Justice as a Dynamic Construct: Effects of Individual Trajectories on Distal Work Outcomes 
 
John P. Hausknecht, Cornell University 
Michael C. Sturman, Cornell University 
Quinetta M. Roberson, Villanova University 
 
 
Despite an amassing organizational justice literature, few studies have directly 
addressed the temporal patterning of justice judgments and the effects that changes in 
these perceptions have on important work outcomes. Drawing from Gestalt characteristics 
theory (Ariely & Carmon, 2000, 2003), we examine the concept of justice trajectories (i.e., 
levels and trends of individual fairness perceptions over time) and offer empirical evidence 
to highlight the value of considering fairness within a dynamic context. Participants 
included 523 working adults who completed surveys about their work experiences on 4 
occasions over the course of 1 year. Results indicate that justice trends explained additional 
variance in distal work outcomes (job satisfaction, organizational commitment, and 
turnover intentions) after controlling for end-state levels of justice, demonstrating the 
cumulative effects of justice over time. Findings also reveal that change in procedural 
justice perceptions affected distal work outcomes more strongly than any other justice 
dimension. Implications for theory and future investigations of justice as a dynamic 
construct are discussed. 
 
 
In the continuing search to understand how employees process and react to fairness-related 
information, researchers have begun to study justice from a longitudinal perspective. On the basis of the 
premise that employees adjust their justice perceptions over time as they obtain additional information 
about the organization and its allocation procedures and decisions, such studies have shown that justice 
perceptions are variable and exert time-dependent influence on work outcomes (Ambrose & 
Cropanzano, 2003; Holtz & Harold, 2009; Truxillo, Bauer, Campion, & Paronto, 2002). By demonstrating 
the explanatory power of within-person variance in fairness perceptions, such research suggests that 
static and cross-sectional investigations are bounded in what they can reveal about justice and its 
effects. 
Despite this progress, there is still much that is not known about justice over time. For example, 
imagine a situation in which two employees rate their justice perceptions as “1” and “5,” respectively, 
on a 5-point scale at the beginning of a given year, and both as “3” at the end of the year. Although their 
end-state justice perceptions are identical, they have different meanings for the employees given their 
prior justice perceptions. One employee perceived a decline in the fairness of his or her organizational 
perceptions, whereas the other perceived improved treatment. Thus, despite similarities in the 
magnitude of perceptual change across these individuals, they will likely exhibit divergent attitudes and 
behavior because of both the level and trend (i.e., “trajectory”) of their fairness perceptions. Current 
examinations of justice, however, do not allow insight into such effects. Although research has 
acknowledged that time is an important source of variance in employees’ justice perceptions, it remains 
unclear how the direction and rate of change in these perceptions influences distal work outcomes. 
The goal of this study is to present a dynamic perspective on organizational justice by examining 
the effects of justice trajectories on employee attitudes and intentions. Researchers have examined 
trajectories in other domains, such as job satisfaction (Boswell, Boudreau, & Tichy, 2005; Boswell, Shipp, 
Payne, & Culbertson, 2009; Chen, Ployhart, Cooper-Thomas, Anderson, & Bliese, in press), 
organizational commitment (Bentein, Vandenberg, Vandenberghe, & Stinglhamber, 2005), employee 
turnover (Harrison, Virick, & William, 1996; Kammeyer-Mueller, Wanberg, Glomb, & Ahlburg, 2005; 
Sturman & Trevor, 2001), and individual and team performance (Chen, 2005; Mathieu & Rapp, 2009).1 A 
common thread underlying these studies is that employees use past experiences as a backdrop for 
evaluating and reacting to ongoing job experiences (Boswell et al., 2005). As a result, theories, results, 
and conclusions change when focusing on trajectories versus (or in addition to) static assessments. 
Although some justice research has considered prior justice experiences as temporal frames of 
reference (e.g., van den Bos et al., 2005), few studies have investigated how people draw upon their 
earlier experiences of fair and unfair treatment, and the subsequent effects on attitudes and behavior. 
Justice trajectories, however, may capture unique information that is not accounted for in single-wave 
research designs. Because individuals’ past justice experiences provide information by which to evaluate 
future justice experiences, we believe that directly exploring the rise and fall of justice perceptions over 
time can improve the precision of theory testing while adding to the predictive validity of justice in 
                                                          
1 Note that what sets studies of trajectories apart from “time-lagged” longitudinal designs (i.e., separating 
predictor and outcome measurement in time) is that repeated assessments of the focal construct must be 
collected. Time-lagged designs, although valuable, do not allow one to detect that the construct itself has changed 
over time. Multiple assessments, ideally three or more, are required to construct and test individual trajectories 
(Singer & Willett, 2003). 
explaining work outcomes. Thus, using longitudinal data from 523 working adults, we examine justice 
trajectories for perceptions of distributive, procedural, interpersonal, and informational justice, and the 
predictive validity of such trajectories in explaining future job satisfaction, organizational commitment, 
and turnover intentions. 
