Justice and personality: Using integrative theories to ...

Organizational Behavior and Human Decision Processes 100 (2006) 110–127

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Justice and personality: Using integrative theories to derive moderators of justice eVects �

Jason A. Colquitt a,¤, Brent A. Scott a, Timothy A. Judge a, John C. Shaw b

a University of Florida, USAb Mississippi State University, USA

Received 29 July 2004Available online 10 November 2005

Abstract

Although organizational justice has been shown to have behavioral consequences, there remains a surprising amount of variationin how individuals react to fair and unfair treatment. The present study drew on three integrative theories in the justice literature—fairness heuristic theory, uncertainty management theory, and fairness theory—to identify personality traits that could explain suchvariation. From these theories, we identiWed trust propensity, risk aversion, and morality (rooted in circumplex models of personal-ity) as potential moderators. A laboratory study provided some support for the prediction that the three traits moderate the eVects ofprocedural, interpersonal, and distributive justice on task performance and counterproductive behavior. The moderating eVects ofthe three traits explained more variance in the outcomes than moderators based in the justice literature (equity sensitivity, sensitivityto befallen injustice) or the Wve-factor model of personality. Taken together, the results suggest that the three integrative theories caninform the search for personality-based moderators of justice eVects.© 2005 Elsevier Inc. All rights reserved.

Keywords: Organizational justice; Fairness; Trust; Personality

Fair treatment impacts an organization’s members ina number of ways. It provides evidence that organiza-tional authorities are trustworthy, reducing fears ofexploitation while enhancing the legitimacy of organiza-tional actions (Lind, 2001; Tyler & Lind, 1992; Van denBos, 2001a). Fair treatment also makes future eventsmore predictable and controllable, reducing some of theuncertainty experienced in day-to-day working life (Lind& Van den Bos, 2002; Thibaut & Walker, 1975). Finally,fair treatment signals an adherence to moral and ethicalstandards on the part of authorities, potentially bringing

� An earlier draft of this manuscript was presented in T.A. Judge andJ.A. Colquitt (Chairs), The how and why of fairness: Mediators/modera-tors of justice eVects. Symposium conducted at the annual meeting ofthe Society for Industrial and Organizational Psychology, Chicago, IL.

* Corresponding author. Fax: +1 352 392 6020.E-mail address: [email protected] (J.A. Colquitt).

0749-5978/$ - see front matter © 2005 Elsevier Inc. All rights reserved.doi:10.1016/j.obhdp.2005.09.001

more meaning to working life (Cropanzano, Byrne, Bob-ocel, & Rupp, 2001; Folger, 1998).

The members of an organization can evaluate fairnessalong a number of dimensions. Distributive justice refersto the perceived fairness of decision outcomes and isjudged by gauging whether rewards are proportional tocosts (Homans, 1961), whether outcomes adhere toexpectations (Blau, 1964), and whether outcome/inputratios match those of a comparison other (Adams, 1965).Procedural justice refers to the perceived fairness of deci-sion-making procedures and is judged by gaugingwhether procedures are accurate, consistent, unbiased,and correctable (Leventhal, 1980), and open to employeeinput (Thibaut & Walker, 1975). Interactional justicerefers to the perceived fairness of the enactment orimplementation of procedures (Bies & Moag, 1986) andhas two subfacets. Interpersonal justice captures the sin-cerity and respectfulness of authority communication,

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J.A. Colquitt et al. / Organizational Behavior and Human Decision Processes 100 (2006) 110–127 111

while informational justice concerns the use of honestand adequate explanations for decisions (Colquitt, 2001;Greenberg, 1993a).

These justice dimensions have been associated with anumber of behavioral reactions on the part of employees(for meta-analytic reviews, see Cohen-Charash & Spec-tor, 2001; Colquitt, Conlon, Wesson, Porter, & Ng,2001), including counterproductive behavior (Green-berg, 1990, 1993b, 2002; Skarlicki, Folger, & Tesluk,1999) and task performance (Konovsky & Cropanzano,1991; Van den Bos, Vermunt, & Wilke, 1996). However,meta-analytic results suggest that a substantial amountof variation exists in these relationships, and that moder-ators could explain much of that variation (Colquittet al., 2001). Indeed, the relationships between the justicedimensions and performance are some of the mostinconsistent eVects in the literature.

