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European Journal of Work and Organizational
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Psychological contract breaches and employee voice
behaviour: The moderating effects of changes in social
relationships
a
b
Thomas W. H. Ng , Daniel C. Feldman & Marcus M. Butts
c
a
School of Business and Economics , University of Hong Kong , Hong Kong
b
Terry College of Business, University of Georgia , Athens , GA , USA
c
Department of Management , University of Texas at Arlington , Arlington , TX , USA
Published online: 12 Mar 2013.
To cite this article: Thomas W. H. Ng , Daniel C. Feldman & Marcus M. Butts (2014) Psychological contract breaches and
employee voice behaviour: The moderating effects of changes in social relationships, European Journal of Work and
Organizational Psychology, 23:4, 537-553, DOI: 10.1080/1359432X.2013.766394
To link to this article: http://dx.doi.org/10.1080/1359432X.2013.766394
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European Journal of Work and Organizational Psychology, 2014
Vol. 23, No. 4, 537–553, http://dx.doi.org/10.1080/1359432X.2013.766394
Psychological contract breaches and employee voice behaviour: The
moderating effects of changes in social relationships
Thomas W. H. Ng1, Daniel C. Feldman2, and Marcus M. Butts3
1
School of Business and Economics, University of Hong Kong, Hong Kong
Terry College of Business, University of Georgia, Athens, GA, USA
3
Department of Management, University of Texas at Arlington, Arlington, TX, USA
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2
Guided by social exchange theory, this study found support for the prediction that the relationship of psychological contract
breaches to voice behaviour (both constructive and aggressive) would be moderated by changes in leader–member exchange
and coworker exchange over time. Specifically, the positive relationship between psychological contract breach and aggressive
voice behaviour was weakened when employees had experienced increases in leader–member exchange during the preceding
8-month period. In addition, the relationships of psychological contract breaches with constructive and aggressive voice were
also moderated by changes in coworker exchange over time. The article concludes with a discussion of the importance of
improving the quality of relationships with superiors and colleagues as a means of mitigating breaches of psychological
contracts with the organization as a whole.
Keywords: Changes; Coworker exchange; Leader–member exchange; Psychological contracts; Social exchange theory; Voice.
Over the past two decades, there has been a great deal of
research conducted on psychological contract breaches.
Psychological contract breaches (PCBs) are employees’
perceptions of the extent to which employers have failed
to fulfil their obligations or promises to them (Morrison &
Robinson, 1997). Although the negative effects of PCBs on
employee attitudes and behaviours have been frequently
documented (Isaksson, De Cuyper, Oettel, & De Witte,
2010; Rigotti, 2009; Zhao, Wayne, Glibkowski, & Bravo,
2007), in some cases it appears that employees’ reactions to
PCBs are moderated by their relationships with their supervisors and coworkers (Dulac, Coyle-Shapiro, Henderson,
& Wayne, 2008; Restubog, Bordia, Tang, & Krebs, 2010;
Suazo, 2011; Zagenczyk, Gibney, Kiewitz, & Restubog,
2009). Moreover, the findings regarding the direction of
that moderating effect are mixed. For example, some studies have found that employees react less strongly to PCBs
when the quality of relationships with supervisors and
coworkers is high (Dulac et al., 2008; Zagenczyk et al.,
2009). In contrast, other studies have found that employees
react more strongly to PCBs when the quality of relationships with supervisors and coworkers is high (Restubog
et al., 2010; Suazo, 2011).
To reconcile these mixed findings, we take a theoretical approach infrequently used in this research area,
namely, examining changes in employees’ relationships
with supervisors and coworkers over time (rather than
levels of relationships with supervisors and coworkers at
one point in time) as moderators of the relationships
between PCBs and outcomes. Increases or decreases in
the quality of relationships with supervisors and coworkers represent true gains or losses in social resources
(Hobfoll, 1989, 2002), which could ameliorate or
exacerbate the negative experience of PCBs. Moreover,
because employees’ relationships with supervisors and
coworkers are not static but evolve over time, a theoretical focus on changes in (rather than levels of) relationship quality provides a more realistic portrait of the
workplace context (Chan & Schmitt, 2000; Jokisaari &
Nurmi, 2009) and can better model the reality of organizational life (Weick, Sutcliffe, & Obstfeld, 2005;
Wrzesniewski, Dutton, & Debebe, 2003). In so doing,
this theoretical focus should help untangle previously
inconclusive research results as well.
In the present study, we take voice as our major
outcome variable of interest. Employee voice behaviour
can be either constructive or destructive. Constructive
voice behaviours are expressions of change-oriented
ideas and suggestions which are motivated by employees’ desires to improve their current work situations
Correspondence should be addressed to Thomas W. H. Ng, School of Business and Economics, University of Hong Kong, 7/F Meng Wah
Complex, Pok Fu Lam, Hong Kong. Email: [email protected]
© 2013 Taylor & Francis
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538 NG, FELDMAN, BUTTS
(Morrison, 2011). In contrast, destructive voice behaviours are intended to hurt the employer (Gorden,
1988; Rusbult, Farrell, Rogers, & Mainous, 1988).
Unlike constructive voice behaviour, then, destructive
voice behaviour worsens rather than nurtures the wellbeing of the organization as a whole (Klaas & DeNisi,
1989).
We chose to study these types of voice behaviour for
two reasons. First, employee voice is a legitimate and
important dimension of job performance but has not
been studied extensively in the PCB literature (see
Lemire & Rouillard, 2005, and Turnley & Feldman,
1999, as exceptions). The use of constructive voice can
lead to the identification of operational problems overlooked by supervisors and to the successful implementation of innovation (Axtell, Holman, & Wall, 2006;
Dundon & Gollan, 2007; Graham & Van Dyne, 2006;
Van Dyne & LePine, 1998), whereas the use of destructive voice distracts employees themselves as well as their
colleagues from real work. Second, voice is often seen as
a risky behaviour because employees who display voice
(whether it is constructive or destructive) may be perceived as trouble makers intent on disrupting the status
quo (Detert & Burris, 2007; Milliken, Morrison, &
Hewlin, 2003). Because of this risk, the predictors of
voice behaviour may be very different from those of
other types of work behaviour (e.g., inrole task performance or helping behaviour).
We use social exchange theory (Blau, 1964) as our
framework for exploring whether employees’ relationships with supervisors and coworkers positively or negatively moderate the link between PCBs and employee
voice behaviours. Our core argument is that improving
the employee’s relationships with supervisors and coworkers over time makes the relationship between the
employee and the organization as a whole less salient.
In turn, when employees subsequently experience PCBs,
the effects of those PCBs on employees’ voice behaviour
will be weaker. In the sections that follow, we introduce
the major constructs used in this study, the key tenets of
social exchange theory, and our hypotheses.
THE THEORETICAL NATURE OF
PSYCHOLOGICAL CONTRACT BREACHES
(PCBS)
Psychological contracts consist of individuals’ beliefs
regarding the mutual obligations between themselves
and their employers (Rousseau, 1989, 1995). These psychological contracts are breached when employees perceive that their employers have failed to fulfil at least one
obligation or promise (Turnley, Bolino, Lester, &
Bloodgood, 2003; Turnley & Feldman, 1999).
