Content uploaded by Neil Paulsen
Author content
All content in this area was uploaded by Neil Paulsen on Dec 05, 2014
Content may be subject to copyright.
Uncertainty during organizational change: Is it all
about control?
Prashant Bordia, Elizabeth Hunt, and Neil Paulsen
University of Queensland, St. Lucia, Australia
Dennis Tourish
Robert Gordon University, Aberdeen, UK
Nicholas DiFonzo
Rochester Institute of Technology
Uncertainty is a major source of psychological strain during organizational
change. This study tested a model of change-related communication,
uncertainty, and control and their relationship with psychological strain, job
satisfaction, and turnover intentions. Self-report data were obtained from staff
at a psychiatric hospital undergoing restructuring. Results indicated that
uncertainty had a direct and an indirect (via feelings of lack of control)
relationship with psychological strain. Partialling out common method
variance led to a complete mediation of this relationship by control. Other
predictions about the relationship of these variables with psychological strain,
job satisfaction, and turnover intentions were supported. Implications for
future research and practice of change communication are discussed.
One of the most difficult aspects of the organizational change experience for
employees is the uncertainty associated with the process and outcomes of the
change (DiFonzo & Bordia, 1998). Not knowing how the change will affect
their advancement opportunities, training requirements, or even if they will
have a job in the restructured or merged organization can be highly stressful.
It has been suggested that people have two fundamental needs in this
connection—predictive needs, concerned with the ability to predict what is
going to happen next, and explanatory needs, concerned with the ability to
explain why things are as they are (Berger, 1987). While management
frequently strives to address this uncertainty through communication, it often
#2003 Psychology Press Ltd
http://www.tandf.co.uk/journals/pp/1359432X.html DOI: 10.1080/13594320444000128
Correspondence should be addressed to Prashant Bordia, School of Psychology, University
of Queensland, St. Lucia, QLD 4072, Australia. Email: prashant@psy.uq.edu.au
PEWO07_03
EUROPEAN JOURNAL OF WORK AND ORGANIZATIONAL PSYC HOLOGY,
2003, 00 (0), 000–000
Pre print version - Published in:
EUROPEAN JOURNAL OF WORK AND ORGANIZATIONAL PSYCHOLOGY, 2004, 13 (3), 345–365
falls short of expectations (Covin, 1993; DiFonzo & Bordia, 1998; Harcourt,
Richerson, & Wattier, 1991; Smeltzer, 1991). The uncertainty and stress lead
to low morale and job satisfaction and valued employees may choose to leave
the organization (Bastien, 1987; Johnson, Bernhagen, Miller, & Allen, 1996).
While the literature on change management has repeatedly noted
uncertainty as a major source of stress during change (Ashford, 1988;
Schweiger & Denisi, 1991), and called for communication practices to deal
with the uncertainty (DiFonzo & Bordia, 1998), it has not elaborated upon
why uncertainty is so aversive. There is a dearth of empirical research
linking uncertainty with negative outcomes such as reduced control and
well-being during organizational change. In this article, we develop and test
a model that outlines the relationships between communication, uncertainty,
control, and well-being. We begin by reviewing the literature on each of the
key variables and predict relationships among them. These relationships will
then be summarized in the form of a theoretical model of uncertainty and its
effects (see Figure 1).
CHANGE COMMUNICATION
Communication is vital to the effective implementation of organizational
change (DiFonzo & Bordia, 1998; Lewis & Seibold, 1998; Schweiger &
Denisi, 1991). Indeed, Lewis and Seibold (1998) conceptualize change
implementation as primarily a communication problem: ‘‘Communication
processes are inherently a part of these implementation activities, including
announcement of change programs, training of users, and users’ interaction
and feedback regarding change programs, to name only a few’’ (p. 96,
original emphasis). Poorly managed change communication results in
widespread rumors, which often exaggerate the negative aspects of the
Figure 1. The hypothesized model with indirect (paths c & e) and direct (path d) effects of
uncertainty.
2BORDIA ET AL.
change (DiFonzo, Bordia, & Rosnow, 1994; Smeltzer & Zener, 1992) and
build resistance towards the change. In the absence of timely communication,
employees may learn about the change from external sources such as the
news media (Bastien, 1987; Richardson & Denton, 1996; Smeltzer, 1991).
Most studies suggest that employees generally prefer to receive information
from immediate supervisors and others within the organizational hierarchy,
rather than from sources perceived as extraneous to organizational
boundaries (e.g., Hargie & Tourish, 2000; Larkin & Larkin, 1994). The
uncertainty that results from disregarding such preferences leads to feelings
of disappointment and distrust of the management (DiFonzo & Bordia,
1998). During and after changes such as mergers or reductions in workforce,
effective communication helps organizations deal with employee uncertainty,
job satisfaction and retention (Bastien, 1987; Johnson et al., 1996).
A major aim of the change communication is to reduce employees’
uncertainty and keep them informed of anticipated events. Bastien (1987)
noted that ‘‘personal uncertainty [during change] is pervasive and must be
managed through communication management’’ (p. 28). In a field
experiment, Schweiger and Denisi (1991) found that uncertainty was lower
in the group that was exposed to a systematic program of change
communication. Similarly, Johnson et al. (1996) found that career future
uncertainty was negatively related to management communication prior to a
reduction in workforce. Therefore, a timely, accurate and trustworthy
communication program that provides information on the reasons for the
change should be successful in preventing or reducing uncertainty among the
affected staff. Thus, we predict that quality of change communication (QCC)
will be negatively related to the amount of uncertainty regarding the change.
While a number of features of the changing organizational context could
lead to a perceived lack of control, we expect communication to be
positively related to control. First, the information gain from communica-
tion should provide knowledge and predictability of events related to the
change, thus increasing a sense of control (Miller, 1981). This implies that
the effects of QCC upon control will be mediated by uncertainty reduction.
Second, in addition to the content of the communication, the implementa-
tion of a systematic program of communication has symbolic value
(Schweiger & Denisi, 1991). When managed effectively, this may lead to
feelings of participation and increased involvement on the part of the
employees, which would enhance their sense of personal control. This
suggests that QCC will have a direct positive relationship with control.
Finally, satisfaction with communication has also been consistently
linked with job satisfaction (Muchinsky, 1977; O’Reilly, 1978, 1980).
Communication clarifies role expectations and enhances performance and
satisfaction (Schuler, 1979). Therefore, we predict that QCC will be
positively related to job satisfaction.
