A R T I C L E S
Resistance, Justice, and
Commitment to Change
Rex D. Foster
This research focused on individual responses to organizational change by
exploring the relationships among individual resistance, organizational jus-
tice, and commitment to change following organizational change implemen-
tations in three organizations. To accomplish this, Web-based questionnaires
were used to gather individual-level quantitative data from 218 employees
within three organizations located in the United States. The previously vali-
dated measures used included Oreg’s (2003) resistance to change scale,
Colquitt’s (2001) four-factor organizational justice scale, and the Herscovitch
and Meyer (2002) commitment to change scale. The survey data were ana-
lyzed with the use of structural equation modeling to test for relationships
among constructs, and results demonstrated that organizational justice was
strongly associated with commitment to organizational change, the strongest
relationship being between procedural justice and affective commitment to
change. In addition, resistance to change was not significantly related to jus-
tice or commitment to change. These findings on resistance to change support
recent conceptual arguments that conventional views of resistance to change
are not useful for informing organizational change implementation efforts.
Change is a phenomenon that individuals and organizations face on a daily
basis, and because of this, questions about its nature and about responses to
change continuously emerge. In addition, the difficulties associated with under-
standing change have contributed to many failed change efforts that can cost
organizations a great deal of time, money, and other resources (Kotter, 1995).
The overarching aim of this research was to investigate the nature of individual
responses to change in hopes of contributing to a better understanding of how
organizations can make change efforts more successful. More specifically, this
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research explored the relationships among resistance to change and organiza-
tional justice as determinants of individual commitment to change.
Whereas past research on justice and organizational change has focused
largely on change outcomes, such as layoffs and turnover (Brockner et al., 1994;
Daly & Geyer, 1994; Kickul, Lester, & Finkl, 2002; Paterson, Green, & Cary,
2002), this study focused on individual commitment to change. Additionally,
past studies of commitment have focused primarily on outcomes of commit-
ment to an organization (e.g., Meyer & Allen, 1991, 1997), whereas this study
examined resistance to change and organizational justice as antecedents of
commitment to change. There are well-established bodies of literature related
to organizational change, organizational justice, and organizational commit-
ment, but there are very few studies examining the individual nature of com-
mitment to organizational change (Meyer, Srinivas, Lal, & Topolnytsky, 2007).
As organizations strive to remain as effective and efficient as possible,
change initiatives are essential and ongoing. Ironically, change efforts often stir
up unforeseen challenges, and employee responses to changes ultimately deter-
mine whether the change efforts succeed or fail. Organizational change and
resistance to change have traditionally been examined at an organizational level
of analysis; however, several authors have noted the need for studies to exam-
ine change at the individual level of analysis (e.g., Herscovitch & Meyer, 2002;
Judge, Thoreson, Pucik, & Welbourne, 1999; Wanberg & Banas, 2000). Many
have also argued that individual commitment to change is a necessary compo-
nent in garnering support for planned organizational change efforts (Armenakis &
Bedeian, 1999; Judge et al., 1999; Klein & Sorra, 1996; Kotter, 1995). Accord-
ing to Klein and Sorra (1996), commitment is central to effective innovation
implementation. Armenakis and Bedeian (1999) also emphasized commitment in
their framework of successful organizational change, noting that commitment is
clearly a relevant criterion variable to be considered in change implementation.
In addition to the importance of commitment, there is a need to under-
stand more about the complexities of individual response to change associated
with resistance to change (Dent & Goldberg, 1999; Lines, 2005). Piderit
(2000) pointed out that many studies of change have oversimplified individ-
ual responses, often dichotomizing them as either altogether negative or pos-
itive. In an effort to deepen understanding and to move away from a
dichotomous framework of individual response to change, this study embraced
a multidimensional conceptualization.
Organizational justice was examined in this study because it has been
shown to be predictive of higher levels of openness to change, acceptance of
change, cooperation with change, and satisfaction with change (Blader & Tyler,
2005; Greenberg, 1994; Wanberg & Banas, 2000). In addition, justice plays
a significant role in many organizational dynamics related to change, such
as leader–follower relationships (Meindl, 1989), organizational citizenship
behavior (Moorman, 1991), and individual response to change (Greenberg,
1994). Organizational justice is also relevant because it shares many of the
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philosophical underpinnings of human resource development (HRD), and
more specifically of organization development (OD) (Wooten & White, 1999).
French and Bell (1999) and McLean (2006) specifically highlighted the impor-
tance of democratic and humanistic values in OD. HRD research and practice
can benefit from a better understanding of individual response to change
because this knowledge can inform individual development efforts, system
improvement efforts, and organizational interventions related to helping
change succeed.
The purpose of this study was to gain a better understanding of individ-
ual response to organizational change and to learn more about what compo-
nents of change implementation relate to successful organizational change.
This was accomplished by examining the relationships between resistance,
organizational justice, and commitment to change. The research question for
this study asked, “What are the relationships among the factors of employee
resistance, employee perceptions of organizational justice, and commitment to
change?”
This study has practical significance because the results have implications
for HRD scholars and practitioners in the planning and implementation of orga-
nizational-change–related initiatives. As stated by Swanson and Holton (2001),
“change has been a central concept in HRD since its origins” (p. 285). Because
HRD scholars and practitioners constantly deal with change efforts, further
knowledge of how individuals respond to change can inform HRD activities
such as training programs and OD interventions. Another practical contribu-
tion of this study includes implications for employee–employer relationships.
For example, organizations, leaders, and employees can all benefit from
increased awareness and application of fairness (i.e., justice) in the workplace.
By examining the relationships between resistance, justice, and commit-
ment to change, this study also contributes to the theoretical knowledge of
individual response to change. As noted by Piderit (2000), Herscovitch and
Meyer (2002), and Judge et al. (1999), there is a need to have a better under-
standing of organizational change from the individual perspective. This study
is significant to the study of resistance because it used Oreg’s (2003) four-
dimensional conceptualization rather than often-used dichotomous conceptu-
alizations. Studying resistance to change alongside commitment to change also
offered insights into the nature of each of these constructs. Although some
might consider resistance and commitment to change as opposites, this study
aimed to illuminate the complexity of each by identifying the relationships
existing among the various dimensions. Commitment to change as presented
by Herscovitch and Meyer (2002) allows understanding of how an individual
is committed to the change (i.e., affective, continuance, normative).
Conceptualizing Organizational Change. Organizational change has been
studied from many perspectives with the use of many methods. In their review
of organizational change theory and research, Armenakis and Bedeian (1999)
identified five themes common to change efforts: (a) content issues, which deal
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with the substance and nature of a particular change; (b) contextual issues,
which deal with forces and conditions existing in an organization’s internal and
external environments; (c) process issues, which deal with the actions taken in
the implementation of an intended change; (d) criterion issues, which deal with
outcomes assessed in organizational change efforts; and (e) affective and behav-
ioral reactions to change. Each of these five themes can be used to frame
research and theory, and each has strengths and weaknesses. This study
focused primarily on aspects of change that are captured by the Armenakis and
Bedeian process and affective and behavioral reactions themes.
Resistance to change, justice, and commitment to change can each be
thought of as having process and affective/behavioral components. First, Oreg’s
(2003) measures of resistance to change were designed to capture cognitive,
affective, and behavioral components of resistance to change disposition, and
resistance to change is also a major consideration in many conceptualizations
of the change implementation process (e.g., Jaffe, Scott, & Tobe, 1994; Judson,
1991; Lewin, 1951). Second, Colquitt’s (2001) measures of organizational jus-
tice assess perceptions of the change process (i.e., procedural justice), and per-
ceptions of treatment during the change process (i.e., interpersonal justice).
Third, the Herscovitch and Meyer (2002) measures of commitment to change
specifically measure affective commitment to change (as well as continuance
and normative commitment to change).
Many models of change implementation exist (e.g., Armenakis, Harris, &
Field, 1999; Burke & Litwin, 1992; Judson, 1991; Kotter, 1995); yet reviews by
Armenakis and Bedeian (1999) and Weick and Quinn (1999) were quick to note
that under the surface, many change models have roots in Lewin’s three-phase
conceptualization of change. Lewin’s (1951) conceptualization includes unfreez-
ing, moving, and refreezing. Resistance to change, justice, and commitment are
all concepts that appear in several of the mentioned change implementation
models. In Lewin’s terms, resistance to change is typically included as part of the
unfreezing phase, justice is typically a component of the unfreezing or moving
phases, and commitment is typically a component of the refreezing phase. The
following section includes a review of Lewin’s theory and related issues, as well
as summaries of other well-known change implementation models.
In Lewin’s (1951) field theory, behavior is conceptualized as taking place
in a field in which there are many forces. Within this field, behavior is dis-
cussed as a function of the interaction between a person and the environment,
or in mathematical terms, B
f(P, E), where B behavior, P person, and
E
environment. The forces within the field are psychological in nature,
and because they differ, tension is created. Some forces act to maintain the sta-
tus quo, whereas others promote change. One common way to represent this
phenomenon is through a force field analysis. When the forces are equal, the
field is in a state of what Lewin called quasistationary social equilibrium; how-
ever, when the equilibrium is interrupted, change, or movement from the status
quo, takes place. On the individual level, the field is considered an individual’s
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life space, and this concept also applies at other levels, such as the group or
the organization. Regardless of the level, a particular field and the forces within
it are constantly changing, and how a change unfolds depends on the specific
forces at that point in time.
