Journal of Management
http://jom.sagepub.com/
Change-Supportive Employee Behavior: Antecedents and the Moderating Role of
Time
Tai Gyu Kim, Severin Hornung and Denise M. Rousseau
Journal of Management 2011 37: 1664 originally published online 9 April 2010
DOI: 10.1177/0149206310364243
The online version of this article can be found at:
http://jom.sagepub.com/content/37/6/1664
Published by:
http://www.sagepublications.com
On behalf of:
Southern Management Association
Additional services and information for Journal of Management can be found at:
Email Alerts: http://jom.sagepub.com/cgi/alerts
Subscriptions: http://jom.sagepub.com/subscriptions
Reprints: http://www.sagepub.com/journalsReprints.nav
Permissions: http://www.sagepub.com/journalsPermissions.nav
Citations: http://jom.sagepub.com/content/37/6/1664.refs.html
>> Version of Record - Oct 5, 2011
Proof - Apr 9, 2010
What is This?
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Journal of Management
Vol. 37 No. 6, November 2011 1664-1693
DOI: 10.1177/0149206310364243
© The Author(s) 2011
All rights reserved.
Change-Supportive Employee Behavior:
Antecedents and the Moderating Role of Time
Tai Gyu Kim
Korea University
Severin Hornung
Hong Kong Polytechnic University
Denise M. Rousseau
Carnegie Mellon University
This study investigates antecedents of change-supportive behavior and how these antecedents
vary over the course of an organizational transition. Change-supportive behavior is defined as
actions employees engage in to actively participate in, facilitate, and contribute to a planned
change. Drawing on the theory of planned behavior, (a) the anticipated benefits of the change,
(b) the quality of the employment relationship, and (c) the formal involvement in the change are
examined as antecedents. Hypotheses are tested in a two-wave panel of 72 employees from a
hospital undergoing a strategic reorientation toward continuous improvement. Formal involvement in the change had stable positive effects in each wave, conducted 18 and 42 months after
the change was initiated. The effects of both anticipated benefits of the change and the quality
of the employment relationship were moderated by time, such that the former became less and
the latter more important as the change progressed from an earlier phase of implementation to
a later stage of institutionalization. Moderating effects of time correspond with theory regarding
discontinuous information processing and gradual shifts in employees’ cognitive models of their
relationship with the organization. Implications for managing employee behavioral support in
different phases of change are discussed.
Acknowledgments: We thank Michael DeKay, Mark Fichman, Paul Goodman, Don Moore, Sandra Slaughter, and
Laurie Weingart for helpful comments on an earlier version of this article. Seung Hyun Kim helped with data coding. The H. J. Heinz II chair provided support for this research.
Corresponding Author: Severin Hornung, Department of Management and Marketing, Hong Kong Polytechnic
University, Hung Hom, Kowloon, Hong Kong
E-mail: [email protected]
1664
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1665
Keywords: organizational change; change-supportive behavior; anticipated benefits; employment relationship; time as a moderator
The frequency and speed of change in contemporary organizations is unprecedented. Highly
competitive markets, pressure for return on invested capital, rapid technological innovation,
and the adoption of new management practices all contribute to the efforts organizations
undertake to change and adapt (e.g., Dawson, 2003; Goodman, 2000; Harigopal, 2006). Yet,
according to optimistic estimates, only 30% to 40% of the change efforts organizations initiate attain their intended objectives (Golembiewski, 2000; Miller, 2002). Multiple reasons
offered for this low success rate include management error, lack of critical resources, and
employee resistance (e.g., Beer, Eisenstat, & Spector, 1990). Nonetheless, the latter notion
of employees as change resisters has been met with a growing body of research identifying
factors motivating workers to support rather than oppose change (e.g., Piderit, 2000).
The present study contributes to research on organizational change in three ways: (a) It
identifies a gap in the literature on employee support for organizational change and suggests
a conceptualization of change-supportive behavior (CSB) that fills this gap; (b) it draws on
the theory of planned behavior (TPB; Ajzen, 1991) to specify and investigate antecedents of
CSB; and (c) it develops and tests theory regarding the moderating role of time in the relationship of CSB with its postulated antecedents. With regard to the last contribution, better
integration of time and associated processes has been identified as a major challenge in
studying organizational change (Pettigrew, Woodman, & Cameron, 2001). We address this
issue by investigating potential shifts in the reasons why employees support a change as it
progresses from its implementation phase to higher levels of institutionalization. As such,
our study contributes to alleviating the “liabilities of atemporal analysis in organizational theorizing and empirical research” (Pettigrew et al., 2001, p. 699), which are especially grave in
studying such an inherently dynamic phenomenon as organizational change.
We define CSB as actions employees engage in to actively participate in, facilitate, and
contribute to a planned change initiated by the organization. This type of behavior so far has
received only limited research attention. Moreover, despite the ubiquity of change in contemporary organizations, there is a dearth of theoretical models to explain employee behavior during change (e.g., Weick & Quinn, 1999). Recently, Jimmieson, Peach, and White
(2008) identified the TPB (Ajzen, 1991) as a suitable framework for predicting behavioral
support for change. Following their lead, in this study we apply the TPB to investigate antecedents of CSB. According to the TPB, human behavior is a function of attitudes, subjective
norms, and perceived behavioral control. Drawing on this stream of research, we suggest
that (a) anticipated benefits of the change, (b) the quality of the employment relationship,
and (c) formal involvement in the change are three major antecedents of those employee
behaviors aimed at actively contributing to the implementation of organizational change.
Further, we propose that anticipated benefits of the change will be a more important antecedent in earlier phases of implementing change. The quality of the employment relationship is
suggested to be more important in the later stages of institutionalization, when the change
has lost some of its novelty and has become more integrated into the status quo. As such,
time is suggested to moderate the effects of anticipated benefits of the change and quality of
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1666 Journal of Management / November 2011
the employment relationship on CSB in opposite directions. Discontinuous information
processing (Louis & Sutton, 1991) and gradual changes in employees’ cognitive models of
their employment relationships (Rousseau, 2001) are proposed as psychological mechanisms underlying this moderating role of time.
Hypotheses are tested in a two-wave panel of 72 employees from a hospital undergoing
a strategic reorientation toward continuous improvement of service quality and operational
efficiency. Two-group structural equation modeling (SEM) compares the antecedents of
CSB between the first and the second wave, conducted 18 and 42 months after the change
was initiated. As part of our data analysis strategy, we used path analysis and panel regression to substantiate SEM results. Each of these alternative approaches offers specific methodological advantages that will be discussed. Our study makes a unique contribution to the
literature by providing a theory-based investigation of the antecedents of CSB, which
includes time as a potential moderating factor in the relationships between CSB and its predictors. It thus provides a basis to derive differential strategies for managing employee involvement as planned change interventions unfold over time.
Change-Supportive Behavior
Past Research Related to CSB
Planned organizational change refers to the managerial task of moving an organization
from its present state to a desired future state (Harigopal, 2006). Employee support has been
identified as a crucial factor for the success of various types of planned change, ranging from
quality initiatives (e.g., Coyle-Shapiro, 1999) and building relocations (e.g., Peach, Jimmieson, &
White, 2005) to restructuring and strategic change (e.g., Jansen, 2004; Nurick, 1985; Wanberg &
Banas, 2000). In addressing this important and timely issue, a host of constructs has been
developed, including openness to change (Miller, Johnson, & Grau, 1994), readiness to
change (Armenakis, Harris, & Mossholder, 1993), attitudes toward organizational change (Elias,
2009), commitment to change (Herscovitch & Meyer, 2002), program commitment (Neubert &
Cady, 2001), and intentions to engage in CSB (Jimmieson, Peach, & White, 2008). Taken
together, these cover a wide range of positive mind sets toward change and willingness to get
involved and contribute to its success.
Compared with the extensive research on change-related psychological states, actual
employee behavior to support change has received limited attention. A notable exception is
the work of Meyer and colleagues (Herscovitch & Meyer, 2002; Meyer, Srinivas, Lal, &
Topolnytsky, 2007), who have examined behavioral support as a consequence of commitment to change. These authors have conceptualized behavioral support of change as a continuum of active resistance, passive resistance, compliance, cooperation, and championing.
This construct was operationalized by presenting the above degrees of support as semantic
anchors on a 101-point continuous scale, which was scored in 20-point increments. As
Coyle-Shapiro (1999) has pointed out, using a behavioral continuum is preferable to assessing CSB through dichotomous measures of having either taken part in certain change-related
activities or not (e.g., quality circles or improvement groups). However, the equality of
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1667
differences between the semantic anchors described above is arguable, raising methodological issues regarding the interval nature of the data (i.e., the question whether the difference
in behavioral support between active resistance and passive resistance equals the difference
between compliance and cooperation or cooperation and championing). Although the equality issue pertains to a general concern in survey research (e.g., Clogg & Shihadeh, 1994;
Harwell & Gatti, 2001), the underlying problem is likely to be aggravated by the bipolar
nature of the scale, as evidence suggests that negative and positive evaluative processes are
psychologically distinct (Cacioppo, Gardner, & Berntson, 1997). Furthermore, it may be of
concern that single-item measures are considered “less valid, less accurate, and less reliable
than their multiitem equivalents” (McIver & Carmines, 1981, p. 15), a potential shortcoming
that also applies to Coyle-Shapiro’s (1999) single-item measure on the extent of employee
participation in a total quality management (TQM) change initiative.
Possibly in anticipation of such methodological concerns, Meyer and colleagues included
a conventional multi-item measure on behavioral change support in some of their studies
(Herscovitch & Meyer, 2002; Meyer et al., 2007). This scale was supposed to capture the three
dimensions of compliance (i.e., minimal and reluctant support), cooperation (i.e., going
along with the change and accepting modest sacrifices), and championing (i.e., enthusiasm,
exceptional contributions, and promotion of the change to others). Factor analysis, however,
failed to support the empirical distinctness of these three dimensions. Instead, items were
eventually allocated to the subscales “based on an intuitive judgment of construct-relevance”
(Herscovitch & Meyer, 2002, p. 478). We note that only championing explicitly refers to
active support and facilitation of a change, whereas cooperation and compliance are more
passive in nature.
Reactive or even passive change-related behaviors capture ways employees adjust to and
constructively deal with change-related stress, uncertainty, and new demands. Such constructs
include coping with change (Ashford, 1988; Judge, Thoresen, Pucik, & Welbourne, 1999),
adaptive performance (Pulakos, Arad, Donovan, & Plamondon, 2000), and adaptivity (Griffin,
Neal, & Parker, 2007). More active views of change-oriented or proactive behavior have been
studied in terms of voice (Van Dyne & LePine, 1998), taking charge (Morrison & Phelps,
1999), and change-oriented organizational citizenship behavior (OCB; Choi, 2007). In line
with other conceptualizations of proactive performance, such as personal initiative (Frese &
Fay, 2001) and proactivity (Griffin et al., 2007), these constructs refer to organizationally functional changes workers initiate themselves, independent of any organizational change effort
(i.e., spontaneously or in a self-starting fashion). A related construct is strategy-supportive
behavior (Gagnon, Jansen, & Michael, 2008). Although discussed in the context of a lean
management initiative, its generic operationalization (e.g., looking for ways to improve one’s
work effectiveness) makes it fit better with proactive behaviors rather than with CSB.