UNCERTAINTY AND ORGANIZATIONAL CHANGE 3
UNCERTAINTY
Uncertainty has been a widely researched topic in communication,
psychology, and the organizational sciences. Research areas that include
uncertainty as a key variable include interpersonal communication (Berger
& Bradac, 1982), environmental uncertainty (Huber & Daft, 1997; Milliken,
1987), new employee socialization (Kramer, 1999; Teboul, 1994), decision
making (Kahneman, Slovic, & Tversky, 1982), role ambiguity (Pearce,
1981), and change communication (DiFonzo & Bordia, 1998; Ellis, 1992;
Schweiger & Denisi, 1991), among others. Our focus in this article is
primarily on change communication. However, we will draw upon other
literatures where appropriate.
Uncertainty has been defined as a characteristic of the environment or a
psychological state. Our focus is on the psychological or phenomenological
uncertainty, based on an individual’s perception, as opposed to an objective
state of the environment. Thus, uncertainty can be defined as ‘‘an individual’s
perceived inability to predict something accurately’’ (Milliken, 1987, p. 136).
Uncertainty is considered to be an aversive state (Schuler, 1980). Not
knowing something about ourselves or the environment around us is
maladaptive as we cannot prepare for or deal with the unknown. This idea
is inherent in several theories that treat uncertainty reduction as a
motivational force. Berger’s uncertainty reduction theory (Berger & Bradac,
1982) and a recent adaptation by Kramer (1999) are examples of this notion in
the communication literature. Uncertainty was accorded a similar role by
Festinger in the theories of social comparison (1954) and by Hogg (Hogg &
Abrams, 1993; Hogg & Mullin, 1999) as a motivation for social or group
identification. It is also considered a primary motivation for rumor generation
and transmission (DiFonzo & Bordia, 1998, 2002; DiFonzo et al., 1994).
1
Uncertainty is widespread during organizational change and transitions
(Ashford, 1988; DiFonzo & Bordia, 1998; Nadler, 1987; Schweiger &
Denisi, 1991; Schweiger & Ivancevitch, 1985). This uncertainty is typically
about the aim, process, and expected outcomes of the change and its
implications for an individual’s job security, future prospects, or changes to
the organizational structure and culture (Buono & Bowditch, 1993; Jackson,
Schuller, & Vredenburgh, 1987). The change literature has also emphasized
the psychological discomfort associated with uncertainty. Miller and Monge
(1985) found that uncertainty was related to anxiety. Schweiger and Denisi
(1991) found that uncertainty had a moderate correlation with stress,
1
2
1
We do acknowledge that people do not always want to reduce uncertainty (Brashers, 2000)
or seek control over personal circumstances (Folkman, 1984). Nevertheless, in general,
reduction of uncertainty and increased control over the change are important for employee well-
being and adaptation to change.
4BORDIA ET AL.
averaging around .30 across several time periods. Ashford (1988) noted
similar relationships between uncertainty and stress (measured using a range
of symptoms such as tiredness, depression, and nervousness). Based on these
findings, we predict that uncertainty will be positively related to employee
well-being outcomes, such as psychological strain.
Further, we propose that uncertainty regarding events and outcomes of
organizational change will lead to a feeling of lack of control. If employees
do not know the nature and consequences of the change upon their job,
status, or reporting structures, they will feel ill-equipped to deal with the
change. In other words, they lack personal control over the change. As
Terry and Jimmieson (1999) assert, ‘‘knowledge of outcomes is a pre-
requisite to the ability to influence the outcomes’’ (p. 95). Berger and Bradac
(1982) claimed that knowledge (i.e., the opposite of uncertainty) is essential
to gain control and achieve desired aims from interpersonal interactions.
Several authors allude to a similar effect in the context of organizational
change. Bastien (1987), in an analysis of employee reactions to mergers,
noted ‘‘uncertainty also seems to be associated with a fear of loss due to
change in locus of control from within the individual (in their known
organizational context) to outside of the individual (in an unknown
organizational context)’’ (p. 29). Albrecht and Adelman (1987) provide a
similar account of the relationship between communication, uncertainty,
and control: ‘‘the significance of supportive communication that reduces
one’s perceptions of uncertainty is that it helps the receiver in developing a
sense of perceived control over stressful circumstances’’ (p. 24). Therefore,
we predict that uncertainty will be negatively related to overall perceptions
of personal control at work.
The discussion above implies two competing perspectives on the effects of
uncertainty on psychological strain. The first predicts a direct effect of
uncertainty upon strain. Thus, uncertainty is considered a stressor in and of
itself. The second would suggest that the effect of uncertainty upon strain is
mediated by control. That is, the reason uncertainty is stressful is because it
leads to a feeling of lack of control. These two competing predictions (i.e.,
direct versus indirect effects of uncertainty upon psychological strain) were
tested in the study reported below.
CONTROL
Greenberger and Strasser (1986) define personal control as ‘‘a psychological
construct reflecting an individual’s beliefs, at a given point in time, in his or her
ability to effect a change, in a desired direction, on the environment’’ (p. 165).
Thus, personal control is a subjective appraisal of control, as opposed to a
role-based objective level of control. Desire for control is considered a
motivational force (Greenberger & Strasser, 1986; Rothbaum, Weisz, &
UNCERTAINTY AND ORGANIZATIONAL CHANGE 5
Snyder, 1982). People dislike being in situations where they lack control and
try to regain control by various means, such as information seeking or
acquiring mastery over a skill domain (Ashford & Black, 1996). Control is an
important determinant of employee well-being at work (Ganster & Fusilier,
1989; Greenberger & Strasser, 1986; Terry & Jimmieson, 1999). Low levels of
control have been associated with learned helplessness (Martinko & Gardner,
1982), decrements in performance (Bazerman, 1982), and poorer psycholo-
gical and physiological well-being (Jimmieson, 2002; Terry & Jimmieson,
1999). In general, the more control we have over stressful events, the less
harmful the consequences of the stressors. Karasek (1979), in the demand
control model, proposed that control buffers the negative impact of
workplace stressors, such as high workload. Thus, the stress literature has
also considered control as a moderator variable, though with mixed success
(Terry & Jimmieson, 1999). There is more consistent support for the direct
effects of work control on psychological well-being (Fletcher & Jones, 1993;
Greenberger, Strasser, Cummings, & Dunham, 1989). We are interested in
this direct effect of lack of control brought about by organizational change.
