671409

research-article2016
JABXXX10.1177/0021886316671409The Journal of Applied Behavioral ScienceJones and Van de Ven

Article
The Journal of Applied Behavioral Science
2016, Vol. 52(4) 482­–506
The Changing Nature © The Author(s) 2016
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DOI: 10.1177/0021886316671409
An Examination of the jabs.sagepub.com

Moderating Impact of Time

Stephen L. Jones1 and Andrew H. Van de Ven2

Abstract
This research examines whether relationships between change resistance and its
consequences and antecedents strengthen or weaken over time during an extended
duration of organizational change. In 40 health care clinics undergoing a 3-year
period of significant organizational changes, we found that resistance to change had
increasingly negative relationships over time with two important consequences:
employees’ commitment to the organization and perceptions of organizational
effectiveness. That these relationships became stronger (rather than weaker) over
time suggests festering effects of resistance to change. We also found that over time
supportive leadership was increasingly impactful in reducing change resistance. A
major implication of this research for practice is that it is important for change agents
to address employee resistance because, left unchecked, it can fester and increasingly
inflict harm. Also, engaging in supportive leader behaviors can be particularly useful in
ameliorating resistance to change at later stages of a change initiative.

Keywords
organizational change, individual responses to change, resistance to change,
organizational commitment, organizational effectiveness

Organizational change represents not only a macro shift in structure, systems, and
routines, it also has important and often underestimated behavioral and psycho-
logical implications for individual employees (Choi, 2011). Organizations only

1University of Wyoming, Laramie, WY, USA

2University of Minnesota, Minneapolis, MN, USA

Corresponding Author:
Stephen L. Jones, College of Business, University of Wyoming, 1000 East University Avenue, Laramie,
WY 82071, USA.
Email: stephen.jones@uwyo.edu
Jones and Van de Ven 483

change and act through their members (Judge, Thoresen, Pucik, & Welbourne,
1999), and a “change persists over the long term only when individuals alter their
on-the-job behaviors in appropriate ways” (Choi, 2011, p. 480). Indeed, according
to Woodman and Dewett (2004), “it is not possible for organizations to change in
meaningful ways unless employees change—people must think differently, they
must believe differently, and they must behave differently” (p. 32). Hence, the
effectiveness of most organizational change initiatives is a function of the extent
to which employees are motivated and enabled to implement those initiatives
(Armenakis & Harris, 2009).
However, not all employees within a given organization respond alike to the
changes ongoing in their organization. Some employees respond to organizational
changes with enthusiasm and as opportunities for learning and growth, some resist
the changes and feel a growing sense of frustration, alienation, and grief (Caldwell,
Herold, & Fedor, 2004; Thompson & Van de Ven, 2000), while others are ambivalent
and do not change their behaviors (Piderit, 2000). Indeed, Dahl and Lindblom (1953)
observed in the case of welfare organization reform that changes were heralded by
some, attacked and sabotaged by some, and apathetically ignored by the majority of
constituents.
More recently, scholars have recognized—along with different responses to
change—that the way individuals experience and construct meaning about organiza-
tional change evolves as change unfolds (Isabella, 1990; Sonenshein, 2010). Balogun,
Bartunek, and Do (2015), for example, found that senior managers’ sensemaking of a
large strategic change evolved as they dialogued with those above and below them.
Huy, Corely, and Kraatz (2014) discovered a cascading resistance to change over time
at a large information technology firm, even though managers had initially accepted
the radical transformation. Such evolution is particularly salient in massive initiatives
such as mergers and acquisitions and other forms of strategic renewal, where numer-
ous changes are made to organizational structures, systems, and governance that often
require years to unfold (Agarwal & Helfat, 2009; Engler, Jones, & Van de Ven, 2013;
Sackmann, Eggenhofer-Rehart, & Friesl, 2009).
These more recent qualitative discoveries concerning the temporal evolution of
change have exposed a limitation in our understanding of change based on years of
quantitative analysis. In a meta-analysis, Oreg, Vakola, and Armenakis (2011) expertly
summarized 60 years’ worth of quantitative studies on individual change reactions.
Their summary indicates that researchers have broadly probed the antecedents and
consequences of such change reactions, but only in a static way. Yet the more recent
qualitative research suggests that the relationships among change concepts will not be
static. Instead, they hint that relationships between change reaction and its antecedents
and consequences could strengthen or weaken as changes unfold. If these relationships
are not static, then we may incorrectly assume, for instance, that certain variables are
influential throughout a change process when they actually play a role only near the
beginning or ending stages. We may also miss the true impact of change resistance
without recognizing that its influence (i.e., its relationships with outcomes) can change
over time, even though the amount of resistance may remain stable.
484 The Journal of Applied Behavioral Science 52(4)

With the opportunity to add a temporal dimension to existing theory, we ask: Do the
relationships between change resistance and its outcomes strengthen or weaken over
time as change persists? We also ask: Do organizational antecedents become more or
less influential on change resistance over time?
We empirically examine these questions using a longitudinal study of the creation
of a large medical group. The group was established through the integration of 40
primary care clinics. The integration effort entailed numerous organizational changes
that affected all aspects of the business and extended over multiple years. Unlike past
studies of change that often look at an organization at a single point in time, we track
individuals who experienced significant integration changes over three annual sur-
veys. This allows us to view the changing ways in which individuals react to change.
We find that resistance to change has increasingly negative relationships over time
with employees’ commitment to the organization and perceptions of organizational
effectiveness. These relationships become stronger (rather than weaker) over time,
suggesting festering effects of resistance to change. We also find that the negative
relationship between one organizational antecedent, supportive leadership, and change
resistance increases over time. This indicates that supportive leadership becomes more
crucial in reducing change resistance at later stages in the change process. And, con-
trary to our expectation, we find that the influence of organization fairness on change
resistance weakens over time, suggesting that fairness plays its most crucial role near
the beginning of change processes.
Our findings have important implications both for organizational change theory
and for practitioners who are enacting change. First, we suggest that a more dynamic
conceptualization of organizational change is warranted, especially in the context of
major, long-term change initiatives. We contribute to theory by recognizing that ante-
cedents (supportive leadership and organization fairness) of attitudes toward change
may play larger or smaller roles depending on duration and stage of change. Their
influence is not static over time. Similarly, we suggest that the effect of change resis-
tance is not static; instead, it can have a negative, festering effect on relationships with
perceived organizational effectiveness and commitment to the organization over time.
This study also provides insights for change agents. Change resistance that persists
into or emerges in later change stages is particularly damaging. It would be unwise to
ignore early change resistance because, if it continues, it could create greater issues for
employees and their organizations. New resistance at later change stages could poten-
tially emerge as well, which should be monitored and managed. Furthermore, when
attempting to reduce employee resistance at early stages of a change initiative, it is
important to ensure that changes are just and fair. At later change stages, supportive
leaders can play an important role in ameliorating resistance.