It is important to note here that we are studying
contract breaches rather than contract violations. A contract breach refers to a cognitive assessment of the
discrepancy between what is promised and what is
delivered, whereas a contract violation refers to the emotional response to such a breach (Morrison & Robinson,
1997). We focus on breaches rather than on violations
for two reasons. Theoretically, we are more interested in
how cognitive assessments of breaches prompt employees to dissociate themselves from their relationships with
their employers. Methodologically, previous researchers
have observed that breaches and violations are often
quite strongly correlated (e.g., Robinson & Morrison,
2000; Suazo & Stone-Romero, 2011). Consequently,
following other studies of psychological contracts, we
examine contract breaches here as well (Bordia,
Restubog, Bordia, & Tang, 2010; Ng, Feldman, &
Lam, 2010).
Employee voice behaviour
Haagedoorn, Van Vperen, Van de Vliert, and Buunk
(1999) proposed that there are two distinctive forms of
voice. The first we consider here is “constructive voice”.
Interestingly, voice was initially conceptualized as a
form of organizational citizenship behaviour (OCB)
which promotes the organization by maintaining and
strengthening its social system (Organ, 1997).
Examples of affiliation-oriented OCBs include staying
late to help a coworker complete an assignment or promoting the reputation of firm in the community. In subsequent treatments of voice behaviour, the
conceptualization of voice has been refined. Other
researchers (e.g., Morrison, 2011; Van Dyne & LePine,
1998) view constructive voice as a form of discretionary
OCB that extends beyond mere participation in organizational activities to include making opinions and ideas
heard by others. Thus, constructive voice can also be
challenge oriented. That is, constructive voice can promote positive change in an organization even if it runs
against the preferences of colleagues and supervisors
(MacKenzie, Podsakoff, & Podsakoff, 2011; Van Dyne,
Cummings, & Parks, 1995).
Haagedoorn et al. (1999) call the second form
“aggressive voice”. They view it as less constructive
and define it as the employee’s efforts to “win” without
considering the effects of that win on supervisors and
colleagues. Examples of aggressive voice behaviours
include continually confronting others until they give in
to personal demands, deliberately overstating a grievance
in order to draw more attention to one’s problems, and
involving external constituencies to put pressure on
internal opponents. Unlike constructive voice, aggressive
voice is more likely to create a hostile workplace climate
and interfere with managers’ strategic decision making
and operational effectiveness.
Both types of voice behaviour warrant further attention from organizational researchers. In the case of constructive voice, employees may refrain from speaking up
even if they have good suggestions because they fear
their attempts to change procedures or decisions will
PSYCHOLOGICAL CONTRACT BREACH
offend coworkers and supervisors or lead to retaliation
(Milliken et al., 2003). As a result, employees will continue to remain silent and ideas for organizational innovation will be stifled (Van Dyne, Ang, & Botero, 2003). In
the case of aggressive voice, employees might use it to
disrupt the group’s functioning until personal demands or
grievances are addressed. Thus, identifying the conditions
under which employees are willing to use constructive
and aggressive voice constitutes an additional important
direction for research in the organizational sciences.
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Social exchange theory and responses to
PCBs
Social exchange theory (Blau, 1964) is particularly useful for understanding employees’ reactions to PCBs.
Among many possible exchange rules in social relationships (reciprocity, rationality, altruism, group gain, status
consistency, and competition; Meeker, 1971), social
exchange theorists have especially focused on the rule of
reciprocity (Cropanzano & Mitchell, 2005; Gouldner,
1960). This norm suggests that one party in the exchange
will reciprocate positively to the other partner when that
partner makes a move to improve the quality of the relationship (e.g., doing a favour). Once the positive reciprocation
process starts, each reciprocating act creates a self-reinforcing cycle (Molm, Whitham, & Melamed, 2012). Over
time, the growth of the norm of positive reciprocity leads
social exchanges to be characterized by stable levels of
loyalty, mutual commitments, and emotional investments
(Shore, Coyle-Shapiro, Chen, & Tetrick, 2009). Thus,
social exchange theory provides a solid theoretical basis
for us to predict that, when an employer honours psychological contracts, employees are likely to reciprocate with
more constructive voice and less aggressive voice.
Conversely, when employers breach psychological
contracts with their workers, social exchange theory suggests that employees will respond with more aggressive
voice behaviour and less constructive voice behaviour.
Particularly relevant to the present study is Turnley and
Feldman’s (1999) finding that PCBs were associated with
greater intensity of negative voice (which was conceptualized as voicing displeasure and complaints to an employer
in order to remove a personal problem or concern).
More broadly, previous research suggests that employees are likely to respond to PCBs with negative job attitudes and behaviours (Coyle-Shapiro, 2002). For instance,
PCBs decrease the degree of mutual respect and trust
between employees and their employers (Robinson,
1996), which in turn lead to negative reciprocation behaviours (Restubog, Hornsey, Bordia, & Esposo, 2008).
PCBs have also been found to be negatively related to
job satisfaction, trust, OCB, organizational commitment,
and performance, while being positively related to
employee cynicism, absenteeism, turnover, and counterproductive work behaviour (Chao, Cheung, & Wu, 2011;
Conway & Briner, 2002; Ng & Feldman, 2012; Pugh,
539
Skarlicki, & Passell, 2003; Restubog, Bordia, & Tang,
2006; Sutton & Griffin, 2004). Based on this discussion
of the norm of reciprocity, we thus predict:
Hypothesis 1: PCB will be negatively related to
constructive voice behaviour (H1a) and positively
related to aggressive voice behaviour (H1b).
Social exchange theory and the moderating
effects of changes in LMX and CWX
Social exchange theory also posits that, although the
quality of the relationship between the organization and
the employee is most directly determined by the respective behaviours of those two parties, the impact of other
social exchange relationships on a focal relationship
should not be overlooked (Blau, 1964). That is, the
salience of a particular exchange relationship may be
influenced by exogenous factors, such as the quality of
other exchange relationships and how important those
other exchange relationships are to individuals. People
have multiple social relationships, and the salience of
one relationship may increase (or decrease) at the
expense of other relationships (Hogg, Abrams, Otten,
& Hinkle, 2004). For instance, previous research has
suggested that a strong relationship with one group can
compensate for poor relationships with other groups
(Kreiner & Ashforth, 2004; Stryker & Serpe, 1982). As
Sluss and Ashforth (2007) argue, an employee’s definition of self is not only influenced by his or her relationship with the organization as a whole, but also by
interpersonal relationships with coworkers and supervisors. Thus, as the salience of relationships with supervisors and coworkers increases, the salience of the
relationship with the employer may weaken.
Leader–member exchange (LMX). LMX is the
extent to which leaders develop close or deep relationships
with subordinates (Dienesch & Liden, 1986; Graen & UhlBien, 1995). High quality LMX is characterized by mutual
respect, trust, and a sense of obligation. In addition,
researchers suggest that LMX and employment relationships are empirically distinct constructs (Setton, Bennett, &
Liden, 1996; Wayne, Shore, Bommer, & Tetrick, 2002).
There are four studies which have examined the moderating effects of LMX on the relationships between PCBs
and work outcomes. First, Dulac et al. (2008) found that,
among individuals who perceived higher levels of LMX at
Time 1, the association between PCBs and feelings of
contract violation was weaker at Time 2. Consistent with
that study, Zagenczyk et al. (2009) found that, for individuals who had a mentor (vs. no mentor) at Time 1, the
association between PCBs at Time 1 and perceived organizational support at Time 2 was weaker.
In contrast to these two studies, Restubog et al.
