisions about [the change initiative] have been
made by employees from many levels of the
organization.
2-15 The need for [the change initiative] was justified by
members of top management only
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Section III. Readiness for Change
This section asks about how ready you have been and continue to be for [the change initiative].
Please provide your opinion whether you agree or disagree with the following statements. When
responding to the statements, think of the situation specific to [the change initiative].
Question
Str
ong
ly
dis
agre
e
Dis
agre
e
Nei
ther
agre
e n
or
dis
agre
e
Ag
ree
Str
ong
ly
agre
e
3-1 With the implementation of [the change initiative], I
believe there is something for me to gain.
3-2 When I set my mind to it, I can learn everything that
is required by the adoption of [the change initiative].
3-3 I feel I can handle [the change initiative] with ease.
3-4 [The change initiative] makes my job more
effective.
3-5
In the long run, I feel it will be worthwhile for me
that [the organization] has adopted [the change
initiative].
3-6 My future in this job will be limited because of [the
change initiative].
3-7 Management has sent a clear signal that [the
organization] is going to change.
3-8 I have the skills that are needed to make [the change
initiative] work.
3-9 The senior managers want [the change initiative] to
be implemented.
3-10 I have a lot of problems adjusting to the work
because of the adoption of [the change initiative].
3-11 Our senior leaders have encouraged all of us to
embrace [the change initiative].
3-12 [The change initiative] will improve [the
organization]’s overall efficiency.
3-13 There are some tasks required by [the change
initiative] that I don’t think I can do well.
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3-14 It makes much sense for us to have initiated [the
change initiative].
3-15
[The organization]’s top decision makers have put
all their support behind the [the change initiative]
effort.
3-16 There are legitimate reasons for our implementing
[the change initiative].
3-17 [The change initiative] disrupts many of the
personal relationships I have developed.
3-18 [The organization]’s most senior leader is
committed to [the change initiative].
3-19 [The change initiative] matches the priorities of [the
organization].
3-20 There are a number of rational reasons for our
implementing [the change initiative].
3-21
I am worried I will lose some of my status in the
organization because of the implementation of [the
change initiative].
3-22 I think that [the organization] does and will continue
to benefit from [the change initiative].
3-23
The time we have been spending on [the change
initiative] should have been spent on something
else.
3-24
My past experiences made me confident that I
would be able to perform successfully after [the
change initiative] was adopted.
3-25 Every senior manager has stressed the importance of
[the change initiative].
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Section IV. Organizational Learning Culture
A learning culture means a set of beliefs and values about the functioning of an organization that
support organizational learning. This section asks about the learning culture in [the organization].
Please provide your opinion on the degree to which each statement is or is not true of [the
organization].
Question
Alm
ost
Nev
er
Rar
ely
So
met
imes
Oft
en
Alm
ost
Alw
ays
4-1 At [the organization], people help each other learn.
4-2 At [the organization], people are given time to
support learning.
4-3 At [the organization], people are rewarded for
learning.
4-4 At [the organization], people give open and honest
feedback to each other.
4-5 At [the organization], whenever people state their
view, they also ask what others think.
4-6 At [the organization], people spend time building
trust with each other.
4-7 At [the organization], teams/groups have the
freedom to adapt their goals as needed.
4-8
At [the organization], teams/groups revise their
thinking as a result of group discussions or
information collected.
4-9
At [the organization], teams/groups are confident
that the organization will act on their
recommendations.
4-10 [The organization] creates systems to measure gaps
between current and expected performance.
4-11 [The organization] makes its lessons learned
available to all employees.
4-12 [The organization] measures the results of the time
and resources spent on training.
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4-13 [The organization] recognizes people for taking
initiative.
4-14 [the organization] gives people control over the
resources they need to accomplish their work.
4-15 [The organization] supports employees who take
calculated risks.
4-16 [The organization] encourages people to think from
a global perspective.
4-17 [The organization] works together with the outside
community to meet mutual needs.
4-18
[The organization] encourages people to get answers
from across the organization when solving
problems.
4-19 At [the organization], leaders mentor and coach
those they lead.
4-20 At [the organization], leaders continually look for
opportunities to learn.
4-21 At [the organization], leaders ensure that the
organization’s actions are consistent with its values.
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Section V. Personality
This section has questions about your personality. Specifically, this scale consists of a number of
words that describe different feelings and emotions. Read each item and then make the
appropriate answer in the space next to that word. Please indicate to what extent you generally
feel this way, that is, how you feel on the average.
Question
Ver
y s
lightl
y
or
not
at a
ll
A l
ittl
e
Moder
atel
y
Quit
e a
bit
Extr
em
ely
5-1 Interested
5-2 Distressed
5-3 Excited
5-4 Upset
5-5 Strong
5-6 Guilty
5-7 Scared
5-8 Hostile
5-9 Enthusiastic
5-10 Proud
5-11 Irritable
5-12 Alert
5-13 Ashamed
5-14 Inspired
5-15 Nervous
5-16 Determined
5-17 Attentive
5-18 Jittery
5-19 Active
5-20 Afraid
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Section VI. Demographic Information
Please answer the following questions.
6-1. What is your gender? Male [ ] Female [ ]
6-2. What is your age? ___________ years
6-3. What is the highest level of education completed?
[ ] High school graduate
[ ] Associate’s degree
[ ] Bachelor’s degree
[ ] Master’s degree
[ ] Professional degree
[ ] Doctorate
[ ] Other (please specify) ________________
6-4. How long have you been with [the organization]? ___________years
6-5. What is your primary work area or unit? Select ONE answer.