The purpose of the present study was to identify per-sonality-based moderators that could explain some ofthe inconsistencies in the eVects of justice on task perfor-mance and counterproductive behavior. According tothe interactional psychology perspective, behavior isdetermined by a complex interplay of personal and situ-ational variables such that personality alters the cogni-tive construction of an individual’s environment andshapes the meaning of the various responses to that envi-ronment (Schneider, 1983). Applied to the study of reac-tions to fair and unfair treatment, this perspective wouldacknowledge that personality alters individuals’ percep-tions of their treatment while also shaping the cognitiveand behavioral reactions triggered by those perceptions.Thus, we focus on personality moderators of justiceeVects, though both personal and situational diVerencescould potentially serve as boundary conditions.

If personality variables indeed are capable of explain-ing variation in justice reactions, the key questionbecomes which personality traits are most worthy ofstudy. To make that critical choice, we drew on the set oftheories that has been introduced in the justice literatureover the past Wve years: fairness heuristic theory (Lind,2001; Van den Bos, 2001a), uncertainty managementtheory (Lind & Van den Bos, 2002; Van den Bos & Lind,2002), and fairness theory (Folger & Cropanzano, 2001).These theories represent what Colquitt, Greenberg, andZapata-Phelan (2005) termed the “integrative wave” ofthe justice literature, described as “a phase in whichscholars began building models and theories that exam-ined the eVects of multiple justice dimensions in combi-nation” (p. 35). The theories are termed “integrative”because, unlike other theories that focus on only onetype of justice (e.g., equity theory, Adams, 1965), theintegrative theories consider multiple forms of justice inconcert. Because these three integrative theories capturemuch of the current thinking on why justice matters topeople and why it impacts their behavior, we reasonedthat the mechanisms in those theories could highlight

potentially impactful moderators. Moreover, given thatLind (2001) suggested that the most relevant dependentvariables in fairness heuristic theory are those variablesthat capture the distinction between cooperative andantisocial behaviors, and Folger and Cropanzano (2001)argued that fairness theory can explain the presence ver-sus absence of retaliatory behaviors, we felt that taskperformance and counterproductive behavior wereappropriate outcomes for examining personality moder-ators of justice eVects.

Past research on moderation of justice eVects

Distributive justice research

Concerns about individual diVerences in justice reac-tions are not new. In one of the Wrst reviews of the sub-ject, Major and Deaux (1982) stated that research onindividual diVerences in justice behavior could bedivided into two categories: (a) individual diVerences inreward allocation decisions, and (b) individual diVer-ences in reactions to inequity. The authors noted that thestudy of personality moderators of equity reactions wasrelatively rare. However, such work was bolstered by theintroduction of equity sensitivity (Huseman, HatWeld, &Miles, 1987), a construct intended to capture sensitivityto diVerences in outcome/input ratios. Equity sensitivitycan be conceptualized as a continuum ranging from“Benevolents” to “Entitleds.” Huseman et al. (1987)originally conceptualized Benevolents as individualswho prefer their outcome/input ratios to be less than acomparison other’s (underreward) and Entitleds as indi-viduals who prefer their outcome/input ratios to begreater than a comparison other’s (overreward). King,Miles, and Day (1993) redeWned Benevolents as havinggreater tolerance for underreward, with Entitleds havinggreater tolerance for overreward. In between Benevo-lents and Entitleds are “Equity Sensitives,” who adhereto Adams’s (1965) original conceptualization of equityreactions—experiencing distress when their ratios diVerin either direction.

Procedural justice research

Though the introduction of procedural justice pro-vided a potential new direction for research on personal-ity moderators of justice eVects, very few studies havepursued this direction. Early studies examined traitssuch as locus of control (Sweeney, McFarlin, & Cotton,1991) and delay of gratiWcation (Joy & Witt, 1992) butdid not explore their moderating eVects on attitudinal orbehavioral reactions. However, subsequent studies haveexplored personality traits as moderators of both behav-ioral and attitudinal reactions to procedural justice. Sch-mitt and Dorfel (1999) found that sensitivity to befallen

112 J.A. Colquitt et al. / Organizational Behavior and Human Decision Processes 100 (2006) 110–127

injustice (SBI) moderated the relationship between pro-cedural justice and self-reported health. Individuals highin SBI are expected to more frequently recall unjustevents, become more angry about them, be more likelyto be preoccupied by them, and have a stronger urge forpunitivity (Schmitt, Neumann, & Montada, 1995).