(2010) found that PCBs had stronger negative relationships with job performance and OCB when LMX was
high. This result was replicated across three empirical
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540 NG, FELDMAN, BUTTS
studies using a mixture of cross-sectional and longitudinal designs. Suazo (2011) also found that the effect of
PCBs at Time 1 on feelings of contract violation at Time
2 was stronger for employees reporting high (vs. low)
LMX at Time 2.
We predict that as the quality of LMX increases over
time, it will lower the salience of the employee’s relationship with the organization as a whole. Increases in
LMX represent true gains in resources. In particular,
increases in LMX can aid an employee’s career development (Kraimer, Seibert, Wayne, Liden, & Bravo,
2011). For instance, previous research has found that
supervisors can expand a subordinate’s social network
both internally and externally (Sparrowe & Liden, 2005;
Venkataraman, Green, & Schleicher, 2010), and these
social ties may become vital when the employee decides
to leave the firm for another employer (Granovetter,
1973). Consequently, the negative effects of PCBs on
an employee’s voice behaviour may be somewhat diluted
because the organization is not the only source from
which an employee can obtain valuable career development resources (Johnson, Chang, & Yang, 2010).
Conversely, when there are declines in LMX over
time, the relationship with the organization becomes
more salient to employees. Employees now have to
rely more heavily on the organization as a whole for
the resources they want for their career development;
those resources cannot be obtained directly from supervisors instead. Indeed, previous research has shown that
unmet expectations are the main reason why employees
react so negatively to PCBs (Kim & Choi, 1996;
Robinson, 1996). Thus, we predict:
Hypothesis 2: Changes in LMX will moderate
the relationship between PCB and voice. The
negative relationship between PCB and constructive voice behaviour will be weaker (H2a) and the
positive relationship between PCB and aggressive
voice behaviour will be weaker (H2b) when LMX
has increased over time.
Coworker exchange (CWX). CWX refers to the
quality of relationships between employees and coworkers
(Sherony & Green, 2002). The content domain of CWX is
similar to that of LMX. That is, a high level of CWX is
characterized by mutual respect for, trust in, and obligations to coworkers as a group. We are aware of no previous
studies that have examined the moderating effects of CWX
in the relationships between PCBs and outcomes.
Arguments similar to those made above about the
moderating effect of LMX can be made about the role
of CWX, too. As CWX increases over time, the salience
of an individual’s relationship with his or her organization may become weaker. That is, as individuals spend
more effort and time in developing and maintaining
relationships with their colleagues, the importance of
their relationship with the organization as a whole may
decrease. For instance, when relationships with coworkers increase, valuable resources such as tangible support (e.g., assistance provided by coworkers in daily
work activities) and intangible support (e.g., emotional
support) are likely to increase as well (Chiaburu &
Harrison, 2008; Sherony & Green, 2002). Further, similar to the case of LMX, increases in CWX also help
employees expand their internal and external social networks (Randel & Ranft, 2007). Therefore, employees
with increased CWX are less reliant on the organization
for additional resources and are less disappointed when
those resources are not delivered. Supporting this hypothesis, previous research has found that a high level of
support from coworkers weakened employees’ psychological distress when they were treated unjustly by their
employers (Rousseau, Salek, Aube, & Morin, 2009).
In contrast, as CWX declines over time, the salience
of an individual’s relationship with the organization as a
whole may grow stronger because the individual is now
more reliant on the organization as a whole to obtain
additional resources for themselves. As a result, employees with declining CWX may feel even greater anger and
disappointment when they experience PCBs. The perceived deprivation of valued resources—coupled with
the lack of opportunity to acquire those resources
directly from colleagues—strengthens employees’ negative reactions to PCBs. Therefore, we predict:
Hypothesis 3: Changes in CWX will moderate
the relationship between PCB and voice. The
negative relationship between PCB and constructive voice behaviour will be weaker (H3a) and the
positive relationship between PCB and aggressive
voice behaviour will be weaker (H3b) when CWX
has increased over time.
Last here, it should be noted that the previous two
hypotheses assume that nurturing relationships with
supervisors and coworkers compete for an employee’s
limited time and emotional resources. Therefore, any
increase in the salience of relationships with supervisors
or colleagues would inherently reduce the salience of
relationships with the organization as a whole.
However, because relationships with supervisors and
coworkers unfold within the context of the organization
as a whole, it is also possible that improvements
(declines) in relationship quality with supervisors and
coworkers might spill over to employees’ overall relationships with their organizations, too. This might be
especially true in the case of LMX because supervisors
are widely perceived to be representatives of their organizations. As a result, employees are likely to view
supervisors’ actions as reflections of the organization as
a whole (e.g., Eisenberger, Stinglhamber, Vandenberghe,
Sucharski, & Rhoades, 2002).
While recognizing the legitimacy of this theoretical
argument, we also note that empirical evidence suggests
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PSYCHOLOGICAL CONTRACT BREACH
that individuals are able to make clear distinctions
between the quality of their relationships with supervisors and the quality of their relationships with employers. Stoner, Gallagher, and Stoner (2011), for instance,
found that the positive relationship between PCBs and
turnover intentions was weakened when employees perceived their supervisors were loyal to them and protective of them. Anand, Vidyarthi, Liden, and Rousseau
(2010) found that only employees with low levels of
LMX reacted positively to the receipt of idiosyncratic
work arrangements; the authors reasoned that employees
saw LMX as a substitute for such additional organizational resources. Taken together, these findings support
the compensation argument we presented earlier and the
notion that employees are indeed able to distinguish
between the resources they receive from supervisors
and those they receive from organizations.
METHOD
Sampling procedure
We utilized Zoomerang.com to collect survey data
online. We used this data collection strategy for several
reasons. First, we hoped to alleviate respondents’ potential reservations about the confidentiality of their data,
which might have arisen had we made entry through
senior management. Second, the use of Zoomerang.
com allowed us to follow up easily with employees,
with multiple waves of data collection over time. Third,
the use of Zoomerang.com allowed us to broaden the
diversity of industries sampled, thereby increasing the
variance in the sample on key constructs. Fourth,
Zoomerang.com allowed us to focus on first-line supervisors and middle managers who were currently
employed by organizations as our sample since, as a
group, they are most likely to have variance in terms of
their PCBs and opportunities to use different forms of
voice. Fifth, we had ex ante expectations that this strategy would prove effective in the present case as other
researchers have already successfully sampled online
respondents through Zoomerang.com (Arora &
Henderson, 2007; Autry, Skinner, & Lamb, 2008;
Gronlund, Carlson, Dailey, & Goodsell, 2009; Kwun &
Alshare, 2007) or through other similar recruiting websites (Montes & Zweig, 2009; Piccolo & Colquitt, 2006).
We constructed the surveys, which Zoomerang.com
then distributed online to participants who were currently
employed by organizations as first-line supervisors or
middle managers at the time of the survey. An invitation
letter stating the purpose of the study was sent along
with the survey. Participation was voluntary, and potential subjects were promised small monetary incentives
(approximately US$5) by Zoomerang.com in return for
their participation.
One of the key concerns with using online surveys is
whether respondents are primarily motivated by extrinsic
541
rewards to participate. However, in their research,
Bruggen, Wetzels, de Ruyter, and Schillewaert (2011)
found that the proportion of online survey takers who
were intrinsically motivated to participate was much
larger than the proportion of online survey takers who
participated simply for extrinsic rewards. Also, in experimental settings, Goritz (2004) found that the different
types and amounts of tangible incentives had no effect
on the quality of online participants’ responses. These
authors, too, concluded that incentives did not represent
a key response motivation for participants in online
research studies.