Conceptual Model
We begin with a baseline mediation model—illustrated in Figure 1—which is consis-
tent with the model presented by Oreg et al. (2011) in their exhaustive review on
individual reactions to change. The key mediating construct is reaction toward change,
Jones and Van de Ven 485

MODERATOR
Time
Antecedents Outcomes
Organizational
Supportive Leadership
MEDIATOR Commitment
Change Resistance
Perceived Org.
Organization Fairness
Effectiveness

Figure 1. Mediated model of perceived organization effectiveness.

which we frame in the negative as resistance toward change (Armenakis & Harris,
2009; Coch & French, 1948; Ford & Ford, 2010; Lawrence, 1954). While there is no
agreed-upon definition of change resistance, Piderit (2000) reviews the social–psy-
chological research that “clearly supports a multidimensional view of attitudes that
can be used to integrate inconsistent definitions of resistance” (p. 787). An overall
attitude toward change includes behavior and cognition as two broad dimensions. The
behavioral dimension focuses on what individuals and organizations do to indicate or
make resistance to change possible, such as communicating (in order to be informed
of a change), exercising influence on a change process (for people tend to resist man-
dated impositions), and taking actions that inhibit (or facilitate) a change process.
Cognitive aspects of resistance deal with intentional or emotional attitudes in support-
ing (or criticizing) a change initiative and feeling confidence (or no trust) in the leaders
of change. Our study focuses on individuals’ attitudes toward change, which is cap-
tured by their self-perceptions of these behavioral and cognitive indicators. We frame
employee attitudes in the negative as resistance to change because resistance is of the
most common interest to scholars and practitioners. We do not examine resistance
from the perspective of organizational change agents as Piderit (2000) and Ford, Ford,
and D’Amelio (2008) discuss. We adopt the perspective of individual employees
because they are best suited to provide a measure of their own perceived resistance to
change (Armenakis & Harris, 2009; Oreg et al., 2011).
As part of our baseline mediation model, we examine the relationship between
change resistance and two critical antecedents—supportive leadership and organiza-
tion fairness—as well as the relationship between change resistance and two important
outcomes—individual commitment to the organization and perceived organizational
effectiveness. Underlying our model is an interactionist perspective that explains orga-
nization behavior in terms of relationships between the individual and the organiza-
tion. From an interactionist perspective, change is a process enacted or placed on
individual employees by the organization. So in choosing antecedents, we selected
concepts that best represent an organization’s change management behaviors from the
employee’s perspective. Organization fairness and supportive leadership represent
two central concepts that personify the organization while an organization is undergo-
ing change (Riolli & Savicki, 2006). They connect the organization to the individual,
486 The Journal of Applied Behavioral Science 52(4)

capturing the juncture between organizational management and individual experience.

They also demonstrate important connections with change reactions in prior research
(Oreg et al., 2011). Similarly, organizational commitment and perceived organiza-
tional effectiveness represent important constructs that connect the individual to the
organization in both retention and performance, and they have demonstrated connec-
tions with change reactions in prior research (Oreg et al., 2011).
In the context of prolonged organizational change, the basic proposition is that time
alters the relationships between change resistance and its antecedents and outcomes.
Specifically, we propose that these relationships will be amplified as the duration of
individuals’ experiences with change lengthens for at least two reasons. First, as
change progresses over time, the way employees interpret the change differs (Isabella,
1990). As change progresses, there is a shift from anticipatory to realized effects of
change, which alter the nature of resistance and which amplify the negative influence
of change resistance on employee outcomes. Second, prolonged, frequent experiences
with organizational changes decrease the patience and increase the anxiety of employ-
ees as they deal with ambiguity (Rafferty & Griffin, 2006). Without appropriate mana-
gerial and organizational support (Williams, 2007), prolonged change can harden the
view that changes are threats, and can lead to amplified resistance over time (Staw,
Sandelands, & Dutton, 1981).
Based on this proposition, we now derive a few specific hypotheses on the conse-
quences and antecedents of resistance to change that were tested in this research.

Change Resistance and Its Consequences

Organizational Commitment. Organizational commitment captures the affective attach-
ment of employees to their organization, and it denotes the extent to which employees
identify with the organization and internalize the organization’s goals and perspec-
tives (Buchanan, 1974; O’Reilly & Chatman, 1986). It is predictive of turnover and of
prosocial behaviors (O’Reilly & Chatman, 1986; Porter, Steers, Mowday, & Boulian,
1974). Moreover, it has important implications for job performance: Committed
employees are more willing to put forth dedicated effort toward the organization’s
success (Meyer, Paunonen, Gellatly, Goffin, & Jackson, 1989). However, resistance
can reduce employees’ commitment to the organization. Employees who are resistant
to change experience negative emotions—usually due to undesirable change experi-
ences or anticipated adverse consequences. As noted before, organizational changes
are often viewed as outside the control of the individual. These emotions and attribu-
tions can lead the individual to loosen their affective attachment and diminish their
identity with the organization. Judge et al. (1999) found that managers who were
unable to cope successfully with change were also less likely to be committed to the
organization.