Other studies have drawn from various theories toidentify personality moderators of procedural justiceeVects such as self-esteem (Brockner et al., 1998) andexchange ideology (Witt, Kacmar, & Andrews, 2001),the latter reXecting an employee’s expectation of (andlikely response to) exchange relationships with his or herorganization (Eisenberger, Cotterell, & Marvel, 1987). Inaddition, Hagedoorn, Buunk, and van de Vliert (2002)examined the belief in a just world as a moderator ofprocedural and distributive justice eVects, and a recentstudy by Van den Bos, Maas, Waldring, and Semin(2003) found support for the moderating role of aVectintensity on emotional reactions to procedural and dis-tributive justice.

Interactional justice research

The introduction of interactional justice providedanother new direction for research on personality mod-erators of justice eVects. We are aware of only two stud-ies that have explored moderators of such eVects.Skarlicki et al. (1999) found that the combination of lowinteractional justice and low distributive justice wasmore likely to result in retaliation when individuals werehigh in negative aVectivity and low in agreeableness.Heuer, Blumenthal, Douglas, and Weinblatt (1999)reported that interactional justice had a stronger eVecton fairness perceptions for high esteem individuals, aresult which provided support for the relational modelof justice (Tyler & Lind, 1992).

Applying integrative justice theories to personality moderators of justice eVects

The articles discussed in the prior section illustratethat scholars have begun to identify personality modera-tors of justice eVects. However, two points should benoted about the extant literature. First, few studies haveexplored justice moderators with behavioral reactions,with outcomes instead consisting of either fairness per-ceptions (e.g., Joy & Witt, 1992; Sweeney et al., 1991) orattitudinal outcomes (e.g., Schmitt & Dorfel, 1999; Wittet al., 2001). Second, studies of moderators of proceduraland interactional justice eVects remain relatively rare,with more work focusing on distributive eVects.

To move the literature examining personality mod-erators of justice eVects forward, we believe it wouldbe useful to establish a more direct linkage to the cur-rent state of theorizing in the justice literature. As

noted above, fairness heuristic theory, uncertaintymanagement theory, and fairness theory capture thecurrent thinking about organizational justice issues.With their focus on multiple justice dimensions, thesetheories could hold potential for identifying personal-ity moderators that cut across more than one type ofjustice. Creating a more direct linkage betweenresearch on moderators of justice eVects and theseintegrative theories could have two primary beneWts.First, the theories could be used to establish a concep-tual framework that explains how and why a giventrait could alter an individual’s response to fair orunfair treatment. Second, the theories could be used toguide the critical question of which traits to examinenext, given the potentially endless list of traits avail-able for study.

A brief review of integrative justice theories

Fairness heuristic theoryFairness heuristic theory, which grew out of earlier

work on the relational model of justice (Tyler & Lind,1992), suggests that individuals in organizations are con-tinually faced with the “fundamental social dilemma”(Lind, 2001; Van den Bos, 2001a). Although cooperatingwith organizational agents can lead to better outcomesin the long term, it also raises the potential of exploita-tion. To cope with that dilemma, individuals use a “fair-ness heuristic”—a psychological shortcut used to decidewhether to cooperate with authorities.

Lind (2001) argued that the fundamental socialdilemma highlights the importance of trust, where trustis deWned as a willingness to accept vulnerability toanother based on positive expectations of that person’sintentions and actions (Mayer, Davis, & Schoorman,1995). Unfortunately, the trustworthiness of authoritiescan be diYcult to judge, as it depends on assessments ofunobservable concepts like integrity, benevolence, andability. In contrast, fairness perceptions depend on rela-tively more observable phenomena such as met expecta-tions (Blau, 1964), consistency of procedures (Leventhal,1980), and respectfulness of communication (Bies &Moag, 1986). Thus, fairness heuristic theory argues thatjustice is used as a proxy for trust, with fair treatmentsignaling a trustworthy authority (Lind, 2001; Van denBos, 2001a).

The theory suggests that the fairness heuristic isformed quickly during a “judgmental phase” usingwhatever fairness information is Wrst gathered or is mostinterpretable. Once the heuristic has been formed, thetheory argues that individuals will use it as a proxy fortrust to guide day-to-day actions (see Van den Bos,Wilke, & Lind, 1998a, for empirical support), a periodtermed the “use phase” (Lind, 2001). Individuals con-tinue to employ the heuristic until a “phase shiftingevent,” such as a particularly important or unexpected


change at work, causes the individual to reconsider fair-ness levels and return to the judgmental phase.