Change-Supportive Behavior as Distinguished in the Present Study
The present study explicitly addresses the positive and active role that employees can
play in supporting organizational change. We define change-supportive behavior, or CSB, as
actions employees engage in to actively participate in, facilitate, and contribute to a planned
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1668 Journal of Management / November 2011
Table 1
Change-Supportive Behavior and Related Concepts
Change-Supportive
Behavior
Change-Supportive
Psychological States
Adaptive Behavior
Proactive Behavior
Description
Behavior aimed at
actively participating
in, facilitating, and
contributing to a
planned change
initiated by the
organization
Positive attitudes and
Responding to
evaluations, willingness,
change by
or intentions to support
adjusting to and
organizational change
constructively
dealing with
stress,
uncertainty, and
new demands
Individuals initiating
functional
workplace changes
spontaneously or
self-starting
Examples
• Participation in total
quality management
(Coyle-Shapiro,
1999)
• championing
(Herscovitch &
Meyer, 2002)
• Readiness to change
(Armenakis, Harris, &
Mossholder, 1993)
• Openness to change
(Miller, Johnson, &
Grau, 1994)
• Commitment to
change (Herscovitch &
Meyer, 2002)
• Intentions to support
change (Jimmieson,
Peach, & White, 2008)
• Coping with
change (Judge,
Thoresen, Pucik,
& Welbourne,
1999)
• Adaptive
performance
(Pulakos, Arad,
Donovan, &
Plamondon,
2000)
• Compliance/
cooperation
(Herscovitch &
Meyer, 2002)
• Adaptivity
(Griffin, Neal, &
Parker, 2007)
• Voice (Van Dyne
& LePine, 1998)
• Taking charge
(Morrison &
Phelps, 1999)
• Personal initiative
(Frese & Fay,
2001)
• Proactivity
(Griffin et al.,
2007)
• Strategysupportive
behavior (Gagnon,
Jansen, &
Michael, 2008)
Distinction
• Actual behavior
• Active contributions
• Planned change
• Not actual behavior
• Not active
contributions
• Not planned
change
change initiated by the organization or, more precisely, the organization’s management. This
definition contains three elements that set it apart from previously studied constructs: (a) It
focuses on actual behavior rather than change-related psychological states, such as attitudes
or behavioral intentions; (b) it emphasizes active contributions to change rather than the more
passive responses of complying, adapting to, or coping with change; and (c) it entails support
for a planned, collective change effort, as opposed to individually initiated improvements.
Table 1 summarizes our conceptualization of CSB and its distinctiveness from changerelated psychological states and adaptive and proactive behavior. Most proximal to our
definition of CSB is Herscovitch and Meyer’s (2002) conceptualization of championing.
Coyle-Shapiro’s (1999) assessment of the extent to which employees actively participate in
a TQM intervention also captures similar behavior. As noted above, however, both constructs are hampered by methodological problems. Intentions to engage in change-supported
behaviors are conceptualized as a psychological precursor of CSB (Jimmieson et al., 2008);
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1669
yet, as a change-supportive psychological state, intentions are conceptually distinct from
actual behavior. Further, our definition puts CSB conceptually in between constructs of
employee adaptivity and proactivity (Griffin et al., 2007). That is, it implies active contributions that go beyond mere adaptive behavior, but it specifically refers to planned organizational change, which proactive behavior does not.
Finally, we note a fundamental difference between CSB and organizational participation.
CSB contains elements of participation as it is aligned with “intentional programs or practices
developed by the organization to involve multiple employees” (Glew, O’Leary-Kelly, Griffin, &
Van Fleet, 1995, p. 401). However, participation refers to a “process which allows employees
to exert some influence over their work and the conditions under which they work” (Strauss,
1998, p. 15). In contrast, CSB refers to employee contributions to a process top management
has designed and authorized to transform the organization into a desired future state. In other
words, participation is a form of worker control (e.g., Spector, 1986), whereas CSB is an
aspect of performance (e.g., Griffin et al., 2007). This is reflected in the different research
designs used to study organizational participation and change. The former is typically treated
as an independent variable to investigate the impact of participatory practices on individual and
organizational outcomes (e.g., Spector, 1986; Wagner, 1994; Weber, Unterrainer, & Schmid,
2009). Conversely, change-supportive employee attitudes and behaviors represent organizationally desirable outcomes, which are examined as dependent variables (e.g., Elias, 2009;
Meyer et al., 2007). Having established CSB as the distinctive and central construct of our
study, we next turn to its expected antecedents and their dynamics.
Antecedents of Change-Supportive Behavior
Identifying factors that motivate individuals to support organizational change is of vital
interest for the successful management of changes, where employee involvement is instrumental, and indeed essential, to accomplish specified objectives (e.g., increasing product quality or
operational efficiency). Previous research has confirmed a number of contextual antecedents
of change-supportive attitudes and behaviors; these include organizational commitment and
social relationships at work (e.g., Iverson, 1996; Madsen, Miller, & John, 2005; Meyer et al.,
2007; Neubert & Cady, 2001), information about the change and beliefs regarding its personal
consequences (e.g., Coyle-Shapiro, 1999; Miller et al., 1994; Rousseau, & Tijoriwala, 1999),
and the possibilities for participation in decision-making and change-related self-efficacy
(e.g., Jansen, 2004; Jimmieson, Terry, & Callan, 2004; Wanberg & Banas, 2000). The cumulative progress of empirical research notwithstanding, little attempt has been made to organize
these potential antecedents within a theory-based framework (e.g., Armenakis, Bernerth, Pitts,
& Walker, 2007; Piderit, 2000). Not until relatively recently have scholars suggested and demonstrated the utility of the TPB in this regard (Ajzen, 1991; Jimmieson et al., 2008; Peach
et al., 2005). This late adoption in change research is surprising, as the TPB is established as
a powerful predictive model of behavior in many fields, including health sciences, education,
and marketing (e.g., Armitage & Christian, 2004; Armitage & Conner, 2000).
Developed as an expansion of the theory of reasoned action (Ajzen & Fishbein, 1980), the
TPB specifies that individuals make conscious decisions to engage in a certain behavior,
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1670 Journal of Management / November 2011
influenced by (a) personal beliefs regarding the behavior and evaluations of its outcomes
(attitude), (b) normative beliefs regarding its social desirability and perceived social pressure
to carry it out (subjective norm), and (c) control beliefs regarding the ability and opportunity
to perform the respective behavior (perceived behavioral control). Taken together, these
three factors are suggested to determine an individual’s readiness to perform the respective
behavior (behavioral intention), which, in turn, has been shown to be a strong predictor of
actual behavior (e.g., Armitage & Conner, 2000). The applicability of the TPB to change
management has been demonstrated by previous research in which all three dimensions were
related to employees’ behavioral intentions to support a building relocation project
(Jimmieson et al., 2008; Peach et al., 2005). In the present study, we draw on the TPB to investigate the influence on CSB of employee beliefs regarding three organizational factors: (a)
anticipated benefits of the change, (b) the quality of the employment relationship, and (c) formal employee involvement in the change.
Although our research approach is informed by the TPB, it differs from previous work that
has applied this theory to organizational change. First, we focus on organizational rather than
individual influences. That is, to represent the TPB’s attitudinal component, we do not investigate employee beliefs regarding the outcomes of their individual behaviors but their assessment of personally desirable outcomes of the change as a whole. Similarly, the nature of the
employment relationship, that is, the degree to which it is perceived as a social exchange,
operationalizes the TPB’s component of subjective norm. Formal involvement refers to
membership in one of the participatory bodies (worker councils) implemented by the organization under study to facilitate the change. Formal involvement corresponds with behavioral
control in the sense of the TPB, as it increases opportunities for employees to engage in CSB.
Second, this study differs from past TPB-based change research in its focus on actual behavior rather than behavioral intentions (Jimmieson et al., 2008). In conclusion, we investigate
predictors relevant to offering guidance for the practice of change management.
Anticipated Benefits of the Change
Anticipation of positive outcomes is a well-established motivating force in human behavior. The importance the TPB attributes to behaviors is strongly influenced by Vroom’s (1964)
expectancy theory of motivation, positing that individuals are likely to engage in behavior
they anticipate to lead to a desired result (expectancy), which, in turn, is connected to positive second-order consequences (instrumentality) that they personally value and seek to
attain (valence). Organizational change research widely recognizes the importance of positive expectations regarding change outcomes in determining the level of employee support (e.g.,
Bartunek, Rousseau, Rudolph, & Depalma, 2006; Piderit, 2000; Rousseau & Tijoriwala, 1999).
For example, a recent qualitative review of organizational change publications reported that
19 out of 45 studies included a variable related to the benefits workers anticipated from a
change (Armenakis et al., 2007). Drawing on Vroom (1964), Armenakis and colleagues
(2007) refer to anticipated benefits as beliefs about the valence of change, which they define
as “the attractiveness (from the change recipient’s perspective) associated with the perceived
outcome of the change” (Armenakis et al., 2007, p. 488).
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1671
Nonetheless, in light of the wide range of possible change outcomes, the question remains
as to what kind of benefits workers can typically expect from an organizational transition.
Armenakis and colleagues (2007) suggest that change valence can have extrinsic (e.g., rewards,
benefits) as well as intrinsic components (e.g., more autonomy for decision making). In
constructing their scale of valence beliefs, however, one item on extrinsic benefits had to be
dropped (fringe benefits), whereas the other (higher pay) had a low factor loading (.51)
compared with intrinsic sense of accomplishment (.83), self-fulfillment (.79), and perceived
benefits of the change in general (.74). Subsequent versions of the scale focused exclusively
on intrinsic benefits. Intrinsic benefits are also at the core of Fedor, Caldwell, and Herold’s
(2006) construct of change favorableness, although conceptualized as a group-level variable
of observed rather than anticipated consequences (e.g., “people’s quality of life at work has
improved”). The construct of individual job impact, developed by the same authors, has a
different connotation, referring to negative rather than positive outcomes (e.g., “experiencing more pressure”; Caldwell, Herold, & Fedor, 2004).