Based on previous research on work control, we predict that control will be
negatively related to psychological strain.
PSYCHOLOGICAL STRAIN, JOB SATISFACTION,
AND TURNOVER INTENTIONS
At the individual level, one of the most harmful impacts of the
organizational change experience is reduced psychological well-being, as
evidenced in heightened emotional exhaustion and other stress symptoms
(Ashford, 1988; Jackson et al., 1987; Miller & Monge, 1985; Schweiger &
Denisi, 1991; Terry, Callan, & Sartori, 1996). The uncertainty and lack of
control over issues of great personal significance (such as, job security,
status, or training needs) lead to a feeling of being overwhelmed by events.
The strain caused by the change experience leads to lowered job satisfaction
and higher intention to leave the organization (Johnson et al., 1996;
Schweiger & Denisi, 1991). For example, Miller, Ellis, Zook, and Lyles
(1990) found that emotional exhaustion at work led to lower job
satisfaction. Johnson et al. (1996) found that employees who felt uncertain
about their future in a downsizing organization had low job satisfaction and
high turnover intentions. Therefore, we predict that psychological strain as a
result of uncertainty and lack of control during change will be negatively
related with job satisfaction and positively with turnover intentions.
Empirical research has consistently found a negative correlation between
job satisfaction and turnover intentions (Cotton & Tuttle, 1986; Lum,
Kervin, Clark, Reid, & Sirola, 1998; Mobley, Griffeth, Hand, & Meglino,
1979). Based on the large amount of evidence for this relationship, we
6BORDIA ET AL.
predict a negative relationship between job satisfaction and turnover
intentions.
THE PROPOSED THEORETICAL MODEL
Figure 1 describes the theoretical relationships hypothesized in the preceding
sections. Thus, the model proposes that QCC will be negatively related to
the amount of uncertainty experienced by employees (path a). QCC will also
be positively related to control (path b) and job satisfaction (path i).
Uncertainty will be negatively related to control (path c). Further, it could
either have an indirect relationship with psychological strain (mediated
through control; paths c and e) or a direct positive relationship (path d).
Control will be negatively related to psychological strain (path e).
Psychological strain will be negatively related to job satisfaction (path f)
and positively related to turnover intentions (path g). Finally, job
satisfaction will be negatively related to turnover intentions (path h).
While our model only includes QCC as a determinant of uncertainty, we
do not imply that QCC is the sole source of variance in uncertainty. Indeed,
there are many other reasons why perceptions of uncertainty may vary from
one employee to another, even when they are part of the same organization
undergoing change. These sources of variance in uncertainty may include
the extent to which change impacts upon an employee, individual differences
in appraisal of situations as threats or opportunities (Schuler, 1980),
uncertainty orientation (Sorrentino, Holmes, Hanna, & Sharp, 1995), and
structural variables such as hierarchical level in the organization (Clare &
Sanford, 1996; Jabes, Jans, Frazer-Jans, & Zussman, 1992). However, of
these, only change communication is directly under the control of change
managers. Thus, the study of the effectiveness of change communication has
practical implications for management of uncertainty and is the primary
focus of this study. Also, perceptions of the quality of communication could
vary from one employee to another, even when ostensibly they have been
exposed to the same program of communication. These sources of variance
in perceptions of quality of communication may include trust in the source
(Rousseau & Tijoriwala, 1999) and whether the communication meets
individual information needs (DiFonzo & Bordia, 1998; Smeltzer, 1991).
METHOD
Sample and procedure
Data to test the proposed model were collected from staff at a psychiatric
hospital undergoing large-scale restructuring which involved redefinition of
jobs, changes to organisational structure, and a move to a new building.
UNCERTAINTY AND ORGANIZATIONAL CHANGE 7
Surveys were distributed to all staff (N= 660) a week before major staff
redeployment decisions were announced and uncertainty was expected to be
high. A memorandum from management informing staff of the survey and
requesting their participation was included with the survey. Respondents
were given the option of returning the surveys in a sealed envelope via
internal mail, directly to the research team. Alternatively, a member of the
research team visited staff in their work units for 2 days following survey
distribution and staff was encouraged to return surveys directly to the
researcher at this time. A total of 222 employees returned completed
surveys. The age range of these participants was between 18 and 63 years
with a mean age of 42.6 years. There was an approximately equal
distribution of males (47.7%) and females (46.4%) in the sample.
Measures
The survey measure contained scales for each of the variables in the model.
Some of the scales were developed for this study, while others were adapted
from pre-existing measures (see details below). All items used to measure the
constructs in this study are listed in Table 1.
Quality of change communication (QCC). QCC was measured by a
seven-item scale developed for the purpose of this study. Respondents were
asked to rate the change communication on various dimensions, such as
informativeness and accuracy obtained from the change communication
literature (Miller & Monge, 1985; Miller et al., 1990; Richardson & Denton
1996; example item, ‘‘the official information provided about the change
communicates the reasons for the change’’). The responses were made on a
7-point response format (1 = strongly disagree to 7 = strongly agree).
Uncertainty. A nine-item scale was designed to measure uncertainty
during change. The items, some of which were adapted from Schweiger and
Denisi (1991), asked respondents to indicate how uncertain they were
regarding effects of the change for the structure of the organization and the
nature of their work (e.g., whether they will have to learn new job skills,
whether they will have to relocate to another section of the hospital, etc.).
The responses were made on a 7-point response scale (1 = not uncertain at
all to 7 = very uncertain).
Control. Measures of control used in previous research tend to be about
job control (Smith, Tisak, Hahn, & Schnieder, 1997) or individual
differences variables (locus of control; Spector, 1988). We were interested
in employees’ global perceptions of control over their work life. In the
absence of pre-existing measures, we developed a three-item measure
8BORDIA ET AL.
TABLE 1
Standardized Path Coefficients from the Measurement Model
(Confirmatory Factor Analysis)
Item
Standardized
Path Coefficients
Quality of change communication
The official information provided about the change: .85
1. Kept you informed throughout the change process, even after the
official announcement.