Data were collected from respondents at four points in
time over a 1-year period. Within the pool of employees
in Zoomerang.com’s database, subjects were chosen randomly. The research company sent out 2500 surveys at
Time 1. Five hundred and forty usable surveys were
returned (response rate = 22%). Four months later, the
Time 2 survey was sent to those 540 respondents who
participated in the first survey. We received 359 usable
surveys back (response rate = 66%). Four months after
Time 2 (i.e., 8 months after the Time 1 survey), the Time
3 survey was sent to those 359 respondents who participated in both the first and second surveys. We received
244 usable surveys back (response rate = 68%). Finally,
4 months after Time 3 (i.e., 12 months after the Time 1
survey), the Time 4 survey was sent to those 244 respondents who participated in the previous three surveys.
Excluding those respondents who had changed organizations in the preceding 1-year period, we received 192
usable surveys back (response rate = 79%).
Baruch and Holtom (2008) report that, across survey
studies published in 2000 and 2005, the average
response rate was 39%. In meta-analyses of response
rates of electronic surveys in particular, response rates
have averaged around 34% (Cook, Heath, & Thompson,
2000; Shih & Fan, 2008). Although our initial response
rate (22%) was lower than 34%, it was consistent with
those of other initial surveys conducted by Zoomerang.
com. In addition, we compared our response rates at
Time 2, Time 3, and Time 4 to those of other studies
that had recruited online respondents through
Zommerang.com. These studies reported response rates
ranging from 8% to 28% (Autry et al., 2008; Kwun &
Alshare, 2007). Thus, our response rates for the second,
third, and fourth survey administrations were higher than
those typically observed in electronic surveys (Baruch &
Holtom, 2008; Cook et al., 2000; Shih & Fan, 2008).
Sample characteristics
The average age of the participants in the study was 41
years old (SD = 10.91). Forty-one per cent of respondents were female. Sixty-three per cent of the sample had
at least some college education. All respondents resided
in the United States. Average organizational tenure was
542 NG, FELDMAN, BUTTS
8.8 years; average job tenure was 7.2 years. We compared the responses of individuals who participated in all
four surveys with those of individuals who dropped out
without completing all four surveys. There were no
differences on key demographic variables. Specifically,
we found that the average age, percentage of male versus
female employees, modal educational level, and average
job and organizational tenure were not significantly different between respondents and nonrespondents.
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Research design
Previous studies using latent growth modelling to examine changes in employee attitudes and behaviours have
adopted time frames as short as 1 month and as long as 6
months (Chan & Schmitt, 2000; Jokisaari & Nurmi,
2009; Lance, Vandenberg, & Self, 2000; Peterson,
Luthans, Avolio, Walumbwa, & Zhang, 2011). In the
present study, we used time lags of 4 months.
In choosing which time interval we should use
between surveys, we wanted a lag greater than 1 month
to lower the influence of common method variance,
since surveys separated by only 1 month might still
have residual, artifactual effects on respondents. On the
other hand, we did not want to use 6 months as the time
interval because we planned to have four waves of
measurements, which would have taken 2 years to finish
if 6-month intervals were used. Such an extended period
might increase subject attrition rate. Therefore, we chose
lags of an intermediate length of 4 months in order to
balance obtaining variance on our key variables with
reducing common method variance and avoiding high
rates of subject attrition.
We measured both LMX and CWX at Time 1, Time 2,
and Time 3; three measurement waves are needed to
assess linear changes in LMX and CWX over time. At
Time 3, we also measured PCBs. That is, participants’
experiences of PCBs were assessed at the end of an 8month period during which levels of LMX and CWX
might have changed. At Time 4, we measured both constructive and aggressive voice behaviours.
It should be noted that we examined longitudinal
changes only in the case of employees’ relationships
with supervisors and coworkers (LMX and CWX). The
other key study variables (PCB, constructive voice, and
aggressive voice) were all measured at one point in time
(PCB at Time 3, constructive and aggressive voice at
Time 4). We used this design so that we could illustrate
how intraindividual changes in employees’ relationships
with supervisors and coworkers might impact the effects
of subsequent PCBs on outcome variables. At the same
time, this design allowed us to directly compare our
research findings to those of previous studies which
examined employees’ relationships with supervisors
and coworkers as moderators in cross-sectional (rather
than longitudinal) designs.
Measures
Except where noted, survey items were measured on 5point Likert-format scales. Response scales ranged from
1 (“strongly disagree”) to 5 (“strongly agree”). Means,
standard deviations, and correlations are provided in
Table 1.
LMX. LMX was measured at three points in time
over an 8-month period with Graen and Uhl-Bien’s
(1995) seven-item scale (α = .91, .93, and .93, respectively). A sample item is: “I have an effective working
relationship with my supervisor.”
To estimate linear changes in levels of LMX over
time for each employee, we used latent growth curve
modelling (Bollen & Curran, 2006). That is, we first
specified a second-order growth factor to capture the
linear change in the first-order LMX latent factor across
the three time points. Each first-order LMX latent factor
was represented by its respective measurement items.
Furthermore, error variances of those measurement
items repeatedly used across time points were allowed
to be correlated.
By specifying these parameters, each employee’s
change trajectory can be estimated. A positive score
TABLE 1
Means, standard deviations, and correlations among study variables (N = 192)
Variable
1. LMX (Time 1)
2. LMX (Time 2)
3. LMX (Time 3)
4. CWX (Time 1)
5. CWX (Time 2)
6. CWX (Time 3)
7. PCB (Time 3)
8. Constructive voice (Time 4)
9. Aggressive voice (Time 4)
Mean
Standard deviation
1
2
3
4
5
6
7
8
9
—
.49**
.53**
.65**
.35**
.36**
−.42**
.33**
−.08
3.73
0.82
—
.63**
.31**
.47**
.49**
−.44**
.21**
−.00
3.71
0.90
—
.39**
.35**
.61**
−.60**
.17*
−.13
3.66
0.95
—
.58**
.42**
−.39**
.18*
−.07
3.65
0.67
—
.53**
−.45**
.03
.05
3.67
0.68
—
−.42**
.12
.03
3.62
0.75
—
−.12
−.03
2.59
1.17
—
.12
3.77
0.88
—
2.25
0.87
LMX = leader–member exchange; CWX = coworker exchange; PCB = psychological contract breach. **p < .01, *p < .05.
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PSYCHOLOGICAL CONTRACT BREACH
indicates a positive slope of linear change over time (i.e.,
increase in LMX over time), whereas a negative score
indicates a negative slope of linear change over time
(i.e., decrease in LMX over time). We then utilized
these scores on the growth factors to test for moderation
effects.
Because we were interested in changes in levels of
LMX over time, we also examined whether our LMX
scale demonstrated measurement invariance longitudinally (Chan, 1998; Vandenberg & Lance, 2000). Based on
chi-squared difference tests, we found that one item in
the LMX scale had significantly different factor loadings
at the three points in time. Having a small amount of
partial metric invariance here is not surprising, though,
given that the underlying assumption of our research is
that there will be changes in LMX over time (Pentz &
Chou, 1994). Fortunately, the latent growth curve modelling technique we utilized (described earlier) takes into
consideration such variant items in the estimation of
latent growth scores.
CWX. CWX was also measured at three points in
time over an 8-month period with Sherony and Green’s
(2002) six-item scale (α = .85, .87, and .86, respectively). A sample item is: “I have an effective working
relationship with my coworkers.”