Of particular interest for our study is the work of Coyle-Shapiro (1999, 2002), who used
a three-wave longitudinal study to show that the perceived benefits of a TQM intervention
predicted the extent to which employees participated in TQM activities (continuous improvement teams). Moreover, she demonstrated that the predominant causal direction was from
perceived benefits to participation. A reverse causal effect was observable but less pronounced
(Coyle-Shapiro, 1999). A critical examination of the instrument used to measure perceived
benefits, however (Coyle-Shapiro, 2002, p. 65), suggests that it may include not only anticipated benefits (“will benefit me in my job”) but also more general attitudes (“is not part of my
job”) and indifference (“is no better or worse than previous initiatives”) toward the change.
Anticipated benefits of the change refer to expected change outcomes of personal valence
to employees (Armenakis et al., 2007). Moreover, we conclude that evidence for the extrinsic benefits of change is less consistent than for the intrinsic aspects. Efforts to operationalize this construct need to take into account the context-specific characteristics of the change
under study (i.e., what employees can realistically expect to gain from a specific change) and
avoid confounding anticipated benefits with broader attitudes toward the change, one’s job,
or the organization in general. Theoretically and intuitively an important predictor of active
involvement in change, anticipated benefits are expected to be a major motivator in the decision to personally contribute to a planned change effort.
Hypothesis 1: Anticipated benefits of the change will be positively related to CSB.
Quality of the Employment Relationship
According to the TPB, a second determinant of behavior is social norms. Normative pressure arises from the perception that relevant others want the focal person to perform a certain
behavior (Ajzen, 1991). Whereas the subjective norm in the TPB refers to interpersonal
influence (e.g., peer pressure), organizational research has identified the quality of the relationship between the individual and the organization as a powerful motivating force for
employee behavior (e.g., Coyle-Shapiro, Shore, Taylor, & Tetrick, 2004). People ascribe
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1672 Journal of Management / November 2011
quasi-human qualities to their work organizations and psychologically construe their
employment as an exchange relationship with one coherent other (Levinson, 1965). Research
on the individual–organization relationship is widely based on social exchange theory, which
Cropanzano and Mitchell (2005) attest to be “among the most influential conceptual paradigms for understanding workplace behavior” (p. 874). In high-quality employment relationships, the primary economic purpose of trading labor for wage is assumed to be com­plemented
by open-ended reciprocal contributions to broadly support the other party. On the employee
side, these are based on “feelings of personal obligation, gratitude, and trust” (Blau, 1964,
p. 94) and motivated by a social norm of reciprocity (Gouldner, 1960) rather than by direct
personal benefits.
Informed by social exchange theory, research on the employment relationship addresses
perceived organizational support (POS; Eisenberger, Huntington, Hutchison, & Sowa,
1986), psychological contracts (Rousseau, 1995, 2001), and organizational commitment
(Mowday, Porter, & Steers, 1982). Of particular relevance for our study, POS has been
defined as employee perceptions regarding “the extent to which the organization values their
contributions and cares about their well-being” (Eisenberger et al., 1986, p. 500). A prolific
body of work has demonstrated that employees reciprocate POS through positive affective
responses (e.g., affective commitment, job involvement) and higher in-role and extrarole
performance (i.e., job performance and OCB; Rhoades & Eisenberger, 2002). Social
exchange has been postulated as the psychological mechanism behind these observed relationships. More recently, Shore, Tetrick, Lynch, and Barksdale (2006) have extended the
framework of organizational support theory to explicitly include employees’ social exchange
perceptions as a mediator between POS and reciprocation through increased performance
and higher OCB. Highly interrelated with POS (zero-order correlations of r = .72 and .68 in
the two reported studies) yet psychometrically distinct from POS, social exchange perceptions appear to be more proximal to employee behavior than POS itself. In this study, we
therefore draw on Shore et al.’s work in operationalizing the perceived quality of the
employment relationship.
The premise that employees in high-quality relationships are more likely to actively
engage in CSB draws on previous findings with regard to OCB (Konovsky & Pugh, 1994;
Organ, 1990), which has been established as an outcome of POS and other constructs relating to social exchange (e.g., relational psychological contracts; Rousseau, 1995). Note that,
whereas OCB refers to behaviors employees engage in to support the organization or other
members, it is generally not oriented toward change (although its more proactive forms
may be directed at initiating change, as discussed above; cf. Podsakoff, MacKenzie, Pain, &
Bachrach, 2000). However, several studies on change have also found positive relationships between affective commitment (an established outcome of POS and strongly correlated with Shore et al.’s 2006 measure of social exchange) and positive attitudes toward
change (e.g., Elias, 2009; Iverson, 1996; Madsen et al., 2005). Taken together, these findings suggest that the quality of the employment relationship is a factor in motivating CSB
as a form of reciprocity.
Hypothesis 2: The quality of the employment relationship will be positively related to CSB.
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1673
Formal Involvement in the Change
The third antecedent proposed by the TPB is perceived behavioral control, which, in the
context of change, refers to the “extent to which employees believe that various factors will
either facilitate or impede their ability to act in change-supportive ways” (Jimmieson et al.,
2008, p. 240). Such factors are exemplified by self-efficacy and perceived opportunity to
engage in the respective behavior (Ajzen, 1991). Focusing on organizational rather than
individual aspects, we include formal involvement in the change as a factor increasing the
opportunity to engage in CSB. Formal involvement, here, refers to membership in a worker
council, implemented by the organization under study as a central element of the change.
Although formal involvement need not imply active contribution, we suggest that it provides
employees with a better position and more resources (e.g., time, information, access to management) to engage in CSB.
Hypothesis 3: Formal involvement in the change will be positively related to CSB.
The Moderating Role of Time
Organizational change is a complex and dynamic process. The classic metaphor is that it
proceeds through the consecutive phases of unfreezing, transformation, and refreezing
(Lewin, 1951; Lippit, Watson, & Westley, 1958). However, this model of episodic change is
rather static and simplistic. As Weick and Quinn (1999) have discussed, the objective of
change in today’s dynamic work environment may not be to “refreeze” the organization at a
certain point but to enhance its capability for continuous adaptation. The major challenge
these authors have identified is to “gain acceptance of continuous change throughout the
organization” (Weick & Quinn, 1999, p. 381). The interplay of episodic and continuous
change thus seems to be better represented by thinking about the phases of change in terms
of initiation, implementation, and institutionalization, where the last stage does not necessarily signify a return to organizational inertia but the achievement of higher levels of adaptability and continuous improvement (cf. Armenakis, Harris, & Feild, 1999; Goodman, 2000;
Van de Ven & Poole, 1995).
Despite their obvious limitations in capturing the complexity of organizational development, phase models are useful in calling attention to the underemphasized role of time in
understanding change (e.g., Pettigrew et al., 2001). Although theorizing has focused on how
the features and objectives of change evolve from its initiation to institutionalization, little
empirical research has addressed how the responses of those affected by the change might vary
over time (e.g., Dawson, 2003; Harigopal, 2006; Weick & Quinn, 1999). In this regard, we
propose that a motivational shift occurs over time. We will argue that the importance of two
antecedents, anticipated benefits and the quality of the employment relationship, will vary as
novel practices become increasingly integrated in organizational structures and routines.
The Importance of Anticipated Benefits in Earlier Phases of Change
People process information differently in familiar and novel situations (e.g., Sims &
Gioia, 1986). The anticipation of personally beneficial outcomes is essentially a cognitive
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1674 Journal of Management / November 2011
assessment of the likelihood that the change will entail positive consequences for the focal
employee. Louis and Sutton (1991) have coined the term shifting cognitive gears to describe
the changeover from automated to conscious cognitive modes or from habitual to active
thinking. Automated mental routines tend to be the standard mode of business as usual in
the workplace. Active information processing is triggered by (a) novel or unfamiliar situations, (b) explicitly being asked to think or act differently, or (c) discrepancies between the
expected and actual consequences of one’s actions.
Organizational change (e.g., the introduction of new processes, structures, or technology)
is a prototypical event for a switch from an automated to a conscious cognitive mode (Louis &
Sutton, 1991). In fact, it qualifies for all three of the above criteria as it confronts employees
(a) with a new situation in which they are (b) typically requested to do things differently,
whereas (c) sticking to the old patterns will be less successful or less valued by the organization. Once adequate strategies for the new situation have been established and integrated in
the cognitive models and behavioral repertoire of the affected individuals (i.e., modified
ways of thinking and behaving have become habitualized), a switch back to the psychologically more efficient automated mode occurs. A similar cyclical process of changing cognitive structures and behavior patterns has been postulated in the attentional control theory by
Lord and colleagues (Lord & Levy, 1994), who refer to these two modes as top-down and
bottom-up cognition.
Discontinuous information processing is also addressed in the concept of sense making
(Weick, 1995), which frequently has been applied to organizational change (e.g., Balogun &
Johnson, 2004; Bartunek et al., 2006). Sense making refers to the psychological processes by
which individuals (or groups) attribute meaning to their environment under conditions of
incomplete information. The need to engage in sense making is particularly pronounced in
so-called weak situations, which are characterized by high levels of uncertainty and ambiguity (Weick, 1995, 2001). The implementation of organizational change is a disruptive event,
prompting employees to actively search for and consciously interpret cues regarding the
potential gains and losses involved for them, or—put differently—to ask “why” questions
(Wong & Weiner, 1981).
Uncertainty about the consequences of an organizational transition and ambiguity regarding the employees’ role in it are especially high in earlier phases of the change. Using an
ethnographic approach, Gioia and Chittipeddi (1991) have stressed the importance of sense
making by employees and sense giving by management during the beginning stages (i.e., the
first year) of a strategic change in a university setting. Their study illustrates that at the outset of change employee support relies heavily on management’s ability to provide a convincing
answer to the question of why they should participate—that is, what is in for them (cf. Piderit,
2000; Rousseau & Tijoriwala, 1999)?
The longer a change program is in effect, the more institutionalized and integrated into
organizational structures and processes it is likely to become; also, more information and
personal experiences regarding the change become available to employees (e.g., Armenakis
et al., 1999). As the novelty and “weakness” of the situation decreases, so does the necessity
to engage in sense making and to continue to remain in a consciously controlled mode of
top-down cognition. Over time, CSB should become increasingly habitualized and governed
by automated bottom-up processes that draw on previously established (or altered) mental
and behavioral routines or schemata (Louis & Sutton, 1991). At this point, the respective
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1675
behavior is less consciously reflected and its personal utility less likely to be questioned. We
therefore suggest that the conscious assessment of potential benefits will be more decisive
for eliciting behavioral support in earlier stages of the change than in its subsequent phases.
Hypothesis 4: The positive relationship between anticipated benefits of the change and CSB will be
moderated by time, such that this association is stronger in an earlier phase (Time 1) than in a
later phase of the change (Time 2).