Perceived Organizational Effectiveness. According to Cameron (1995), effectiveness is

commonly defined in terms of organizational goal accomplishment. Organizations
typically have multiple goals and must satisfy multiple stakeholders. To reflect this
Jones and Van de Ven 487

reality, we adopted a multidimensional definition of organizational effectiveness in

attaining goals related to profitability, efficiency, quality, customer satisfaction, and
employee morale. Employee perceptions of organization effectiveness provide a key
indicator of organizational performance (McCabe & Dutton, 1993) and match well
with objective measures (Wall et al., 2004). Effectiveness perceptions are influenced
by organizational change initiatives, and employees who perceive change negatively
are likely to view the organization less favorably as their fit in the organization declines
(Caldwell et al., 2004). When commitment for change from organizational members is
low, performance perceptions are likely to be lower (Lok, Hung, Walsh, Wang, &
Crawford, 2005; Oreg et al., 2011). Moreover, employees who have negative experi-
ences with past change efforts are more likely to become suspicious and less willing to
support future change efforts than employees who perceive that past change efforts
have been successful (Reichers, Wanous, & Austin, 1997; Wanous, Reichers, & Aus-
tin, 2000). Thus, past experiences with organizational changes can affect future per-
ceptions of organization effectiveness.

Moderating Impact of Time. Temporal aspects of change are commonly captured by

Lewin’s (1951) three-phase model of unfreezing, changing, and refreezing. Isabella
(1990) built on Lewin’s work to create a cognitive model of phased change in which
employees interpret and construct meaning differently as change progresses. Early
on, employees assemble information to speculate on how change will unfold and
anticipate its impact. Later, as change is concluding, employees revise their interpre-
tations with more certain before-and-after knowledge of the state of the organiza-
tion. This sensemaking process is one that evolves over time as changes unfold
(Balogun et al., 2015). Recognizing this shift in interpretation over time is particu-
larly important for longer term change initiatives such as the strategic initiatives we
study here.
Isabella’s work provides insight into why the impact of change resistance on orga-
nizational commitment and perceived effectiveness can amplify over time. Though
change resistance may remain consistent over time, the interpreted meaning given to
change can shift, leading to stronger relationships with the outcomes we study.
Specifically, early on when change is commencing, change resistance is primarily
concerned with potential negative outcomes in the future. These negative outcomes
have not occurred, but they are anticipated, which leads to change resistance. Even
though resistance may be strong, the impact of resistance on organizational commit-
ment is muted because the negative impact of change is not yet realized. Employees
are still committed because of the uncertainty of their speculated future. Similarly, the
impact of change resistance on perceived organizational effectiveness is muted
because the anticipated future state does not represent the current state of the organiza-
tion. However, as change progresses and resistant employees experience the realized
effects of change, the impact of resistance is amplified. Their interpretation of the
change shifts to become based on before-and-after understandings of the change. Their
resistance remains, but what was anticipatory before is now (in their view) confirmed.
Such change in interpretation leads to reduced trust and belief in the legitimacy of
488 The Journal of Applied Behavioral Science 52(4)

management (Huy et al., 2014). Thus, change resistance in later stages of the change
process is more strongly tied to perceptions of organization effectiveness and organi-
zational commitment. In long-term change initiatives, the interpretive shift plays out
over an extended period, essentially demonstrating a festering effect. Thus, we hypoth-
esize the following:

Hypothesis 1: As change persists, the negative relationship between (a) change

resistance and organizational commitment and (b) change resistance and perceived
organizational effectiveness will be amplified.

Change Resistance and Its Antecedents

With the threat of further decline by employees who are resistant to change, a logical
next question is whether and how organizations can mitigate the negative effects of
resistance in long-term organizational changes programs. We posit below that support-
ive leadership and organization fairness have such potential.

Supportive Leadership. The immediate supervisor is typically an employee’s most

immediate personification of the organization (Nadler & Tushman, 1990). A fun-
damental proposition guiding research on leadership is that individual leaders
establish conditions that influence the ability of employees to achieve organiza-
tion goals. While a myriad leadership theories have been developed, we take our
direction from Yukl (2012), who builds on the classic Ohio State leadership stud-
ies (e.g., Halpin & Winer, 1957; Stogdill, 1974). These studies found that leader-
ship behaviors emphasizing consideration (defined as relationship-oriented
behaviors) and initiating structure (defined as task instrumental or work-related
behavior) are strongly related to employee satisfaction and performance (see
reviews by Behling & Schriesheim, 1976; Yukl, 2012). Supportive leadership is
indicated when employees perceive their immediate supervisors to provide both
consideration and initiating structures for work accomplishment. These elements
of leadership are critical for employees as they traverse organizational change.
The ambiguity and potential threats surrounding change can lead employees to
fear unforeseen negative consequences and to act rigidly against the changes (Staw
et al., 1981). Supportive leadership can ameliorate these fears as well as help indi-
viduals feel that they are an important part of the change process (Coyle-Shapiro
& Marrow, 2003; Martin, Jones, & Callan, 2005; Rafferty & Griffin, 2006). In
support of these arguments, Oreg et al. (2011) found a strong link between sup-
portive leadership and change perceptions in their broad review of the literature on
reactions to change.

Organization Fairness. Organization fairness is captured by the concepts of distribu-

tive and procedural justice. Homans (1961) introduced the concept of distributive
justice, referring to the perceived fairness of reward distribution. Thibaut and
Walker (1975) introduced a related concept, procedural justice, referring to the
Jones and Van de Ven 489

perceived fairness of policies and procedures used to allocate resources (both ben-
efits and costs) among employees. Studies have found that perceptions of distribu-
tive justice are strongly related to job satisfaction and satisfaction with rewards
(Janson, Levy, Sitkin, & Lind, 2008). Procedural justice is also strongly related to
organizational commitment, policy and procedure acceptance, and minimizing neg-
ative reactions to adverse outcomes such as layoffs or pay cuts (for a review, see
Greenberg, 1990). Thus, employees are more likely to be willing to exert effort to
implement organizational changes if they perceive that limited resources are dis-
tributed fairly, that the organization treats employees fairly, and that the organiza-
tion follows due process procedures (Janson et al., 2008). In her study of ongoing
change in a European human resources firm, Kiefer (2005) found that the organiza-
tion’s treatment of its employees was tied to the employees’ negative or positive
emotions during change. These arguments suggest that organization fairness will
foster less resistance to change.