We found complete measurement equivalence (that is,
full metric invariance) for the CWX scale. As in the case
for LMX, we obtained changes in CWX over time by
estimating for each employee a linear growth score using
latent growth curve modelling.
PCB. PCB was measured at Time 3 (8 months after
initial data collection) with a five-item scale adapted
from Robinson and Morrison’s (2000) scale (α = .97).
These items were modified so that they did not refer only
to those promises made by employers during recruitment. Instead, they tapped respondents’ global perceptions of whether the promises made by their employers
during their entire period of employment had been honoured. A sample item is: “My employer has not broken
its promises to me” (reverse-scored). Higher scores indicate higher levels of PCBs.
Constructive voice behaviour. Constructive voice
behaviour was measured at Time 4 (α = .94). Here we
utilized LePine and Van Dyne’s (1998) six-item scale,
which assesses voice as a form of OCB. A sample item
is: “I develop and make recommendations concerning
issues that affect the organization.”
Aggressive voice behaviour. This was also measured at Time 4 (α = .86). Here we used Hagedoorn et
al.’s (1999) six-item scale. A sample item is “I deliberately make a problem sound more problematic than it
really is.”
Self-reported measures of voice behaviour are not
uncommon in the organizational sciences (Axtell et al.,
2000; Parker, Williams, & Turner, 2006). Compared to
supervisors or peers, employees themselves are apt to be
more aware of the subtleties of their suggestions and
543
whether those recommendations are fundamentally valuable, incrementally valuable, or are meant to delay or
undermine useful change. Moreover, to the extent that
voice is a discretionary behaviour (LePine & Van Dyne,
1998), employees themselves may be in the best position
to assess the intensity or frequency of their voice
behaviours.
Control variables
Control variables were collected at Time 1. We included
several sociodemographic variables as controls in our
analyses: gender, age, education level, organizational
tenure, job level, and job tenure. We control for gender
because, compared to men, women could have systematically different career paths (Ohlott, Ruderman, &
McCauley, 1994), which, in turn, might affect the intensity and content of the voice they use at work. Older
workers, more educated workers, and workers with
longer organizational tenure are more likely to engage
in OCB (Ng & Feldman, 2008, 2009, 2010) and, as
such, these three sociodemographic variables might be
related to voice behaviour as well. Last here, individuals
who work on higher level jobs or who work in a job for
longer periods of time may be more willing to speak up
or have more valuable information they could contribute
to the firm. Therefore, both job level and job tenure were
included as control variables, too.
In addition, we obtained a Time 1 measure of PCB so
that we could rule out the confounding effects of the
initial level of PCBs on subsequent changes in LMX or
CWX over time. We also collected data on perceived
organizational support (POS) at Time 1 for use as a
control variable in our moderated regression analyses.
We did so because we wanted to examine the moderating
effects of social exchanges with supervisors and coworkers in the relationship between PCB and voice above
and beyond their social exchanges with their employers
(e.g., Ng & Sorensen, 2008; Shore et al., 2004). Previous
research suggests that the variable that best captures the
exchange quality of the relationship between an
employee and an employer is POS (Wayne, Shore, &
Liden, 1997), and so POS (measured by Shanock and
Eisenberger’s, 2006, six-item scale; α = .94) was measured as a control variable at Time 1 as well.
Confirmatory factor analyses
Measurement models. Before we proceeded to hypothesis testing, we first examined whether the measurement
models of our constructs had acceptable model fit
(Anderson & Gerbing, 1988). To that end, we examined
the fit of each scale’s measurement model separately and
then specified all five variables into a single confirmatory
factor analysis (CFA) and evaluated its fit. These five
variables include: LMX (Time 3), CWX (Time 3), PCB
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544 NG, FELDMAN, BUTTS
(Time 3), constructive voice behaviour (Time 4), and
aggressive voice behaviour (Time 4).
Next, each variable was specified as a latent construct
represented by its respective measurement items. That is,
each measurement item was allowed to load only on the
construct that it was intended to represent. Each measurement model was then identified by setting the construct variance equal to the value of one (Anderson &
Gerbing, 1988). In addition, the intercorrelations among
all the variables were allowed to be freely estimated.
The fit of the CFA model was evaluated by various fit
indices recommended by Hu and Bentler (1998): TuckerLewis Index (TLI), Bollen’s Fit Index (BL89), comparative fit index (CFI), and standardized root mean squared
residual (SRMR). Hu and Bentler recommend these fit
indices in maximum likelihood-based applications of
covariance structure modelling because they are sensitive
to model misspecification (especially SRMR). To conclude a model fits the data well, Hu and Bentler (1999)
suggest that TLI, BL89, and CFI should be close to .95
and SRMR should be close to .08. The fit statistics are
presented in Table 2. With one exception (aggressive
voice), all the scales’ fit indices met or closely
approached Hu and Bentler’s (1999) cutoff scores (especially on SRMR).
The combined measurement model (which contained
all five scales) only had marginal fit, most likely because
of the relatively lower fit of the aggressive voice scale.
Nonetheless, SRMR (which is the fit index most sensitive to model misspecification) was .08, meeting the
suggested cutoff score of Hu and Bentler (1999). In
addition, all factor loadings in the CFA were statistically
significant. In sum, then, all the scales in the study had
acceptable psychometric properties except aggressive
voice—and the testing of alternative models, discussed
later, reinforced our choice to treat aggressive voice as a
separate construct from constructive voice.
In the first alternative model we tested, we treated the
items of LMX and CWX as measuring one underlying
construct. Here we wanted to examine whether respondents were able to distinguish between these two types
of social exchanges. As shown in Table 2, this alternative model had much poorer fit than the original CFA
model. For instance, the SRMR changed from .08 to .10.
The second alternative model we tested was one in
which the items of aggressive voice and constructive
voice were both specified to represent one underlying
construct. Here we wanted to examine whether respondents were able to distinguish between these two types of
voice behaviours. As shown in Table 2, we found that this
second alternative model had much worse fit than the
original CFA model. This alternative model, for example,
had a much higher value of SRMR (.13). These results
provide further support for our original CFA model, which
treated the five constructs as independent.
Common method variance. In addition, we also
examined the extent of common method variance
because all study variables were self-reported.
Podsakoff, MacKenzie, Lee, and Podsakoff (2003)
observed that, among many ways to detect common
method variance, the inclusion and specification of a
latent common method variance factor is one of the
most frequently adopted approaches. That is, measurement items are allowed to load on their underlying
theoretical construct and on a latent common method
factor. Next, the significance of the factor loadings and
factor correlations observed in the model which includes
a common method factor are compared with those
observed in the model without the common method
factor included. Any significant changes in patterns of
significant (vs. nonsignificant) results would suggest that
common method variance plays a role. Therefore, we
added such a common method factor to the previously
mentioned single CFA model.