The Importance of the Employment Relationship in Later Phases of Change
In high-quality employment relationships, workers reciprocate by contributing to the organization above and beyond their formal job duties (Coyle-Shapiro et al., 2004; Rhoades &
Eisenberger, 2002). Reciprocation is not primarily instrumental; rather, it is social behavior
(Blau, 1964). It is motivated by positive affect, trust, and felt obligation. The particular
behaviors employees engage in to reciprocate, however, are not specified a priori. They depend
on how employees construe their own roles in the exchange relationship, based on the social
norms and cues they receive in the organization (Rousseau, 1995). Establishing an organizationally desired behavior as a new form of reciprocity thus requires that employees revise
their current role definitions and mental models of the employment relationship.
Research on psychological contracts suggests that high-quality employment relationships
are characterized by both flexibility and inertia (Rousseau, 2001). Flexibility arises from the
dynamic and open-ended nature of social exchange. Social exchange evolves in repeated
interactions over time to progressively include broader and more contextualized contributions that take into account the other parties’ present needs and circumstances (Blau, 1964).
In psychological contract theory, the process by which employees develop more complex
mental representations of their employment relationships and their associated obligations
to the organization is referred to as elaboration (Rousseau, 2001). Moreover, high-quality
employment relationships have been shown to entail greater tolerance for delayed fulfillment and perceived breaches by the employer (Robinson, 1996). The downside of this relative stability in employee beliefs about their employment relationships is that, once
established, these cognitive structures tend to develop a certain degree of inertia and—at
least in the short term—resist revision (Hodgkinson & Healey, 2008, p. 400 and following;
Rousseau, 1995, p. 162). Psychological contract adaptation or modification is a slow or gradual
process often at odds with the pace of change in contemporary organizations (De Vos,
Buyens, & Schalk, 2003; Robinson, Kraatz, & Rousseau, 1994; Schalk & Freese, 2000).
An implication of psychological contract theory for the present study is that workers
enjoying a high-quality relationship with their employer may not be among the most enthusiastic supporters of change shortly after it is initiated. At the outset of change, a particularly
positive employment relationship may bring to bear the postulate of prospect theory that
the potential losses associated with the change loom larger than the anticipated gains
(Kahneman & Tversky, 1979). Being content with the status quo can make change unattractive
for workers with high-quality employment relationships (e.g., Van Dyne & LePine, 1998).
The longer the change is in effect and the more part of the organization’s routines it becomes,
the stronger will be the social-normative pressure employees experience to participate. The
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1676 Journal of Management / November 2011
higher level of institutionalization the change attains, the more clearly it conveys the message
to employees that the new practices will not “blow over” but need to be dealt with constructively in order to support the organization. Given enough time to revise or elaborate upon
their mental models regarding obligations toward the employer, workers in high-quality
exchange relationships should increasingly adopt CSB as a form of reciprocity.
Employment relationships based on social exchange tend to be flexible to incorporate
new ways of supporting the organization in the medium or longer term but are also characterized by a certain degree of inertia due to the psychological investments employees have
made in them. We therefore suggest that the perceived quality of the employment relationship will be more relevant for predicting sustained behavioral support in later phases of the
change than for initial participation in its beginning stages.
Hypothesis 5: The positive relationship between the quality of the employment relationship and
CSB will be moderated by time, such that this association is stronger in a later phase (Time 2)
than in an earlier phase of the change (Time 1).
Method
Organizational Context
The setting for this study was a midsize general hospital in the eastern United States,
located in a highly competitive region for health care providers. In the 10 years preceding
our study, the hospital had experienced severe financial difficulties, high staff turnover,
problems with the quality of care, and declining patient numbers. Increasing unionization
had led to the installation of closed-shop policies in some nonclinical areas and was viewed
as a threat by the hospital’s management. Two years prior to our study, a new CEO was hired
to manage a strategic turnaround considered necessary by the board of directors. The new
CEO, known to have led a similar change at another hospital, formulated new strategic goals
for quality improvement, budget consolidation, and enhancement of employee morale. At the
same time, the hospital sought to expand its medical services to regain competitive advantage.
To achieve this strategic turnaround, a change initiative according to the principles of
shared leadership—a change program for health care organizations—was introduced
(Henderson-Ioney, 1996). Similar to TQM, shared leadership advocates employee participation and empowerment as a means to continuously improve operational efficiency and service quality. The rationale for choosing this approach was the realization, that—given the
hospital’s history of management–labor disputes—the necessary transition would require all
employees to recognize the need to change and take personal responsibility for improving
quality and reducing costs.
A core element of the change was the installation of two worker councils—the Work-Life
Council and the Clinical Council. Similar to the worker councils found in many European
countries (but without legal rights and responsibilities), their function was to represent the
workforce and facilitate its communication with management. The councils held monthly
meetings, including briefings on recent developments by the hospital’s CEO and/or the human
resources manager. Strategic management decisions, such as budget changes, restructuring
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1677
of departments, and implementation of new services, as well as their underlying reasons,
thus were communicated through the councils. The councils functioned as an employee suggestion and grievance system to channel bottom-up communication and improve change
implementation.
All departments were instructed to assign one representative to the Work-Life Council
and to rotate this position among the unit members at least on a yearly basis. Departments
involved in patient treatment (e.g., nursing, rehabilitation, therapy) dispatched a second
representative to the Clinical Council. The councils thus each consisted of 15 to 20 rank-andfile workers. Varying across units, representatives were elected by department members,
were volunteers, or were assigned by supervisors. Their role was that of change agent and
link between the councils and their units. As council membership was not entirely voluntary
(each department had to send at least one representative) and did not necessarily imply active
contributions, it constitutes our indicator of formal involvement in the change.
CSB in this context refers to behaviors that all employees were encouraged to engage in
to improve the quality and efficiency of the hospital’s operations. All workers were asked to
make suggestions for the continuous improvement of the organization to the councils, either
by talking to their unit representatives, submitting a written proposal to a council, or appearing at a council meeting to state their case. Suggestions for how to improve the quality of
patient care were addressed to the Clinical Council. Issues concerning the quality of working
life were brought to the attention to the Work-Life Council. The councils, in turn, had the
task of discussing relevant matters with hospital management and informing their peers on
the decisions reached and actions to be taken. Suggestions made to the Clinical Council
included, for example, new nursing techniques or ways to avoid medication errors; those
brought to the Work-Life Council ranged from small matters (e.g., changing the uniform
color of kitchen workers) to pointing out conflicts impeding collaboration within or between
departments (e.g., leadership problems) or ways to improve the work organization or substantially cut costs (e.g., by changing suppliers or stock policies). Active use of the council
system was the central element of the hospital’s change strategy of getting all employees
involved in the continuous improvement of the organization. Our conceptualization of CSB
reflects this objective.
Survey Timing and Administration
Two employee surveys were conducted in the hospital. The first wave, Time 1 (T1), took
place 18 months after the councils were implemented, the second, Time 2 (T2), 24 months
later. The timing of measurements was determined in consultation with the hospital’s management and council members based on the progress of the change. By the time of the initial
wave, all employees were assumed to have had an opportunity to develop beliefs about the
change’s personal consequences and engage in CSB. A period of two years between T1 and
T2 was chosen to provide sufficient time for the council system to become more accepted
and institutionalized.
Employees from all hospital units and professional groups (except physicians, who were
not hospital employees) participated. Questionnaires were distributed and collected by the
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1678 Journal of Management / November 2011
researchers on-site during a period of 2 weeks. Alternatively, completed surveys could be
sent directly to the researchers’ university in supplied prestamped envelopes. Participants were
permitted to complete the survey during work hours, which took between 15 and 30 minutes.
Each provided a personal code derived from his or her social security number, which was
used to generate panel data. All respondents signed and separately returned a consent form
approved by the university’s internal review board. The form stated the purpose of the
research and that participation was voluntary, and it ensured confidentiality.
Sample
The total number of workers employed was 350 at T1 and had risen to 400 at T2 as the
hospital expanded its services. Annual turnover was 20%. Consequently, only half of the
workers at T2 had also been employed by the hospital at T1. Survey participation was 166
(47.4%) at T1 and 207 (51.8%) at T2. Initially, 74 repeat responders were matched. After
listwise deletion of missing data, 72 were included in the analyses (approximately 36.0% of
workers employed at both T1 and T2). Participants included clinical, clerical, and support
staff. Most (84.7%) were female. Median categories for age and tenure were 46 to 50 years
and 6 to 10 years, respectively; 27.8% reported having a high school diploma, 8.3% a registered nurse diploma, 26.4% an associate’s degree, 33.3% a bachelor’s degree, and 4.2% a
master’s degree. Present or former council membership had increased from 15 at T1 to 24 at T2.
Chi-square tests assessed demographic differences between the panel and one-time responders at T1 and T2. At T2, repeat responders had higher tenure. Other than this logical difference,
no dissimilarities were detected.
Measures
Development of context-specific measures. To develop contextually appropriate measures
for CSB and anticipated benefits of the change, semistructured interviews were conducted
by the first and third authors with the hospital’s CEO and human resources manager separately. Based on interview notes, items were developed in discussion by the research team.
Questions assessed the ways in which management wanted employees to get involved in the
change and what positive outcomes they might expect. With regard to the former, three activities were identified: (a) making suggestions on how to improve current practices; (b) openly
addressing problems so that they could resolved; and (c) stimulating communication among
coworkers regarding current developments, problems, and hospital performance. The focus
of these activities was the council system, implemented as a medium for channeling communication and the improvement suggestions of all employees. Due to the precarious financial situation of the hospital, the program did not offer extrinsic benefits (e.g., rewards for
suggestions). From the perspective of management, however, employees could benefit intrinsically. Based on their responses and the shared leadership literature, we identified three
potential gains for employees: (a) higher control over the work environment (e.g., by making
suggestions on how to improve working conditions), (b) participation in decision making
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1679
(e.g., via their own input to the councils and information sharing by management through
the councils), and (c) general improvements of the work experience (e.g., better working
conditions, improved management–labor relations). Measures thus derived are reported next.
Change-supportive behavior. Three items operationalized the key activities of behavioral
change support: “I have made suggestions to be addressed in the Councils,” “I have raised
issues with a Council representative,” and “I have discussed Council issues with coworkers.”
Internal consistency was .85 (T1) and .91 (T2). A five-point scale from 1 = not at all to 5 =
to a very great extent was used for all measures.
Anticipated benefits of the change. Based on the interviews, three items measured potential benefits of the change for employees: “I will have more control over my work environment through Shared Leadership,” “Shared Leadership will enable me to participate in making
decisions formerly made by management,” and “Shared Leadership will make it more pleasant to work in this organization.” Reliability was .91 (T1) and .89 (T2).