[ ] Medicine (nonsurgical) [ ] Rehabilitation
[ ] Surgery [ ] Pharmacy
[ ] Obstetrics [ ] Laboratory
[ ] Pediatrics [ ] Radiology
[ ] Emergency Department [ ] Anesthesiology
[ ] Intensive Care Unit (Any Type) [ ] Physician Office
[ ] Psychiatry/Mental Health [ ] Other
[ ] Many different hospital units/No specific unit
6-6. What is your staff position in the hospital? Select ONE answer that best describes your staff
position.
[ ] Registered Nurse [ ] LVN/LPN
[ ] Dietician [ ] Pharmacist
[ ] Respiratory Therapist [ ] Unit Assistant/Clerk/Secretary
[ ] Attending/Staff Physician [ ] Administration/Management
[ ] Resident Physician/Physician in Training
[ ] Physician Assistant/Nurse Practitioner
[ ] Patient Care Assistant/Hospital Aide/Care Partner
[ ] Physical, Occupational, or Speech Therapist
[ ] Technician (e.g., EKG, Lab, Radiology)
[ ] Other
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APPENDIX B
RECRUITING LETTER
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―Are your Employees Ready for the Change?‖
UGA’s HROD Program is Recruiting Organizations for a Survey Study on
Individual Readiness for Organizational Change
What is the success rate of change initiatives in your organization? Researchers estimate that
more than two-thirds of change projects fail.
Why do so many change initiatives fail? We often consider employees’ resistance to change to
be the main cause of the failure. But, is it really true? Or, more fundamentally, do you find this
concept of resistance useful? Instead of asking why employees are resistant, how about asking a
different question—―Are the employees really ready for the change?‖ This question shifts our
attention to another issue—understanding and seeking to help employees feel more ready for an
organizational change.
In Winter, 2010, Myungweon Choi, a student of the Human Resource and Organizational
Development (HROD) program at the University of Georgia working with the supervision of Dr.
Wendy Ruona, will be conducting a study to explore individual readiness for organizational
change. For this study, we are recruiting organizations which will allow us to collect survey data
from its employees.
What the study is about
After reviewing the literature, we made hypotheses that the way employees experience
the change strategies (change process), the organizational culture (change context), and
the impact of change on their jobs (change content) may shape their readiness for change.
To examine our hypotheses and draw practical implications from them, we’re planning to
conduct a survey study.
About the Survey
The survey has approximately 80 questions. It consists of six parts, which explore an
employee’s perceptions of change strategies used in the organization, the organizational
learning culture, their readiness for change, and the impact they believe the change will
have on their job. The survey will also include a demographic section and a few questions
that capture information about personality.
The survey will be web-based and administered online in January-February 2010.
Employees will be provided a link to the online survey. The survey data will be kept
anonymous and confidential. Except for the report for your organization, the survey
results will be used only for academic research purpose.
The Survey at Your Organization
To participate in this research study, your organization will need to do the following:
1. Select a research project liaison who can be the primary point of contact for this
project.
2. Identify a specific change initiative which is or will soon be underway. This is
important so that employees will have a specific change in their minds when
completing the survey. It will also allow us to customize a portion of the survey so it
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is appropriate to the situation in your organization.
3. Provide e-mail addresses of employees working in the unit that will be affected by the
change (identified in step 2) or agree to internally disseminate the invitation to
participate and link to the on-line survey.
4. Support data collection and high return rate of the survey through reminders to the
employees, etc.
Ideally, we need more than 100 participants per organization. However, the number can
be adjusted depending on how many other organizations also participate in the study.
After you decide to participate in the study, we can discuss the proper sample size in your
organization later.
Benefits to the Organization
Your organization will receive a report that helps you understand your employees’
readiness for the change (that is selected), how they perceive the change strategies in use,
and how they evaluate the learning culture in their unit(s). In addition, if you want, we
can also provide a 2-hour free interpretive session about the results.
The survey results, as well as the potential implications and recommendations drawn
from the results, should help your organization enhance employees’ readiness for change
and, thus, increase the likelihood for the success of the change initiative.
Benefits to the Profession
In many organizations the role of HRD is still confined to the traditional role of providing
training services. However, HRD is required to be more strategic from both inside and
outside of its profession and, therefore, should concern itself with efforts which
potentially add value to the organization. In this respect, HRD need to embrace the topic
of organizational development and change to which it has important insights to bring. We
expect this study to contribute to improving the capacity of HRD professionals to affect
positive change more effectively in organizations and to defining and expanding the role
of HRD in organizations.
What I’m asking for you
If you’re interested or have any questions, please contact Myungweon Choi
([email protected] ) or Dr. Wendy Ruona ([email protected] ). Or, you can give us the
contact info of the person in your organization with whom we can communicate
concerning the survey.
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APPENDIX C
MEASUREMENT MODELS
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Figure 6.1. CFA for change strategies
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Figure 6.2. First-order CFA for the dimensions of a learning culture
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Figure 6.3. First-order CFA for overall learning culture
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Figure 6.4. Hierarchical CFA for a learning culture
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Figure 6.5. First-order CFA for the dimensions of readiness for change
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Figure 6.6. First-order CFA for overall readiness for change
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Figure 6.7. Hierarchical CFA for readiness for change
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Figure 6.8. CFA for change impact