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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,

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


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

© 2011

Myungweon Choi

All Rights Reserved


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

iv

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

v

support I received from them and let them feel what I feel now.

vi

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

vii

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

viii

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

ix

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

x

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

xi

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

xii

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


between the empirical-rational strategy (ER) and overall readiness for change…..155


between the empirical-rational strategy (ER) and change-specific efficacy (R1)....156


between the empirical rational strategy (ER) and appropriateness of the change

(R2)…………..…………………………..…………….………………...…...……156


between the empirical-rational strategy (ER) and management support for the change

(R3).……………………….…………..……...……..……...…………...…………156


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

xiii

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


efficacy (R1).....…....………...………………...………...…………….…………172

Figure 4.13: Moderating effect of empowering people toward a collective vision (LC4) on the


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


the relationship between the normative-reeducative strategy (NR) and change-

specific efficacy (R1)…...………...……………………….……......……………173


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

xiv

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

1

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

2

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).

3

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

4

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,

5

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.

6

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

7

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.

8

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

9

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).

10

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

11

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;

12

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

13

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


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)

14

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).

15

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.

16

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.


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

17

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.

18

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

19

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.

20

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.

21

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-

22

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;

23

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.

24

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;

25

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

26

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.

27

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

28

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).

29

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.


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

30

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

31

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.

32

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

33

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

34

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.

35

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

36

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

37

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

38

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

39

(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

40

(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.

41

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.

42

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,

43

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.

44

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

45

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

46

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.

47

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).

48

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.

49

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

51

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

54

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

57

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

60

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


61

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 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


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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


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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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.



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.



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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.


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.





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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.



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






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.





3. How does the impact of change on individuals’ jobs affect the two relationships


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:





3. How does the impact of the change on individuals’ jobs affect the two relationships


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


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).

123

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

125

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.

126

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)


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


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

127

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

128

(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

129

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

130

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.

131

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.





132













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.






133

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.







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

134

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.

135

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

136

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,

137

this study focused on examining the relationships among the variables of interest which were

derived from the relevant literature.


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.

138

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.

139

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

*

140

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

141

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

142

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).

143

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.

144

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.,

145

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).

146

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




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 — — —



147

Table 4.6

Relative Importance of Change Strategies: Appropriateness of the Change (R2)

Variables already

in the equation




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 — — —



Table 4.7

Relative Importance of Change Strategies: Management Support for the Change (R3)

Variables already

in the equation




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 — — —



148

Table 4.8

Relative Importance of Change Strategies: Personal Benefit of the Change (R4)

Variables already

in the equation




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 — — —



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%).

149

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


Total effect (k=2) .093 .008 .041

M (Cxi) .167 .058 .115


R2 Direct effect (k=0) .357 .280 .383


Total effect (k=2) .061 .000 .070

M (Cxi) .168 .099 .186


R3 Direct effect (k=0) .299 .379 .396


Total effect (k=2) .013 .028 .049

M (Cxi) .115 .162 .181


R4 Direct effect (k=0) .324 .180 .199


Total effect (k=2) .121 .000 .009

M (Cxi) .195 .063 .077


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.

150

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,

151

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.

152

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.

153

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

154

Table 4.11

Moderating Effect of NR on the Relationship between ER and Readiness for Change


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


benefit of the change. †p<.10, *p<.05, **p<.01, ***p<.001.

155

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

156

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)




strategy (ER) and appropriateness of the

change (R2)




strategy (ER) and management support for the

change (R3)




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

157

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,

158

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*


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

159

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.

160

Table 4.13

Readiness for Change Regressed on Overall Learning Culture


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.

161

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).

162

Table 4.14

Moderating Effect of Overall Learning Culture on the Relationship between NR and Readiness for Change


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



163

Table 4.15

Moderating Effect of Creating Continuous Learning Opportunities (LC1) on the Relationship between NR and Readiness for Change


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.

164

Table 4.16

Moderating Effect of Promoting Inquiry and Dialogue (LC2) on the Relationship between NR and Readiness for Change


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:


165

Table 4.17

Moderating Effect of Encouraging Collaboration and Team Learning (LC3) on the Relationship between NR and Readiness for

Change


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.

166

Table 4.18

Moderating Effect of Empowering People toward a Collective Vision (LC4) on the Relationship between NR and Readiness for

Change


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


167

Table 4.19

Moderating Effect of Establishing Systems to Capture and Share Learning (LC5) on the Relationship between NR and Readiness for

Change


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


168

Table 4.20

Moderating Effect of Connecting the Organization to Its Environment (LC6) on the Relationship between NR and Readiness for

Change


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.

169

Table 4.21

Moderating Effect of Providing Strategic Leadership for Learning (LC7) on the Relationship between NR and Readiness for Change


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:


170

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.