Quality of the employment relationship. To measure the quality of the employment relationship, we used five items by Shore et al. (2006) that capture the perceived degree of social
exchange between the focal employee and the organization; sample items are “My relationship with this organization is based on mutual trust” and “There is a lot of give and take in
my relationship with this organization.” Reliability was .85 (T1) and .80 (T2).
Formal involvement in the change. A single item was used to assess council membership
(0 = no formal involvement, 1 = present or former council member).
Demographic information. Gender was assessed with a dichotomous variable (0 = male,
1 = female), age with 11 categories (1 = below 21 to 11 = over 65), organizational tenure
with 10 options (1 = a year or less to 10 = more than 30 years), and education with 5 options
(1 = high school diploma to 5 = master’s degree).
Data Analysis Strategy
Our primary method of data analysis is SEM with maximum-likelihood estimation using
AMOS 17.0 (e.g., Byrne, 2001). Multiple-group SEM is used for a two-group time-series
(panel) design, where Group 1 refers to data obtained at T1 and Group 2 to data from the
same respondents obtained at T2. In multiple-group SEM, a model is fitted to all groups
simultaneously (i.e., only one set of fit indices is computed), whereas parameters (i.e., factor
loadings, structural paths, etc.) are initially estimated for each group separately (e.g., Kline,
2004). Fit indices therefore refer to the pooled sample of N = 144; parameter estimates in
each group are based on n = 72. Constraining certain parameters to be equal across groups
and observing fit changes will test if these parameters are equivalent or moderated by group
membership. Here, time (Survey 1 or 2) is the basis for each group.
To evaluate model fit, we used established indices and conventional cutoffs (e.g., Byrne,
2001; Kline, 2004). Chi-square, or c²(df), refers to the absolute discrepancy to the data. A
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1680 Journal of Management / November 2011
nonsignificant chi-square indicates good fit, and the relative chi-square should be below 2.0.
For comparative fit indices, such as the incremental fit index (IFI), Tucker-Lewis index (TLI),
and comparative fit index (CFI), values above .90 are adequate. The root mean square error
of approximation (RMSEA) accounts for model complexity and sample size. It should be
below .05, its confidence interval (CI) should not include values above .08, and an additional
test that RMSEA is above .05 in the overall population should yield a nonsignificant result.
To compare models before and after imposing equality constraints between the two groups
(T1/T2), we used chi-square statistics. A nonsignificant change in chi-square, or Dc²(Ddf),
indicates that constrained parameters are invariant over time, whereas a significant change
denotes a moderating effect of time. In addition, we compare the respective unstandardized
path coefficients between T1 and T2 using students’ t tests to provide effects sizes for the
extent of moderation (Cohen’s d).
Two alternative methods of analysis are used to follow up and substantiate our SEM results:
path analysis and panel regression. Path models are based on manifest instead of latent variables and therefore impose lower requirements on sample size. Panel regression is an established approach to analyzing time-series data, which addresses the problem of unmeasured
time-varying influences by including a dummy estimator for time of measurement (e.g.,
Jaccard & Turrisi, 2003). The advantages of these two alternative methods come with certain
limitations. Therefore, they are used as supplementary analyses. Table 2 gives an overview
of our data analysis strategy, reflected in the presentation of results.
Results
Preliminary Analyses
Descriptive statistics and intercorrelations are displayed in Table 3. Between T1 and
T2, Anticipated Benefits of the Change decreased slightly, MT1 = 3.15, SD T1 = 1.03;
M T2 = 3.00, SD T2 = 1.06; t(71) = –1.25, ns, whereas Quality of the Employment Relation­
ship, MT1 = 3.05, SD T1 = 0.89; MT2 = 3.15, SD T2 = 0.80; t(71) = 0.81, ns, and CSB both
increased, MT1 = 2.90, SD T1 = 1.17; MT2 = 3.06, SD T2 = 1.05; t(71) = 1.06, ns. Pairwise tests
indicated that mean changes were nonsignificant. Demographic data were not related to the
dependent variable.
Confirmatory Factor Analysis
In the first step, a two-group confirmatory factor analysis (CFA) was conducted, where
each of the two survey waves (T1/T2) constitutes a group. The measurement model contained 11 items, allocated to three latent factors (Anticipated Benefits of the Change: 3 items;
Quality of the Employment Relationship: 5 items; CSB: 3 items). The unconstrained measurement model fitted the data well across the two groups: c²(82) = 96.83, ns; c²/df = 1.18;
IFI = .98; TLI = .97; CFI = .98; RMSEA = .036, CI = .000-.061, ns. The theoretical measurement
model was compared with several nested alternatives. Fit was worst when combining all
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1681
Table 2
Data Analysis Strategy
Method of Analysis
Test Criteria
1. Confirmatory factor analysis
Two-group analysis—Time 1 (T1)/Time 2 (T2)
1a. Unconstrained estimation
1b. Factor loadings constrained equal
between T1 and T2
2. Structural equation modeling
Latent variables, two-group analysis (T1/T2)
2a. Unconstrained estimation
2b. Structural paths constrained equal
between T1 and T2
2c. Comparison of unstandardized path
coefficients between T1 and T2
Advantage: Provides effect size for moderation
Testing for
Fit indices
Change in fit (Dc²)
Factor structure
Factor invariance
Fit indices, paths (b, p)
Hypotheses 1, 2, and
3 (effects)
Hypotheses 4 and 5
(moderation)
Hypotheses 4 and 5
(moderation)
Change in fit (Dc²)
t tests; Cohen’s d
3. Path analysis
Manifest variables, two-group analysis (T1/T2)
3a, 3b, and 3c similar to 2a, 2b, and 2c
Advantage: Lower sample size requirements
Similar to 2a, 2b, and 2c;
no fit indices (df = 0)
Similar to 2a, 2b, 2c
4. Panel Regression
Manifest variables, pooled data (T1 + T2),
time dummy variable
4a. Multiple regression across both T1 and T2
Weights (b, p), F
Hypotheses 1, 2, and
3 (effects)
Hypotheses 4 and 5
(moderation)
4b. Including interaction terms with time dummy
Weights, (b, p) DF
Advantage: Controlling for unobserved
time-varying influences
constructs in one general factor, Dc²(6) = 484.22, p < .01, followed by the two-factor model
combining Quality of the Employment Relationship and CSB, Dc²(4) = 248.65, p < .01; the
two-factor model combining Anticipated Benefits of the Change and CSB, Dc²(4) = 245.67,
p < .01; and the the-factor model combining Quality of the Employment Relationship and
Anticipated Benefits of the Change, Dc²(4) = 235.23, p < .01. Having ruled out these alternatives, invariance of the initially specified three-factor model over time was established.
Constraining all factor loadings equal for T1 and T2 did not increase chi-square, Dc²(8) =
4.23, ns. Complete CFA results are provided in the appendix.
Structural Equation Modeling
In the second step, we transformed the measurement model into a structural model. Formal
Involvement in the Change was included as a manifest independent variable. The model is
displayed in Figure 1 and was supported by all fit indices: c²(98) = 107.91, ns; c²/df = 1.10;
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1682
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
(11)
(15.3%)
6.471.94
–.08
4.382.37
–.05
.50**
2.801.28
–.35**
–.01
–.12
(15)
(20.8%)
–.21
–.05.07
–.00
(24)
(33.3%)
–.13
–.00
–.02
.16
.58**
3.15
1.03
–.39** .11
–.15 .16 .25* .09
.91b 3.00
1.06
–.23
.27*
.09 .02 .00
.01
.45** .89b 3.05
0.89
–.11 –.00
–.13 .17 .05
.01
.30* .16
.85b 3.15
0.80
–.03
.22
.04 .10 –.06 –.10
.31** .43** .25* .80b 2.90 1.17 –.17 –.16 –.02 .18 .39**.28* .27*.02 –.03–.08 .85b
3.06 1.05 –.01–.05 –.04.10.26*.32**.12.06 .03.20*
.32**
.91b
1. Gendera (female)
2. Agea
3. Tenurea
4. Educationa
5. Formal Involvement in the Change T1a
6. Formal Involvement in the Change T2a
7. Anticipated Benefits of the Change T1
8. Anticipated Benefits of the Change T2
9. Quality of the Employment Relationship T1
10. Quality of the Employment Relationship T2
11.Change-Supportive Behavior T1
12.
Change-Supportive Behavior T2
Note: N = 72; M = scale mean; n = absolute number of cases; T1 = Time 1; T2 = Time 2.
a
Categorical variables.
b
Cronbach’s alpha reliability coefficients.
*p < .05. ** p < .01.
M (n)
SD (%)1 23456789
10
11
12
Table 3
Descriptive Statistics and Correlations
Kim et al. / Change-Supportive Behavior 1683
Figure 1
Structural Equation Model
Formal
Involvement
in the Change
T1: .33**
T2: .36**
T1: .21
T2: .09
X1
T1: .06
T2: –.07
X2
X3
Anticipated
Benefits of the
Change
–
T1: .33*
T2: .45**
X6
X7
ChangeSupportive
Behavior
Time
+
X4
X5
T1: .30*
T2: –.13
Quality of the
Employment
Relationship
Y1
Y2
Y3
T1: R2 = .23
T2: R2 = .18
T1: –.17
T2: .31*
X8
Note: Two-group analysis, Time 1 (T1)/Time 2 (T2); n = 72/72. Model fit: c²(98) = 107.91, ns; c²/df = 1.10; incremental fit index = .99; Tucker-Lewis index = .98; comparative fit index = .99; root mean square error of approximation = .027; confidence interval = .000-.053, ns.
*p < .05. **p < .01.
IFI = .99; TLI = .98; CFI = 0.99; RMSEA = .027, CI = .000–.053, ns. In an additional step,
this final model was reestimated with gender, age, organizational tenure, and education
included as manifest independent control variables. Chi-square increased, c²(162) = 170.71,
ns, and model parsimony was reduced (parsimony ratio = 0.60 compared with 0.74 without
controls). None of the demographic variables made a significant contribution to explaining
CSB at either T1 or T2 (gender: b = –.12/.05, ns; age: b = –.16/–.07, ns; organizational
tenure: b = .12/.09, ns; education: b = .14/.03, ns). Other paths remained unaffected. To
maintain a parsimonious and well-fitting model for the following analyses, control variables
were subsequently dropped.
Next, we examined the structural paths, estimated separately for both groups (i.e., T1 and
T2). Anticipated Benefits of the Change related positively to CSB only at T1 (b = .30, p <
.05) but not at T2 (b = –.13, ns). Conversely, Quality of the Employment Relationship showed
no association with CSB at T1 (b = –.17, ns), but had a positive effect at T2 (b = .31, p < .05).
Formal Involvement in the Change related positively to CSB in both waves (T1: b = .33, p <
.01; T2: b = .36, p < .01). Accordingly, Hypothesis 1 and Hypothesis 2 each received support
only for one of the two measurement points, whereas Hypothesis 3 was fully supported.