Lewin (1951) pointed out that, in order for change to occur, it is easier
and more effective to reduce the forces maintaining the status quo than it is to
increase the forces driving change. Additionally, a strong initial force is required
to unfreeze the system. After this, the equilibrium point must move (move-
ment), and then the new state of equilibrium must be reinforced through some
process of refreezing. The Armenakis and Bedeian (1999) review of the change
literature outlined some conceptualizations of the change process as related to
Lewin’s (1951) three-stage model. Parallels that Armenakis and Bedeian (1999)
noted between Lewin’s model and other models of change included:
(a) unfreezing corresponds with readiness and resistance to change, (b) mov-
ing corresponds with adoption and exploration, and (c) refreezing corresponds
with commitment and institutionalization.
Unfreezing is the first of the three steps in the change process, and it
requires some change in the forces acting to maintain equilibrium. This can
result from the reduction of forces that resist change, or by increasing forces
that favor change. Lewin (1951) also noted that this stage is complex because
it is influenced by inner resistance to change, which is related to social habits,
customs, and group dynamics.
Often a force from an external source can cause individuals or groups to
unfreeze, which can then lead to change. Lewin emphasized group dynamics
in his discussion of change because groups often hold to norms and standards
to which individuals abide, and these serve as psychological forces maintain-
ing the status quo. For example, an individual might be reluctant to act out-
side of the group norms for fear of rejection or punishment.
In models of change implementation, unfreezing has been conceptualized
and operationalized in many different ways. Kotter (1995) included stages that
correspond with unfreezing, including: (a) establishing a sense of urgency,
(b) forming a coalition of individuals who embrace and support the change,
and (c) creating a vision of change success. Judson (1991) also included stages
that correspond to unfreezing; they are labeled analyzing and planning the
change, and communicating the change. Judson also explained that resistance
to change is likely to occur, and suggested techniques such as bargaining and
the use of alternative forms of media to aid in the unfreezing process.
Resistance to change is a concept that is commonly discussed in conjunc-
tion with the unfreezing stage of Lewin’s (1951) change model (Armenakis &
Bedeian, 1999). Typically portrayed as a negative barrier to change (Dent &
Goldberg, 1999), resistance to change is often defined with Lewin’s physics-
related terminology, as a restraining force acting to maintain the current state
of equilibrium (i.e., status quo). A more detailed discussion of resistance to
change is presented later in this article.
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Another important concept related to unfreezing is readiness for change
(Armenakis, Harris, & Mossholder, 1993). Armenakis et al. (1993) defined
readiness as the “cognitive precursor to the behaviors of either resistance to,
or support for, a change effort” (p. 682). They also argued that change agents
play the primary role of creating readiness for change through the message for
change, that should incorporate five components: (a) discrepancy (need to
change), (b) self-efficacy (have the capability to change), (c) personal valence
(in our best interest to change), (d) principal support (those affected are behind
the change), and (e) appropriateness (desired change fits the organization)
(Armenakis et al., 1999). Although readiness for change is related to the con-
cepts in this study, organizational justice and resistance to change were used
to measure individual “cognitive precursors.” Furthermore, Armenakis and
Harris (2002) suggested that organizational justice should inform readiness
efforts.
Movement is the stage in which the actual change takes place, be it at the
individual, group, or organizational level. Movement can relate to a variety
of outcomes, such as behaviors, values, attitudes, structures, or processes
(Cummings & Worley, 2005). In this stage, a shift in the forces changes the
equilibrium point away from the status quo. In change implementation mod-
els, movement has been conceptualized as changing from the status quo to the
desired state (Judson, 1991) and changing structures, systems, policies, and
procedures that are not consistent with the vision (Kotter, 1995).
Refreezing is the third phase in Lewin’s theory and must occur in order for
the results of a change effort to endure. This is necessary because refreezing
secures the new state of equilibrium that prevents movement back toward the
status quo. This can be accomplished by the establishment of new norms or
by other mechanisms that create and maintain forces that support the new
equilibrium level. For example, this could involve institutionalizing adjust-
ments that have been made in regard to organizational culture, structure, or
policies (Cummings & Worley, 2005).
Most models of change implementation include a stage that corresponds
to refreezing. For example, Kotter (1995) included components that address
the need to change organizational structures, systems, procedures, and poli-
cies, as well as the need to institutionalize new approaches associated with
change efforts. Another well-known organizational change model that
addresses refreezing is the Burke-Litwin (1992) model, which includes both
transformational and transactional dynamics of change. Transformational
components related to refreezing include culture, mission, and strategy; and
transactional components include management practices, structure, systems,
and skills. Some authors specifically mention the importance of employee
commitment in carrying out successful change efforts (Armenakis et al., 1999;
Klein & Sorra, 1996; Kotter, 1995); however, few studies have examined what
variables are related to establishing commitment to change, which is
addressed in this study.
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In summary, organizational change and its different components have
been conceptualized, operationalized, and studied in many ways. This study
took an individual-level perspective of change implementation, which has tra-
ditionally been conceptualized following Lewin’s (1951) three-stage theory. For
more information on perspectives of organizational change, see reviews by
Armenakis and Bedeian (1999), Van de Ven and Poole (1995), and Weick and
Quinn (1999).
Overview of Resistance to Change. The use of the term resistance to change
gained popularity in the 1950s and 1960s following Lewin’s (1951) work on
field theory. Since that time, resistance to change has been generally accepted
as a part of the change process, and is included in many OD, management, and
organizational behavior texts. Recently, however, some have highlighted that
many accepted ideas about resistance to change are neither true to Lewin’s orig-
inal ideas, nor useful for informing change implementation (e.g., Dent &
Goldberg, 1999; Ford, Ford, & D’Amelio, 2008; Oreg, 2003; Piderit, 2000).
The following sections summarize the literature addressing resistance to
change. First, works that take a traditional approach to resistance to change
are summarized, and then works that call for resistance to change to be con-
ceptually reframed are presented.
In their classic study, Coch and French (1948) examined the question “Why
do people resist change so strongly?” In order to measure this, they conceptual-
ized resistance to change as a dichotomous behavioral variable. Desirable/
compliant behaviors were interpreted as nonresistant, and nondesirable behav-
iors were interpreted as resistant—employees were either compliant or resistant.
Coch and French then devoted a considerable portion of their discussion to
employee participation (e.g., group planning meetings) as a suggested method
for preventing resistance to change. This 1948 study had great influence on
many subsequent discussions of change implementation problems. Lawrence
(1954) also made several important contributions to the resistance literature in
an early conceptual article. Critiquing Coch and French, Lawrence argued that
participation is an oversimplified solution to resistance, and that attaining
employee perceptions of participation would be a complex endeavor. Another
key observation from Lawrence was that change has both technical and social
characteristics—with a lack of attention to the social characteristics that often
end up causing resistance to change. Lawrence went on to explain that attitudes
play a significant role in how managers think about resistance to change, and
that expecting resistance from employees often leads to just that. In order to
combat such negative thinking, he suggested that managers begin thinking of
resistance to change as a useful signal that something is going wrong.
Other scholars have conceptualized resistance to change as an emotional
reaction rather than a behavioral one. For example, Argyris and Schon (1978)
discussed resistance in terms of defensive routines and frustration, and Kanter
(1985) described feelings of uncertainty and loss of control in understanding
responses to change. These ideas were important contributions to the resistance
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to change literature because they expanded conventional perceptions of how
resistance to change could be conceptualized. In contrast to one-dimensional
conceptualizations of resistance to change, Piderit (2000) argued that resistance
toward change could be better understood if conceptualized as multidimen-
sional, thus accounting for the possibility of ambivalence toward change. Piderit
noted that resistance to change has been conceptualized as undesirable behav-
iors in response to change (Coch & French, 1948), as emotional frustration or
anxiety expressed through defensive routines (Argyris & Schon, 1978), and as
cognitive resistance to change shown through thought patterns or unreadiness
(Armenakis et al., 1993). In response to shortcomings with existing conceptu-
alizations, Piderit proposed a tripartite, attitudinal model of resistance to change
that includes three components: (a) emotional (affective), (b) intentional (behav-
ioral), and (c) cognitive. This perspective allows for a fuller understanding of
how employees respond to change than is possible with unidimensional per-
spectives. For example, an individual might desire to act in accordance with a
change effort, but also feel that the change conflicts with his/her ethics or with
his/her knowledge of day-to-day work. The result of these mixed feelings is
what Piderit referred to as ambivalence.
Dent and Goldberg (1999) claimed that the term resistance to change has
taken on a meaning inconsistent with Lewin’s (1951) original conceptualiza-
tion, and that the current mental framework of resistance to change is flawed.
Lewin (1951) conceptualized resistance to change as a phenomenon that is
affected by any number of forces existing within a system, whereas many
authors discuss resistance to change as a phenomenon that exists only in
humans, and particularly in subordinate employees (Dent & Goldberg, 1999).
Rather than assuming that resistance exists within subordinate employees,
which could result in a self-fulfilling prophecy, Dent and Goldberg suggested
that change efforts should begin with an understanding of the knowledge and
attitudes of employees. Dent and Goldberg also pointed out reactions to the way
a change is introduced or to unrealistic expectations might be perceived by
managers as employee resistance to change, when, in fact, it is the actions of the
managers that are problematic. Kotter’s (1995) extensive research and observa-
tion dealing with organizational change supported this notion by reporting that
overt, malicious, or intentional resistance to change was extremely rare. In fact,
employees in lower levels of an organization may indeed be eager to make
changes, but might find resistance to change in superiors. This approach to
resistance takes a worker-based perspective as opposed to a more traditional
manager-based perspective. In this study resistance to change refers to an indi-
vidual’s dispositional inclination to resist changes (Oreg, 2003).