Theoretical Background and Hypotheses Gestalt Characteristics 
Recent work in behavioral decision making has reasoned the processes through which subjective 
evaluations develop over time. In particular, Ariely and Carmon (2000, 2003) have conceptualized 
people’s experiences as they unfold over time in terms of experience profiles, or a series of episodes 
varying in intensity (e.g., pleasurable experiences such as a vacation, painful experiences such as 
extreme heat). Critical to their conceptualization is the idea that “when people form summary 
assessments of experiences, they do not combine the individual components of the experience profiles” 
(Ariely & Carmon, 2003, p. 324). That is, rather than simply average the transient experiences that 
constitute the experience profile, individuals draw upon both static (e.g., end-state evaluations) and 
dynamic (e.g., trend over time) properties of the experience profile— or “Gestalt characteristics”—when 
forming overall evaluations. 
Given certain limitations of human cognition, which allow individuals to only remember key 
features of their experiences (Fredrickson & Kahneman, 1993), Ariely and Carmon (2000, 2003) have 
contended that Gestalt characteristics are useful for making judgments about future experiences. 
Specifically, individuals evaluate the favorability of past experiences to make predictions about the 
desirability of future episodes. However, rather than base their evaluations on the intensity of specific 
episodes, Ariely and Carmon have argued that people form judgments based on the relationship 
between episodes within an experience profile. In other words, summary assessments of one’s 
experiences are driven by trends in the favorability of episodes over time. Such dynamic Gestalt 
information provides cues about likely future states, allowing people to extrapolate from the past to 
determine whether to repeat or pursue similar experiences, an argument that is consistent with 
Kahneman’s (1999) contention that decisions to remain or depart from a given situation depend on the 
pattern of states experienced over time. 
Within an organizational setting, Reb and Cropanzano (2007) applied a Gestalt characteristics 
perspective to performance evaluation. Manipulating sales performance profiles, the authors found that 
raters attended to both static (i.e., mean performance) and dynamic characteristics (i.e., performance 
trend over time) when rating performance. Performance trends explained additional variance in ratings 
beyond mean performance such that an improving trend led to higher ratings even though the mean 
performance was identical. Chen et al. (in press) applied a logic similar to that of Gestalt characteristics 
to the domain of work attitudes, arguing that relative improvements or decrements in job satisfaction 
are influential in determining individuals’ evaluations of whether to remain or leave their current 
position. Drawing from prospect theory (Kahneman & Tversky, 1979), within-person spirals (Hsee & 
Abelson, 1991; Lindsley, Brass, & Thomas, 1995), and sense-making rationales (Louis, 1980), they 
developed an integrative theoretical framework for understanding job satisfaction change, proposing 
that (a) satisfaction from earlier time points provide a reference point for interpreting satisfaction at 
later time points, and (b) the degree of change in job satisfaction over time shapes interpretations and 
expectations of current and future work conditions. Using four different samples, they found empirical 
support for their framework—specifically, the added value of job satisfaction change in predicting 
turnover intentions beyond average (static) job satisfaction levels. Taken together, these studies suggest 
an important role for studying both static and dynamic characteristics of individuals’ reactions to 
ongoing experiences. 
Although the study of Gestalt characteristics has not been extended to the organizational justice 
domain, related theory and empirical findings provide a foundation for drawing such a linkage. For 
example, fairness heuristic theory (Lind, 2001; van den Bos, 2001) gives prominence to the conceptual 
role of time in explaining how justice judgments develop. According to the theory, individuals draw upon 
repeated exchanges with supervisors, procedures, and outcomes to form justice judgments, and they 
use them to determine whether organizations are fair. More specifically, fairness heuristics are formed 
during a “judgmental phase” using whatever justice information is available. Individuals then use such 
heuristics as a guide for their subsequent attitudes and behaviors (Lind, 2001), relying upon the 
established fairness heuristics until a “phase-shifting event,” such as a critical or unexpected work event 
or the acquisition of new information that is contradictory with the heuristic, causes them to reenter the 
judgmental phase and to recalibrate their perceptions (Lind, 2001; van den Bos, 2001). 
Consistent with this expectation, researchers have shown that justice perceptions indeed 
change over time and that the magnitude and direction of change varies within and between individuals 
(Ambrose & Cropanzano, 2003; Holtz & Harold, 2009; Loi, Yang, & Diefendorff, 2009). Loi et al. (2009) 
tracked justice perceptions and job satisfaction among full-time employees in Hong Kong across 25 days, 
and they found evidence of daily variations in the justice–satisfaction relationship. Holtz and Harold 
(2009) also conducted a longitudinal examination of justice by assessing people’s perceptions of overall 
organizational and supervisory justice at three points in time over a 3-month period. The results showed 
significant within-person variability in overall justice perceptions across time and between-person 
variability in how these perceptions developed over time. 