An established approach to testing moderating effects in multiple-group SEM is to constrain the parameter of interest to be equal across groups and observe resulting changes in
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1684 Journal of Management / November 2011
fit (e.g., Byrne, 2001; Kline, 2004). A significant change in chi-square indicates a moderating effect of the grouping variable—in our case, time. To test the first moderation hypothesis, Hypothesis 4, we constrained the path from Anticipated Benefits of the Change on CSB
to be equal across T1 and T2. This reduced model fit significantly, Dc²(1) = 5.19, p < .05.
To test Hypothesis 5, the second moderation hypothesis, an equality constraint was imposed
on the path from Quality of the Employment Relationship on CSB. Again, fit decreased,
Dc²(1) = 5.81, p < .05. Consequently, both relationships were moderated by time, supporting
Hypotheses 4 and 5.
To calculate effect sizes (Cohen’s d) for the extent of moderation, students’ t tests compared unstandardized path coefficients (B) and standard errors of measurement (SE) between
T1 and T2. Again, results indicated changes in the association of Anticipated Benefits of the
Change, BT1 = 0.31, SET1 = 0.14; BT2 = –0.11, SET2 = 0.12; DB = –0.41, SED = 0.18, t(142) =
2.27, p < .05, and Quality of the Employment Relationship, BT1 = –0.27, SET1 = 0.22; BT2 =
0.53, SET2 = 0.27; DB = –0.80, SED = 0.34, t(142) = 2.32, p < .05, with CSB. Effects were in
a medium range (d = 0.38 and 0.39).
Path Analysis
Commonly recommended for SEM are samples of 100 to 200 observations (Kline, 2004),
whereas ours was based on N = 144 in total. To address this concern, we replicated analyses
in a simple path model with scale-level manifest indicators (AMOS 17.0), reducing the
number of variables to four at each point in time. Resolving the problem of sample size, this
approach also has disadvantages: (a) Aggregating items neglects measurement error and differences in factor loadings, and (b) with zero degrees of freedom in the model (df = 0), fit
indices are not computed.
Again, significant variance in CSB was explained by Anticipated Benefits of the Change
at T1 (b = .25, p < .05) but not at T2 (b = –.07, ns), Quality of the Employment Relationship
at T2 (b = .24, p < .05) but not at T1 (b = –.13, ns), and Formal Involvement in the Change at
both T1 (b = .30, p < .01) and T2 (b = .31, p < .01). Constraining paths to be equal across
T1 and T2 freed up 1 degree of freedom, and the chi-square change was significant for both
Anticipated Benefits of the Change, Dc²(1) = 3.75, p = .053, and Quality of the Employment
Relationship, Dc²(1) = 4.92, p < .05. The t-test results and effect sizes correspond to previous
results for both Anticipated Benefits of the Change, BT1 = 0.28, SE T2 = 0.13; BT2 = –0.07,
SET2 = 0.12; DB = –0.35, SED = 0.18, t(142) = 1.95, p = .054; d = 0.32, and Quality of the
Employment Relationship, BT1 = –0.17, SE T1 = 0.15; T2: BT2 = 0.32, SE T2 = 0.16; DB = –0.49,
SEΔ = 0.22, t(142) = 2.24, p < .05; d = 0.37. Results thus remained completely stable, reducing concern about sample size.
Panel Regression
Lastly, we conducted a fixed-effects panel regression in the pooled sample of N = 144
with CSB as the dependent variable, using ordinary least squares estimation (SPSS 16.0) and
including time as a dummy-coded independent variable (time = 0/1 for T1/T2). This approach
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1685
Table 4
Panel Regression
Change Supportive Behavior
Step 1
b
Step 2
T
Time (Time 1 = 0, Time 2 = 1)
.04
0.44
.30**
3.74
Formal Involvement in the Change
Anticipated Benefits of the Change
.12
1.39
Quality of the Employment Relationship
.03
0.29
Time × Anticipated Benefits of the Change
Time × Quality of the Employment Relationship
R2 (adjusted R2)
.12 (.10)
F(df1 = 4/6; df2 = 139/137)
4.90**
DF(Ddf = 2)
b
.03
.31**
.27*
–.13
–.24*
.25*
.16 (.13)
4.45**
3.24*
T
0.41
3.82
2.29
–1.19
–2.00
2.21
Note: N = 144.
*p < .05. **p < .01.
does not take into account the measurement model and provides limited fit indices (e.g.,
F statistics). An advantage it offers, however, is to control for unmeasured time-varying influences. Changes in the dependent variable between T1 and T2, which are not captured by independent variables, should be absorbed in the effect of the time dummy (e.g., Wooldridge, 2002).
Time, Formal Involvement in the Change, Anticipated Benefits of the Change, and Quality
of the Employment Relationship were entered into the regression equation first. In a second
step, interaction terms for Time × Anticipated Benefits of the Change and Time × Quality of
the Employment Relationship were included (variables were centered before calculating
interaction terms). Time in itself had no independent effect (b = .04, ns). As discussed above,
this speaks against unobserved time-varying influences on CSB. Across both points in time
neither Anticipated Benefits of the Change (b = .12, ns) nor Quality of the Employment
Relationship (b = .03, ns) had an effect on CSB. The former relationship attained significance
only in the second step (b = .27, p < .05), whereas the latter remained nonsignificant
(b = –.13, ns). The interaction term of Time × Anticipated Benefits of the Change had a
negative effect (b = –.24, p < .05) and the Time × Quality of the Employment Relationship
interaction a positive effect (b = .25, p < .05). Entering interaction terms improved the regression model, DF(2) = 3.24, p < .05. Consequently, from T1 to T2, anticipated change benefits
had become less and employment relationship quality more predictive of CSB (Table 4).
Discussion
The results of our study shed new light on employee support for organizational change.
Using a two-wave panel design, it demonstrated that the antecedents of CSB—defined as
actions employees engage in to actively participate in, facilitate, and contribute to a planned
change—varied over the course of the intervention studied. Anticipated benefits of the
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1686 Journal of Management / November 2011
change were positively related to behavioral support only in the first wave, 18 months after
the change was initiated. The quality of the employment relationship—conceptualized as the
degree of social exchange with the organization—related positively to CSB only in the second wave, 24 months after the first one. In accordance with our hypotheses, results suggest
that both relationships are moderated by time, so that the cognitive assessment of anticipated
benefits becomes less important and the socioemotional quality of the employment relationship more important for predicting active behavioral support as the change progresses. This
moderating role of time was more pronounced than expected, which resulted in each of the
predictors attaining significance only in one of the two waves, while showing negative,
yet nonsignificant, effects at the other measurement point. In contrast, formal involvement
in the change—operationalized as membership in one of the advisory councils implemented
by the organization to channel employee participation—had stable positive effects across
both waves.
In specifying antecedents of CSB, we have drawn on the TPB (Ajzen, 1991), which has
been proposed as a suitable framework to organize crucial precursors of behavioral responses
to change (e.g., Armenakis et al., 2007; Jimmieson et al., 2008). Our predictors of CSB—
anticipated benefits of the change, perceived quality of the employment relationship, and
formal involvement in the change—reflect the three TPB domains of attitude, subjective
norm, and behavioral control. The moderation hypotheses were based on theory regarding
discontinuous information processing (Louis & Sutton, 1991) and psychological dynamics
underlying the employment exchange (Rousseau, 2001). Taking these elements together, our
study makes an important contribution to overcoming what has been criticized as the atheoretical and atemporal nature of organizational change research (Pettigrew et al., 2001; Weick &
Quinn, 1999). It provides further evidence for the utility of using established models of human
behavior from other fields to inform organizational change management. Moreover, our
results provide clear support for George and Jones’s (2000) claim that time should be treated
more explicitly in research because—among other things—it can change the relationships
between constructs. These authors have cautioned researchers that neglecting time may lead
to flawed theorizing and biases in interpreting results. Our study illustrates that. If two
groups of researchers each had access to data from only one of the two waves in our study,
they would come to contradicting conclusions. One would assume that the anticipated benefits of the change were relevant in explaining CSB, but the quality of the employment
relationship was not. The other group would conclude the opposite. In either case, the available information would lead to an incomplete appreciation for the role both aspects play in
organizational change. Our research thus demonstrates the inadequacy of the still “ubiquitous
use of the single-snapshot technique” (Avital, 2000, p. 666) in studying organizational
change (cf. Pettigrew et al., 2001). Change is a dynamic phenomenon, a basic fact that methods used for studying it must reflect. In this regard, the two-wave panel design of the present
study is a beginning, but not an end.
Alternative explanations, particularly with regard to the observed moderating effects of
time, need to be taken into account. For example, the decreasing relevance of the anticipated
benefits of change could be due to revised employee beliefs about the change’s outcomes
based on new information available to them at T2. From a stress theory perspective, Lazarus
and colleagues (e.g., Lazarus & Folkman, 1984) have described the cognitive processes by
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1687
which individuals continuously reappraise situations based on the consequences of their own
actions. In this vein, it could be that benefits anticipated at T1 have been already realized at
T2 or, alternatively, that employees might have become less optimistic about the change’s
outcomes. In both cases, the motivation for continuous support based on the perceived future
valence of the change would be reduced—either because initially anticipated benefits have
already occurred or because of lowered expectations that they eventually will occur at all.
Concurrently, lack of association between the quality of the employment relationship and
CSB at T1 could be due to violations of employees’ psychological contracts at the change’s
outset. This, in turn, could have reduced their felt obligation to reciprocate to the employer
(e.g., Robinson & Morrison, 1995). Although both alternatives are plausible, they do not fully
account for the observed results. Both imply that the respective predictor should be rated
considerably lower at one of the two measurement points than at the other. Although there
is some variability in the scale means between T1 and T2, mean differences are slight and
do not attain statistical significance. Therefore, the evidence does not support these alternative
explanations.
Limitations
Several methodological limitations warrant attention. One concern is sample size. To
ensure that the data permitted a valid testing of our hypotheses, we conducted a priori power
analyses, using the procedures and conventional effect sizes suggested by Cohen (1988). The
recommended power level of .08 in a multiple regression model (e.g., path analysis) with
three predictors and a medium combined effect (Cohen’s f² = .15, corresponding to R² = .13;
p < .05) requires a minimum sample size of 76. As our actual sample of 72 for each measurement point was only slightly smaller, this was of minor concern. For detecting a difference
(p < .05) between a conventional small- and a large-sized relationship between two variables
(r1 = .10 and r2 = .38) a power level of .08 requires a sample size of 91; however, the sample
size of 72 results in a still acceptable power of .07. Acknowledging that SEM imposes higher
sample requirements, multiple analyses supported the stability of our results, demonstrating
that they are not artifacts of any particular analytic approach.