2. Included information about changes to the organization’s structure. .68
3. Addressed your personal concerns regarding the change. .77
4. Was accurate. .74
5. Gave as much information as possible. .79
6. Involved employees in the change process and decisions made. .61
7. Communicated the reasons for the change. .66
Uncertainty
1. Whether you will have to relocate to another section of the hospital. .67
2. The level of influence you will have over changes in your job. .74
3. Whether the culture of the organization will change. .71
4. Whether you will fit in the culture of the ‘‘new’’ organization. .79
5. Whether you will get to work with people you have become friends with. .80
6. The possibility of a promotion. .64
7. Whether you will have to learn new job skills. .72
8. The extent to which your job role/tasks will change. .59
9. Whether your pay/salary will change. .59
Control
1. I feel I am in control of my future in this organization. .81
2. I feel I can influence the nature of change in my work unit. .72
3. I feel in control of the direction in which my career is headed. .80
Psychological strain
1. I feel used up at the end of a work day. .76
2. I feel fatigued when I get up in the morning and have to face another
day on the job.
.82
3. Working with people all day is a real strain on me. .69
4. I feel burned out from my work. .83
5. I feel I am working too hard on my job. .66
6. I feel like I am ‘‘at the end of my rope.’’ .74
Job satisfaction
@
1. I really enjoy my job and couldn’t enjoy it more. .84
2. I am extremely satisfied with my job, and couldn’t be more satisfied. .91
3. I am extremely happy with my job, and couldn’t be more happy. .91
Turnover intentions
1. I often seriously think about asking for a transfer to another job. .59
2. I often seriously think about resigning from my job. .88
3. I often seriously think about making a real effort to enter a new and
different occupation.
.57
4. I frequently think of quitting my job. .89
Note:
@
The labels at the positive end of the 5-point scale are listed for this measure. All path
coefficients were significant at p5.001.
UNCERTAINTY AND ORGANIZATIONAL CHANGE 9
describing control over their future in the organization, nature of changes to
their work unit, and the direction in which their career is headed (e.g., ‘‘I feel
I am in control of my future in this organization’’). The responses were
made on a 7-point scale ranging from 1 = strongly disagree to 7 = strongly
agree.
Psychological strain. Psychological strain was measured by the emo-
tional exhaustion subscale of the Maslach Burnout Inventory (Maslach &
Jackson, 1981; e.g., ‘‘I feel used up at the end of a work day’’). The seven-
item scale has previously been used in the change communication literature
by Miller et al. (1990). We used a 7-point response format (1 = strongly
disagree to 7 = strongly agree).
Job satisfaction. Job satisfaction was measured by a three-item measure
of global job satisfaction developed by Warr (1991). The three items,
measured on a 5-point scale, ask respondents to indicate their levels of
enjoyment, satisfaction, and happiness with their job (e.g., 1 = I am not
happy, 2 = I am just about happy, 3 = I am quite happy, 4 = I am very
happy, 5 =I am extremely happy with my job and couldn’t be more happy).
Turnover intentions. A six-item scale was used to measure turnover
intentions. The measure was adapted from previous scales used by Fried,
Tiegs, Naughton, and Ashworth (1995) and Meyer, Allan, and Smith (1993).
For example, ‘‘I often seriously think about resigning from my job’’
(1 = strongly disagree to 7 = strongly agree).
RESULTS
Table 2 presents the means, standard deviations, intercorrelations, and
internal consistency alphas for all the variables. All bivariate correlations
TABLE 2
Means, Standard Deviations (S.D.), Inter-correlations and Internal Consistency Alphas
for the Study Variables
Mean S.D. 1 2 3 4 5 6
1. Quality of change communication 3.12 1.26 (.89)
2. Uncertainty 4.43 1.61 7.32 (.89)
3. Control 3.12 1.78 .35 7.43 (.82)
4. Psychological strain 3.67 1.66 7.24 .43 7.35 (.88)
5. Job satisfaction 2.90 1.03 .38 7.24 .30 7.52 (.91)
6. Turnover intentions 3.18 1.80 7.24 .28 7.17
@
.52 7.55 (.82)
Note. N = 222; all unmarked correlations are significant at p5.01.
@
p5.05.
10 BORDIA ET AL.
between the attitudinal variables were statistically significant and in the
predicted direction. For example, uncertainty was negatively related to
QCC, control, and job satisfaction but positively with psychological strain
and turnover intentions. The correlations were moderate in size (the highest
being .55 between job satisfaction and turnover intentions), providing
evidence for construct independence of the measures. The internal
consistency alphas were all above .80.
To test the hypothesized models in Figure 1, we used the structural
equations modelling technique. In this technique, the pattern of covariances
predicted in the model is compared to the covariance matrix obtained from
the sample. The match between the predicted and obtained covariance
matrices is assessed by a chi-square test. A significant chi-square indicates
that the predicted pattern is significantly different from the observed pattern
of covariances. However, the chi-square test is sensitive to sample size and
with larger sample sizes, it is very easy to get a significant chi-square. It is
recommended that a chi-square value that is less than three times the degrees
of freedom (chi-square/df 53) indicates a good fit of the model. Various
other fit indices have been developed and the commonly used ones include
the Tucker-Lewis Index (TLI; Bentler & Bonett, 1980), Comparative Fit
Index (CFI; Bentler, 1990), and the root mean square error of approxima-
tion (RMSEA; Browne & Cudeck, 1993). TLI and CFI range between 0 to
1, with values of 0.90 and above indicating a good fit. A value of 0.05 or less
for the RMSEA is considered a good fit.
The data were analysed using the Analysis of Moment Structures
program (AMOS Version 4.0). We used the two-step approach recom-
mended by Anderson and Gerbing (1988). The first step involved the
development and test of the measurement model. The aim of this step is to
establish the construct validity of the items used to measure the latent
variables. The measurement model, consisting of correlated latent factors
and their respective indicator variables (i.e., the items), had an adequate fit,
chi-square = 1187.48, df =547, p5.001; TLI = 0.95; CFI = 0.96;
RMSEA = 0.073. However, some of the observed variables had highly
correlated error terms. To ensure unidimensionality of measurement
(Anderson & Gerbing, 1988) and improve the fit, one item from the
emotional exhaustion scale (‘‘I feel frustrated by my job’’) and two items
from the turnover intentions scale (‘‘I am planning to search for a new job
during the next 12 months’’; ‘‘If I have my own way I will leave this
organization to work in another organization one year from now’’) were
removed. This led to a substantial improvement in fit as indicated by the
various fit measures, chi-square = 700.24, df = 449, p5.001; TLI = 0.98;
CFI = 0.98; RMSEA = 0.050. The standardized path coefficients for each
of the items are given in Table 1. As the table shows, all the indicator
variables have high path coefficients from their latent factor. This, together
UNCERTAINTY AND ORGANIZATIONAL CHANGE 11
with the high internal consistency alphas for each of the factors and
moderate size correlations between factors, provides confidence in the
measurement scales used in this study.