Uncertainty management theoryIn subsequent work, Lind and Van den Bos deempha-

sized uncertainty about trust per se, instead focusing onmore general forms of uncertainty. For example, Vanden Bos (2001b) asked participants to describe the emo-tions they typically feel when they are uncertain or not incontrol. Results showed that justice had a stronger eVecton reactions when uncertainty was high than whenuncertainty was low. Such studies led to the formalintroduction of uncertainty management theory, whichwas cast as a successor to fairness heuristic theory (Lind& Van den Bos, 2002; Van den Bos & Lind, 2002).

Uncertainty management theory recognizes thatmany aspects of work and family life may contain uncer-tainty. According to the theory, fairness can removetrust-related uncertainty and mitigate the discomfortassociated with other forms of uncertainty—even if theyhave nothing to do with authorities. The authors sum-marized this key tenet as follows: “What appears to behappening is that people use fairness to manage theirreactions to uncertainty, Wnding comfort in related oreven unrelated fair experiencesƒ” (Lind & Van den Bos,2002, p. 216).

Fairness theoryFairness theory argues that individuals engage in

counterfactual thinking to determine the fairness of aparticular event and whether authorities should beblamed for that event (Folger & Cropanzano, 2001).More speciWcally, an individual makes three diVerentcounterfactual determinations: would, could, and should.An individual assesses what would have happened whenhe or she imagines plausible alternative states of being tothe current situation. An individual assesses what couldhave happened when he or she determines whetherevents were under the discretion of an authority. Whenan individual assesses what should have happened, he orshe considers whether the authority’s behavior was mor-ally appropriate.

According to the theory, individuals typically react toa decision-making event by Wrst judging whether welfarehas been reduced or threatened. If individuals determinethat an injury has occurred, the next question is whetherthe authority can be blamed. That judgment of blamedepends on the presence of other feasible alternatives, asauthorities cannot be blamed if they had no control overtheir choice of actions. Folger and Cropanzano (2001)further suggested that blame can only be placed if someethical principal of social conduct has been violated.

The characteristics of fairness theory can be distin-guished from fairness heuristic theory and uncertaintymanagement theory on a number of levels. First, thecounterfactual thinking described in fairness theory is

triggered by a discrete event, whereas the fairness heuris-tic is used and maintained across a number of events. Sec-ond, the process of judging fairness is more deliberate infairness theory, relative to the almost subconscious short-cuts described in the other two theories. Third, the mech-anisms that guide behavioral reactions are decidedlydiVerent. With its emphasis on blame, fairness theory isideally suited to explaining counterproductive reactions(Folger & Cropanzano, 2001). In contrast, fairness heu-ristic theory’s emphasis on cooperation makes it morerelevant to explaining prosocial behaviors (Lind, 2001).

Which traits worthy of study can be derived from the integrative theories?

The integrative theories reviewed above can be usedto create a conceptual framework that describes howand why a given personality trait could moderate theeVects of certain justice dimensions. Each of the theoriesconsiders three distinct questions in some form: (a) Whydo individuals care about justice—what triggers justiceconcerns in the Wrst place? (b) How carefully and inten-sively do individuals ruminate on justice informationonce their concerns have been triggered? (c) Whatactions could individuals take once they believe thatunfairness has been experienced? As summarized inFig. 1, these three questions provide three diVerentmechanisms that could be aVected by an individual’spersonality.

Consider a personality trait that makes individualsmore sensitive to justice, causes them to ruminate on jus-tice information more deliberately, and increases thelikelihood that they will react to injustice with someaction. That trait should amplify the eVects of justice onbehavioral reactions, and that result should be fairlyrobust across contexts because it is being realizedthrough three distinct mechanisms. Judge and Larsen(2001) used similar logic in their stimulus–organism–response (S–O–R) model of personality inXuences on jobsatisfaction. They argued that personality variablesshould have a signiWcant eVect on job satisfaction to theextent that they aVect sensitivity to environmental stim-uli, inXuence the cognitive and emotional processing ofthose stimuli within the organism, and heighten the like-lihood of an eventual response. The subsequent sectionsof this manuscript review traits, derived from the inte-grative theories, that are likely to inXuence more thanone of the mechanisms shown in Fig. 1.