A distinctive advantage of our study is its genuine panel design, which rules out selection
effects between the two measurement points (as opposed to so-called quasi-panels, where
participants vary between waves). Our sample represented approximately 36% of all potential responders (i.e., workers employed at both T1 and T2), which is reasonable for a panel
study (Groves, Dillman, Eltinge, & Little, 2002). No meaningful differences in demographic
information or variable means could be detected between panel responders and those onetime participants, who were excluded, at either measurement point. Nonetheless, we cannot
rule out the possibility that those responding less positively to the change did not complete
the surveys or had left the organization. Self-selection is a general problem recognized in field
research, although actual evidence of this bias is limited (e.g., Groves et al., 2002; Wei &
Cowan, 1988).
Another limitation is reliance on self-reports, raising concerns about common method bias.
These can be dispelled by our research design. Even if common method variance were present,
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1688 Journal of Management / November 2011
there is no reason to believe it affected the two measurement points differently. The distinct
result patterns for the two waves rules out this bias as an alternative explanation.
A crucial issue is the timing of measurement points. In consultation with the hospital’s
management, the first wave was conducted at a time when all employees were expected to
have had sufficient opportunity to actively contribute (18 months after the implementation
of the council system). The rollout of the change was rather slow and the first year mostly
spent establishing appropriate procedures (e.g., getting all departments to designate and send
council representatives). At the time of the second wave, the change had been in effect
42 months and, according to management and our own observations, had reached a phase of
institutionalization. Measurement points were chosen carefully based on the progress of the
change but also included pragmatic considerations. Generally, it would have been preferable
to conduct more than two waves, including baseline measures taken before or immediately
after the change was initiated. However, our interest here was CSB. Measuring such activities before employees actually had a chance to engage in them would have been nonsensical.
One way to resolve this problem would have been to assess employee intentions to contribute. Another reason for reliance on two waves was panel mortality (i.e., dropout rates), which
typically increases considerably with each measurement point. Judging from the size of our
two-wave panel, it is questionable whether an additional measurement point would have
generated sufficient matching data to track developments across three points in time. Finally,
the initiation of the change coincided with a change in the hospital’s top management. We
refrained from conducting an initial survey before the new CEO had built up a basis of trust,
out of concern that it might fuel employee suspicion regarding the anonymity and use of survey
responses.
Lastly, the question arises regarding how far our results are generalizable to other contexts and types of change. Our findings apply to situations where employee involvement is
desired to facilitate and contribute to a planned change effort. These include quality initiatives and continuous improvement processes like TQM, kaizen, lean production, employee
suggestion systems, and related management concepts. Our major postulate that anticipated
benefits of the change will be more important for promoting supportive employee behavior
in earlier phases of change, whereas the quality of the employment relationship attains higher
relevance in later phases once the change has become more institutionalized, is likely to be
generalizable across various types and degrees of change where active employee support
matters. Nonetheless, generalizability is an empirical question for follow-up research to address.
Implications
In managing organizational change, practitioners should bear in mind that active employee
support is a dynamic function of anticipated beneficial outcomes, the quality of the employment relationship, and formal involvement in change-related activities. The observed stable
effect of council membership on CSB suggests the value of structurally integrating employees into change processes. Establishing such formal assignments and regular rotations among
employees is a promising strategy for promoting the workforce’s active support. Further, our
results indicate that in early phases of the change employees are especially sensitive to its
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1689
anticipated outcomes. Supporting and guiding employees’ sense making by actively engaging
in sense giving is a management task that warrants high priority during the initiation and early
implementation of change (e.g., Gioia & Chittipeddi, 1991). This requires managers to reflect
on employees’ perspectives and effectively communicate the mutual gains of the transition
(e.g., Rousseau & Tijoriwala, 1999). Change managers should consider the possibility that
high-quality employment relationships need not make workers early adopters of the change.
On the contrary, individuals with a lot invested in their relationships with the firm may perceive
that there is much to lose in changing the status quo; thus, they need time to adapt to the new
situation. In the longer term, however, employment relationships based on trust and mutual
support can facilitate the institutionalization and sustainability of change. Employees who appear
to be “change resisters” early in the change could become its backbone in a later phase.
Our study demonstrates the positive and active role employees can play in facilitating and
contributing to organizational change. It calls for greater attention by change managers to the
psychological dynamics underlying change-supportive employee behavior over time. Reluctance
to change, after all, is a perfectly rational response if employees cannot see its benefits and if
they feel little obligation to contribute. Actively supporting change, in turn, is an equally rational
decision if employees have opportunity and the reason to do so—at the right time.
Appendix
Items and Factor Loadings (confirmatory factor analysis)
I have made suggestions to be addressed in the Councilsa
I have raised issues with a Council representativea
I have discussed Council issues with coworkersa
I will have more control over my work environment through Shared Leadershipb
Shared Leadership will enable me to participate in making decisions formerly made by
managementb
Shared Leadership will make it more pleasant to work in this organizationb
There is a lot of give and take in my relationship with this organizationc
My relationship with this organization is based on mutual trustc
This organization has made a significant investment in mec
I try to look out for the best interests of this organization because I can rely on them to take
care of mec
The things I do on the job today will benefit my standing in this organization in the long runc
T1
T2
.80d
.82
.83
.96d
.84d
.96
.86
.95°
.78
.79
.93
.67d
.82
.68
.82
.59d
.72
.68
.77
.71
.68
.68
Note: N = 72 for both Time 1 (T1) and Time 2 (T2); p < .001 for all freely estimated loadings.
Latent factor: Change-Supportive Behavior.
b
Latent factor: Anticipated Benefits of the Change.
c
Latent factor: Quality of the Employment Relationship.
d
Fixed reference parameters.
a
References
Ajzen, I. 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50: 179-211.
Ajzen, I., & Fishbein, M. 1980. Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ:
Prentice Hall.
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1690 Journal of Management / November 2011
Armenakis, A. A., Bernerth, J. B., Pitts, J. P., & Walker, H. J. 2007. Organizational change recipients’ beliefs scale:
Development of an assessment instrument. Journal of Applied Behavioral Science, 43: 481-505.
Armenakis, A. A., Harris, S. G., & Feild, H. S. 1999. Making change permanent: A model for institutionalizing
change interventions. In W. A. Pasmore & R. W. Woodman (Eds.), Research in organizational change and
development: 97-128. New York: JAI.
Armenakis, A., Harris, S., & Mossholder, K. 1993. Creating readiness for organizational change. Human Relations,
46: 1-23.
Armitage, C. J., & Christian, J. (Eds.). 2004. Planned behavior: The relationship between human thought and
action. New Brunswick, NJ: Transaction Publishers.
Armitage, C. J., & Conner, M. 2000. Efficacy of the theory of planned behavior: A meta-analytic review. British
Journal of Social Psychology, 40: 471-499.
Ashford, S. J. 1988. Individual strategies for coping with stress during organizational transitions. Journal of Applied
Behavioral Science, 24: 19-36.
Avital, M. 2000. Dealing with time in social inquiry: A tension between method and lived experience. Organization
Science, 11: 665-673.
Balogun, J., & Johnson, G. 2004. Organizational restructuring and middle manager sensemaking. Academy of
Management Journal, 47: 523-549.
Bartunek, J. M., Rousseau, D. M, Rudolph, J., & Depalma, J. 2006. On the receiving end: Sensemaking, emotion,
and assessments of an organizational change initiated by others. Journal of Applied Behavioral Science, 42:
182-206.
Beer, M., Eisenstat, R. A., & Spector, B. 1990. Why change programs don’t produce change. Harvard Business
Review, 68: 158-166.
Blau, P. M. 1964. Exchange and power in social life. New York: John Wiley.
Byrne, B. M. 2001. Structural equation modeling with Amos: Basic concepts, applications, and programming.
Mahwah, NJ: Lawrence Erlbaum.
Caldwell, S. D., Herold, D. M., & Fedor, D. B. 2004. Toward an understanding of the relationships among organizational change, individual differences, and changes in person-environment fit: A cross-level study. Journal of
Applied Psychology, 89: 868-882.
Cacioppo, J. T., Gardner, W. L., & Berntson, G. G. 1997. Beyond bipolar conceptualizations and measures: The
case of attitudes and evaluative space. Personality and Social Psychology Review, 1: 3-25.
Choi, J. N. 2007. Change-oriented organizational citizenship behavior: Effects of work environment characteristics
and intervening psychological processes. Journal of Organizational Behavior, 28: 467-484.
Clogg, C. C., & Shihadeh, E. S. 1994. Statistical models for ordinal variables. Thousand Oaks, CA: Sage.
Cohen, J. 1988. Statistical power analysis for the behavioral sciences. New York: Lawrence Erlbaum.
Coyle-Shapiro, J. 1999. Employee participation and assessment of an organizational change intervention: A threewave study of total quality management. Journal of Applied Behavioral Science, 35: 439-456.
Coyle-Shapiro, J. 2002. Changing employee attitudes: The independent effects of TQM and profit sharing on continuous improvement orientation. Journal of Applied Behavioral Science, 38: 57-77.
Coyle-Shapiro, J. A. M., Shore, L. M., Taylor, M. S., & Tetrick, L. E. (Eds.). 2004. The employment relationship:
Examining psychological and contextual perspectives. Oxford, UK: Oxford University Press.
Cropanzano, R., & Mitchell, M. S. 2005. Social exchange theory: An interdisciplinary review. Journal of Management,
31: 874-900.
Dawson, P. 2003. Understanding organizational change. Thousand Oaks, CA: Sage.
De Vos, A., Buyens, D., & Schalk, R. 2003. Psychological contract development during organizational socialization: Adaptation to reality and the role of reciprocity. Journal of Organizational Behavior, 24: 537-559.
Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D. 1986. Perceived organizational support. Journal of
Applied Psychology, 71: 500-507.
Elias, S. M. 2009. Employee commitment in times of change: Assessing the importance of attitudes toward organizational change. Journal of Management, 35: 37-55.
Fedor, D. B., Caldwell, S. D., & Herold, D. M. 2006. The effects of organizational changes on employee commitment: A multilevel investigation. Personnel Psychology, 59: 1-29
Frese, M., & Fay, D. 2001. Personal initiative: An active performance concept for work in the 21st century.
Research in Organizational Behavior, 23: 133-187.
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1691
Gagnon, M., Jansen, K., & Michael, J. H. 2008. Employee alignment with strategic change: A study of strategysupportive behavior among blue collar employees. Journal of Managerial Issues, 20: 425-443.
George, J. M., & Jones, G. R. 2000. The role of time in theory and theory building. Journal of Management, 26:
657-684.
Gioia, D. A., & Chittipeddi, K. 1991. Sensemaking and sensegiving in strategic change initiation. Strategic
Management Journal, 12: 433-448.