Step two of the analysis involved testing the structural model
hypothesized in Figure 1 (the mediated effects model, i.e., no path d). The
model, with predicted relationships among the latent variables, was analysed
using AMOS. This model had a good overall fit to the obtained covariance
matrix, chi-square = 727.64, df = 456, p5.001; chi-square/df = 1.59;
TLI = 0.97; CFI = 0.98, RMSEA = 0.052. All the predicted paths were
significant and in the expected direction (see Table 3, column 2 for the
standardized path coefficients).
To test the competing model with a direct effect of uncertainty upon
psychological strain, we added a path linking these two variables (i.e., path
d). This improved the overall fit of the model, chi-square = 706.31,
df = 455, p5.001; chi-square/df = 1.55; TLI = 0.98; CFI = 0.98;
RMSEA = 0.05, and the difference in chi-square between the two models
was significant, chi-square difference = 21, df =1, p5.001. Also, the path
between uncertainty and control was significant, standardized regression
weight = 0.38, p5.01 (see Table 3, column 3 for all standardized path
coefficients in this model). Thus, uncertainty had a direct and indirect (via
control) effect on psychological strain.
Analysis controlling for common method variance
Self-report data collected from a single survey often lead to inflated
relationships between variables due to common method variance (CMV;
Podsakoff & Organ, 1986). To assess the effects of common method
variance on the test of the hypothesized model, we statistically controlled
for this source of variance and repeated the structural analysis reported
above. Following the recommendation of MacKenzie, Podsakoff, and
Fetter (1993) and Netemeyer, Boles, McKee, and McMurrian (1997), we
introduced a factor in the model (called the CMV factor), with paths
leading to each of the indicator variables (also see Podsakoff, MacKenzie,
Lee, & Podsakoff, 2003 for a detailed discussion of this strategy). This
factor may account for the variance shared by the indicator variables
owing to the common method used to measure them. The addition of
this factor led to a significant improvement in the fit of the model
compared to the hypothesized model, chi-square = 619.57, df = 424,
p5.001; chi-square/df = 1.46; TLI = 0.98; CFI = 0.98; RMSEA = 0.046;
chi-square difference = 108.07, df = 32, p5.001. All the paths to the
indicator variables from their respective latent factor continued to be
significant at p5.001. The relationships between the latent factors were
altered slightly, but not substantively, and they remained statistically
12 BORDIA ET AL.
TABLE 3
Standardized Path Coefficients (SPCs) From the Structural Models
Paths
SPCs for the
hypothesized
model in Figure 1
(minus path d)
SPCs for the
alternate model (with
Uncertainty ?Strain
direct path)
SPCs for the
hypothesized model
(after controlling for
common method variance)
SPCs for the
alternate model
(after controlling for
common method variance)
QCC
@
?uncertainty 7.36** 7.36** 7.18* 7.19*
Uncertainty ?control 7.44** 7.41** 7.48** 7.48**
QCC ?control .24** .25** .28** .29**
Control ?psychological strain 7.43** 7.20** 7.35** 7.29**
Uncertainty ?psychological strain – .39** – .11
Psychological strain ?job satisfaction 7.51** 7.51** 7.47** 7.48**
QCC ?job satisfaction .29** .29** .30** .30**
Job satisfaction ?turnover intentions 7.39** 7.39** 7.41** 7.42**
Psychological strain ?turnover intentions .34** .35** .25** .28**
Note.
@
Quality of Change Communication.
** p5.01
*p= .05
UNCERTAINTY AND ORGANIZATIONAL CHANGE 13
significant (see Table 3, column 4 for the standardized path coefficients
from this model).
Once again, to test the competing model with direct effects of uncertainty
on psychological strain we added the path linking the two variables (i.e.,
path d). This did not lead to any improvement in the fit of the model, chi-
square = 619.05, df = 423, p5.001; chi-square/df = 1.46; TLI = 0.98,
CFI = 0.98; RMSEA = 0.046; chi-square difference = 0.52, df = 1, n.s.
Also, the path from uncertainty to psychological strain was not significant
(standardized regression weight = 0.11, n.s.; see Table 3, column 5 for all
standardized path coefficients from this model). Thus, after controlling for
common method variance, the direct effects model (uncertainty related to
psychological strain) was not supported. Instead, there was support for the
mediated model. That is, the effects of uncertainty upon psychological strain
were mediated by control.
DISCUSSION
The aim of this article was to test a model outlining the role of uncertainty
during organizational change in terms of its antecedents (QCC), direct
consequences (lack of control), and indirect effects of organizational
significance, such as employee well-being, job satisfaction, and turnover
intentions. Overall, the results supported the predicted model and were
consistent with previous research. The findings related to the specific
predictions are discussed below.
As predicted, communication quality was significantly negatively related
to uncertainty. This result suggests that a systematic program of
communication during change is warranted in order to reduce employee
uncertainty. The importance of communication was further reinforced by its
significant positive relationship with perceptions of control and job
satisfaction. These findings are in accordance with previous change
communication research (DiFonzo & Bordia, 1998; Lewis & Seibold,
1998; Schweiger & Denisi, 1991). Communication not only reduces
uncertainty but also increases a sense of control over personal circumstances
related to change. As noted in the introduction, this could be due to two
reasons. First, it could be due to greater change-related knowledge acquired
from management communication. This may make employees feel more
prepared and able to cope with the change. Second, a well-managed
communication program is likely to include input and participation from
employees (Jackson, 1983). Thus, having contributed to the change process,
employees may feel more in control of the change outcomes. To test these
ideas, future research should separate the measurement of communication
content (i.e., credibility and informativeness) and process (i.e., participation)
to further understand the relationship between communication and control.
14 BORDIA ET AL.
We also predicted that uncertainty would be positively related to
psychological strain and negatively related to control. Both predictions were
supported. Bivariate correlations indicated that uncertainty was negatively
related to control and positively related to psychological strain. Once again,
this finding supports previous research (Ashford, 1988; Schweiger & Denisi,
1991) and provides clear evidence for the aversive nature of uncertainty for
the organizational change participant. However, this study extends previous
research by testing alternative theoretical pathways by which uncertainty
leads to psychological strain. We found a direct and an indirect (via control)
relationship between uncertainty and psychological strain. Interestingly, the
direct relationship between uncertainty and psychological strain became
statistically non-significant when we controlled for common method
variance. Indeed this was the only relationship rendered non-significant.