Moderating Impact of Time. Notions of threat rigidity are useful for understanding why
the relationships between these antecedents and change resistance can become ampli-
fied over time. Threat rigidity argues that changes in one’s environment can be inter-
preted as a threat to one’s welfare, which can lead to rigid responses that follow
well-learned behaviors (Staw et al., 1981). For instance, a major strategic change can
lead to loss of power, responsibility, or status, which can lead employees to be more
insistent on maintaining the status quo. Importantly, change can be particularly threat-
ening when it is frequently experienced. This is because change is not seen as a dis-
crete event but as a continuing saga—one that is highly uncertain (Rafferty & Griffin,
2006). Long-term organizational change containing many change components repre-
sents such a case. Individuals are apt to become strongly entrenched in their resistant
positions during later stages of a change process because of the continual threat they
have experienced.
Managers and organizations can work to alleviate rigidity by adopting threat-man-
agement practices, which have the effect of building trust and cooperation (Williams,
2007). Supportive leaders who help employees see a successful path forward through
the change and who empathize with them can reduce the threatening nature of the
change. Organization fairness can reduce threats of unequal or unwarranted loss due
to change. We argue that supportive leadership and organization fairness can have
even greater impact at later stages of a change initiative because individuals’ reactions
to change threats are apt to be more pronounced. In other words, without supportive
leadership and organization fairness, individuals are prone to feel more threatened
later on in the change process than initially. Thus, more fair and supportive environ-
ments are likely to have greater effect on change resistance later in the change process
and less effect earlier in the process:

Hypothesis 2: As change persists, the negative relationship between (a) supportive

leadership and change resistance and (b) organization fairness and change resis-
tance will be amplified.
490 The Journal of Applied Behavioral Science 52(4)

Method
Field Research Setting
This research examines three annual employee surveys, from 1997 to 1999, which are
part of a larger longitudinal study of ongoing organizational integration changes in a large
Midwest-managed health care system in the United Status. This system, which we call
Midwest, emerged as a vertically integrated health care provider (with 20,000 employees
and $2 billion in revenue) through a merger in 1994 of 15 hospitals, 40 primary care clin-
ics, a variety of homecare and ancillary services, and several health insurance plans that
cover more than one million people. From 1994 to 2002, our study tracked the formation
and integration of Midwest’s medical group of primary care clinics, with the most signifi-
cant changes in organizational integration occurring from 1997 to 1999.
Integrating the clinics entailed numerous change projects. Following the Burke and
Litwin (1992) model, this is best described as a massive transformational and transac-
tional change. The transformation change included a significant shift in the strategy of
Midwest as it vertically integrated and diversified into other health care activities and
as it worked to integrate the cultures of disparate acquisitions. The transactional
changes included new structures, management practices, systems, and climate during
the integration phase.
More specifically, group managers consolidated some previously stand-alone clinics
to decrease operating expenses, requiring clinic staff and physicians to accommodate
new locations and new working relationships. The group practice negotiated a uniform
payment reimbursement contract with health insurance companies that treated all clinics
as one provider. This represented a major departure from the previous procedure where
individual (and more-or-less powerful) clinics negotiated their own reimbursement con-
tracts with health plans. The group developed and implemented uniform and consoli-
dated patient billing, supplies purchasing, equipment maintenance, and laboratory
services. These changes required clinics to sever some old vendor relationships and
develop new relationships, and sometimes to let go of staff who had provided these func-
tions within the clinics. With extensive physician input, several group-wide initiatives
were also undertaken, such as clinical care quality improvement, drug formularies, and
risk management programs. The group also adopted some new operating procedures,
including a system allowing same-day scheduling for patients and automated electronic
medical records. To promote equity in compensation and improve productivity in all
clinics, a uniform compensation system for all clinic employees was adopted, and a
standardized physician productivity metric was implemented based on an industry stan-
dard of relative value per unit of care (RVU). These are just a few of many changes that
the medical group and its clinics implemented over the 3-year integration period.

Data Collection
Measurements of employee change resistance and their antecedents and conse-
quences were obtained using a survey questionnaire that was distributed to all
Jones and Van de Ven 491

Midwest employees annually to empirically track Midwest’s organizational develop-

ment and change journey over time. Following a pilot test in 1996, annual Midwest
employee surveys were conducted from October to December in each of 1997, 1998,
and 1999 (corresponding to Years 1, 2, and 3 in our sample). Each year, our research
team mailed the survey with return addresses and stamped envelopes to all 2,600
Midwest employees who worked in clinic locations. We sent three follow-up letters,
each 2 or 3 weeks apart, either thanking respondents for completing their surveys or
reminding them to complete their survey. The response rate to each survey was 37%
in Year 1, 33% in Year 2, and 33% in Year 3. Response rates varied by occupational
group, with average response rates of 43% from managers, 44% from physicians,
29% from clinical support, and 33% from administrative staff.
In the annual surveys, the majority of respondents identified themselves by name,
allowing us to track their perceptions of organizational change over time. A total of
289 employees responded to all three surveys and 316 employees responded to two
consecutive surveys (Years 1 and 2 or Years 2 and 3). Our final sample included 1,478
employee-year observations from the 605 employees.
We tested for nonresponse bias by comparing the responses of employees in our
sample with employees who responded at least once, but who did not provide suffi-
cient responses to merit inclusion in our longitudinal analysis. We conducted t tests to
see whether the mean response for change resistance, perceived organizational effec-
tiveness, or organizational commitment was significantly different between the two
groups, but no significant difference was found.
Because we used the surveys completed by the same people to collect independent
and dependent variables, common method variance is of potential concern. However,
our hypotheses only examine moderated relationships, which limits the risk of com-
mon methods variance (Evans, 1985).

Variables
Table 1 presents the factor loadings from confirmatory factor analysis of all items used
to measure the variables in the annual survey, along with internal consistency reliabili-
ties (coefficient alpha) of items in each index in Year 1. The results of this psychomet-
ric analysis found good evidence for convergent and discriminant validities
(comparative fit index [CFI] = 0.94; nonnormed fit index [NNFI] = 0.93; root mean
square error of approximation [RMSEA] [90% confidence interval] = 0.056 [0.054,
0.059]). All items intended to measure one of the four constructs converged with high
loadings on a single factor and clearly discriminate by having low loadings on all other
factors. Alpha values and construct loadings were very similar in Years 2 and 3 as well.
The items used to measure these constructs are now briefly described.

Organizational Commitment. Organizational commitment was measured using the

average response to three items initially developed by Porter et al. (1974), which cap-
ture the affective attachment that employees feel toward Midwest (coefficient α = .79).
Items were presented on a 5-point scale (1 = disagree strongly, 5 = agree strongly).
492 The Journal of Applied Behavioral Science 52(4)

Table 1. Constructs and Items (Confirmatory Factor Analysis).