Although these studies highlight the importance of considering justice over time, they show the 
presence of dynamic perceptions of justice and not the effects of this dynamism on subsequent work 
outcomes. In this article, we therefore extend the domain of theoretical work on organizational justice 
by adopting an “experience profile” perspective on justice. Because individuals use trends of their 
experiences to form summary judgments (Ariely & Carmon, 2000, 2003) and, relative to fairness, use 
past justice evaluations to form heuristics that guide future evaluations and subsequent reactions (Lind, 
2001), we examine the relationships between justice trajectories and distal work outcomes. Specifically, 
we focus on the influence of justice levels and trends on job satisfaction, organizational commitment, 
and turnover intentions— thereby seeking to capture the effects of justice more fully. Given the 
subjectivity and volatility of justice relative to other attitudes over time (Greenberg & Colquitt, 2005; Loi 
et al., 2009), this study of within-person variability in justice also allows insight into justice as a dynamic 
construct. More importantly, as people use perceptions of justice to determine their reactions to future 
experiences, temporal changes in such perceptions may be considered a Gestalt characteristic. 
We expect that examining the impact of justice trajectories on work outcomes may reveal 
fairness as a defining feature of the affective profile of employees’ organizational experiences. Given 
this logic, fairness trends should explain additional variance in employees’ future attitudes and 
intentions. Returning to our opening example, of the two employees with identical end-state justice 
evaluations (ratings of “3”), trend information would help explain employees’ reactions. If individuals 
indeed rely upon trends to predict the likelihood that conditions will continue to improve (in the case of 
a positive trend) or worsen (negative trend), the extrapolation-based argument (Ariely & Carmon, 2003) 
suggests that although they share identical end-state ratings, trend information will explain additional 
variance in work outcomes because individuals are forecasting how the future is likely to unfold. 
Negative justice trends may be indicative of heightened uncertainty or the reduced trustworthiness of a 
supervisor or organization, thus engendering dissatisfaction with the job and detachment from the 
organization. Positive trends may signal increased confidence in future states, thereby increasing 
satisfaction and lowering intentions to leave. Accordingly, we expect that employees will be more 
satisfied, committed, and less likely to leave an organization if justice trends indicate that conditions are 
improving. Specifically, we hypothesize the following: 
• Hypothesis 1: Justice trends will be positively related to job satisfaction (above and 
beyond the effects of end-state justice perceptions). 
• Hypothesis 2: Justice trends will be positively related to organizational commitment 
(above and beyond the effects of end-state justice perceptions). 
• Hypothesis 3: Justice trends will be negatively related to turnover intentions (above and 
beyond the effects of end-state justice perceptions). 
Method 
Sample and Procedure 
The sample consists of 523 working adults from a variety of occupations who completed surveys 
about their work experiences in January, April, July, and October of 2007. We recruited our sample from 
a panel of participants registered with the Study Response Project, which is an online service that 
connects social science researchers with individuals who are interested in study participation 
(http://studyresponse.syr.edu). Other samples have been drawn from the panel, as reported in previous 
research (e.g., Inness, LeBlanc, & Barling, 2008; Piccolo & Colquitt, 2006). A total of 3,286 participants 
were contacted to participate in the study, and 2,464 completed the January (Time 1) survey (response 
rate _ 75.0%). Subsequent surveys were sent to individuals who participated in the survey from the 
previous wave. Response rates for the April (Time 2), July (Time 3), and October (Time 4) surveys were 
67.6%, 65.2%, and 72.0%, respectively. A sampling frame of 1 year was selected to allow for natural 
variation in the company practices that are known to influence justice perceptions (e.g., pay decisions, 
performance reviews, and so on). To match our interest in time-specific perceptions, participants were 
asked to consider their work experiences over the past 3 months when completing each survey, and 
slight wording changes were made to existing scales as necessary to maintain consistency with this 
focus. Individuals who changed jobs over the course of the year were excluded from further analysis 
because they would be reacting to different procedures, outcomes, and interactions at various points of 
the study. In all, by including only those with all four observations who did not change jobs and who had 
sufficient data for the analyses, our final sample was 523 (overall response rate _ 15.9%). When 
comparing the final sample with the excluded sample, no statistically significant differences were found 
for gender, job tenure, organizational tenure, procedural justice, distributive justice, or interpersonal 
justice. However, participants in the final sample were older (M _ 39.7 vs. 37.6) and reported higher 
perceptions of informational justice (M _ 3.6 vs. 3.5). After a Bonferroni correction was applied to adjust 
for multiple comparisons, only the age difference remained statistically significant. 