Resistance to Change and Commitment to Change. There are few stud-
ies that have examined resistance to change and commitment to change as
done in this study, although some prior studies have investigated related ideas
(e.g., Oreg, 2006; Wanberg & Banas, 2000). In some of the initial studies on
the four-dimensional model of resistance to change, Oreg (2003) found that
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resistance tendencies were strongly associated with affective reactions to
change (B
0.52), which suggests a relationship with affective commitment
to change. Another study ( Judge et al., 1999) found that tolerance for ambi-
guity and positive affectivity are strongly related to coping with change (both
relationships, r
0.69). In addition to suggesting a relationship between
resistance and commitment to change, these findings offer further support for
the notion that resistance and commitment to change are complex and nondi-
chotomous.
In this study, commitment to change refers to “a force (mind-set) that binds
an individual to a course of action deemed necessary for the successful imple-
mentation of a change initiative” (Herscovitch & Meyer, 2002, p. 475). Addi-
tionally, according to Herscovitch and Meyer this mind-set is made up of
affective commitment to change, continuance commitment to change, and nor-
mative commitment to change. Affective commitment to change is a desire to pro-
vide support for the change based on a belief in its inherent benefits,
continuance commitment to change is a recognition that there are costs associated
with failure to provide support for the change, and normative commitment to
change is a sense of obligation to provide support for the change. Meyer and
Allen (1997) pointed out that individuals with strong organizational continu-
ance commitment are unlikely to leave an organization. This characteristic
bears resemblance to Oreg’s (2003) cognitive rigidity, routine seeking, and
short-term thinking because they each involve a desire to maintain the current
situation. For example, according to Oreg, individuals who engage in short-
term thinking might resist change because they dislike the difficult adjustments
required at the beginning of the change.
In addition, Meyer, Allen, and Smith (1993) found that affective commit-
ment was positively related to an individual’s voice (willingness to suggest
improvements). Oreg’s (2003) discussion of resistance to change illustrated
that an individual who demonstrates routine seeking would direct energy
toward maintaining current conditions and that an individual who demon-
strates cognitive rigidity is not inclined to change his/her thinking patterns.
Affective commitment to change is developed through means such as individ-
ual voice (e.g., during organizational change implementation); participation in a
change, training and development; or identification with a cause (Herscovitch &
Meyer, 2002; Meyer & Allen, 1997). These actions represent examples that
involve a degree of initial effort, with the ultimate goal being some sort of
future benefit (e.g., successful implementation of an organizational change).
On the other hand, Oreg’s short-term thinking reflects the extent to which an
individual avoids initial discomforts (which might be associated with an orga-
nizational change) regardless of potential long-term benefits. Continuance
commitment to change measures the extent to which individuals commit to a
course of action based on mental calculations of perceived costs (Herscovitch &
Meyer, 2002; Meyer & Herscovitch, 2001). Similarly, routine seeking
and short-term thinking are both characteristics associated with sticking to a
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particular course of action (i.e., resisting a change) because the alternatives are
less appealing.
Based on the preceding discussion, it is expected that individual resistance
to change will relate to commitment to change as follows:
H
YPOTHESIS
1
A
:
Employees’ dispositional resistance to change will be negatively
related to affective commitment to change.
H
YPOTHESIS
1
B
:
Employees’ dispositional resistance to change will be negatively
related to continuance commitment to change.
H
YPOTHESIS
1
C
:
Employees’ dispositional resistance to change will be negatively
related to normative commitment to change.
Organizational Justice and Commitment to Change. Organizational jus-
tice refers to individual perceptions of fairness within organizations. Fairness
(procedural justice) has been shown to influence organizational commitment
positively (B
0.29; Folger & Konovsky, 1989), and it is reasonable to con-
sider that individuals would demonstrate commitment when they are treated
fairly. For example, Greenberg (1994) demonstrated that employees were more
committed to a smoking ban when treated fairly. Specifically, employees were
more likely to accept the smoking ban when they received more thorough and
accurate information (informational justice), and when the information was
delivered in a sensitive manner (interpersonal justice).
Four aspects of organizational justice were examined in this study, includ-
ing distributive justice, procedural justice, interpersonal justice, and informa-
tional justice (Colquitt, 2001). Distributive justice is defined as “the perceived
fairness of the outcomes or allocations that an individual receives” (Folger &
Cropanzano, 1998, p. xxi); procedural justice is defined as “the fairness issues
concerning the methods, mechanisms, and processes used to determine
outcomes” (Folger & Cropanzano, 1998, p. 26); interpersonal justice refers to
respectful, proper, and/or appropriate treatment of individuals and the extent
to which actions are perceived as such (Bies & Moag, 1986; Greenberg, 1993);
and informational justice addresses whether information is timely, accurate, ade-
quate, and whether it offers explanations for decisions (Bies & Moag, 1986;
Greenberg, 1993).
Meyer and Herscovitch (2001) pointed out that involvement with the spec-
ified target (e.g., implementation of a change effort) leads to affective commit-
ment. By definition, procedural justice addresses involvement, and Folger and
Konovsky (1989) found a positive relationship between involvement and com-
mitment. A connection between justice and normative commitment can also
be drawn from Meyer and Allen (1991), who found that, when individuals
receive a benefit, they might feel a need to reciprocate. This specifically relates
to the notion of overreward as outlined in Adams’s (1965) equity theory.
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Although some relationships between fairness and commitment are fairly
self-evident, others are more obscure. For example, it might be assumed that
an individual’s response to a planned organizational change is contingent upon
the outcome of the change effort (i.e., successful or not successful). However,
reviews of procedural justice research suggest that justice influences employee
reactions even if outcomes are negative (Brockner et al., 1994; Brockner &
Wiesenfeld, 1996). For example, Brockner et al. (1994) found that regardless
of the outcome of a particular organizational decision, fair treatment resulted
in more favorable employee reactions. This leads to the supposition that jus-
tice will have a positive influence on commitment to change, regardless of the
outcome of the change initiative.
Distributive justice deals with the fairness related to the allocation of out-
comes, such as pay, resources, and recognition (Folger & Cropanzano, 1998).
On a related note, continuance commitment to change deals with the costs an
individual perceives to be associated with being committed to or not being
committed to a change (Herscovitch & Meyer, 2002). If an employee perceives
fairness in the allocation of outcomes, his/her mental equity-based calculations
(Adams, 1965) are less likely to result in a high perceived cost associated with
commitment.
The research question for this study asked, “What are the relationships
among the factors of employee resistance, employee perceptions of organiza-
tional justice, and commitment to change?” With the previously mentioned
considerations in mind, the following relationships are hypothesized:
H
YPOTHESIS
2
A
: Employees’ perceptions of organizational justice will be positively
related to affective commitment to change.
H
YPOTHESIS
2
B
: Employees’ perceptions of organizational justice will be positively
related to continuance commitment to change.
H
YPOTHESIS
2
C
: Employees’ perceptions of organizational justice will be positively
related to normative commitment to change.
Resistance to Change and Organizational Justice. Organizational justice
has been studied in conjunction with numerous organizational phenomena,
many of which relate to conceptualizations of resistance to change. In one
change-related study, Schweiger and DeNisi (1991) found that justice curbed
employee uncertainty and increased perceptions of organizational trustworthi-
ness and honesty. In Lewin’s (1951) terms, both of these studies illustrated that
justice lowered resistance, which helped to unfreeze the system and allow for
a more successful change implementation.
Turnover is another phenomenon that has been examined often in relation
to justice (e.g., Brockner et al., 1994; Daly & Geyer, 1994; Paterson et al., 2002).
Although not typically what one might think of as a planned organizational
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change, turnover can be considered as such, and the findings of these studies are
helpful in thinking about other types of change. Brockner et al. (1994) found
that attention to justice in layoffs led to more favorable employee reactions to
the outcomes. Considering these relationships, the following relationship is
hypothesized:
H
YPOTHESIS
3:
Employees’ dispositional resistance to change will be related to per-
ceptions of organizational justice.
Methods
The following sections present the organizational context, measures, validity,
reliability, and data analysis techniques for this study.
Organizational Context, Participants, and Procedure. Resistance to
change, organizational justice, and commitment to change are relevant in
most work settings, and this study examined these constructs in three U.S.-
based organizations. In order to maximize variance, efforts were made to
obtain participants from various work settings. The organizations participat-
ing in this study were selected based on convenience sampling. The partici-
pating organizations varied in size and industry and included one
biotechnology organization (42 participating employees), one manufacturing
division of a large Fortune 500 organization (100 participating employees),
and one health care system consisting of three hospitals and three outpatient
clinics (700 participating employees). The biotechnology organization spe-
cializes in preclinical research studies to evaluate the safety of medical devices.
In addition, it has undergone three ownership changes within the past 4
years. This study took place within 6 months of the most recent ownership
change. The participating manufacturing organization is a division of a For-
tune 500 company that employs over 25,000. In efforts to improve perfor-
mance, the manufacturing division had recently implemented a performance
improvement system. The health care system had recently gone through a
merger, and the questionnaire was sent to all 700 employees who were a part
of one of the merging entities. According to the CEO of the health care sys-
tem, the merger took place because it was financially beneficial for both orga-
nizations. The questionnaire asked respondents from each of the three
participating organizations to refer to the specific change event described
above as they answered the survey questions. This is similar to the approach
adopted by Herscovitch and Meyer (2002).
The potential respondents for the study held a variety of job roles includ-
ing manufacturing plant workers, nurses, medical staff, administrative staff,
and managers. Out of a total of 842 e-mail invitations sent, 218 individuals
responded for an overall response rate of 26%. Of the 218, 66% were female,
34% were male, and the average age was 41 years. Slightly more than half
(54.7%) of the respondents had at least a 4-year college degree, and 46.3%
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worked at the nonsupervisory level. The average tenure of employment for
respondents was 9.1 years. Table 1 provides more details on the sample.