This implies that the relationship may be an artifact of the measurement
strategy and that the aversive nature of uncertainty is due to the lack of
control it engenders. However, this evidence for mediation effect should be
considered tentative as we cannot be entirely sure that the variance that was
partialled out was entirely due to common method variance (Podsakoff et al.,
2003). In other words, the CMV factor may include some substantive (true)
variance shared by uncertainty and psychological strain.
Finally, as predicted, psychological strain was negatively related to job
satisfaction and positively with turnover intentions. These findings are in
accordance with the large literature on stress, job satisfaction, and turnover
intentions during organizational change (Johnson et al., 1996; Schweiger &
Denisi, 1991). The increase in psychological strain as a consequence of
organizational change has considerable implications for organizationally
relevant outcomes, such as employee satisfaction and retention. The strain
caused by uncertainties regarding future job role, job security, and career
outcomes may lead to withdrawal of valued employees from the organization.
Directions for future research on uncertainty
The nature of uncertainty needs further elaboration. For example, Buono
and Bowditch (1993) and Jackson et al. (1987) refer to uncertainty regarding
issues at various levels in the organization. Thus, organizational-level
uncertainty refers to uncertainty regarding strategic issues, such as the
reasons for change. At the intermediate level, there might be uncertainty
regarding the organizational structure (e.g., how the reporting structures
will change). Finally, at the job level, uncertainty could be about training
needs, job security, or the significance of a redefined job role. While these
different levels of uncertainty may be related, they may have differential
impacts on well-being (Jackson et al., 1987). For example, we would expect
that uncertainty regarding job level issues would be the most stressful,
UNCERTAINTY AND ORGANIZATIONAL CHANGE 15
although this could be related to an employee’s position in the organiza-
tional hierarchy such that more senior employees may be more likely to be
affected by uncertainty at the organizational level.
In addition to developing insight into the nature of uncertainty during
change, future research should seek to understand ways in which employees
deal with the uncertainty. The literature on new employee socialization has
shown that new entrants adopt various active and passive strategies
including observing and information seeking from co-workers and super-
visors (Ashford & Black, 1996; Teboul, 1994). Do employees engage in
similar activities to reduce uncertainty during change? Who or what tends to
be their preferred source of information? Answers to these questions would
be of considerable interest to change managers. Moreover, the literature on
uncertainty has long noted the role of individual differences in uncertainty
orientation (Kramer, 1999). That is, not all individuals are equally
motivated to reduce uncertainty. Individual differences in uncertainty
orientation may be an important moderator of the effects of uncertainty
on well-being and uncertainty reduction activities. Finally, future research
should include a measure of resistance to change to assess the effects of
uncertainty and lack of control on this variable.
It is important to note that communication does not always lead to
uncertainty reduction. Indeed, it may lead to increased uncertainty
(Brashers et al., 2000). Further, complete uncertainty reduction may not
be an achievable (DiFonzo & Bordia, 1998) or even a desired goal
(Eisenberg & Witten, 1987). Management need to balance the need for
strategic competitiveness versus employee empowerment in their commu-
nication efforts. Also, the consequences of accurate and informative
communication programs for employee morale may depend on whether
the information being communicated is good or bad news. However, we
maintain that in the long run, it is better to keep employees informed so they
are in a better position to help themselves and the organization cope with
changing circumstances.
A major limitation of this study was the cross-sectional nature of the data
used to test the model. This makes it impossible to draw causal inferences.
Indeed, we have avoided the use of causal terminology and instead
emphasized relationships (rather than effects) between variables. Future
research should strive to temporally separate the measures of uncertainty
from outcome measures to allow for causal inferences. This may also reduce
concerns associated with common method variance.
Practical implications
The findings of this study have considerable practical implications.
Communication is vital in managing employee uncertainty, sense of control,
16 BORDIA ET AL.
and job satisfaction during change. Therefore, organizations should invest a
great deal of effort in communication programs aimed at information
dissemination, participative decision making, and employee empowerment.
Further, enhancing a sense of control may be even more important than
reducing uncertainty. The direct relationship between quality of commu-
nication during change and control suggests one possible means of
increasing perception of control. Systematic and credible communication
prior to, during, and after organizational change will not only equip staff
with necessary information but also engender a sense of control via feelings
of participation and inclusion in change planning.
CONCLUSION
While uncertainty continues to be of interest to organizational researchers
(Clampitt, DeKoch, & Cashman, 2000; Clampitt, DeKoch, & Williams,
2002; Ito & Brotheridge, 2001) there is a dearth of research on the causes,
consequences, and management of uncertainty during organizational
change. This study provided empirical evidence for the harmful effects of
uncertainty and elaborated on the reasons why uncertainty is aversive.
However, it also raised further questions about the nature of uncertainty
and employee responses to uncertainty. Given the importance of uncertainty
for individual and organizational outcomes, we hope these questions are
addressed in future research.
REFERENCES
Albrecht, T. L., & Adelman, M. B. (1987). Communicating social support. Newbury Park, CA:
Sage.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review
and recommended two-step approach. Psychological Bulletin,103, 411 – 423.
Ashford, S. J. (1988). Individual strategies for coping with stress during organizational
transitions. Journal of Applied Behavioral Science,24, 19 – 36.
Ashford, S. J., & Black, J. S. (1996). Proactivity during organizational entry: The role of desire
for control. Journal of Applied Psychology,81(2), 199 – 214.
Bastien, D. T. (1987). Common patterns of behavior and communication in corporate mergers
and acquisitions. Human Resource Management,26(1), 17 – 33.
Bazerman, M. H. (1982). Impact of personal control on performance: Is added control always
beneficial? Journal of Applied Psychology,67, 472 – 479.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin,107,
238 – 246.
Bentler, P. M., & Bonett, D.G. (1980). Significance tests and goodness of fit in the analysis of
covariance structures. Psychological Bulletin,88, 588 – 606.
Berger, C. R. (1987). Communicating under uncertainty. In M. Roloff & G. Miller (Eds.),
Interpersonal processes: New directions in communication research (pp. 39 – 62). London:
Sage.
UNCERTAINTY AND ORGANIZATIONAL CHANGE 17
Berger, C. R., & Bradac, J. J. (1982). Language and social knowledge: Uncertainty in
interpersonal relations. London: Edward Arnold.