Measures 
Organizational justice. We measured four dimensions of organizational justice at all four time 
points using the measure validated by Colquitt (2001). Four items assessed distributive justice (e.g., “The 
outcomes that I receive reflect what I contribute to the organization”), seven items assessed procedural 
justice (“In my organization, procedures are based on accurate information”), four items assessed 
interpersonal justice (“My supervisor treats me in a polite manner”), and five items assessed 
informational justice (“My supervisor communicates details in a timely manner”). The item anchors 
ranged from 1 (strongly disagree) to 5 (strongly agree). 
Job satisfaction. Job satisfaction was measured using six items from Hackman and Oldham 
(1975). A sample item is “Considering everything, I am satisfied with my job.” The anchors for each item 
ranged from 1 (strongly disagree) to 5 (strongly agree). Job satisfaction measured at Time 4 is the 
dependent variable in Hypothesis 1. 
Organizational commitment. We measured affective organizational commitment using eight 
items from Allen and Meyer (1990). A sample item is “My organization has a great deal of personal 
meaning for me.” Anchors ranged from 1 (strongly disagree) to 5 (strongly agree). Organizational 
commitment measured at Time 4 is the dependent variable in Hypothesis 2. 
Turnover intentions. Three items from Kelloway, Gottlieb, and Barham (1999) were used to 
assess quit intentions. A sample item is “I am thinking about leaving my organization.” The anchors for 
each item ranged from 1 (strongly disagree) to 5 (strongly agree). Turnover intentions measured at Time 
4 are the dependent variable in Hypothesis 3. 
Control variables. To test whether justice trends explain variance beyond end-state perceptions, 
we control for Time 4 justice in all of our models. Further, when considering any variable across time, it 
is important to ensure that we are examining the effects specifically associated with our independent 
variables, and not spurious effects that, in a longitudinal context, may be associated with both our 
dependent and independent variables. Thus, for each hypothesis test, we included a lagged variable as a 
control (e.g., when predicting Time 4 job satisfaction, Time 1 job satisfaction is included as a control). 
Including the lagged dependent variable partials out stable effects associated with the dependent 
variable that may also be associated with the independent variables of interest (Sturman, 2007). 
Furthermore, because our longitudinal data are all same source, controlling for other variables likely to 
be similarly affected by any potential common method variance (CMV; i.e., the same measure at a 
different time, and an attitudinal measure at the same time) will help diminish any potential effect of 
CMV in subsequent regression analyses with multiple independent variables (Siemsen, Roth, & Oliveria, 
2010). This a priori methodological approach to dealing with CMV is also preferable to post hoc tests 
because of the general unreliability and inaccuracy of post hoc correction techniques (Richardson, 
Simmering, & Sturman, 2009). 
Results 
Descriptive Statistics 
Means, standard deviations, correlations, and coefficient alpha estimates are reported in Table 
1. Across the four justice dimensions at Time 4, alphas ranged from .93 to .97, indicating good internal 
consistency. To quantify the relative proportion of inter-individual variance, we calculated an intraclass 
2
correlation coefficient (ICC) using the standard formula for longitudinal designs (𝜌 = 𝜎0 �𝜎 2 + 𝜎 2) . ICC 0 𝜀
values were .62 (distributive justice), .75 (procedural justice), .70 (informational justice), and .66 
(interpersonal justice). Thus, between 62% and 75% of the variance in justice perceptions was found to 
lie between people, and between 25% and 38% constituted within-person variance over time. 
 
Measurement Issues 
To examine the validity of our measurement model at each time point, we conducted a series of 
confirmatory factor analyses using item-level data from the seven attitude measures. We compared the 
fit of our theorized seven-factor model (procedural justice, distributive justice, informational justice, 
interpersonal justice, job satisfaction, organizational commitment, turnover intentions) with five 
plausible alternative models. As shown in Table 2, across all four time points the seven-factor model 
(i.e., four justice dimensions and three outcomes) provided better fit than any alternative model. We 
also conducted tests of longitudinal measurement invariance following recommendations outlined by 
Vandenberg and Lance (2000) to determine whether justice perceptions were measured similarly across 
time. For each of the four justice dimensions, we conducted four measurement invariance tests: 
configural invariance (test of equivalent factor structures), metric invariance (test of invariant factor 
loadings), invariant uniqueness (test of equal error variances), and invariant factor variances (test of 
equal variance in latent constructs). As shown in 
Table 3, in all cases, model fit remained stable as 
additional constraints were imposed, thereby 
supporting the measurement equivalence of the 
justice dimensions over time. 
Hypothesis Tests 
To test Hypotheses 1–3, we first confirmed 
that individuals exhibited variability around the 
linear trend component of each justice dimension (if 
they did not, hypothesis tests would not be 
meaningful). We used hierarchical linear modeling 
(HLM; and specifically, the HLM software) to model 
each individual’s intercept and trend for each justice 
dimension, specifying each dimension of justice as 
the dependent variable and an intercept and linear 
time vector as independent variables (Y _ b0 _ b1 _ 
time). All models allowed for estimation of random 
variation around both the intercept (b0) and the 
linear coefficient (b1) for time. That is, Level 2 
random effects were modeled for both Level 1 
terms. Results, shown in Table 4, indicate that for all four justice dimensions, there was statistically 
significant between-person variance in trends, providing evidence that individuals indeed develop 
different justice trends over time and confirming that it is appropriate to test whether justice trends 
predicted work outcomes. 