Measures. A self-administered Web-based questionnaire was used to col-
lect data on the three constructs under investigation in this study: resistance
to change, organizational justice, and commitment to change. All survey items
were adopted from existing multi-item scales used in past research and were
unchanged from the originals. Table 2 outlines the constructs that were mea-
sured by the questionnaire.
In addition to the constructs outlined in Table 2, one question regarding the
nature of the organizational change was asked at the beginning of the question-
naire administered to the health care organization. This is the same method that
was used by Herscovitch and Meyer (2002). This question was originally
included on the questionnaires for all three organizations, but sponsoring man-
agers at the manufacturing and biotechnology organizations requested that this
question be adapted to address specific changes that their organizations had
undergone. The manufacturing organization had recently implemented a new
performance improvement system, and the biotechnology organization had
recently come under new ownership. As a result, respondents in organizations
1 and 3 were referring to the mentioned changes as they completed the ques-
tionnaire. Although organization 2 had recently undergone a merger, employ-
ees were still given the option to refer to any change in their responses.
A review of the responses revealed that the majority of respondents did in fact
refer to the merger in their completion of the questionnaire.
Measuring Resistance to Change. Resistance to change was measured with
the use of the 17-item Resistance to Change Scale (RTCS) developed by Oreg
(2003). The scale consists of four dimensions, including routine seeking, emo-
tional reaction, short-term thinking, and cognitive rigidity. In accordance with
the originally developed items, these items were measured on a 6-point
Likert-type scale ranging from 1 (strongly disagree) to 6 (strongly agree). The pri-
mary aim of the RTCS is to measure an individual’s dispositional inclinations
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Table 1. Demographic Information (N
ⴝ 218)
Female
59.2%
Median age
40–49 years
Median tenure
1–5 years
High school diploma
10 (4.6%)
Some college
34 (15.6%)
Two-year degree/certificate
31 (14.2%)
Four-year college degree
72 (33.0%)
Master’s degree
44 (20.2%)
Other/missing
27 (12.5%)
16
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to resist changes. Examples of the routine-seeking subscale include: “I gener-
ally consider changes to be a negative thing” and “I’d rather be bored than sur-
prised.” Examples of emotional reaction include: “When I’m informed of a
change of plans, I tense up a bit” and “When things aren’t going according to
plan it stresses me out.” Examples of the short-term thinking subscale include:
“Changing plans seems like a real hassle to me” and “I sometimes feel myself
avoiding changes that I know will be good for me.” Examples of cognitive
rigidity include: “I often change my mind” and “My views are very consistent
over time.”
Other studies have measured resistance to change indirectly by using per-
sonality traits or situational measures (Coch & French, 1948; Judge et al.,
1999). For example, the scales used by Judge et al. (1999) were originally
developed for purposes other than measuring resistance to change. However,
Oreg’s (2003) scale was specifically designed to measure individual inclination
to resist change, which is the reason it was selected for this study.
Measuring Organizational Justice. Perceived organizational justice was mea-
sured with items from Colquitt’s (2001) 20-item scale. This scale is composed
of four factors including procedural justice, distributive justice, interpersonal
justice, and informational justice. As originally developed, items were measured
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Table 2. Description of Constructs and Scales Used in this Study
Number of
Construct
Scale/Source of Items
Items
Resistance to change
Routine seeking
Oreg (2003)
5
Emotional reaction
Oreg (2003)
4
Short-term thinking
Oreg (2003)
4
Cognitive rigidity
Oreg (2003)
4
Organizational justice
Distributive justice
Colquitt (2001); Leventhal (1976)
7
Procedural justice
Colquitt (2001); Thibaut & Walker (1975);
4
Leventhal (1980)
Interpersonal justice
Colquitt (2001); Bies & Moag (1986)
4
Informational justice
Colquitt (2001); Bies & Moag (1986);
5
Shapiro, Buttner, & Barry (1994)
Commitment to change
Affective commitment
Herscovitch & Meyer (2002); Meyer &
6
to change
Allen (1991, 1997)
Continuance commitment
Herscovitch & Meyer (2002); Meyer &
6
to change
Allen (1991, 1997)
Normative commitment
Herscovitch & Meyer (2002); Meyer &
6
to change
Allen (1991, 1997)
Total items
55
on a 5-point Likert-type scale ranging from 1 (to a very small extent) to 5 (to a
very large extent).
Other justice scales exist that have anywhere from one to four dimensions,
and that conceptualize justice dimensions differently (e.g., Folger & Konovsky,
1989; Moorman, 1991; Sweeney & McFarlin, 1993). Colquitt’s (2001) scale
was selected for several reasons. First, it draws directly from seminal theoret-
ical works in the justice literature, including Thibaut and Walker (1975),
Leventhal (1980), and Bies and Moag (1986). Second, Colquitt’s scale is con-
structed so that it can be customized to fit specific contexts by adapting the
outcomes. Third, the most recent empirical evidence, including confirmatory
factor analyses (Colquitt & Shaw, 2005), and meta-analysis (Colquitt et al.,
2001), suggested that four dimensions offer the most robust measurement of
justice (Colquitt, 2001).
The distributive justice subscale measures the perceived fairness of the
ratio of inputs (education, knowledge, effort) to outcomes (pay, rewards, sat-
isfaction). Colquitt (2001) designed these items to be customized to each study
depending on the outcomes of interest. In this study the outcomes of interest
were general in nature and were defined as “outcomes received from your
job . . . such as pay, rewards, evaluations, and promotions.” This terminology
was used to describe outcomes because it is in alignment with previous stud-
ies (e.g., Colquitt, 2001), and it was clarified via personal communication
( J. A. Colquitt, personal communication, November 6, 2006). Examples of
distributive justice items include: “Do the outcomes received from your job
reflect the effort you have put into your work?” and “Are the outcomes received
from your job justified, given your performance?”
The procedural justice subscale measures the fairness of organizational
decision making related to issues such as process consistency and the sharing
of unbiased, accurate information. Examples of items include: “Have you been
able to express your views and feelings during the procedures?” and “Have the
procedures been free of bias?”
The interpersonal justice subscale measures the degree to which individ-
uals receive respectful, considerate treatment in the enactment of organiza-
tional procedures. As previously noted, Bies and Moag (1986) identified four
rules for fair interpersonal treatment—truthfulness, justification, respect, and
propriety. Examples of interpersonal justice items include: “Has (he/she)
treated you in a polite manner?” and “Has (he/she) treated you with dignity?”
The informational justice subscale measures whether information given
is timely and adequate. Examples of items include: “Were (his/her) explana-
tions regarding the procedures reasonable?” and “Has (he/she) communicated
details in a timely manner?” On the original instrument, the interpersonal and
informational justice sections are preceded by noting that the items refer to an
“authority figure”; however, feedback from two pilot study participants sug-
gested that this term be clarified. As a result, the wording was modified for this
study to read “authority figure (e.g., a manager, supervisor, leader, etc.).”
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Measuring Commitment to Change. Commitment has been conceptualized
using different measures (e.g., Mowday, Porter, & Steers, 1982; O’Reilly &
Chatman, 1986); however, these efforts were specifically aimed at measuring
organizational commitment. The Herscovitch and Meyer (2002) commitment
to change scale (CTCS) is the only scale the researcher was aware of specifi-
cally designed to measure commitment to change. This 18-item scale measures
three dimensions of commitment to change, including affective, continuance,
and normative. In accordance with the originally developed items, these items
were measured with the use of a 7-point Likert-type scale ranging from 1
(strongly disagree) to 7 (strongly agree) (Herscovitch & Meyer, 2002).
The affective commitment to change subscale measures an individual’s
desire to be committed to a change. This is a psychological conceptualization
that refers to an individual’s emotional attachment or identification with the tar-
get of the commitment (Meyer & Allen, 1991). Example items include: “I believe
in the value of this change” and “This change serves an important purpose.”
The continuance commitment to change subscale measures the perceived
costs associated with a change. Drawing on Becker’s (1960) side-bet theory,
continuance commitment refers to commitment that individuals exhibit
because they perceive that it is more costly to not be committed than it is to
be committed. Example items include: “I have no choice but to go along with
this change” and “I have too much at stake to resist this change.”
The normative commitment subscale measures an individual’s feeling of
obligation toward a change. Individuals might demonstrate normative com-
mitment if they feel that being committed is the right or moral thing to do, or
if they feel that they should be committed. Example items include: “I feel a
sense of duty to work toward this change” and “I do not think it would be right
of me to oppose this change.”
In addition, demographic information was collected at the end of
the questionnaire. Participants were asked to provide their gender, age, tenure
with the organization, level of formal education, and current position in the
organization.
Reliability. To establish reliability of the items measured in this study,
Cronbach’s alpha values were calculated for each of the scales used. Cronbach’s
alpha is a measure of internal consistency—in other words, it measures the
extent to which a respondent answers items in a consistent manner (Gall et al.,
2003). A scale has high reliability when an individual’s responses to the items
within a particular scale are highly correlated. Cronbach’s alpha scores of 0.70
or greater are generally considered to be acceptable (Nunnelly, 1970). Table 3
reports the reliability scores based on previous studies and this study.
As shown in Table 3, the reliability scores for each of the scales used in
this study are in the acceptable range when compared to previous studies.
With the exception of one subscale (cognitive rigidity), the alphas calculated
in this study are all greater than the suggested 0.70. In this study, the alpha
for the original four-item cognitive rigidity scale was 0.66, which was just below
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the acceptable range. This scale also had low reliability in initial validation stud-
ies, but subsequent studies demonstrated acceptable reliability (Oreg, 2003).