We found that specifying a common method factor
underlying all 29 measurement items did not change the
patterns of significant findings from those observed in
the CFA model without the common method factor
included. All the substantive factor loadings in the CFA
model (that is, the relationships between items and the
underlying constructs intended to measure) were statistically significant and in the expected direction even when
TABLE 2
Confirmatory factor analyses
CFA – LMX
CFA – CWX
CFA – PCB
CFA – Constructive voice
CFA – Aggressive voice
Combined Measurement Model
Alternative Model 1
Alternative Model 2
χ2
df
TLI
BL89
CFI
SRMR
102.97
83.94
19.17
42.42
112.29
1408.47
1727.67
1910.89
9
9
5
9
9
367
371
371
.90
.88
.98
.96
.79
.89
.86
.84
.94
.93
.99
.98
.87
.90
.87
.85
.94
.93
.99
.98
.87
.90
.87
.85
.04
.06
.01
.03
.10
.08
.10
.13
CFA = confirmatory factor analyses; LMX = leader–member exchange; CWX = coworker exchange; PCB = psychological contract breach; χ2 = chisquared value; df = degree of freedom; TLI = Tucker-Lewis Index; BL89 = Bollen’s Fit Index; CFI = Comparative Fit Index; SRMR = standardized
root mean squared residual.
PSYCHOLOGICAL CONTRACT BREACH
we controlled for the influence of the common method
factor. By way of contrast, only five of the 29 factor
loadings on the common method variance factor (which
represent the relationships between items and the method
factor) were statistically significant, and there was no clear
pattern here regarding those five factor loadings either.
Thus, common method variance did not seem to be a
serious threat to the interpretation of our results.
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Data analysis techniques
To test the proposed moderation effects, we used moderated hierarchical regression. In the first step, control
variables were entered into the model. In addition to the
control variables discussed earlier (sociodemographic
variables, PCB at Time 1, and POS at Time 1), we
included the scores of LMX (or CWX) at Time 1 as
controls here, too. We did so because our interest was in
the effects of changes in LMX (or CWX) above and
beyond their static effects at Time 1.
In the second step, the main effects of PCB at Time 3
and changes in LMX (or CWX) in the preceding 8month period were entered.
In the third step, the two-way interaction term was
entered. Variables were centred before the interaction
term was created in order to reduce nonessential multicollinearity (Pedhazur, 1997). If the two-way interaction
term was a significant predictor of employees’ constructive or aggressive voice behaviour, it supported the idea
that the relationship between PCB and voice behaviour
was moderated by changes in LMX or CWX. Where we
found significant interaction effects, we also graphically
plotted the relationship to determine if its direction supported the proposed interaction hypothesis.
RESULTS
The regression results associated with our hypotheses are
presented in Tables 3 and 4; Table 3 presents the results
for LMX as a moderator, and Table 4 presents the results
for CWX as a moderator.
Hypothesis 1 predicted that PCBs would be negatively related to constructive voice behaviour (H1a) and
positively related to aggressive voice behaviour (H1b).
As shown in Table 3 (Step 1), we found that PCBs were
indeed negatively related to constructive voice behaviour, β = –.19, p < .05, above and beyond the effects
of sociodemographic variables, LMX, and POS.
Similarly, as shown in Table 4 (Step 1), we found that
PCBs were indeed negatively related to constructive
voice behaviour, β = –.31, p < .01, above and beyond
the effects of sociodemographic variables, CWX, and
POS. However, PCBs were not related to aggressive
voice (cf. Tables 3 and 4). Therefore, Hypothesis 1a
was supported, but Hypothesis 1b was not.
Hypothesis 2 addressed the moderating effects of
changes in LMX in the relationships of PCBs and voice.
545
Hypothesis 2a predicted that changes in LMX moderate
the relationship between PCB and constructive voice behaviour such that the negative relationship would be weaker
when LMX had been increasing over time. Hypothesis 2a
was not supported. As shown in Table 3, the interaction
effect of PCB at Time 3 and changes in LMX in the
preceding 8 months was not significantly related to constructive voice behaviour at Time 4.
Hypothesis 2b predicted that changes in LMX moderate the relationship between PCB and aggressive voice
behaviour such that the positive relationship would be
weaker when LMX had been increasing over time. As
shown in Table 3, the interaction effect of PCB at Time 3
and changes in LMX in the preceding 8 months was
significantly related to aggressive voice behaviour at
Time 4, β = –.25, p < .01, after controlling for both the
control variables and main effects.
To probe the nature of these interaction effects, we
plotted the interaction effect in Figure 1. Consistent with
our expectation, we found that when LMX had been
decreasing in the preceding 8-month period (that is,
when the change scores were negative), the relationship
between PCB at Time 3 and aggressive voice behaviour
at Time 4 was weakly positive, b = 0.13, SE = 0.09, β =
.18, t = 1.53, p < .10. That is, consistent with most
research on the negative outcomes of PCBs, we found
that organizational breaches of employees’ psychological
contracts were associated with greater use of aggressive
voice. On the other hand, when LMX had been increasing in the preceding 8-month period (that is, when the
change scores were positive), the relationship between
PCB at Time 3 and aggressive voice behaviour at Time 4
was negative, b = –0.12, SE = 0.07, β = –.16, t = –1.72,
p < .05. That is, an improving relationship with supervisor alleviated the adverse effects of organizational
breaches on employees’ use of aggressive voice.
Therefore, Hypothesis 2b was supported.
Hypothesis 3 addressed the moderating effects of
changes in CWX in the relationship between PCBs and
voice. Specifically, Hypothesis 3a predicted that changes
in CWX moderate the relationship between PCB and
constructive voice behaviour such that the negative relationship would be weaker when CWX had been increasing over time. As shown in Table 4, the interaction effect
of PCB at Time 3 and changes in CWX in the preceding
8 months was significantly related to constructive voice
behaviour at Time 4 (β =.18, p < .05) above and beyond
the effects of control variables and main effects.
We then plotted this interaction effect in Figure 2.
Consistent with our expectation, we found that when
CWX had been decreasing in the preceding 8-month
period, the relationship between PCB at Time 3 and
constructive voice behaviour at Time 4 was negative,
b = –0.13, SE = 0.07, β = –.17, t = –1.73, p < .05.
That is, organizational breaches of employees’ psychological contracts were associated with less use of constructive voice. When CWX had been increasing in the
546 NG, FELDMAN, BUTTS
TABLE 3
Regression results for LMX
Dependent variable
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Constructive voice behaviour
Demographic control variables
Gender
Age
Education level
Job level
Job tenure
Organizational tenure
ΔR2
Attitudinal control variables
PCB Time 1
LMX Time 1
POS Time 1
ΔR2
Main effects
PCB Time 3
Changes in LMX
ΔR2
Interaction effects
PCB Time 3 × Changes in LMX
ΔR2
F-value
Total R2
Aggressive voice behaviour
−.13
.26**
.12
.09
−.05
−.03
.11**
−.15
.26**
.12
.10
−.05
−.03
.11**
−.15
.26**
.12
.10
−.05
−.04
.11**
−.12
−.32**
.11
−.05
.06
.12
.09**
−.06
−.32**
.10
−.05
.06
.13
.09**
−.08
−.35**
.12
−.09
.07
.17
.09**
−.19*
.29**
−.12
.12**
−.22*
.28**
−.09
.12**
−.22*
.28**
−.09
.12**
−.17
−.15
−.06
.02
−.14
−.13
−.13
.02
−.13
−.10
−.18
.02
.07
.04
.00
.07
.03
.00
−.11
−.13
.02
−.14
−.02
.02
5.12**
.23**
.01
.00
4.67**
.23**
2.34*
.13*
−.25**
.05**
3.09**
.18**
6.22**
.23**
2.45*
.11*
PCB = psychological contract breach; LMX = leader–member exchange; POS = perceived organizational support; **p < .01, *p < .05.