Loading SE t value Coefficient α

Perceived organizational effectiveness (Rate you clinic on . . . ) .85
Quality of services provided 0.70 0.02 48.29
Amount of work produced 0.48 0.02 29.81
Cost efficiency of services provided 0.55 0.02 34.79
Patient or customer responsiveness 0.79 0.02 47.94
Financial profitability 0.51 0.02 27.67
Improving patient health 0.63 0.02 43.12
Organizational commitment .79
I am proud to be part of Midwest 0.94 0.02 49.42
I do not feel a strong sense of belonging 0.76 0.02 31.56
to Midwesta
What Midwest stands for has a great 0.83 0.02 39.75
deal of personal meaning for me
Change resistance (Extent to which you . . . ) .83
Are kept informed about changes going 0.60 0.02 31.87
on in Midwesta
Are given opportunities to influence 0.60 0.02 33.14
these changesa
Are confident in the Midwest leaders 0.90 0.02 54.52
directing these changesa
Support these changesa 0.74 0.02 49.21
Can influence Midwest policies and 0.69 0.02 29.00
proceduresa
Supportive leadership (Extent to which leader . . . ) .83
Gives constructive feedback about your 0.89 0.02 41.72
work
Emphasizes getting the work 0.68 0.02 28.24
accomplished
Emphasizes maintaining interpersonal 0.97 0.02 45.33
working relationships
Encourages you to do your best work 1.14 0.02 52.14
Organization fairness .83
Midwest managers treat me fairly 0.84 0.02 43.36
Midwest treats all its employees fairly 0.92 0.02 47.66
Midwest treats patients fairly 0.63 0.02 36.38
Programs and policies at Midwest are 0.78 0.02 45.22
fair
I am rewarded fairly for my effort 0.65 0.03 26.17

Note. N = 2,490; χ2 (df) = 1956.7 (220); p < .001; comparative fit index (CFI) = 0.94; nonnormed fit index
(NNFI) = 0.93; root mean square error of approximation (RMSEA) [90% CI] = 0.056 [0.054, 0.059]. All
loadings significant at p < .001.
aReverse coded.
Jones and Van de Ven 493

Perceived Organizational Effectiveness. Perceived organizational effectiveness was mea-

sured using the average response to six questions asking respondents to assess output
quality, quantity, efficiency, profitability, and responsiveness to patients. Items were pre-
sented on a 5-point scale (1 = not at all, 5 = to a great extent). The measures were ini-
tially developed and evaluated by Van de Ven and Ferry (1980). We changed names of
the organizational units to which the survey questions applied, such as “clinic” or “health
care system” and to the goals set by Midwest leaders during this period of organizational
change (as described above). The measure captures important dimensions of effective-
ness that concern customers (i.e., patients), investors, and employees. The six items
comprising this multidimensional index are listed in Table 1 (coefficient α = .82).

Change Resistance. Change resistance was measured using the average response to five
items (coefficient α = .83). Items were presented on a 5-point scale (1 = not at all, 5 =
to a great extent). Oreg et al. (2011) and Piderit (2000) recognized that change resis-
tance can have behavioral (or intentional), cognitive, and emotional dimensions,
which denote an overall attitude toward change. A limitation of our study is that we did
not measure the emotional dimension of change resistance. Instead, our scale includes
three behavioral and two cognitive items. The behavioral measures focus on the extent
to which employees are informed of organizational changes and are given opportuni-
ties to influence organizational changes and policies. Armenakis and Harris (2009)
emphasized the importance of including a behavioral measure of participation because
“without participation, genuine buy-in to sustainable change is unlikely” (p. 130). The
cognitive dimension of resistance includes items on the extent to which employees
support the organizational changes and change leaders. These items capture employ-
ee’s attitudes toward change, whether positive or negative. We reverse the coding on
the items to present employee attitudes in the negative, as change resistance.

Supportive Leadership. Supportive leadership refers to behaviors of leaders that support

people in doing their work by providing constructive feedback, building interpersonal
relationships, and encouraging work accomplishment. Table 1 lists the four items used
to measure supportive leadership (coefficient α = .83). Items were presented on a
5-point scale (1 = not at all, 5 = to a great extent). These measures were based on Van
de Ven and Chu’s (1989) index of leadership supportiveness.

Organization Fairness. Organization fairness is defined as the extent to which respon-

dents perceive that the organization’s managers behave fairly, the organization’s pro-
grams and policies are fair, and employees are rewarded fairly for their efforts. Fairness
was measured by the five items listed in Table 1 (coefficient α = .83). Items were
presented on a 5-point scale (1 = not at all, 5 = to a great extent). These measures were
adapted from research conducted by Wallace (1995) and Price and Mueller (1981).

Time. Time was measured as an ordinal value: Years 1, 2, and 3 were coded as 0, 1,
and 2, respectively.
494
Table 2. Descriptive Statistics and Cross-Year Correlations.
Year 1 Year 2 Year 3

Mean SD (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17)