Upon further investigation, item analysis revealed that the item “I often change
my mind” (CR1) had a low item–total correlation of 0.18, suggesting that it did
not measure the same phenomenon as other items in the scale. Based on
Hinkin’s (1998) suggestion to discard any items that correlate less than 0.40
with all other items, this item was deleted from analyses. After modification, the
three-item cognitive rigidity scale had a stronger reliability of 0.75.
Validity. An instrument is said to be valid when it measures what it claims
to measure. As presented in this section, the validity of the constructs mea-
sured in this study have all been addressed in previous studies.
Validity of the Organizational Justice Scales. Colquitt (2001) addressed
content validity by examining seminal theoretical writings on organizational
justice in the process of creating the items. Construct validity was also
supported through the examination of organizational justice factor structures
with the use of confirmatory factor analysis (CFA). The four-factor structure
used in this study was found to be the best fitting model. In addition,
Colquitt’s studies supported discriminate validity as demonstrated by cor-
relations between variables.
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Table 3. Cronbach’s Alpha Reliability Results
Number
a in Present
a in Previous
Measure
of Items
Study
Studies
Organizational justice
Distributive justice
4
0.95
0.92
a
Procedural justice
7
0.83
0.83
a
Interpersonal justice
4
0.95
0.92
a
Informational justice
5
0.92
0.88
a
Resistance
Routine seeking
5
0.75
0.80
b
Emotional reaction
4
0.80
0.87
b
Short-term thinking
4
0.83
0.84
b
Cognitive rigidity
3
c
0.75
c
0.86
b
Commitment to change
Affective commitment to change
6
0.94
0.94
d
Continuance commitment to change
6
0.86
0.94
d
Normative commitment to change
6
0.75
0.86
d
a
Meta-analysis data, as reported by Colquitt and Shaw (2005).
b
Alpha levels from foundational studies, as reported by Oreg (2003).
c
Originally four items with reliability of 0.66 (below the acceptable reliability standard of 0.70); one
item was subsequently removed.
d
Alpha levels from foundational studies, as reported by Herscovitch and Meyer (2002).
20
Foster
Validity of Resistance to Change Scales. Oreg (2003) addressed the
construct validity of the resistance to change scales by conducting an
exploratory factor analysis (EFA) on six potential sources of resistance identi-
fied in the literature. The six sources initially identified included (a) reluctance
to lose control, (b) cognitive rigidity, (c) lack of psychological resilience,
(d) intolerance to the adjustment period involved in change, (e) preference for
low levels of stimulation and novelty, and (f) reluctance to give up old habits.
After some items were eliminated because they did not load significantly on
one factor, the results of the EFA supported the four-factor structure used in
this study. Following the EFA, a CFA was conducted, which offered further
support for the four-factor model. The moderate correlations that Oreg found
between variables provided evidence for discriminate validity.
Validity for Commitment to Change Scales. Herscovitch and Meyer
(2002) conducted a principal-axis factor analysis to test that the three factors
were distinct. The analysis resulted in three factors with eigenvalues higher
than 1.0, which offered support for the validity of the three-factor model.
Data Analysis. Several data analysis techniques were used to address the
research question. First, descriptive statistics (e.g., means, standard deviations,
and percentages) were calculated to provide basic information about the scales
used in this study and to provide a description of the sample.
Second, to analyze the relationships among factors as stated in the
research question, product-moment correlation coefficients (also known as a
Pearson r) were utilized. Pearson’s correlation is used to test the strength of lin-
ear relationships between variables (Gall et al., 2003). Product-moment corre-
lation was selected because the variables being tested were considered to be
continuous. The significance levels were set at 0.01 and 0.05.
Next, to analyze the strength of the relationships between each of the
dimensions of resistance to change, justice, and commitment to change as
stated in the research question, and as presented in the proposed conceptual
model, structural equation modeling (SEM) analysis techniques were used.
SEM was selected for numerous reasons. First, SEM allowed for examination
of patterns of correlations between variables within the proposed model. This
is in alignment with the purpose of this study, to gain a better understanding
of individual responses to change by examining the relationships among orga-
nizational justice, resistance to change, and commitment to change. Second,
unlike other traditional multivariate techniques, SEM specifies measurement
error rather than assuming that there is not any. Third, SEM has the capability
to incorporate unobserved (latent) and observed variables (Byrne, 2001).
A two-step approach to SEM was employed in this study; it involves first
evaluating the measurement models and then evaluating the structural model.
To evaluate the measurement models, both CFA and EFA were conducted. The
fit indices used to evaluate the results included chi-square (
x
2
), chi-square to
degrees of freedom ratio (
x
2
兾df), comparative fit index (CFI), and root-mean-
square error of approximation (RMSEA). These measures of fit were selected
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because Burnett and Williams (2005) noted that CFI and RMSEA were the two
most highly recommended indices, and a review of closely related literature
revealed that these were the most often reported. The structural model was
evaluated with the use of AMOS software.
Results
Scale Analyses. After conducting the CFAs, examination of the results
(see Tables 5, 7, and 9) suggested that the data collected in this study were not
a strong fit with the a priori factor structures (commitment to change in par-
ticular). First, the CFA for resistance to change revealed exceptionally high cor-
relations between factors (0.75 between routine seeking and short-term
thinking, and 0.79 between emotional reaction and short-term thinking). Sec-
ond, the results from the justice CFA also revealed high correlations between
factors (0.70 between interpersonal and informational justice). Third, although
the commitment to change factors did not reveal any noticeably high correla-
tions, the CFA fit indices indicated poor fit to the data (
x
2
兾df 3.43, CFI
0.86, RMSEA
0.106). Table 4 presents the fit indices for all three constructs.
For the reasons previously mentioned, EFAs were subsequently con-
ducted. Specific reasons for conducting EFA on each of the constructs are dis-
cussed in detail below and take into account previous research results and
specific indicators of misspecification from the CFAs in this study.
The purpose of conducting EFAs was to determine if the a priori factor
structures were indeed the best representation of the data, and to see if the
items were loading on the factors as originally designed by the authors of
the items of the resistance to change, organizational justice, and commitment
to change scales. Yang (2005) noted that exploratory techniques should be used
if the originally tested CFA model(s) does not adequately fit the data. In addi-
tion, Yang emphasized the use of caution in exploratory approaches because
such modeling capitalizes on relations that could be specific and unique to a
particular data set. In conducting the EFA analyses, maximum-likelihood
extraction with oblique (direct oblimin) rotation was used. Oblique rotation
was selected because this method allows correlations among extracted factors
whereas orthogonal rotation (e.g., varimax) assumes that factors are uncorre-
lated (Yang, 2005). Allowing correlations among factors is considered to be a
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Table 4. Fit Indices for the Measurement Models
Measure
x
2
df
x
2
兾
df
CFI
a
RMSEA
Organizational justice
372.83
164
2.27
0.94
0.077
Resistance
180.85
98
1.84
0.93
0.062
Commitment to change
452.36
132
3.43
0.86
0.106
a
CFI
Comparative Fit Index.
22
Foster
more realistic representation of social science phenomena such as the ones
measured in this study.
Factor Analysis of Organizational Justice. As shown in Table 4, the model-
fit indices for organizational justice revealed a good fit of the model to the data.
CFI was equal to 0.90 or greater (0.94), and the
x
2
兾df ratio was less than
3 (
x
2
兾df 2.27). Additionally, the RMSEA of 0.077 indicates a reasonable fit.
The factor loadings displayed in Table 5 are moderate to strong for each of the
four factors, and the procedural justice factor demonstrated the lowest load-
ings 0.54 and 0.58. However, upon examination of the correlations between
factors, there was cause for concern because interpersonal and informational
justice had a 0.70 correlation. As previously discussed, Colquitt and Shaw
(2005) noted that, while there is room for debate regarding correlations in the
0.60s, correlations in the 0.70s are “worthy of aggregation” (p. 138). They also
noted that interpersonal and informational justice have been highly correlated
in past studies but are generally in the 0.60s. For this reason, EFA was con-
ducted in order to further examine the items and underlying factors.
In order to assess the items and the factor structure for organizational jus-
tice, first an EFA was conducted with no restriction on the number of extracted
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Table 5. Confirmatory Factor Analysis Organizational Justice
Item
Distributive
Procedural
Interpersonal
Informational
DJ1
0.88
DJ2
0.91
DJ3
0.96
DJ4
0.89
PJ1
0.58
PJ2
0.54
PJ3
0.60
PJ4
0.73
PJ5
0.78
PJ6
0.58
PJ7
0.76
IP1
0.95
IP2
0.98
IP3
0.96
IP4
0.78
IJ1
0.80
IJ2
0.87
IJ3
0.89
IJ4
0.85
IJ5
0.75
factors. This analysis revealed five factors that had eigenvalues greater than 1.0;
however, as previously noted, simply using the eigenvalues rule can lead to too
many factors. Upon examination, the fifth factor had an eigenvalue of only
1.03, it accounted for only 5% of the variance, and four factors explained
72.89% of the variance. For these reasons, another EFA was conducted in
which four factors were extracted. The four-factor structure is the hypothe-
sized structure and is also supported in previous studies (e.g., Colquitt, 2001).
Results from the EFA are presented in Table 6.
The four factor structure accounted for 72.89% of the variance, and inter-
personal and informational justice items revealed strong factor loadings and
high levels of discrimination. For these reasons, the original hypothesized
four-factor structure was used in the SEM analyses. In addition, as in the CFA,
the procedural justice scale was of some concern because it accounted for the
least amount of variance, and items PJ1 and PJ2 demonstrated lower loadings.