Glew, D. J., O’Leary-Kelly, A. M., Griffin, R. W., & Van Fleet, D. D. 1995. Participation in organizations: A review
of the issues and proposed framework for future analysis. Journal of Management, 21: 395-421.
Golembiewski, R. T. 2000. Success rates in planned change: Five aspects of an optimistic diagnosis. In R. T. Golembiewski
(Ed.), Handbook of organizational consultation (2nd ed.): 535-542. New York: Marcel Dekker.
Goodman, P. S. 2000. Missing organizational linkages: Tools for cross-level research. Thousand Oaks, CA: Sage.
Gouldner, A. W. 1960. The norm of reciprocity: A preliminary statement. American Sociological Review, 25:
161-178.
Griffin, M. A., Neal, A., & Parker, S. K. 2007. A new model of work role performance: Positive behavior in uncertain and interdependent contexts. Academy of Management Journal, 50: 327–347.
Groves, R. M., Dillman, D. A., Eltinge, J. L., & Little, R. J. A. 2002. Survey nonresponse. New York: John Wiley.
Harigopal, K. 2006. Management of organizational change: Leveraging transformation (2nd ed.). New Delhi:
Response Books.
Harwell, M. R., & Gatti, G. G. 2001. Rescaling ordinal data to interval data in educational research. Review of
Educational Research, 71: 105-131.
Henderson-Ioney, J. 1996. Shared leadership: A new model for a next century. Non-profit World, 14: 40-44.
Herscovitch, L., & Meyer, J. P. 2002. Commitment to organizational change: Extension of a three component
model. Journal of Applied Psychology, 87: 474-487.
Hodgkinson, G. P., & Healey, M. P. 2008. Cognition in organizations. Annual Review of Psychology, 59:
387-417.
Iverson, R. D. 1996. Employee acceptance of organizational change: The role of organizational commitment.
International Journal of Human Resource Management, 7: 122-149.
Jaccard, J., & Turrisi, R. 2003. Interaction effects in multiple regression (2nd ed.). Thousand Oaks, CA: Sage.
Jansen. K. J. 2004. From persistence to pursuit: A longitudinal examination of momentum during the early stages
of strategic change. Organization Science, 15: 276-294.
Jimmieson, N. L., Peach, M., & White, K. M. 2008. Utilizing the theory of planned behavior to inform change
management: An investigation of employee intentions to support organizational change. Journal of Applied
Behavioral Science, 44: 237-262.
Jimmieson, N., Terry, D., & Callan, V. 2004. A longitudinal study of employee adaptation to organizational change:
The role of change-related information and change-related self-efficacy, Journal of Occupational Health
Psychology, 9: 11-27.
Judge, T. A., Thoresen, C. J., Pucik, V., & Welbourne, T. M. 1999. Managerial coping with organizational change:
A dispositional perspective. Journal of Applied Psychology, 84: 107-122
Kahneman, D., & Tversky, A. 1979. Prospect theory: An analysis of decision under risk. Econometrica, 47:
263-291.
Kline, R. 2004. Principles and practice of structural equation modeling (2nd ed.). New York: Guilford.
Konovsky, M. A., & Pugh, S. D. 1994. Citizenship behavior and social exchange. Academy of Management Journal,
37: 656-669.
Lazarus, R. S., & Folkman, S. 1984. Stress, appraisal, and coping. New York: Springer.
Levinson, H. 1965. Reciprocation: The relationship between man and organization. Administrative Science Quarterly,
9: 370-390.
Lewin, K. 1951. Field theory in social science. New York: Harper & Row.
Lippit, R., Watson, J., & Westley, B. 1958. The dynamics of planned change. New York: Harcourt Brace.
Lord, R. G., & Levy, P. E. 1994. Moving from cognition to action: A control theory perspective. Applied Psychology:
An International Review, 43: 335-367.
Louis, M. R., & Sutton, R. I. 1991. Switching cognitive gears: From habits of mind to active thinking. Human
Relations, 44: 55-76.
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
1692 Journal of Management / November 2011
Madsen, S. R., Miller, D., & John, C. R. 2005. Readiness for organizational change: Do organizational commitment and social relationships in the workplace make a difference? Human Resource Development Quarterly,
16: 213-234.
McIver, J. P., & Carmines, E. G. 1981. Unidimensional scaling. Thousand Oaks, CA: Sage.
Meyer, J. P., Srinivas, E. S., Lal, J. B., & Topolnytsky, L. 2007. Employee commitment and support for an organizational change: Test of the three-component model in two cultures. Journal of Occupational and Organizational
Psychology, 80: 185-211.
Miller, D. 2002. Successful change leaders: what makes them? What do they do that is different? Journal of Change
Management, 2: 359-368.
Miller, V. D., Johnson, J. R., & Grau, J. 1994. Antecedents to willingness to participate in a planned organizational
change. Journal of Applied Communication Research, 22: 59-80.
Morrison, E. W., & Phelps, C. C. 1999. Taking charge at work: Extrarole efforts to initiate workplace change.
Academy of Management Journal, 42: 403-419.
Mowday, R. T., Porter, L. W., & Steers, R. M. 1982. Employee–organization linkages—The psychology of commitment, absenteeism, and turnover. New York: Academic Press.
Neubert, M. J., & Cady. S. H. 2001. Program commitment: A multi-study of its impact and antecedents. Personnel
Psychology, 54: 421-448.
Nurick, A. J. 1985. Participation in organizational change. New York: Praeger.
Organ, D. W. 1990. The motivational basis of organizational citizenship behavior. Research in Organizational
Behavior, 12: 43-72.
Peach, M., Jimmieson, N. L., & White, K. M. 2005. Beliefs underlying employee readiness to support a building
relocation: A theory of planned behavior perspective. Organization Development Journal, 23: 9-22.
Pettigrew, A. M., Woodman, R. W., & Cameron, K. S. 2001. Studying organizational change and development:
Challenges for future research. Academy of Management Journal, 44: 697-713.
Piderit, S. K. 2000. Rethinking resistance and recognizing ambivalence: A multidimensional view of attitude toward
an organizational change. Academy of Management Review, 25: 783-794.
Podsakoff, P. M., MacKenzie, S. B., Pain, J. B., & Bachrach, D. G. 2000. Organizational citizenship behaviors: A critical review of the theoretical and empirical literature and suggestions for future research. Journal of Management,
26: 513-563.
Pulakos, E. D., Arad, S., Donovan, M. A., & Plamondon, K. E. 2000. Adaptability in the workplace: Development
of a taxonomy of adaptive performance. Journal of Applied Psychology, 85: 612-624.
Rhoades, L., & Eisenberger, R. 2002. Perceived organizational support: A review of the literature. Journal of
Applied Psychology, 87: 698-714.
Robinson, S. L. 1996. Trust and breach of the psychological contract. Administra­tive Science Quarterly, 41: 574-599.
Robinson, S. L., Kraatz, M. S., & Rousseau, D. M. 1994. Changing obligations and the psychological contract: A
longitudinal study. Academy of Management Journal, 37: 137-152.
Robinson, S. L., & Morrison, E. W. 1995. Psychological contracts and OCB: The effect of unfilled obligations on
civic virtue behavior. Journal of Organiza­tional Behavior, 16: 289-298.
Rousseau, D. M. 1995. Psychological contracts in organizations: Understanding written and unwritten agreements.
Thousand Oaks, CA: Sage.
Rousseau, D. M. 2001. Schema, promise and mutuality: The building blocks of the psychological contract. Journal
of Occupational and Organizational Psychology, 74: 511-541.
Rousseau, D. M., & Tijoriwala, S. A. 1999. What’s a good reason to change? Motivated reasoning and social
accounts in promoting organizational change. Journal of Applied Psychology, 84: 514-528.
Schalk, R., & Freese, C. 2000. The impact of organizational changes on the psychological contract and attitudes
towards work in four health care organizations. In K. Isaksson, C. Hogstedt, C. Eriksson, & T. Theorell (Eds.),
Health effects of the new labour market: 129-143. New York: Kluwer Academic/Plenum.
Shore, L. M., Tetrick, L. E., Lynch, P., & Barksdale, K. 2006. Social and economic exchange: Construct development and validation. Journal of Applied Social Psychology, 36: 837-867.
Sims, H. P., & Gioia, D. A. (Eds.) 1986. The thinking organization. San Francisco: Jossey-Bass.
Spector, P. E. 1986. Perceived control by employees: A meta-analysis of studies concerning autonomy and participation at work. Human Relations, 39: 1005-1016.
Downloaded from jom.sagepub.com at Korea University on October 27, 2011
Kim et al. / Change-Supportive Behavior 1693
Strauss, G. 1998. An overview. In F. Heller, E. Pusic, G. Strauss, & B. Wilpert (Eds.), Organizational participation:
Myth and reality: 8-39 Oxford, UK: Oxford University Press.
Van de Ven, A. H., & Poole, M. S. 1995. Explaining development and change in organizations. Academy of Management
Review, 20: 510-540.
Van Dyne, L., & LePine, J. A. 1998. Helping and voice extra-role behaviors: Evidence of construct and predictive
validity. Academy of Management Journal, 41: 108-119.
Vroom, V. H. 1964. Work and motivation. New York: John Wiley.
Wagner, J. A., III. 1994. Participation’s effects on performance and satisfaction: A reconsideration of research evidence. Academy of Management Review, 19: 312-330.
Wanberg, C. R., & Banas, J. T. 2000. Predictors and outcomes of openness to change in a reorganizing workplace.
Journal of Applied Psychology, 85: 132-142.
Weber, W. G., Unterrainer, C., & Schmid, B. E. 2009. The influence of organizational democracy on employees’
socio-moral climate and prosocial behavioral orientations. Journal of Organizational Behavior, 30: 1127-1149.
Wei, L. J., & Cowan, C. D. 1988. Selection bias. In N. L. Johnson & S. Kotz (Eds.), Encyclopedia of statistical
sciences (Vol. 8): 332-334. New York: John Wiley.
Weick, K. E. 1995. Sense making in organization. Thousand Oaks, CA: Sage.
Weick, K. E. 2001. Organizational redesign as improvisation. In K. E. Weick, Making sense of the organization:
57-91. Malden, MA: Blackwell Press.
Weick, K. E., & Quinn, R. E. 1999. Organizational change and development. Annual Review of Psychology, 50:
361-386.
Wong, P. T .P., & Weiner, B. 1981. When people ask “why” questions, and the heuristics of attribution search.
Journal of Personality and Social Psychology 40: 649-663.
Wooldridge, J. M. 2002. Econometric analysis of cross section and panel data. Cambridge, MA: MIT Press.
Downloaded from jom.sagepub.com at Korea University on October 27, 2011