 
We then used the Bayes-estimated HLM coefficients for the trend (b1), for each justice 
dimension and for each person, as independent variables when testing Hypotheses 1–3. These 
hypotheses were tested using ordinary least squares regression. We predicted that the justice trend 
would be positively associated with job satisfaction (Hypothesis 1), positively associated with 
organizational commitment (Hypothesis 2), and negatively associated with turnover intentions 
(Hypothesis 3). As noted earlier, these effects are estimated after controlling for the lagged dependent 
variable from Time 1 to partial out any stable effects that otherwise may be associated with both the 
dependent and independent variables. Similarly, all of these tests control for the current level of justice 
(i.e., each justice dimension at Time 4), so that results attributed to justice trends are beyond the 
variance explained by the end-state or “static” levels of justice for that dimension. 
 
Table 5 presents the job satisfaction results. In all models, Time 4 justice dimensions and Time 1 
job satisfaction were positive and statistically significant predictors of Time 4 job satisfaction. Supporting 
Hypothesis 1, Models 1–4 show that justice trends were statistically significant and positively related to 
Time 4 job satisfaction for all justice dimensions. These results indicate that, holding constant their most 
recent justice perceptions, individuals who reported increasingly favorable justice perceptions over time 
were more satisfied with their jobs at the end of the period, and those who indicated a decline were less 
satisfied. 
 
Table 6 shows results for organizational commitment. In all models, Time 4 justice dimensions 
and Time 1 organizational commitment were positive and statistically significant predictors of Time 4 
organizational commitment. Models 1–4 indicate that justice trends were statistically significant and 
positively related to Time 4 organizational commitment for all justice dimensions. These results support 
Hypothesis 2 and indicate that, regardless of their most recent justice perceptions, individuals who 
reported increasingly favorable justice perceptions over time were more committed to the organization 
at the end of the period, and those who indicated a decline were less committed. 
 
Table 7 displays results for turnover intentions. In all models, Time 4 justice dimensions (with 
the exception of interpersonal justice) and Time 1 turnover intentions were statistically significant 
predictors of Time 4 turnover intentions. Models 1–4 reveal that justice trends were statistically 
significant and negatively related to Time 4 turnover intentions for all justice dimensions. These results 
support Hypothesis 3 and indicate that, holding constant their most recent justice perceptions, 
individuals who reported increasingly favorable justice perceptions over time had lower intentions to 
leave the organization at the end of the period, and those who indicated a declining trend had higher 
quit intentions.2 
 
As a supplemental analysis, we tested the relative effects of each justice dimension in a single 
equation for each of the three work attitudes. Model 5 in Tables 5–7 shows the results of simultaneous 
prediction of each outcome using Time 4 level and the trend for each of the four justice dimensions. For 
all three work attitudes, the procedural justice trend was statistically significant and in the expected 
direction, whereas the distributive justice trend was not statistically significant in any case. The 
informational justice trend was statistically significant when predicting job satisfaction, and the 
interpersonal justice trend was statistically significant when predicting turnover intentions. Thus, 
controlling for the trend of the other three justice dimensions, only the procedural justice trend 
remained a statistically significant predictor of all three work outcomes. 
In summary, our findings indicate support for the end-state and dynamic attributes of justice, as 
justice trends explained variance in job satisfaction, organizational commitment, and turnover 
                                                          
2 In addition to controlling for the most recent level of justice perceptions (i.e., Time 4, as reported here), we ran 
additional models controlling for the individual’s average justice level over the entire period (i.e., mean of Times 1–
4). The pattern of findings (i.e., coefficient sign and significance) and conclusions are consistent with those 
reported here (details available upon request). 
intentions beyond the most recent level of justice perceptions. Controlling for end-state perceptions, 
employees with negative trends over time (i.e., moving to lower perceptions of justice) were ultimately 
less satisfied, less committed, and more likely to consider leaving the organization, whereas those with 
positive trends were more satisfied, more committed, and more willing to stay. When testing justice 
trends for all four dimensions simultaneously, we found that only procedural justice retained 
explanatory power for all three work outcomes. 
Discussion 
Although studies of organizational justice have multiplied in recent years, few have directly 
addressed how perceptions of justice change over time and how such change influences important work 
outcomes. To fill this gap, we drew from Gestalt characteristics theory (Ariely & Carmon, 2000, 2003) 
and conceptualized justice in terms of individual trajectories to highlight the value of considering justice 
as a dynamic construct. Consistent with our theorizing, we focused on the levels and trends of people’s 
justice evaluations over time and examined how they shape distal employee attitudes and intentions. 