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Table 6. Exploratory Factor Analysis Organizational Justice:
Four Factors
Item
Factor 1
Factor 2
Factor 3
Factor 4
DJ1
0.02
0.90
0.05
0.01
DJ2
0.03
0.87
0.05
0.02
DJ3
0.02
0.96
0.03
0.03
DJ4
0.01
0.87
0.05
0.02
PJ1
0.22
0.02
0
0.44
PJ2
0.04
0.02
0.07
0.49
PJ3
0.07
0.06
0.02
0.58
PJ4
0.06
0.05
0.05
0.78
PJ5
0.01
0.20
0.06
0.71
PJ6
0.18
0.01
0.19
0.54
PJ7
0.11
0.13
0.06
0.67
IP1
0.91
0
0.08
0.00
IP2
0.95
0
0.03
0.05
IP3
0.86
0.03
0.12
0.02
IP4
0.70
0.04
0.10
0.04
IJ1
0.24
0.06
0.61
0.04
IJ2
0.03
0.04
0.81
0.05
IJ3
0.04
0.07
0.77
0.09
IJ4
0.02
0.02
0.87
0.01
IJ5
0.062
0.011
0.76
0.07
Eigenvalue
8.59
2.90
1.82
1.27
Variance explained
42.93%
14.48%
9.12%
6.36%
24
Foster
A review of the correlations between PJ1 and PJ2 and the other items did not
raise any further concerns.
Factor Analysis of Resistance to Change. The CFA for the resistance scales
(Table 7) in this study revealed overall good fit. The value for RMSEA (0.062)
indicated reasonable fit, while the
x
2
兾df ratio of 1.84 and the CFI of 0.93 indi-
cated good fit. With the exception of one item with a weak loading (RS4
0.31) in the routine seeking scale, all factor loadings were strong.
As was the case with organizational justice, resistance to change factors
also demonstrated high correlations with each other. In particular, routine
seeking and short-term thinking had a 0.75 correlation, and emotional reac-
tion had a 0.79 correlation with short-term thinking. For this reason, EFA was
conducted in order to investigate further the factor structure of resistance to
change. There is not enough empirical evidence surrounding Oreg’s (2003)
instrument to support alternative a priori factor structures other than the four
factors originally proposed. For this reason, an EFA was conducted without
restricting the number of factors. Five factors had eigenvalues over 1.0, but the
fifth factor’s eigenvalue was only 1.01, accounting for only 6% of the variance.
For these reasons, another EFA was conducted, restricting the analysis to four
factors. Table 8 reports the factor loading results of the four-factor structure.
The four-factor structure of resistance accounted for 60.53% of total vari-
ance. This is a low percentage given the rule of thumb that retained factors
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Table 7. Confirmatory Factor Analysis Resistance to Change
Routine
Emotional Short-Term Cognitive
Item
Seeking
Reaction
Thinking
Rigidity
RS1
0.68
RS2
0.74
RS3
0.79
RS4
0.31
RS5
0.61
ER1
0.78
ER2
0.72
ER3
0.71
ER4
0.61
ST1
0.72
ST2
0.76
ST3
0.73
ST4
0.75
CR2
0.93
CR3
0.67
CR4
0.54
should account for at least 60–70% of total variance. In addition, EFA results
for the four-factor structure indicated adequate loadings for all but one cogni-
tive rigidity and one routine seeking item, and there are some items that load
on multiple factors. In particular, ER1 and ST4 were indiscriminate, and RS4
and ER2 had only moderate loadings, but they each loaded with items from
other factors. Because the EFA revealed that some items were not discriminate
and had weak loadings, items RS4, ER1, ER2, and ST4 were eliminated from
subsequent analyses. The four-factor structure was retained because there was
not sufficient theoretical or empirical evidence to support proposing another
factor structure, and the modifications resulted in improved CFA model fit.
After the four mentioned items were eliminated, another CFA was con-
ducted and the revised model demonstrated good fit (
x
2
72.02, df 48,
x
2
兾df 1.50, CFI 0.97, RMSEA 0.048). These fit indices were also
improvements in comparison to the original resistance to change CFA model.
In addition, there was a reduction in the amount of correlation between the
factors. Routine seeking and short-term thinking still had a rather high 0.70
correlation (but this value was down from 0.75), and emotional reaction and
short-term thinking went down from 0.79 to 0.69.
Factor Analysis of Commitment to Change. Table 9 presents the results for
the CFA on commitment to change. The fit indices for the commitment to
Resistance, Justice, and Commitment to Change
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Table 8. Exploratory Factor Analysis Resistance to Change
Item
Factor 1
Factor 2
Factor 3
Factor 4
RS1
0.14
0.64
0.00
0.15
RS2
0.02
0.64
0.03
0.11
RS3
0.03
0.90
0.03
0.10
RS4
0.22
0.10
0.10
0.38
RS5
0.12
0.58
0.01
0.02
ER1
0.34
0.13
0.02
0.41
ER2
0.24
0.07
0.01
0.50
ER3
0.99
0.06
0.09
0.00
ER4
0.48
0.12
0.00
0.17
ST1
0.19
0.12
0.06
0.57
ST2
0.10
0.07
0.07
0.69
ST3
0.12
0.19
0.04
0.50
ST4
0.11
0.30
0.02
0.45
CR2
0.12
0.05
0.91
0.15
CR3
0.06
0.12
0.63
0.22
CR4
0.04
0.05
0.57
0.12
Eigenvalue
5.68
1.99
1.50
1.12
Variance explained
33.42%
11.72%
8.80%
6.56%
26
Foster
change scales reported in Table 9 indicate that the three-factor commitment
to change structure was a poor fit to the data. Specifically, the
x
2
兾df ratio was
3.43, CFI was 0.86, and RMSEA was 0.106. Although the values are not
extremely far outside of the acceptable ranges, they are cause for concern in
terms of whether the scales accurately represent the commitment to change
construct. In addition, two items in the normative commitment to change had
only moderate loadings (NC3 and NC6).
Although this three-factor structure has been proposed for measuring
commitment to change (Herscovitch & Meyer, 2002), there are few studies
that confirm and support each of the three factors of this conceptualization. In
addition, some have proposed that the three-structure model of organizational
commitment (upon which the commitment to change instrument was based)
is in need of refinement (e.g., van Dijk, 2004). Many studies report measuring
only affective commitment to change (or affective organization commitment)
because this factor has historically demonstrated the strongest validity and
most sizeable effects (Meyer & Allen, 1997).
In order to examine further the intricacies of the underlying factor struc-
tures on commitment to change using data from this study, and because the
CFA revealed poor fit, an EFA was conducted. The results are presented in
Table 10.
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Table 9. Confirmatory Factor Analysis Commitment to Change
Item
Affective
Continuance
Normative
AC1
0.96
AC2
0.96
AC3
0.69
AC4
0.82
AC5
0.82
AC6
0.77
CC1
0.59
CC2
0.64
CC3
0.82
CC4
0.87
CC5
0.64
CC6
0.73
NC1
0.65
NC2
0.78
NC3
0.42
NC4
0.59
NC5
0.64
NC6
0.46
The EFA conducted on commitment to change did not restrict the num-
ber of factors, and the results indicated that the three-factor structure was the
most appropriate. The three factors accounted for 63.38% of the variance,
which is in the acceptable range, and most of the items loaded on factors as
expected. The exceptions were NC3, which had a moderate loading with the
affective commitment to change items, and NC6, which did not have a load-
ing over 0.30 on any of the three factors. Both NC3 and NC6 were also reverse
coded items, which suggests that the wording might have caused confusion in
respondents. A review of the item–total correlations also revealed that NC3
had an item–total correlation of only 0.17 and the item–total correlation for
NC6 was 0.24. For these reasons, NC3 and NC6 were eliminated from subse-
quent analyses. The amended NC scale had an acceptable reliability of 0.77.
Additionally, because AC1 and AC2 reported such high loadings (
0.90), the
interitem correlations were examined, and it was discovered the two items had
a strong correlation of 0.93. As suggested by Byrne (2001), the decision was
made to add a measurement error correlation between AC1 and AC2 in the
SEM analysis. After these modifications, the commitment to change model
revealed improved fit (
x
2
334.84, df 100, x
2
兾df 3.34, CFI 0.90,
RMSEA
0.104).
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Table 10. Exploratory Factor Analysis Commitment to Change
Item
Factor 1
Factor 2
Factor 3
AC1
0.92
0.02
0.07
AC2
0.91
0.04
0.06
AC3
0.68
0.11
0
AC4
0.84
0.02
0.01
AC5
0.85
0.01
0.03
AC6
0.88
0.01
0.14
CC1
0.24
0.51
0.06
CC2
0.09
0.73
0.19
CC3
0.09
0.85
0.01
CC4
0.01
0.76
0.26
CC5
0.04
0.68
0.07
CC6
0.04
0.61
0.27
NC1
0.18
0.02
0.57
NC2
0.03
0.03
0.77
NC3
0.41
0.06
0.14
NC4
0.11
0.02
0.69
NC5
0.03
0.01
0.61
NC6
0.24
0.03
0.27
Eigenvalue
5.96
4.14
1.31
Variance explained
33.13%
22.99%
7.26%
28
Foster
In summary, the CFAs revealed that both the organizational justice and
the resistance models fit the data relatively well, but there were questions
regarding the dimensionality due to high correlations between factors. In addi-
tion, the commitment to change model did not demonstrate fit. Because CFAs
revealed these weaknesses, EFAs were run on each of the constructs. These
analyses offered insight regarding the underlying structure of the data, and
based on examination of factor loadings and item characteristics, the decision
was made to eliminate four resistance to change items and two commitment
to change items in the SEM analyses.
Descriptive Statistics and Correlations. Descriptive statistics and correla-
tions are displayed in Table 11. Results demonstrated that all of the relationships
among the justice and commitment to change variables are significant, with the
exception of the relationship between interpersonal justice and continuance com-
mitment. Overall, the strongest correlations were with affective commitment.