Year 1 (1) Organizational 3.10 0.94

commitment
(2) Perceived effectiveness 3.66 0.64 0.13
(3) Change resistance 3.34 0.78 −0.66 −0.17
(4) Supportive leadership 2.88 1.00 0.36 0.20 −0.40
(5) Organization fairness 3.25 0.82 0.60 0.23 −0.72 0.36
Year 2 (6) Organizational 3.04 0.98 0.69 0.11 −0.66 0.37 0.50
commitment
(7) Perceived effectiveness 3.66 0.69 0.20 0.57 −0.25 0.22 0.25 0.24
(8) Change resistance 3.40 0.78 −0.54 −0.15 0.71 −0.37 −0.54 −0.70 −0.32
(9) Supportive leadership 2.82 1.07 0.31 0.11 −0.31 0.58 0.27 0.39 0.24 −0.44
(10) Organization fairness 3.15 0.83 0.54 0.19 −0.65 0.29 0.64 0.67 0.30 −0.70 0.40
Year 3 (11) Organizational 3.02 0.97 0.66 0.07 −0.56 0.30 0.41 0.69 0.19 −0.62 0.37 0.52
commitment
(12) Perceived effectiveness 3.58 0.66 0.27 0.49 −0.28 0.21 0.26 0.26 0.55 −0.33 0.19 0.27 0.34
(13) Change resistance 3.43 0.81 −0.52 −0.17 0.65 −0.39 −0.48 −0.60 −0.26 0.74 −0.41 −0.56 −0.71 −0.37
(14) Supportive leadership 2.88 1.02 0.24 0.09 −0.25 0.54 0.21 0.28 0.12 −0.35 0.63 0.29 0.36 0.22 −0.40
(15) Organization fairness 3.16 0.85 0.46 0.18 −0.52 0.22 0.53 0.46 0.22 −0.57 0.30 0.63 0.62 0.35 −0.66 0.32
(16) Log FTEs 4.33 0.90 −0.09 −0.18 0.09 −0.06 −0.06 −0.14 −0.01 0.11 −0.02 −0.09 −0.15 −0.15 0.12 0.01 −0.10
(17) Gender 0.76 0.43 −0.11 −0.09 0.25 0.05 −0.26 −0.09 −0.02 0.18 0.08 −0.24 −0.03 −0.02 0.10 0.08 −0.22 0.02
(18) Age 44.45 9.67 −0.06 0.05 0.01 −0.07 −0.02 −0.01 0.00 0.03 −0.15 0.02 0.00 0.01 0.00 −0.11 0.04 −0.01 −0.12

Note. FTE = full-time equivalent; SD = standard deviation.

 Table 3. Linear Mixed Effects Regression.

Model 1: Mediation Model 2: Moderated mediation

Change Organizational Perceived Change Organizational Perceived

resistance commitment effectiveness resistance commitment effectiveness
Constant 4.64*** 3.78*** 3.49*** 4.68*** 3.48*** 3.16***
Time 0.03* 0.00 −0.02 0.02 0.17* 0.18**
Log FTEs 0.02 −0.06* −0.10** 0.02 −0.06* −0.10*
Gender (1 = female) 0.09 −0.14 0.09 0.08 −0.14 0.08
Age 0.00 0.00 0.00 0.00 0.00 0.00
Job category Included Included Included Included Included Included
Supportive leadership −0.11*** 0.04 0.08*** −0.06** 0.04* 0.08***
Organization fairness −0.47*** 0.41*** 0.14*** −0.52*** 0.41*** 0.14***
Change resistance −0.34*** −0.09** −0.28*** −0.04
Supportive leadership * Time −0.05**
Organization fairness * Time 0.05*
Change resistance * Time −0.05* −0.06**
Log likelihood −3756.9 −3744.8
Chi-square test 25.7(4)***

Note. Observations = 1,478; employees = 605; clinics = 40. Chi-square test compares the fit of Model 1 with Model 2; degrees of freedom (dfs) are in
parentheses. FTE = full-time equivalent.
*p < .05. **p < .01. ***p < .001 (two-tailed tests).

495
496 The Journal of Applied Behavioral Science 52(4)

Figure 2. Moderating impact of time on the resistance–outcome relationships.

Controls. We included controls for employee age, gender, and job category. Job cate-
gory is a set of six binary dummy variables capturing an employee’s role in the orga-
nization: executive, manager, physician, nonphysician clinician (e.g., physician
assistant), clinical support staff (e.g., nurse), and administrative support staff (e.g.,
receptionist). We also included a control for clinic size (as the log of the full-time
equivalents [log FTE]).

Analysis and Results

Modeling Strategy
We used a linear mixed effects model to test our hypotheses. Using a linear mixed
effects model has a couple of advantages. First, it adjusts for employees being nested
in clinics and for observations over time nested in individuals. We included random
effects for clinic and individual, which adjust for nonindependence between observa-
tions. Second, following the procedure introduced by Bauer, Preacher, and Gil (2006),
we jointly estimated the effects of the antecedents on change resistance and the effect
of change resistance on our two outcomes. This approach “stacks” the usual Steps 2
and 3 in Baron and Kenny’s (1986) three-step mediation process in one system of
regression equations. This allows us to estimate the direct and indirect effects simulta-
neously, which overcomes concerns with the usual low power of the independent steps
process (MacKinnon, Fairchild, & Fritz, 2007). In using this method, we do not show
the traditional Step 1 (X → Y) in the mediation process. Instead, our analysis mirrors
mediation tests done using structural equation models, where Step 1 is implicit (James,
Mulaik, & Brett, 2006).
Jones and Van de Ven 497

Figure 3. Moderating impact of time on the antecedent–resistance relationships.

Tests of Hypotheses
Table 2 displays the means, standard deviations, and bivariate correlations among all
variables. Change resistance and its antecedents and outcomes are broken down by
year. Table 3 displays two regression models. Model 1 displays the baseline mediation
model. Model 2 adds the moderating impact of time to both the antecedent and out-
come relationships. Column 1 in Model 1 indicates that greater supportive leadership
(β = −0.11; p < .001) and organization fairness (β = −0.47; p < .001) are both predictive
of lower change resistance. Columns 2 and 3 in Model 1 show that greater change
resistance predicts lower organizational commitment (β = −0.34; p < .001) and per-
ceived organization effectiveness (β = −0.07; p < .01). Tests for the significance of the
indirect effects through change resistance were all significant at the .05 level or lower
(Preacher, Rucker, & Hayes, 2007). Thus, the main effects are in line with our expecta-
tions and set the basis for testing the moderating effect of time.
We use columns 2 and 3 in Model 2 to test Hypothesis 1. In support of Hypothesis
1a, the negative relationship between change resistance and organization commitment
becomes significantly more negative over time (β = −0.05; p < .05). In support of
Hypothesis 1b, the negative relationships between change resistance and perceived
effectiveness also become significantly stronger (β = −0.06; p < .01). Thus, Hypothesis
1 is supported overall. The estimations in Model 2 are depicted in Figure 2. The figure
presents the predicted effect of change resistance on organization commitment and
perceived effectiveness at Years 1 and 3. The effect of change resistance on organiza-
tional commitment and perceived effectiveness are more pronounced in Year 3 versus
Year 1.
498 The Journal of Applied Behavioral Science 52(4)

Table 4. Fixed Effects Regression.