Brashers, D. E., Neidig, J. L., Haas, S. M., Dobbs, L. K., Cardillo, L. W., & Russell, J. A.
(2000). Communication in the management of uncertainty: The case of persons living with
HIV or AIDS. Communication Monographs,67(1), 63 – 84.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen &
J. S. Long (Eds.), Testing structural equation models (pp. 136 – 162). Newbury Park, CA: Sage.
Buono, A., & Bowditch, J. (1993). The human side of mergers and acquisitions. San Francisco,
CA: Jossey-Bass.
Clampitt, P. G., DeKoch, R. J., & Cashman, T. (2000). A strategy for communicating about
uncertainty. Academy of Management Executive,14, 41 – 57.
Clampitt, P. G., DeKoch, R. J., & Williams, M. L. (2002). Embracing uncertainty: The hidden
dimension of growth. Ivey Business Journal,66(3), 57 – 67.
Clare, D. A., & Sanford, D. G. (1996). The effect of organizational type and hierarchical level on
nurses’ perceptions of hospital issues. Evaluation and the Health Professions,19, 175 – 193.
Cotton, J., & Tuttle, J. (1986). Employee turnover: A meta-analysis and review with
implications for research. Academy of Management Review,11, 55 – 70.
Covin, T. J. (1993). Managing workforce reduction: A survey of employee reactions and
implications for management consultants. Organization Development Journal,11, 67 – 76.
DiFonzo, N., & Bordia, P. (1998). A tale of two corporations: Managing uncertainty during
organizational change. Human Resource Management,37, 295 – 303.
DiFonzo, N., & Bordia, P. (2002). Corporate rumor activity, belief and accuracy. Public
Relations Review,28, 1 – 19.
DiFonzo, N., Bordia, P., & Rosnow, R. L. (1994). Reining in rumours. Organizational
Dynamics,23, 47 – 62.
Eisenberg, E. M., & Witten, M. G. (1987). Reconsidering openness in organizational
communication. Academy of Management Review,12(3), 418 – 426.
Ellis, B. H. (1992). The effects of uncertainty and source credibility of attitudes about
organizational change. Management Communication Quarterly,6(1), 34 – 57.
Festinger, L. (1954). A theory of social comparison processes. Human Relations,7, 117 – 140.
Fletcher, B. C., & Jones, F. (1993). A refutation of Karasek’s demand-discretion model of
occupational stress with a range of dependent measures. Journal of Organizational Behavior,
14, 319 – 330.
Folkman, S. (1984). Personal control and stress and coping processes: A theoretical analysis.
Journal of Personality and Social Psychology,46, 839 – 852.
Fried, Y., Tiegs, R., Naughton, T., & Ashworth, B. (1996). Managers’ reactions to a corporate
acquisition: A test of an integrative model. Journal of Organizational Behavior,17, 401 – 427.
Ganster, D. C., & Fusilier, M. R. (1989). Control in the workplace. In C. L. Cooper & I.
Robertson (Eds.), International review of industrial and organizational psychology (pp. 235 –
280). New York: Wiley.
Greenberger, D. B., & Strasser, S. (1986). Development and application of a model of personal
control in organizations. Academy of Management Review,11(1), 164 – 177.
Greenberger, D. B., Strasser, S., Cummings, L. L., & Dunham, R. B. (1989). The impact of
personal control on performance and satisfaction. Organizational Behavior and Human
Decision Processes,43, 29 – 51.
Harcourt, J., Richerson, V., & Wattier, M. J. (1991). A national study of middle managers’
assessment of organization communication quality. Journal of Business Communication,28,
348 – 365.
Hargie, O., & Tourish, D. (2000). Charting communication performance in a healthcare
organization, In O. Hargie & D. Tourish (Eds.), Handbook of communication audits for
organizations (pp. 195 – 209). London: Routledge.
18 BORDIA ET AL.
Hogg, M. A., & Abrams, D. (1993). Towards a single-process uncertainty-reduction model of
social motivation in groups. In M. A. Hogg & D. Abrams (Eds.), Group motivation: Social
psychological perspectives (pp. 173 – 190). New York: Harvester Wheatsheaf.
Hogg, M. A., & Mullin, B. A. (1999). Joining groups to reduce uncertainty: Subjective
uncertainty reduction and group identification. In P. Abrams & M. A. Hogg (Eds.), Social
identity and social cognition (pp. 249 – 279). Oxford, UK: Blackwell.
Huber, G. P., & Daft, R. L. (1987). The information environments of organizations. In F. M.
Jablin, L. L. Putnam, K. H. Roberts, & L. W. Porter (Eds.), Handbook of organizational
communication: An international perspective (pp. 130 – 164). Newbury Park, CA: Sage.
Ito, J. K., & Brotheridge, C. M. (2001). An examination of the roles of career uncertainty,
flexibility, and control in predicting emotional exhaustion. Journal of Vocational Behavior,
59, 406 – 424.
Jabes, J, Jans, N., Frazer-Jans, J., & Zussman, D. (1992). Perceptions of leadership and
organization by public sector managers in Australia and Canada as a function of
hierarchical level. In S. Iwawaki, Y. Kashima, & K. Leung (Eds.), Innovations in cross-
cultural psychology (pp. 135 – 146). Amsterdam: Swets & Zeitlinger.
Jackson, S., Schuler, R., & Vredenburgh, D. (1987). Managing stress in turbulent times. In A.
Riley, & S. Zaccaro (Eds.), Occupational stress and organizational effectiveness (pp. 407 –
442). New York: Praeger.
Jackson, S. E. (1983). Participation in decision making as a strategy for reducing job-related
strain. Journal of Applied Psychology,68, 3 – 19.
Jimmieson, N. (2002). The impact of coping resources on employee adjustment to organizational
change: A test of the mediating role of change readiness. Paper presented at the XXVth
international congress of Applied Psychology, Singapore.
Johnson, J. R., Bernhagen, M. J., Miller, V., & Allen, M. (1996). The role of communication in
managing reductions in work force. Journal of Applied Communication Research,24, 139 –
164.
Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment under uncertainty: Heuristics and
biases. New York: Cambridge University Press.
Karasek, R. A. (1979). Job demands, job decision latitude, and mental strain: Implications for
job redesign. Administrative Science Quarterly,24, 285 – 308.
Kramer, M. W. (1999). Motivation to reduce uncertainty: A reconceptualization of uncertainty
reduction theory. Management Communication Quarterly,13(2), 305 – 316.