These three highest correlations with affective commitment to change included
procedural justice (r
0.49, p 0.01), interpersonal justice (r 0.36,
p
0.01), and informational justice (r 0.35, p 0.01). Another finding was
that all of the relationships between continuance commitment to change and
organizational justice were negative. Unexpectedly, few of the relationships with
resistance to change were significant, and none exceeded a correlation of 0.20.
Model Testing. The three measurement models were integrated into a
structural model in order to test the seven proposed hypotheses. These
hypotheses are indicated in Figure 1 as paths in the proposed model. Path
coefficients are also presented in the model. The hypothesized model revealed
an acceptable fit to the data based on the fit indices (
x
2
1,816.90, df
1,064,
x
2
兾df 1.71, CFI 0.89, RMSEA 0.057), and three of the seven
pathways were significant. Interestingly, none of the hypothesized paths related
to resistance to change were significant. Based on squared multiple correlations
(SMC) analyses, the model explained 17% of the variance for normative com-
mitment to change, 5% for continuance commitment to change, and 37% for
affective commitment to change.
The hypotheses (1a, 1b, 1c, 2a, 2b, 2c, 3) were tested by examining the
path coefficients and the critical ratio (CR must be
1.96). Hypotheses 1a,
1b, and 1c predicted negative relationships between resistance to change and
affective, continuance, and normative commitment to change. Each of these
hypothesized paths was found to be nonsignificant, so these three hypotheses
were not supported. Hypothesis 2a proposed that organizational justice would
have a positive influence on affective commitment to change. This hypothesis
was supported, and organizational justice had a sizeable impact on affective com-
mitment to change (
b 0.61, p 0.001). This was the strongest path coeffi-
cient represented in the hypothesized model. Hypothesis 2b was not supported
because the direction of the relationship between organizational justice and con-
tinuance commitment to change was negative rather than positive as proposed
(
b 0.21, p 0.05). Hypothesis 2c predicted a positive relationship between
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T
able 11. Corr
elations Among Resistance to Change, Organizational Justice, and Commitment to Change
MS
D
D
J
P
J
IP
IJ
R
S
E
R
ST
C
R
A
C
C
C
N
C
1. DJ
3.19
1.23
0.95
2. PJ
2.94
0.82
0.45**
0.83
3. IP
4.21
0.88
0.28**
0.41**
0.95
4. IJ
3.52
1.04
0.38**
0.49**
0.67**
0.92
5. RS
2.43
0.79
0.04
0.14
0.19**
0.07
0.75
6. ER
3.07
0.97
0.06
0.17*
0.01
0.06
0.44**
0.80
7. ST
2.44
0.82
0.12
0.20**
0.06
0.06
0.62**
0.65**
0.83
8. CR
3.54
0.91
0.08
0.15
0.03
0.08
0.15*
0.13
0.17*
0.75
9. AC
5.36
1.66
0.23**
0.49**
0.36**
0.35**
0.14
0.08
0.08
0.11
0.94
10. CC
4.84
1.58
0.21**
0.34**
0.12
0.19**
0.09
0.20**
0.06
0.01
0.29**
0.86
11. NC
5.01
1.19
0.20**
0.29**
0.27**
0.24**
0.12
0.03
0.08
0.13
0.46**
0.21**
0.75
Note:
DJ
distributive justice, PJ
pr
ocedural justice, IP
interpersonal justice, IJ
informational justice, RS
routine seeking, ER
emotional r
esponse, ST
short-term thinking, CR
cognitive rigidity
, AC
af
fective commitment to change, CC
continuance commitment to change, NC
normative commitment to change.
Or
ganizational justice items (DJ, PJ, IP
, IJ) wer
e measur
ed on a 5-point Likert-type scale ranging fr
om
a very small extent
(1) to
a very lar
ge extent
(5); r
esistance items (RS,
ER, ST
, CR) wer
e measur
ed on a 6-point Likert-type scale ranging fr
om
str
ongly disagr
ee
(1) to
str
ongly agr
ee
(6); commitment to change items (AC, CC, NC) wer
e
measur
ed on a 7-point Likert-type scale ranging fr
om
str
ongly disagr
ee
(1) to
str
ongly agr
ee
(7).
*Significant at the 0.05 level.
**Significant at the 0.01 level.
30
Foster
organizational justice and normative commitment to change, and this was sup-
ported (
b 0.41, p 0.001). Hypothesis 3 proposed an association between
resistance to change and organizational justice, but this hypothesis was not sup-
ported because the relationship was not significant.
Discussion and Conclusions
This study was designed to examine employee responses to organizational
change in hopes of contributing to a better understanding of how organizations
can make change implementations more successful. The research question
asked, “What are the relationships among the factors of employee resistance,
employee perceptions of organizational justice, and commitment to change?”
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0.54
0.70
0.69
1.00
0.23
–0.00
–0.02
–0.15
–0.21
0.07
0.41
0.61
0.78
0.80
0.72
Resistance to
Change
Routine Seeking
Note: All dotted paths were nonsignificant; all others were significant at p < 0.05.
Short-Term Thinking
Emotional Reaction
Cognitive Rigidity
Distributive Justice
Informational Justice
Interpersonal Justice
Organizational
Justice
Continuance
Commitment to
Change
Normative
Commitment to
Change
Affective
Commitment to
Change
DJ1 DJ2 DJ3 DJ4
PJ1 PJ2 PJ3 PJ4 PJ5 PJ6 PJ7
IP1 IP2 IP3 IP4
IJ1
IJ2
IJ3
IJ4
IJ5
AC2
AC3
AC5
Procedural Justice
AC1
AC4
AC6
CC1
CC2
CC3
CC4
CC5
CC6
NC1
NC2
NC3
NC4
RS1
RS2
RS3
ER3
ER4
ST1
ST2
ST3
CR1
CR2
CR3
Figure 1. Hypothesized Structural Model of Relationships Among
Resistance, Organizational Justice, and Commitment to Change
As predicted, organizational justice was significantly related to commitment to
change in this study. The strongest relationship, between organizational justice and
affective commitment to change, echoed results of previous studies (Bernerth,
Armenakis, Field, & Walker, 2007; Herold, Fedor, & Caldwell, 2007). How-
ever, these previous studies did not examine organizational justice and com-
mitment to change using the same measures, dimensions, or analytical
techniques used in this study. The current study extends existing findings by
reporting that organizational justice had significant impacts on normative com-
mitment to change and continuance commitment to change. In other words,
results revealed that employees who perceived high levels of fairness associ-
ated with an organizational change were more likely to want to be committed
to the change (affective), more likely to feel that they ought to be committed to
the change (normative), and less likely to be committed to the change because
of perceived costs (continuance).
Although much has been written about resistance to organizational
change, until recently there has not been a great deal of in-depth investigation
regarding the nature of individual resistance to change, particularly at the indi-
vidual level of analysis (Dent & Goldberg, 1999; Ford et al., 2008; Piderit,
2000). Oreg (2003) used an individual-differences approach to develop the
resistance disposition measures used in this study, and the initial studies and
personality theory suggested that resistance disposition would be associated
with organizational justice and commitment to change. However, the only sig-
nificant relationships revealed by this study were weak correlations. In addi-
tion, SEM revealed that resistance disposition was not significantly related to
organizational justice or commitment to change.
The results from this study support Ford et al. (2008), Piderit (2000), and
Dent and Goldberg (1999) in suggesting that the traditional discussion of indi-
vidual resistance to change needs to be seriously reconsidered. Contrary to
commonly held beliefs about resistance to change, results from this study
demonstrated that individual resistance to change does not have any relation-
ship to commitment to change. Oreg (2006) and Piderit (2000) have taken ini-
tial steps in reframing resistance to change as a tripartite model, but more
research is need to explore whether Oreg’s (2003) dimensions of dispositional
resistance accurately represent this tripartite conceptualization. In addition, Dent
and Goldberg (1999) and Piderit (2000) suggested that the term resistance to change
is an inaccurate and assumption-laden label, and that it does not offer the best
framework for understanding organizational change implementation. Ford et al.
(2008) further argue that traditional views of resistance to change favor the change
agent and their sponsors, and that resistance should be viewed as an opportunity
for thoughtful consideration of organizational changes. The results of this study
offer evidence to support these ideas, and it is suggested that future research on
related organizational change topics venture away from the traditional notion of
resistance to change. At the individual level, studies could use the term response to
change, as proposed by Piderit (2000). As noted in the review of resistance
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to change literature, resistance has historically been conceptualized as an unde-
sirable trait (e.g., Coch & French, 1948). In examining the nonsignificant resis-
tance to change results in this study it is helpful to keep this in mind, as
respondents might have tried to respond to items in a favorable manner. Such
a positive response bias could influence the validity of the resistance to change
measures. A review of the wording of the resistance to change items reveals a
heavy reliance on traditional views of resistance. Examples of such items
include: “I generally consider changes to be a negative thing” and “Changing
plans seems like a real hassle to me.” Prior to this study, resistance disposition
had not been measured in relationship with commitment to change by using
the Oreg (2003) and Herscovitch and Meyer (2002) instruments, and the non-
significant results from this study suggest that there is little need to explore this
relationship further using these measures.
Colquitt and Shaw (2005) discussed the historical development of justice
measurement, noting that high correlations among interpersonal and informa-
tional justice are not uncommon. Although these two factors have often been
measured together as interactional justice, there is a sufficient amount of evi-
dence supporting separate measurement (Colquitt, 2001; Colquitt et al.,
2001). Upon examination of the underpinning seminal work by Bies and Moag
(1986) on interactional justice, the relationships between interpersonal and
informational justice become evident. Bies and Moag (1986) proposed four cri-
teria for interactional justice, including respect (being polite), propriety
(refraining from improper remarks), truthfulness (candid, not deceitful), and
justification (explaining decisions). Interpersonal justice consists of respect
and propriety, and informational consists of truthfulness and justification.