We tracked employees’ perceptions across an entire year and found that justice trends explained 
variance in their satisfaction, commitment, and turnover intentions beyond that captured by 
contemporaneous, end-state justice levels. Accordingly, we are able to highlight the Gestalt 
characteristics on which people rely to arrive at evaluations of, and reactions to, their justice 
experiences. The results suggest that improving (declining) fairness conditions over time motivate more 
(less) favorable employee attitudes. These results are striking given that we controlled for end-state 
perceptions, which previous research has shown to be particularly influential in driving evaluations (e.g., 
Fredrickson & Kahneman, 1993). 
We also found that Gestalt characteristics of justice varied across different justice types, as our 
investigation revealed that the effects of justice trends on outcomes differed depending on the specific 
dimension of justice. For example, although all four justice dimensions were generally related to our 
three dependent variables (both in terms of level and trend), only procedural justice trends retained 
explanatory power when all dimensions were considered simultaneously. Such a pattern is consistent 
with arguments outlined in the two-factor and agent-system models of justice (see Colquitt, Conlon, 
Wesson, Porter, & Ng, 2001), as both predict that procedural justice has stronger effects on system 
referenced outcomes such as organizational commitment. More importantly, this pattern suggests that 
procedural justice may serve as a salient Gestalt characteristic as people arrive at summary evaluations 
of their justice experiences and generate reactions to such experiences. 
Above all, by framing justice perceptions in terms of trajectories, this study offers a theoretical 
rationale for a dynamic approach to organizational justice and empirically supports the value of moving 
beyond purely cross-sectional perspectives. In addition, consistent with the findings of recent 
longitudinal studies of justice, our empirical results show that fairness evaluations are not static, and the 
relationships documented in cross-sectional research do not account for the total effects of justice on 
work attitudes and intentions. These findings suggest that it is important to consider both trends and 
levels when examining the longer term outcomes of justice perceptions. 
Limitations 
Despite these results, one limitation of our survey-based longitudinal design is that we were 
only able to gather self-report data, which may raise concerns about CMV. We attempted to minimize 
the impact of these issues via temporal separation of measurement and lagged dependent variable 
controls, both of which help alleviate such biases (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003; 
Siemsen et al., 2010). A second limitation concerns the generalizability of findings to other contexts. 
Although the sample was drawn from a cross-section of working adults in a variety of organizations, its 
representativeness of the broader employee population cannot be ensured. A third limitation relates to 
participant attrition. Despite reasonable period-to-period response rates and few differences between 
responders and nonresponders, the final sample size represented a relatively small percentage of those 
initially contacted. 
Managerial Implications 
Given our findings that justice trajectories influence employees’ distal attitudes and intentions, 
managers may find it useful to consider employees’ unique histories of perceived treatment. Our 
findings show that even if all employees hold similar fairness perceptions at a given point, resultant 
attitudes and intentions will differ depending on how employees feel relative to how they have been 
treated in the past. Thus, to retain a satisfied and committed workforce, managers may want to be 
cognizant of how employees are reacting to ongoing workplace experiences over time. For example, 
when organizations engage in employee attitude surveys, our study suggests that it is important for 
them to consider trends in these attitudes and not solely the most current survey results. As our results 
also highlight procedural justice trajectories as particularly influential to employee attitudes and 
turnover intentions, organizational leaders should put resources into ensuring that policies and 
procedures are fairly enacted. 
Future Research 
Above all, our findings suggest that future justice theory and research can benefit from adopting 
a dynamic process perspective. Dynamic process theories are predicated on the notion that phenomena 
can only be understood as “the multiple, mutual, and continuous interaction of all levels of the 
developing system” (Thelen & Smith, 1998, p. 563). Their advantage over cross-sectional perspectives is 
that new forms can emerge when considering the total experience of the entity under study. Although 
this temporal lens provides a new perspective from which to study organizational justice, no single study 
will be sufficient to address the challenges and opportunities associated with this approach. For 
example, although our 1-year timeframe and four-wave, repeated measures design provides an initial 
test of justice trajectories, future research that examines alternative timeframes and behavioral 
outcomes is needed. 
We also encourage justice researchers to consider other time-related concepts. For example, 
“threshold effects” may occur with time such that changes in perceptions of fairness must reach or 
exceed a certain level before they have an appreciable effect on employee attitudes or behaviors 
(Taylor, 2001). Individuals’ perceptions of an organization or supervisor may be relatively stable until, 
consistent with fairness heuristic theory (Lind, 2001), a phase-shifting event that signals a substantive 
change in the relationship with the organization may occur. Such an event may create the expectation 
that treatment by the organization or decision maker is unlikely to exceed (or drop below) that level. It 
is only by measuring perceptions repeatedly that researchers will become able to discern these types of 
effects. 