171

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

172

Figure 4.11. Moderating effect of encouraging

collaboration and team learning (LC3) on the


strategy (NR) and overall readiness for change

Figure 4.12. Moderating effect of encouraging

collaboration and team learning (LC3) on the



(R1)

Figure 4.13. Moderating effect of empowering

people toward a collective vision (LC4) on the



(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

173




reeducative strategy (NR) and change-specific

efficacy (R1)




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

174

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**


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.

175

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.

176

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

177

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).

178

Table 4.24

Moderating Effect of Change Impact on the Relationship between NR and Readiness for Change


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



179

Table 4.25

Moderating Effect of Change Impact on the Relationship between Overall Learning Culture and Readiness for Change


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.

180

Table 4.26

Moderating Effect of Change Impact on the Relationship between Creating Continuous Learning Opportunities (LC1) and Readiness

for Change


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



181

Table 4.27

Moderating Effect of Change Impact on the Relationship between Promoting Inquiry and Dialogue (LC2) and Readiness for Change


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.

182

Table 4.28

Moderating Effect of Change Impact on the Relationship between Encouraging Collaboration and Team Learning (LC3) and



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



183

Table 4.29

Moderating Effect of Change Impact on the Relationship between Empowering People toward a Collective Vision (LC4) and



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



184

Table 4.30

Moderating Effect of Change Impact on the Relationship between Establishing Systems to Capture and Share Learning (LC5) and



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:


185

Table 4.31

Moderating Effect of Change Impact on the Relationship between Connecting the Organization to Its Environment (LC6) and



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



186

Table 4.32

Moderating Effect of Change Impact on the Relationship between Providing Strategic Leadership for Learning (LC7) and Readiness

for Change


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



187

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)


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

188


impact (CI) on the relationship between

creating continuous learning opportunities

(LC1) and personal benefit of the change (R4)



promoting inquiry and dialogue (LC2) and

personal benefit of the change (R4)



establishing systems to capture and share

learning (LC5) and personal benefit of the

change (R4)



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

189

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,

190

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

191

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


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.

192

Table 4.34

Relative Importance of Study Variables: Change-Specific Efficacy (R1)


equation

R2 accounted for by


the equation



— .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 — — —




Table 4.35

Relative Importance of Study Variables: Appropriateness of the Change (R2)


equation

R2 accounted for by


the equation



— .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 — — —


193

Table 4.36

Relative Importance of Study Variables: Management Support for the Change (R3)


equation

R2 accounted for by


the equation



— .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 — — —




Table 4.37

Relative Importance of Study Variables: Personal Benefit of the Change (R4)


equation

R2 accounted for by


the equation



— .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 — — —


194

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.

195

Table 4.38

Relative Importance of Study Variables: Dominance Matrices


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


Total effect (k=3) .173 .041 .002 .025

M (Cxi) .240 .089 .018 .057


R2 Direct Effect (k=0) .393 .196 .024 .108


Total effect (k=3) .217 .065 .000 .043

M (Cxi) .302 .128 .010 .072


R3 Direct Effect (k=0) .380 .181 .010 .107


Total effect (k=3) .212 .031 .002 .055

M (Cxi) .295 .105 .005 .080


R4 Direct Effect (k=0) .325 .094 .085 .083


Total effect (k=3) .173 .012 .023 .015

M (Cxi) .245 .051 .052 .045


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.


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.

196

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


Supported

Hypothesis 1c Partial correlation analysis


Supported

Hypothesis 2 Dominance analysis Not supported

Hypothesis 3a Hierarchical regression analysis

Comparison of regression lines

Not supported

Hypothesis 3b Hierarchical regression analysis


Supported



Supported



Partially supported



Partially supported



Partially supported

Hypothesis 5c Hierarchical regression analysis


Partially supported

197

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 1b: The normative-reeducative change strategy will be positively




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.

198

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

199

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 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.

200

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



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.


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.


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


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,

221

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

223

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.

224

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

225

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

226

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.


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.

227

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APPENDIX A

INFORMED CONSENT AND QUESTIONNAIRE

258

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]

259

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 [ ]

mailto:[email protected]

260

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]).



261

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


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


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


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].

262

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


2-12


creating a division between themselves and those

responsible for carrying out [the change initiative].

2-13


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

263

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.

264

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


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


265

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.

266

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.

267

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

268

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

269

APPENDIX B

RECRUITING LETTER

270

―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


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

271

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.



272

APPENDIX C

MEASUREMENT MODELS

273

Figure 6.1. CFA for change strategies

274

Figure 6.2. First-order CFA for the dimensions of a learning culture

275

Figure 6.3. First-order CFA for overall learning culture

276

Figure 6.4. Hierarchical CFA for a learning culture

277

Figure 6.5. First-order CFA for the dimensions of readiness for change

278

Figure 6.6. First-order CFA for overall readiness for change

279

Figure 6.7. Hierarchical CFA for readiness for change

280

Figure 6.8. CFA for change impact

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