Trust propensityGiven the central role of trust in fairness heuristic the-

ory (Lind, 2001; Van den Bos, 2001a), trust propensitystands out as a personality variable that could moderatejustice eVects. Trust propensity is a generalized expecta-tion about the trustworthiness of others (Mayer et al.,1995), which should impact all three of the mechanisms


in Fig. 1. Suspicious individuals should attend more totheir environment when forming trust judgments, andfairness concerns should be more easily triggered as sus-picions about ability, benevolence, and integrity governday-to-day interactions (Mayer et al., 1995). Suspiciousindividuals should also ruminate on fairness-relevantinformation more deliberately, as the use of the fairnessheuristic continues until an important event causes a“phase shift” that bumps the individual back to thejudgmental phase (Lind, 2001). The threshold for phaseshifting should be lower for suspicious individuals giventheir generally wary reactions to stimuli. If so, individu-als low in trust propensity will more frequently engage incareful analysis of justice information.

Finally, individuals low in trust propensity should bemore likely to respond to unfair treatment with behav-ioral repercussions. Lind (2001) noted that “the fairnessheuristic is an imprecise algorithm for deciding what isthe best thing to do” (p. 66). Relying on the heuristicduring the use phase will inevitably cause individuals togloss over daily or weekly Xuctuations in actual fairnesslevels. Suspicious individuals, on the other hand, will beunlikely to gloss over such Xuctuations. Their more care-ful and frequent analysis of actual fairness levels shouldallow their behaviors to be based on a cognitive ledger oftreatment versus contributions.

Fairness heuristic theory deemphasizes the distinc-tions among the various justice dimensions, arguing thatthe timing and interpretability of fairness experiences ismore relevant than their actual content. Nevertheless, wewould argue that trust propensity will be more likely to

moderate procedural and interactional justice eVects, asopposed to distributive eVects. Models in the trust litera-ture explicitly recognize procedural principles like con-sistency, bias suppression, and ethicality as forms ofintegrity (Mayer et al., 1995). Those same models alsorecognize interactional principles like respectfulness,supportiveness, and openness as forms of benevolence(Mayer et al., 1995). In contrast, distributive principleshave much less presence in trust theorizing. Trust pro-pensity should therefore be more likely to impact theconsideration of (and reaction to) procedural and inter-actional information because these justice dimensionstap trustworthiness issues to a greater extent. We there-fore predicted:

Hypothesis 1. Propensity to trust moderates the eVects of(a) procedural justice, and (b) interactional justice, ontask performance and counterproductive behavior, suchthat the relationships are stronger for individuals low intrust propensity and weaker for individuals high in trustpropensity.

Risk aversionThe shift from fairness heuristic theory to uncertainty

management theory supplanted trust as a central con-cern in favor of more general uncertainty. In discussingthe importance of uncertainty, Lind and Van den Bos(2002) suggested that “tolerance of risk” could be animportant determinant of the importance of justice (p.215). The personality variable that most closely capturessuch tolerance is risk aversion. Risk aversion is an

Fig. 1. Conceptual model of personality moderators of justice eVects.


individual diVerence that captures diVerential attentionto stimuli in potentially risky situations, along with thetendency to react to risk with anxiety and eventual with-drawal (e.g., Cable & Judge, 1994; Maehr & Videbeck,1968). Though risk levels are, to a large extent, driven bysituational characteristics, highly risk-averse individualsview and react to those situations diVerently than lessrisk-averse individuals.

Risk aversion should be associated with increasedsensitivity to justice concerns. Because risk-averse indi-viduals react to uncertainty with more anxiety, theyshould pay close attention to any environmental cuesthat can help them manage or mitigate such uncertainty(Lind & Van den Bos, 2002). That same sense of cautionshould prompt risk-averse individuals to resist relyingon an “imprecise algorithm” like the fairness heuristic(Lind, 2001) in favor of a careful, reasoned analysis ofauthority behavior. The linkage between risk aversionand the likelihood of behavioral response is less straight-forward. It seems likely that risk-averse individuals willrespond to an injustice with a behavioral response thatdoes not create a great deal of anxiety. Because riskaverse individuals react to adverse stimuli with more fre-quent withdrawal (e.g., Cable & Judge, 1994; Maehr &Videbeck, 1968), passive forms of retaliation (likedecreased eVort or task performance) could be likely.Individuals’ likelihood of engaging in more active retali-ation (like counterproductive behavior) should dependon the risk involved in such acts. When the risk involvedis low, counterproductive behavior should provideanother means of retaliation for risk-averse individuals.