References 
Allen, N. J., & Meyer, J. P. (1990). The measurement and antecedents of affective, continuance, and 
normative commitment to the organization. Journal of Occupational Psychology, 63, 1–18. 
Ambrose, M. L., & Cropanzano, R. (2003). A longitudinal analysis of organizational fairness: An 
examination of reactions to tenure and promotion decisions. Journal of Applied Psychology, 88, 
266–275. doi: 10.1037/0021-9010.88.2.266 
Ariely, D., & Carmon, Z. (2000). Gestalt characteristics of experiences: The defining features of 
summarized events. Journal of Behavioral Decision Making, 13, 191–201. 
doi:10.1002/(SICI)1099-0771(200004/ 06)13:2_191::AID-BDM330 3.0.CO;2-A 
Ariely, D., & Carmon, Z. (2003). Summary assessments of experiences: The whole is different from the 
sum of its parts. In G. Loewenstein, D. Read, & R. Baumeister (Eds.), Time and decision: 
Economic and psychological perspectives on intertemporal choice (pp. 323–349). New York, NY: 
Sage. 
Bentein, K., Vandenberg, R., Vandenberghe, C., & Stinglhamber, F. (2005). The role of change in the 
relationship between commitment and turnover: A latent growth modeling approach. Journal of 
Applied Psychology, 90, 468–482. doi:10.1037/0021-9010.90.3.468 
Boswell, W. R., Boudreau, J. W., & Tichy, J. (2005). The relationship between job change and job 
satisfaction: The honeymoon-hangover effect. Journal of Applied Psychology, 90, 882–892. 
doi:10.1037/0021- 9010.90.5.882 
Boswell, W. R., Shipp, A. J., Payne, S. C., & Culbertson, S. S. (2009). Changes in newcomer job satisfaction 
over time: Examining the pattern of honeymoons and hangovers. Journal of Applied 
Psychology, 94, 844–858. doi:10.1037/a0014975 
Chen, G. (2005). Newcomer adaptation in teams: Multilevel antecedents and outcomes. Academy of 
Management Journal, 48, 101–116. 
Chen, G., Ployhart, R. E., Cooper-Thomas, H., Anderson, N., & Bliese, P. D. (in press). The power of 
momentum: A new model of dynamic relationships between job satisfaction change and 
turnover intentions. Academy of Management Journal. 
Colquitt, J. A. (2001). On the dimensionality of organizational justice: A construct validation of a 
measure. Journal of Applied Psychology, 86, 386–400. doi:10.1037/0021-9010.86.3.386 
Colquitt, J. A., Conlon, D. E., Wesson, M. J., Porter, C. O. L. H., & Ng, K. Y. (2001). Justice at the 
millennium: A meta-analytic review of 25 years of organizational justice research. Journal of 
Applied Psychology, 86, 425–445. doi:10.1037/0021-9010.86.3.425 
Fredrickson, B. L., & Kahneman, D. (1993). Duration neglect in retrospective evaluations of affective 
episodes. Journal of Personality and Social Psychology, 65, 45–55. doi:10.1037/0022-
3514.65.1.45 
Greenberg, J., & Colquitt, J. A. (2005). The handbook of organizational justice. Mahwah, NJ: Erlbaum. 
Hackman, J. R., & Oldham, G. R. (1975). Development of the job diagnostic survey. Journal of Applied 
Psychology, 60, 159 –170. doi: 10.1037/h0076546 
Harrison, D. A., Virick, M., & William, S. (1996). Working without a net: Time, performance, and turnover 
under maximally contingent rewards. Journal of Applied Psychology, 81, 331–345. 
doi:10.1037/0021- 9010.81.4.331 
Holtz, B. C., & Harold, C. M. (2009). Fair today, fair tomorrow? A longitudinal investigation of overall 
fairness perceptions. Journal of Applied Psychology, 94, 1185–1199. doi:10.1037/a0015900 
Hsee, C. K., & Abelson, R. P. (1991). Velocity relation: Satisfaction as a function of the first derivative of 
outcome over time. Journal of Personality and Social Psychology, 60, 341–347. 
doi:10.1037/0022- 3514.60.3.341 
Inness, M., LeBlanc, M. M., & Barling, J. (2008). Psychosocial predictors of supervisor, peer, subordinate, 
and service provider targeted aggression. Journal of Applied Psychology, 93, 1401–1411. 
doi:10.1037/ a0012810 
Kahneman, D. (1999). Objective happiness. In D. Kahneman, E. Diener, & N. Schwartz (Eds.), Well-being: 
The foundations of hedonic psychology (pp. 3–25). New York, NY: Sage. 