Model 3 Model 4 Model 5

Change Organizational Perceived

resistance commitment effectiveness
Constant 5.45*** 2.47*** 2.26***
Time 0.06 0.17* 0.21**
Log FTEs 0.01 −0.03 0.00
Supportive leadership −0.02 0.04 0.09**
Organization fairness −0.38*** 0.32*** 0.11***
Change resistance −0.27*** −0.01
Supportive leadership * Time −0.05**
Organization fairness * Time 0.04*
Change resistance * Time −0.05* −0.07***
R2 0.836 0.844 0.742

Note. Observations = 1,478. Fixed effects for employees and clinics included but not shown. FTE = full-
time equivalent.
*p < .05. **p < .01. ***p < .001 (two-tailed tests).

We also use Model 2 to test Hypothesis 2. We found support for Hypothesis 2a but
not Hypothesis 2b. Column 1 of Model 2 indicates that the negative relationship
between supportive leadership and change resistance becomes significantly more neg-
ative with time (β = −0.05; p < .01). However, contrary to expectations, the negative
relationship between organization fairness and change resistance becomes signifi-
cantly less negative with time (β = +0.05; p < .01). Figure 3 illustrates the change
impact of leadership support and fairness. The figure is based on the estimates in
Model 2 and, in the left panel, illustrates that supportive leadership has much greater
impact on change resistance in Year 3 than in Year 1. The right panel illustrates that
over time a fair environment loses some of its influence to combat change resistance
(though it is still significant).
We also tested whether the indirect effect of the antecedents on the outcomes
through change resistance were significant after accounting for the moderating effect
of time (Preacher et al., 2007). In Year 3, supportive leadership and organization fair-
ness had significant indirect effects on organizational commitment and perceived
effectiveness at the .05 level or lower. In Year 1, their indirect effects on organizational
commitment were significant, but their indirect effects on perceived effectiveness
were not.

Robustness Check
One concern with our analysis is that there may be unobservable attributes of individu-
als or clinics that we do not account for that could potentially bias our results. To
account for this possibility, we ran an additional model that includes fixed effects for
Jones and Van de Ven 499

individuals and clinics. We used the same sample of individuals for this test (1,478
employee-year observations from 605 employees). The fixed effects account for all
stable traits of employees and stable characteristics of clinics that we do not measure.
For instance, the fixed effects will account for stable individual differences in an
employee’s tendency to resist change (Oreg, 2003) as well as other personality traits.
The model eliminates between-person variance so that we only observe within-person
effects. In other words, this analysis demonstrates how relationships with resistance to
change differ within an individual over time.
In using a fixed effects (instead of random effects) specification, we separate the
outcome variables (i.e., change resistance, organization commitment, and perceived
effectiveness) into three separate regression equations. The results of the fixed effects
regressions are shown in Models 3, 4, and 5 of Table 4. Because we use fixed effects
gender, age, and the job categories drop out of our models. Models 3 to 5 indicate that
the findings in this alternative specification are consistent with the findings in Model 2.

Discussion
This longitudinal research empirically examined whether relationships between ante-
cedents and consequences of change resistance strengthen or weaken over time during
an extended duration of organizational changes. Based on a study of health care clinics
undergoing a 3-year period of significant organizational changes, we found that resis-
tance to change had increasingly negative relationships over time with employees’
commitment to the organization and perceptions of organizational effectiveness. We
discovered that these relationships become stronger (rather than weaker) over time,
suggesting that there are important festering effects of resistance to change. We also
found that the relationship between supportive leadership and change resistance was
increasingly negative over time. This suggests that supportive leadership has a greater
ability to ameliorate change resistance at later stages of a change initiative. Contrariwise,
we found evidence that organization fairness had a stronger influence on reducing
change resistance during the early stages of change instead of the latter. Currently
these findings are limited to our study, and further research is needed to replicate our
findings in different settings. Still, these findings suggest important implications for
theory and practice.

Implications for Theory

In terms of theory, the novel contribution of this research is that it empirically estab-
lishes a moderating effect of time on the antecedents and consequences of organiza-
tional change resistance. Contrary to the common adage that “time heals all wounds,”
we found the effect of change resistance on important organizational outcomes to
become stronger (rather than weaker) over time. In other words, the negative effects of
resistance to change grow over time. As change unfolds, the nature of resistance
changes (Isabella, 1990), leading to more negative outcomes. These increasingly neg-
ative effects of resistance to change call attention to the need for theories and research
500 The Journal of Applied Behavioral Science 52(4)

that go beyond cross-sectional analysis and examine the temporal implications of

employee perceptions and experiences on individual and organizational performance.
This study also introduces the idea that we not only need to conceptualize “how to
manage change,” but also “what to manage when.” Our findings suggest that organiza-
tion fairness is more important early on in change process and supportive leadership is
more important later on. It was surprising that organization fairness mattered more
earlier instead of later as we hypothesized. On reflection, we give a tentative explana-
tion. First, we recognize that supportive leadership fits well with the theory of threat
management or threat regulation (Williams, 2007). Within threat regulation theory,
perspective taking, threat-reducing behaviors and reflection are practices that reduce
threats. These same behaviors can be categorized as relationship-oriented (consider-
ation) and task-oriented (initiative structure) behaviors that supportive leaders use
(Yukl, 2012). However, organization fairness may not capture these same behaviors
important for threat regulation. It may be working through a different mechanism.
Perhaps the importance of organization fairness is to reduce early uncertainty that
arises when changes are introduced (DiFonzo & Bordia, 1998; Lind & Van den Bos,
2002), such that its effect is stronger during the early stages of change.