TABLE 4
Regression results for CWX
Dependent variable
Constructive voice behaviour
Demographic control variables
Gender
Age
Education level
Job level
Job tenure
Organizational tenure
ΔR2
Attitudinal control variables
PCB Time 1
CWX Time 1
POS Time 1
ΔR2
Main effects
PCB Time 3
Changes in CWX
ΔR2
Interaction effects
PCB Time 3 × Changes in CWX
ΔR2
F-value
Total R2
Aggressive voice behaviour
−.15*
.25**
.08
.11
−.04
−.01
.11**
−.17*
.28**
.07
.10
−.06
−.01
.11**
−.16*
.28**
.06
.08
−.05
−.02
.11**
−.10
−.32**
.14*
−.05
.04
.12
.09**
−.09
−.34**
.15*
−.05
.06
.12
.09**
−.09
−.34**
.16*
−.03
.05
.13
.09**
−.31**
.01
−.02
.08**
−.30**
.07
.05
.08**
−.30**
.10
.08
.08**
−.15
−.10
−.10
.01
−.14
−.14*
−.16
.01
−.15
−.16*
−.18
.01
.06
.18*
.03*
.08
.10
.03*
−.08
−.12
.02
−.10
−.05
.02
4.83**
.22**
.18*
.02*
4.99**
.24**
2.25*
.13*
−.15*
.02*
2.37**
.14**
4.98**
.19**
2.37*
.10*
PCB = psychological contract breach; CWX = coworker exchange; POS = perceived organizational support; **p < .01, *p < .05.
preceding 8-month period, the relationship between PCB
at Time 3 and constructive voice behaviour at Time 4
was not statistically different from zero, b = –0.05, SE =
0.08, β = –.07, t = –0.63, ns. These findings provide
support for our expectation that improving relationships
with colleagues alleviate the negative effects of PCBs on
PSYCHOLOGICAL CONTRACT BREACH
547
Aggressive voice
3
2.5
Decreases in
LMX over time
2
Increases in
LMX over time
1.5
Low
High
Psychological contract breach
The interaction effect of PCB and changes in LMX on aggressive voice.
Constructive voice
4
Increases in
CWX over time
3.5
Decreases in
CWX over time
3
Low
High
Psychological contract breach
Figure 2.
The interaction effect of PCB and changes in CWX on constructive voice.
3
Aggressive voice
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Figure 1.
Decreases in
CWX over time
2.5
Increases in
CWX over time
2
1.5
Low
High
Psychological contract breach
Figure 3.
The interaction effect of PCB and changes in CWX on aggressive voice.
the use of constructive voice. Therefore, Hypothesis 3a
was supported.
We found similar patterns of results for aggressive
voice behaviour. Specifically, Hypothesis 3b predicted
that changes in CWX moderate the relationship between
PCB and aggressive voice behaviour such that the positive relationship would be weaker when CWX had been
increasing over time. As shown in Table 4, the interaction effect of PCB at Time 3 and changes in CWX in the
preceding 8 months was significantly related to aggressive voice behaviour at Time 4, β = –.15, p < .05, above
and beyond the effects of control variables and main
effects.
To probe the nature of the interaction effect, we
plotted it in Figure 3. We found that when CWX had
been decreasing in the preceding 8-month period, the
relationship between PCB at Time 3 and aggressive
voice behaviour at Time 4 was positive but not
548 NG, FELDMAN, BUTTS
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statistically different from zero, b = 0.06, SE = 0.08,
β =.07, t = 0.70, ns. That is, organizational breaches of
employees’ psychological contracts were not associated
with greater use of aggressive voice for employees who
had experienced decreases in CWX. In contrast, when
CWX had been increasing in the preceding 8-month
period, the relationship between PCB at Time 3 and
aggressive voice behaviour at Time 4 was weakly negative, b = –0.11, SE = 0.07, β = –.17, t = –1.63, p < .10.
Therefore, we found support for our prediction that
improving relationships with coworkers alleviate the
adverse effects of PCBs on employees’ use of aggressive
voice. These results provide general support for
Hypothesis 3b.
Cross-sectional versus change analyses of
moderating effects
We performed an additional analysis to highlight the
value of examining changes in employees’ relationships
with supervisors and coworkers over time. Specifically,
we reran the moderated analyses described earlier,
except this time we used LMX (or CWX) at Time 3 as
the moderator rather than changes in LMX (or CWX)
prior to Time 3. This moderated analysis simulates a
cross-sectional research design in which researchers
measure PCB and LMX (or CWX) at the same time
(Time 3) and voice behaviours at a later time (Time 4).
We found that this cross-sectional approach yielded quite
different results compared to the change approach.
Specifically, all three significant moderating effects
we reported earlier when examining changes in LMX
and CWX were no longer statistically significant when
we examined the data cross-sectionally. Moreover, when
we conducted the cross-sectional analysis, we obtained a
significant finding that we had not obtained in our
change analysis, namely, LMX at Time 3 now moderated
the relationship between PCB at Time 3 and constructive
voice behaviour at Time 4.
In sum, the results emerging from the cross-sectional
analyses were very different from the results we found in
our change analyses. Because changes in LMX and
CWX represent a more accurate representation of social
reality—and because measuring PCB, LMX, and CWX
at the same time is susceptible to the influence of common method variance—we believe that the results
revealed by our initial change approach were more accurate and meaningful.
DISCUSSION
Contributions of the present research
Guided by social exchange theory, the present study
makes several important contributions to the literature
on PCBs. First, it helps resolve previous mixed findings
regarding how employees’ relationships with
supervisors and coworkers (LMX and CWX) moderate
the effects of PCBs on work-related outcomes (Dulac
et al., 2008; Restubog et al., 2010; Suazo, 2011;
Zagenczyk et al., 2009). Turnley and Feldman (1999)
found that PCBs were positively related to (aggressive)
voice behaviours expressing employees’ dissatisfaction
with their work situations. In the present study, though,
we found that PCBs had a positive main effect on constructive voice behaviour (cf. Tables 3 and 4), although it
did not have a significant main effect on aggressive voice
behaviour. Indeed, PCBs were not even positively correlated with aggressive voice behaviours (cf. Table 1). One
potential explanation for this result is that the use of
aggressive voice may be heavily constrained in the work
context in which PCBs occur. For instance, employees
may have infrequent opportunities to express their frustration directly to their supervisors. Another possible explanation is that employees are very concerned with the risks
associated with aggressive voice. As such, they may only
be willing to voice their displeasure when they feel they
will not be reprimanded or socially ostracized. Supporting
this latter explanation, we found that the effects of
PCBs on aggressive voice behaviour depended upon
changes in the quality of relationships with supervisors
and coworkers.
The present study also highlights the important role
that time plays in understanding reactions to PCBs.
Consistent with Blau’s (1964) observation that one particular social relationship evolves in the context of multiple
social relationships, this research demonstrates that the
interplay among LMX, CWX, and the employee–organization relationship changes over time—and it is only
through understanding those changes in relationships
that we can truly understand reactions to PCBs. In the
supplemental analyses presented earlier, the model where
LMX and CWX were measured by changes over time
yielded very different findings from the model where
relationships among variables were examined cross-sectionally. Most notably, the change approach yielded three
significant interaction effects that did not emerge in the
cross-sectional analysis. We argue that the results of this
study are more compelling than those found in the four
previous studies of LMX and/or CWX as moderators of
relationships between PCBs and outcome variables
because our research design better reflects the changing
nature of social relationships in the workplace; it does not
assume that social environments are static (Jokisaari &
Nurmi, 2009; Weick et al., 2005; Wrzesniewski et al.,
2003). In addition, the cross-sectional approach is more
vulnerable to the confounding influence of common
method variance. Thus, the present study supports
Ployhart and Vandenberg’s (2010) contention that the
most appropriate way of examining covariation among
constructs is by investigating how changes in variables
over time relate to each other.