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 
47, 263–291. doi:10.2307/1914185 
Kammeyer-Mueller, J. D., Wanberg, C. R., Glomb, T. M., & Ahlburg, D. (2005). The role of temporal shifts 
in turnover processes: It’s about time. Journal of Applied Psychology, 90, 644 – 658. 
doi:10.1037/0021- 9010.90.4.644 
Kelloway, E. K., Gottlieb, B. H., & Barham, L. (1999). The source, nature, and direction of work and family 
conflict: A longitudinal investigation. Journal of Occupational Health Psychology, 4, 337–346. 
doi:10.1037/ 1076-8998.4.4.337 
Lind, E. A. (2001). Fairness heuristic theory: Justice judgments as pivotal cognitions in organizational 
relations. In J. Greenberg & R. Cropanzano (Eds.), Advances in organizational justice (pp. 56–88). 
Stanford, CA: Stanford University Press. 
Lindsley, D. H., Brass, D. J., & Thomas, J. B. (1995). Efficacy-performance spirals: A multilevel perspective. 
Academy of Management Review, 20, 645–678. doi:10.2307/258790 
Loi, R., Yang, J., & Diefendorff, J. M. (2009). Four-factor justice and daily job satisfaction: A multilevel 
investigation. Journal of Applied Psychology, 94, 770–781. doi:10.1037/a0015714 
Louis, M. R. (1980). Surprise and sense making: What newcomers experience in entering unfamiliar 
organizational settings. Administrative Science Quarterly, 25, 226–251. doi:10.2307/2392453 
Mathieu, J. E., & Rapp, T. L. (2009). Laying the foundation for successful team performance trajectories: 
The roles of team charters and performance strategies. Journal of Applied Psychology, 94, 90–
103. doi: 10.1037/a0013257 
Piccolo, R. F., & Colquitt, J. A. (2006). Transformational leadership and job behaviors: The mediating role 
of core job characteristics. Academy of Management Journal, 49, 327–340. 
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in 
behavioral research: A critical review of the literature and recommended remedies. Journal of 
Applied Psychology, 88, 879–903. doi:10.1037/0021-9010.88.5.879 
Reb, J., & Cropanzano, R. (2007). Evaluating dynamic performance: The influence of salient Gestalt 
characteristics on performance ratings. Journal of Applied Psychology, 92, 490 – 499. 
doi:10.1037/0021- 9010.92.2.490 
Richardson, H. A., Simmering, M. J., & Sturman, M. C. (2009). A tale of three paradigms: Examining post 
hoc statistical corrections for common method variance from three divergent perspectives. 
Organizational Research Methods, 12, 762–800. doi:10.1177/1094428109332834 
Siemsen, E., Roth, A., & Oliveira, P. (2010). Common method bias in regression models with linear, 
quadratic, and interaction effects. Organizational Research Methods, 13, 456 – 476. 
doi:10.1177/ 1094428109351241 
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event 
occurrence. New York, NY: Oxford University Press. 
Sturman, M. C. (2007). The past, present, and future of dynamic performance research. Research in 
Personnel and Human Resources Management, 26, 49–110. doi:10.1016/S0742-7301(07)26002-
5 
Sturman, M. C., & Trevor, C. O. (2001). The implications of linking the dynamic performance and 
turnover literatures. Journal of Applied Psychology, 86, 684–696. doi:10.1037/0021-
9010.86.4.684 
Taylor, M. S. (2001). Reflections on fairness: Continuing the progression of justice research and practice. 
Journal of Vocational Behavior, 58, 243–253. doi:10.1006/jvbe.2001.1796 
Thelen, E., & Smith, L. B. (1998). Dynamic systems theories. In W. Damon & R. M. Lerner (Eds.), 
Handbook of child psychology: Vol. 1. Theoretical models of human development (5th ed., pp. 
563–634). Hoboken, NJ: Wiley. 
Truxillo, D. M., Bauer, T. N., Campion, M. A., & Paronto, M. E. (2002). Selection fairness information and 
applicant reactions: A longitudinal field study. Journal of Applied Psychology, 87, 1020 –1031. 
doi: 10.1037/0021-9010.87.6.1020 
Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance 
literature: Suggestions, practices, and recommendations for organizational research. 
Organizational Research Methods, 3, 4–70. doi:10.1177/109442810031002 
van den Bos, K. (2001). Fairness heuristic theory: Assessing the information to which people are reacting 
has a pivotal role in understanding organizational justice. In S. Gilliland, D. Steiner, & D. Skarlicki 
(Eds.), Theoretical and cultural perspectives on organizational justice (pp. 63–84). Greenwich, 
CT: Information Age. 
van den Bos, K., Burrows, J. W., Umphress, E., Folger, R., Lavelle, J. J., Eaglestone, J., & Gee, J. (2005). 
Prior experiences as temporal frames of reference in social justice: The influence of previous 
fairness experiences on reactions to new and old supervisors. Social Justice Research, 18, 99–
120. doi:10.1007/s11211-005-7365-4