Implications for Practice

For managers and change agents, dealing with positive and negative employee
responses to a change initiative represent some of the most time-consuming and frus-
trating experiences in managing an organizational change process (Burke, Lake, &
Paine, 2008). A major implication of this research is that managers must help employ-
ees engage positively in change initiatives throughout the process, not just at the
beginning. If resistance is ignored, its effect may fester into declining organization
effectiveness and employee commitment to the organization. This suggestion appears
especially important when organizations undertake major strategic initiatives (like the
systems integration effort examined here) that entail many changes ongoing for long
periods of time. While some organizational changes may be as brief as a month or two,
these strategic initiatives can take years to accomplish. When change is first intro-
duced there is an abruptness to it that can trigger resistance to the change. Lewin
(1951) posited in his force dynamics theory that equilibrium in organizational pro-
cesses are driven by inertial forces. His notion of unfreezing suggests that inertial
forces must be overcome to introduce a period of fluidity and change. However, one
should not assume that entering a period of fluidity means that the effect of resistance
will diminish (just because plans are moving forward). On the contrary, resistance
later on has even greater negative effects on employees’ attachments and views of an
organization’s achievement.
Additionally, treating employees fairly and providing supportive leadership can
counteract the effect of resistance to change, but each having more or less effect at
different stages. Fairness fosters less resistance to change because employees are more
likely to support organizational changes when they perceive that people are treated
fairly, resources are distributed fairly, and due process procedures are followed. It is
Jones and Van de Ven 501

important throughout a change process, but should be particularly focused on at the

beginning so that employees can see early on that the initiative will be justly executed.
Moreover, while fairness is important, providing supportive leadership may be even
more important in mitigating the negative effects of resistance to change over time. A
supervisor represents an employee’s most direct personification of an organization
(Yukl, 2012). Employees will feel less threatened when this supervisor is viewed as
providing socioemotional consideration for employee needs and concerns and task-
instrumental directions in the organizational change process.
One question managers may have is whether the findings in this health care context
will also apply to their business context. The health care industry is characterized by
dual hierarchies (e.g., administrative and professional), multiple competing goals
(Cyert & March, 1963; Simon, 1964), and conflicting institutional logics (Currie &
Guah, 2007; Thornton, Ocasio, & Lounsbury, 2012). This conflict naturally creates
resistance among some employees as change shifts health care organizations toward
one logic and away from another. For employees who find the organization moving
away from what they think it should be, a festering effect is likely. For any industry
where conflicting logics and dual hierarchies are present—such as education—it is
probable that the festering effect of change resistance will also be found. The effect
may appear in a broad variety of industries beyond, but we estimate the effect to be
most pronounced in organizations like health care organizations that frequently deal
with competing institutional logic and goal tensions.

Limitations
While the response rate was within the range or better than other studies in health care
(e.g., Shortell, Gillies, Anderson, Erickson, & Mitchell, 2000), there is the possibility
that our results are affected by nonresponse bias. We tested for nonresponse bias and
found no evidence of it, but we cannot completely rule out the possibility. We specu-
late that if nonresponse bias did exist and if we were able to collect data from nonre-
sponders, our results would be stronger or more pronounced. It is likely that those who
were most disgruntled with the change left Midwest (so that we could not collect
longitudinal data from them) or that they avoided the survey process. Such individuals
are the employees most likely to demonstrate the festering effect.
We also recognize that we do not build the emotional dimension of change resis-
tance into our measure (Piderit, 2000). This means that we do not observe the moderat-
ing effect of time on the affective dimension of change resistance. However, we are
able to demonstrate the moderating effect of time on the behavior and cognitive
dimensions. Additional research is warranted to capture and observe the affective
dimension of change resistance to understand its interplay with time.

Conclusion
This longitudinal study of a large change initiative in a health care organization dem-
onstrates that the relationship between change resistance and its antecedents and
502 The Journal of Applied Behavioral Science 52(4)

outcomes strengthen with time. This festering effect of change resistance amplifies the
negative effect on perceived organizational effectiveness and organizational commit-
ment. A lack of leadership support, which increases change resistance, is also ampli-
fied with time. We suggest that practicing managers must not ignore change resistance
at later stages of change initiatives because of its stronger impact.
As an epilogue, considerable time has passed since our surveys were conducted in
1997 to 1999, and readers may question what happened to the organizational changes
at Midwest health system and if the findings from this study still apply today. Fortunately,
we maintained periodic contacts with informants who were key managers of the health
care organization integration process. Throughout its integration journey from 1994 to
2001, the Midwest health care system experienced numerous conflicts that system
executives were unable to resolve. In 2001, and under public accusations of misman-
agement by government regulators, the health insurance plan was spun off as an inde-
pendent company like it was before the 1994 merger, and the top system officers and
board directors were replaced to manage the remaining hospitals and clinics in the
health care system. Between 2010 and 2014, five informants reported that under new
leadership, policies and procedures were revised that provided greater recognition for
clinic contributions to the system, clinic and hospital division managers were given
equal voice in system decisions, conflicts were addressed more openly and construc-
tively, and there were significant improvements in the morale of clinic employees.
In addition to surfacing the importance of constructive conflict resolution to manage
change resistance, we also observed some poignant anecdotes of the long-lasting con-
sequences of how unresolved conflicts fester into vicious cycles. This was evident in
several follow-up conversations with the ousted system CEO and board chair during
2003-2005, each expressing feelings of being forced out and treated as “political scape-
goats”—being “falsely accused, publicly disgraced,” and their “careers destroyed” by
government regulators who publicly accused them for mismanagement. Moreover, the
negative feelings persist. During a conversation in 2014—13 years after this event
sequence—the former CEO stated that he has had no contact with the government offi-
cial and expressed animosity toward him. Clearly, negative experiences with organiza-
tion change are not forgotten, and some are perpetuated though social reconstructions.
Finally, we believe that the theoretical implications of our study findings apply equally
well today. An individual–organization interactionist perspective was used to explain our
findings, as exemplified by the changing temporal relationships of organizational fairness
and leadership as well as outcomes with individual resistance to organizational changes.
Our findings are consistent with the interactionist perspective, and we expect other orga-
nizational and individual factors to interact in like fashion. Moreover as our findings sug-
gest, we expect these individual–organization interactions to change with time. This
major finding in this study remains an important future research direction.

Acknowledgments
We gratefully acknowledge the contributions of John Bechara, J. Stuart Bunderson, Rhonda
Enleman, Shawn Lofstrom, Russel Rogers, Frank Schultz, Kangyong Sun, Jeffery Thompson,
Jones and Van de Ven 503

and Jisun Yu. As former research team members on this longitudinal research program, they
assisted in data collection and initial ideas that led to this article. We also appreciate the helpful
suggestions of Joel Baum and Pri Shah on earlier drafts of our paper.

Authors’ Note
Both authors contributed equally to the article; authors are ordered alphabetically.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship,
and/or publication of this article.

Funding
The author(s) received no financial support for the research, authorship, and/or publication of
this article.

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