A review of the interpersonal and informational justice items reveals possible
explanations for the high correlations between the factors. For example, items
from informational justice refer to communications and explanations, and one
item from interpersonal justice refers to “remarks or comments.” Another infor-
mational justice item refers to “candid communication,” and it is possible that
respondents interpreted the word candid to have a similar meaning to polite or
respectful, both words that are used in the interpersonal justice scale.
In this study, the most problematic construct in terms of validity was com-
mitment to change. Not only did the original three-factor model reveal poor
fit to the data, but even after modification, indices revealed only moderately
acceptable fit (
x
2
334.84, df 100, x
2
兾df 3.34, CFI 0.90, RMSEA
0.104). As in previous research (e.g., Herscovitch & Meyer, 2002; Meyer et al.,
2007), affective commitment to change revealed strong correlations and strong
item loadings. Also in accordance with previous research (e.g., Meyer & Allen,
1997), normative commitment to change was less well developed. After fur-
ther investigation, two normative commitment to change items that demon-
strated weak loadings were eliminated. These two items were also reverse
coded, suggesting that the wording of these items might have caused confu-
sion for respondents. Although there are a great many studies investigating
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organizational commitment with the use of the three-component model and
other conceptualizations, there are few studies that have taken a multidimen-
sional look at commitment to change. Because of this, there is a need for fur-
ther theoretical development of commitment to change ideas using different
measures and different research methods to help determine if the nature of
commitment to change differs from that of organizational commitment.
Limitations. Because this study relied on self-report data measured from
one source, single-source, single-method bias is a concern. In addition, the sur-
vey data were collected at only one time, which took place during or after the
organizational changes of interest. This limits any claims regarding causality
among the studied variables. Directionality suggested in this study was based
on support from previous studies and theoretical development.
Another limitation in this study is that there are numerous other variables
that have demonstrated significant influence on employee responses to orga-
nizational change. Kline (2004) explained that structural models are often mis-
specified because researchers are not able to measure all of the relevant
variables associated with a phenomenon. Examples of additional variables that
have demonstrated influence on employee response to change include change
favorableness (how employees feel about consequences of change), impact of
change on work group or individual (amount of disruption caused by change),
and change turbulence (extent to which other changes or distractions influ-
ence the change being studied) (Armenakis & Bedeian, 1999; Fedor, Caldwell, &
Herold, 2006; Herold et al., 2007; Oreg, 2006). It is possible that resistance
disposition could have little or no influence on employee commitment to
change in cases where individuals had strong feelings about the favorableness of
the change. In addition, the changes in this study were primarily the result
of top-down decisions that had an influence on the respondents’ work. The
process of implementation could have interactions with variables measured in
this study; however, further process-based investigation is needed to examine
possible interactions.
Another limitation to this study is that data were gathered in only three
organizations at one point in time. It is possible that the differences in the
nature of the changes taking place in each of the three organizations might
have had an influence on the individual responses to change; however, it was
beyond the scope of this study to investigate the differences related to the type
of change or the effects at the group level of analysis. In addition, the majority
of respondents in this study were employees in the health care system, which
primarily employs nurses and other support-related health care professionals,
so results could be biased toward these professions.
Results of correlation analyses, CFA, and EFA suggested the need for fur-
ther empirical investigation on the constructs associated with resistance to
change, organizational justice, and commitment to change. The results also
bring into question whether all of these measures render data that are useful
for drawing theoretical and practical implications. One problem with the scales
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for organizational justice and resistance to change was high correlations
between factors, also referred to as concept redundancy. Within organizational
justice, interpersonal and informational justice were highly correlated, and
within resistance, routine seeking, short-term thinking, and emotional reac-
tion had high correlations. Item analysis and modifications to the scales
improved model fit, but it is still necessary to scrutinize the underlying issues
that might have contributed to such problems.
Implications for Practice. First, fair practices in the implementation of a
change have significant associations with employee commitment to change.
Managers and supervisors can promote fair implementation processes in many
ways. For example, change leaders can encourage and enable employees to
share their views and feelings about the change. This could be accomplished
with any number of approaches, such as dialogue sessions, interviews, or var-
ious other assessment techniques (also referred to as analysis or diagnosis).
According to McLean (2006), the purpose of such interventions is to gather
information from employees and gain a better understanding of specific issues.
Leaders can also promote process fairness by allowing each individual who is
involved to have influence in the process as well as the opportunity to appeal
decisions. There are many OD interventions that incorporate employee
involvement, and the context and nature of the change should govern which
of these approaches is employed.
Second, in addition to procedural justice, interpersonal and informa-
tional justice were significantly associated with commitment to change. These
forms of fairness are exhibited through interactions (e.g., between managers
and employees). Such practices include thoroughly and truthfully communi-
cating the details of the change in a timely and personable manner, and thor-
oughly explaining each phase of the change. Furthermore, organizational
justice can become institutionalized if such practices become a regular part
of planned change efforts. Techniques that address providing timely, accurate
information to employees can include techniques such as providing feedback
and/or training. These techniques are designed to increase ownership of ini-
tiatives and ensure validity of information interpretation (Cummings &
Worley, 2005; McLean, 2006). In addition, deliberate attention to a change
communication strategy could also be used to address this (Armenakis &
Harris, 2002).
Third, the instrument used to measure organizational justice can be used
to provide valuable information regarding the types of efforts that might be
needed in shaping a change implementation strategy. By gathering information
from employees as a part of planned change efforts, potential problems can be
identified early, needs can be identified, and employee attitudes can be taken
into account. However, the instruments used in this study to measure resis-
tance to change and commitment to change were problematic, so other instru-
ments should be developed or considered if one desires to measure these
constructs.
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Implications for Research. Future research could benefit by examining
the nature of the relationships between resistance to change, organizational
justice, and commitment to change using different measures. In particular,
results from this study indicate the need to clarify the relationships and differ-
ences between interpersonal and informational justice, and between short-term
thinking and emotional reaction. The items in each of these subscales could
be revised to eliminate redundancies and to represent the phenomena of inter-
est more accurately. In addition, the CFA indicated that the construct validity
for commitment to change was questionable. A thorough psychometric analy-
sis and further theoretical investigation could be used to revise these items and
improve the accuracy with which commitment to change could be measured.
It is possible that not all of the items measured with the Herscovitch and Meyer
(2002) instrument offer value for individuals investigating different types of
change implementations. For example, the results of this study were consis-
tent with previous commitment research in that affective commitment to
change demonstrated the strongest results. In some cases, only measuring
affective commitment to change might be the most efficient approach.
Second, the results from this study support Piderit (2000) and Dent and
Goldberg (1999) in suggesting that the discussion of individual resistance to
change needs to be seriously reconsidered. Contrary to commonly held beliefs
about resistance to change, this study demonstrated that individual resistance
to change does not have any relationship to commitment to change. Oreg
(2006) and Piderit (2000) have taken initial steps in reframing resistance to
change as a tripartite model, but more research is needed to explore whether
Oreg’s (2003) dimensions of dispositional resistance accurately represent this
tripartite conceptualization. Additionally, future research should examine
aspects and interactions of organizational change at different levels of analysis,
and how these are accurately measured and integrated.
Dent and Goldberg (1999) and Piderit (2000) suggested that the term
resistance to change is an inaccurate and assumption-laden label, and that con-
cept does not offer the best framework for understanding organizational
change implementation. The results of this study offer evidence to support
these ideas, and it is suggested that future research on related organizational
change topics venture away from the traditional notion of resistance to change.
At the individual level, studies could use the term response to change, as pro-
posed by Piderit (2000).
Third, the relationships between resistance to change and commitment to
change should be further developed and even reconsidered entirely. When com-
mitment and resistance are discussed together, they have often been considered
opposites. The results of this study indicated very little relationship between
resistance and commitment to change, which suggests that traditional concep-
tualizations might not be entirely accurate. However, it is also necessary to note
that these results could be artifacts of the research design or of invalid measures.
This study also conceptualized resistance to change at the individual level, and
Resistance, Justice, and Commitment to Change
35
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as a dispositional inclination toward resistant behavior. Future research should
reconsider whether this is a useful conceptualization, and by taking change con-
text into consideration.
Finally, there is a need to use different methods of investigation to exam-
ine employee responses to organizational change. More mesoresearch perspec-
tives of the change process are needed to provide insights into how organiza-
tional change phenomena at different levels interact (House, Rousseau, &
Thomas-Hunt, 1995). Research designs and data-analysis techniques that allow
multilevel analysis must be explored and utilized in future studies because they
offer the potential to capture the complexities associated with organizational
change. Organizational changes occur in the midst of complex organizational
surroundings, and a deeper understanding of organizational change can be
meaningful for both researchers and practitioners.
Acknowledgments
I would like to thank Kenneth Bartlett, Richard Swanson, Andrew Van de Ven,
Gary McLean, Alexandre Ardichvilli, Baiyin Yang, and the anonymous HRDQ
reviewers for their many valuable suggestions in the development of this
manuscript.
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Rex Foster leads Planning and Evaluation efforts at Lutheran Immigration and
Refugee Service (LIRS), an organization that resettles refugees, protects unaccompanied
refugee children, and seeks alternatives for those in immigration detention. Rex has
extensive experience working on organizational effectiveness initiatives in private,
nonprofit, and governmental organizations. He earned his doctorate from the
University of Minnesota.
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