Larkin, T. J., & Larkin, S. (1994). Communicating change: How to win employee support for new
business directions. New York: McGraw-Hill.
Lewis, L. K., & Seibold, D. R. (1998). Reconceptualizing organizational change implementation
as a communication problem: A review of literature and research agenda. In M. E. Roloff
(Ed.), Communication yearbook 21 (pp. 93 – 151). Beverly Hills, CA: Sage.
Lum, L., Kervin, J., Clark, K., Reid, F., & Sirola, W. (1998). Explaining nursing turnover
intent: Job satisfaction, pay satisfaction, or organizational commitment? Journal of
Organizational Behavior,19, 305 – 320.
MacKenzie, S. B., Podsakoff, P. M., & Fetter, R. (1993). The impact of organizational
citizenship behavior on evaluations of salesperson performance. Journal of Marketing,57,
70 – 80.
Martinko, M. J., & Gardner, W. L. (1982). Learned helplessness: An alternative explanation for
performance deficits. Academy of Management Review,7, 195 – 204.
Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of
Occupational Behaviour,2, 99 – 113.
Meyer, J., Allan, N., & Smith, C. (1993). Commitment to organizations and occupations:
Extension and test of a three component conceptualization. Journal of Applied Psychology,
78, 538 – 551.
1
UNCERTAINTY AND ORGANIZATIONAL CHANGE 19
Miller, K. I., Ellis, B. H., Zook, E. G., & Lyles, J. S. (1990). An integrated model of
communication, stress, and burnout in the workplace. Communication Research,17(3),
300 – 326.
Miller, K. I., & Monge, P. R. (1985). Social information and employee anxiety about
organizational change. Human Communication Research,11(3), 365 – 386.
Miller, S. M. (1981). Predictability and human stress: Toward a clarification of evidence and
theory. Advances in Experimental Social Psychology,14, 203 – 256.
Milliken, F. J. (1987). Three types of perceived uncertainty about the environment: State, effect,
and response uncertainty. Academy of Management Review,12(1), 133 – 143.
Mobley, W. H., Griffeth, R. W., Hand, H. H., & Meglino, B. M. (1979). Review and conceptual
analysis of the employee turnover process. Psychological Bulletin,36, 493 – 521.
Muchinsky, P. M. (1977). Organizational communication: Relationships to organizational
climate and job satisfaction. Academy of Management Journal,20, 592 – 607.
Nadler, D. A. (1987). The effective management of organizational change. In J. W. Lorsch (Ed.),
Handbook of organizational behavior (pp. 358 – 369). Englewood Cliffs, NJ: Prentice-Hall.
Netemeyer, R. G., Boles, J. S., McKee, D. O., & McMurrian, R. (1997). An investigation into
the antecedents of organizational citizenship behaviors in a personal selling context. Journal
of Marketing,61, 85 – 98.
O’Reilly, C. A. (1978). The intentional distortion of information in organizational commu-
nication: A laboratory and field approach. Human Relations,31, 173 – 193.
O’Reilly, C. A. (1980). Individuals and information overload in organizations: Is more
necessarily better? Academy of Management Journal,23, 684 – 696.
Pearce, J. L. (1981). Bringing some clarity to role ambiguity research. Academy of Management
Review,6(4), 665 – 674.
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method
bias in behavioral research: A critical review of the literature and recommended remedies.
Journal of Applied Psychology,88(5), 879 – 903.
Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and
prospects. Journal of Management,12(4), 531 – 544.
Richardson, R., & Denton, D. K. (1996). Communicating change. Human Resource
Management,35(2), 203 – 216.
Rothbaum, F., Weisz, J., & Snyder, S. (1982). Changing the world and changing the self: A two-
process model of perceived control. Journal of Personality and Social Psychology,42, 5 – 37.
Rousseau, D. M., & Tijoriwala, S. A. (1999). What’s a good reason to change? Motivated
reasoning and social accounts in promoting organizational change. Journal of Applied
Psychology,84, 514 – 528.
Schuler, R. S. (1979). A role perception transactional process model for organizational
communication-outcome relationships. Organizational Behavior and Human Performance,
23, 268 – 291.
Schuler, R. S. (1980). Definition and conceptualization of stress in organizations. Organizational
Behavior and Human Decision Processes,25, 184 – 215.
Schweiger, D. M., & Denisi, A. S. (1991). Communication with employees following a merger:
A longitudinal field experiment. Academy of Management Journal,34(1), 110 – 135.
Schweiger, D. M., & Ivancevich, J. M. (1985). Human resources: The forgotten factor in
mergers and acquisitions. Personnel Administrator,30, 47 – 61.
Smeltzer, L. R. (1991). An analysis of strategies for announcing organization-wide change.
Group and Organization Studies,16(1), 5 – 24.
Smeltzer, L. R., & Zener, M. F. (1992). Development of a model for announcing major layoffs.
Group and Organization Management,17(4), 446 – 472.
Smith, C. S., Tisak, J., Hahn, S. E., & Schnieder, R. A. (1997). The measurement of job control.
Journal of Organizational Behavior,18, 225 – 237.
20 BORDIA ET AL.
Sorrentino, R. M., Holmes, J. G., Hanna, S. E., & Sharp, A. (1995). Uncertainty orientation
and trust in close relationships: Individual differences in cognitive styles. Journal of
Personality and Social Psychology,68, 314 – 327.
Spector, P. E. (1988). Development of the Work Locus of Control Scale. Journal of
Occupational Psychology,61, 335 – 340.
Teboul, J. C. B. (1994). Facing and coping with uncertainty during organizational encounter.
Management Communication Quarterly,8(2), 190 – 224.
Terry, D. J., Callan, V. J., & Sartori, G. (1996). Employee adjustment to an organizational
merger: Stress, coping and intergroup differences. Stress Medicine,12, 105 – 122.
Terry, D. J., & Jimmieson, N. L. (1999). Work control and employee well-being: A decade
review. In C. L. Cooper & I. T. Robertson (Eds.), International review of industrial and
organizational psychology (pp. 95 – 148). New York: Wiley.
Warr, P. (1991). Mental health, well-being and job satisfaction. In B. Hesketh & A. Adams
(Eds.), Psychological perspectives on occupational health and rehabilitation (pp. 143 – 165).
London: Harcourt Brace Jovanovich.
Manuscript received February 2003
Revised manuscript received February 2004
UNCERTAINTY AND ORGANIZATIONAL CHANGE 21