The second contribution the present study makes is
drawing needed attention to both constructive voice and
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PSYCHOLOGICAL CONTRACT BREACH
aggressive voice as dependent variables of interest in the
PCB literature. As Rusbult et al. (1988) noted, employees’ responses to dissatisfying jobs can range from the
very constructive to the very destructive. Consequently,
employees’ reactions to PCBs will not only reduce positive job behaviours but will increase negative job behaviours as well. Moreover, the present study also
examines voice behaviours that are challenge oriented
rather than affiliation oriented in nature. These challenge-oriented voice behaviours are particularly interesting to study because they can create social tension in the
workplace (MacKenzie et al., 2011). Indeed, even positively disposed employees may find using voice risky
because coworkers, immediate supervisors, or senior
management might be offended or retaliate for implicit
criticisms of their operations (MacKenzie et al., 2011). In
addition, the use of aggressive voice has to be considered
more thoroughly, too, since employees who experience
PCBs may not only engage in less constructive voice but
also engage in more counterproductive work behaviour
as well (Chao et al., 2011).
Third, the current study highlights the utility of social
exchange theory (Blau, 1964) in understanding the complex relationships among CWX, LMX, and PCBs. On
one hand, the norm of reciprocity suggests that employees will reciprocate with less positive job behaviour and
more negative job behaviour when they experience PCBs
(Coyle-Shapiro & Kessler, 2002). At the same time, social
exchange theory treats social relationships with different
parties as interdependent; how an employee behaviours in
any given exchange relationship also depends upon the
nature of other exchange relationships in the work environment. Moreover, the results here suggest that employees
do not see their coworkers, supervisors, and employer as
entirely separate entities, but rather see their relationships
with these three parties (and the influences of these relationships on their career development) as interconnected.
In order to better understand these patterns of relationships,
we urge researchers to use social exchange theory to
investigate the nomological network of CWX, LMX, and
PCBs in greater detail.
Finally, our finding that changes in LMX moderate
the relationship between PCBs and voice behaviours is
perhaps the more interesting direction for future theoretical and empirical research. We initially argued that
employees who experienced increases in LMX would
react less negatively to PCBs due to the “compensation
effect”. However, it is certainly possible that supervisors,
as agents of the organization, are seen as conjointly
responsible for breaching psychological contracts in the
first place. Consequently, improving LMX may not
reduce (or could even exacerbate) negative reactions to
PCBs if supervisors are believed to be foes rather than
friends. To disentangle the complex relationships
between LMX and PCBs, future researchers should
investigate both employees’ attributions about who
caused the PCBs and corresponding supervisors’
549
attributions about those causes as well (Chao et al.,
2011; Lester, Turnley, Bloodgood, & Bolino, 2002).
Limitations of the present research
The present study has some methodological constraints,
which should be addressed in future research. First, all
the variables in this study were self-reported. We tried to
minimize that methodological threat of common method
variance through the use of multiple waves of surveys. In
addition, we separated our measurements of PCB (the
independent variable) and voice behaviour (the dependent variable) by 4 months to further reduce the influences of common method variance. Fortunately, the CFA
analysis presented earlier suggests that common method
variance is not a major threat to our dataset, but it is not
completely absent, either. Second, although there were
good theoretical reasons for the order of the variables in
our model and data were collected longitudinally, reverse
causation is certainly possible in some of the relationships we investigated. For example, individuals who
used more voice might have been able to prevent PCBs
from occurring in the first place. Future research should
address other possible ways these constructs might be
related to each other. Third, we relied on the compensation argument as the key theoretical argument for why
we expected LMX and CWX would moderate the effects
of PCBs on voice. We were not able to measure the
salience of these social relationships, though, in the present study. Therefore, future research is needed to investigate the salience of employees’ relationships with
supervisors and coworkers more directly.
Fourth, the present research design limited our focus to
linear changes in LMX and CWX that occurred over the
duration of the study. However, it is possible that LMX
and CWX could change in nonlinear patterns, but more
than three collections of LMX and CWX data would be
needed to identify such patterns. Fifth, although response
rates at each time point were reasonable for electronic
surveys, the overall response rate aggregated across all
four time periods is lower than ordinarily desired. Given
that we were collecting data over a 1-year period at four
waves, some subject attrition was inevitable. However, a
larger sample at Time 1 would certainly have been beneficial. Last, more work is needed on the measurement of
aggressive voice. In the present study, although it had an
acceptable level of internal consistency and could be readily differentiated from constructive voice, our measure of
aggressive voice had the weakest psychometric properties.
Future research using different scales of aggressive voice
behaviour will therefore be needed to further corroborate
the current findings.
Implications for management practice
Employee–employer relationships have become shorter
term and more transactional in nature over the years.
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550 NG, FELDMAN, BUTTS
Indeed, it has become harder for senior management to
identify and develop employees who are deeply committed to their organizations (Rousseau, 1998). This
study points out that, in trying to build stronger ties
between employees and organizations, the quality of
workplace relationships with supervisors and coworkers
may be an important pivot point (Stewart & Johnson,
2009; Sue-Chan, Chen, & Lam, 2011). Employees’
responses to PCBs depend not only on the objective
working conditions (such as the failure to get an
expected pay raise), but also upon subjective feelings
about their relationships with the people they work
with on a daily basis. When there are high-quality social
exchanges with supervisors and coworkers, employees
are less likely to respond strongly and negatively to
organizational contract breaches. Therefore, particularly
in times of shrinking resources and limited growth,
organizations should foster higher quality relationships
among employees, supervisors, and coworkers to reduce
the negative effects likely to be associated with subsequent PCBs.
It should also be noted, though, that increasing the
strength of LMX and CWX might come at the expense
of the bond between the employee and the organization.
While improving employees’ relationships with supervisors and coworkers may reduce the negative effects of
PCBs on employees, it is also possible that improving
LMX and CWX might simultaneously weaken the
intended (positive) bond with the organization itself.
Employees might expect promotions on the basis of
high LMX when, in fact, such promotions might be
based on organization-wide criteria rather than unit leader recommendations. As a result, high LMX might
actually lead to more perceived breaches of psychological contracts. Consequently, it might be more appropriate
to consider LMX and CWX as potential compensatory
mechanisms for organization-wide PCBs (for instance,
no pay raises due to poor economic conditions) rather
than as substitutes for poor employee–employer relationships in general.
In addition, in recent years, many organizations have
sought out ways to promote employee voice, treating it
as a source of innovation or a way of enhancing firm
sustainability (Dundon & Gollan, 2007; Wood & Wall,
2007). Our findings support the notion that supervisors
and coworkers do play an important role in encouraging
constructive voice behaviour. However, managers have
perhaps paid too little attention to the extent of aggressive voice behaviour in their units. This destructive voice
behaviour can seriously hurt workplace morale or interfere with the effective functioning of the unit. When
aggressive voice crosses over the line to destructive
voice, managers who fail to address such behaviour
from conflict aversion risk having destructive voice
becoming more contagious and even more destructive
over time.
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Original manuscript received March 2012
Revised manuscript received December 2012
First published online March 2013