Our predictions for trust propensity were limited toprocedural and interactional justice because of their spe-cial relevance to trust—does the same type of distinctionneed to be made for risk aversion? Van den Bos and Lind(2002) deWned uncertainty quite broadly, framing it as theunpredictability of future events that deprives one of con-Wdence about what to expect from the environment.Unfair procedures should create an especially high levelof uncertainty because procedures have a systemic char-acter—they remain in place over the long-term (Sweeney& McFarlin, 1993). Unfair treatment by an authorityWgure also has long-term implications on uncertainty, solong as the authority remains in his or her position for anextended period of time. In contrast, concerns aboutunfair outcome distributions are more short-term in ori-entation, as outcomes tend to have a discrete, episodiccharacter. Nevertheless, distributive unfairness deprivesan individual of conWdence in how to behave and what toexpect. UnfulWlled expectations (Blau, 1964), inconsistentsocial comparisons (Adams, 1965), and divergence inrewards and costs (Homans, 1961) prevent the develop-ment of the behavior-outcome contingencies that areendemic to so many models of volitional behavior (Kan-fer, 1991). We therefore made risk aversion moderationpredictions for all three justice dimensions:

Hypothesis 2. Risk aversion moderates the eVects of (a)procedural justice, (b) interactional justice, and (c) dis-tributive justice on task performance and counterpro-ductive behavior, such that the relationships are strongerfor individuals high in risk aversion and weaker for indi-viduals low in risk aversion.

MoralityIn the years since fairness theory was Wrst introduced,

a great deal of attention has focused on the should com-ponent of the theory, which captures whether an author-ity’s actions have complied with moral or ethicalprinciples. This attention can be seen in the “moral vir-tue” and “deontic” perspectives on justice, which arguethat justice is valued because it signiWes adherence toprevailing moral standards (Cropanzano et al., 2001;Folger, 1998, 2001; Folger, Cropanzano, & Goldman,2005). The “deontic” term comes from the Greek worddeon, meaning duty or obligation (Folger, 2001). Folgeret al. (2005) argued that violations of moral principlescan trigger “deontic anger,” which may prompt retalia-tory behaviors even when such actions are not rational(Folger et al., 2005).

Of course, there are likely to be individual diVerencesin the degree to which individuals experience deonticanger, as well as their responses to such violations. Fol-ger (1998) hinted that an individual’s morality might beone variable that captures such variation. Within thepersonality literature, trait morality can be operationallydeWned as a combination of high agreeableness and highconscientiousness. Hofstee, de Raad, and Goldberg(1992) introduced an integration of the Big Five and cir-cumplex approaches to trait structure. The authorsdescribed 10 diVerent circumplex models, each of whichillustrates various combinations (or blends) of two BigFive factors. Taken together, these 10 circumplex modelswere used to provide operational deWnitions for 540 spe-ciWc traits. One of those traits was “moral”, which waspositioned in the high agreeableness, high conscientious-ness area of one of the circumplex models (see also deRaad, Hendriks, & Hofstee, 1992). Other studies havesimilarly shown that trait morality, and related conceptssuch as trait integrity, seem to represent a blend of highagreeableness and high conscientiousness (Ones, 1994;Saucier & Goldberg, 1996).

The circumplex origin of trait morality is importantin that the intersection of agreeableness and conscien-tiousness is believed to capture a behavior pattern notexplainable by simple additive eVects of those two BigFive dimensions. However, we should acknowledge thatthis trait-based version of morality diVers from Kohl-berg’s (1984) conceptualization of the stages of moraldevelopment. A trait-based view emphasizes static orcross-sectional diVerences in morality across individuals,whereas Kohlberg’s (1984) emphasis was on within-indi-vidual transitions over time (Walker, 2002). To highlight


this critical diVerence and reduce potential confusion,our manuscript intentionally uses the term ‘‘trait moral-ity” when describing our moderator variable.

High levels of trait morality should be associated withincreased sensitivity to justice concerns. From a moralvirtue perspective, justice can help bring meaning toworking life (Cropanzano et al., 2001; Folger, 1998).Highly moral individuals may be more likely to searchfor that meaning and should also be less likely to engagein unjust behaviors themselves. They should thereforereact to others’ instances of injustice with more deonticanger, leading to more deliberate rumination on justice-relevant information. In a fairness theory sense, moralindividuals should have a heightened interest in theshould counterfactual portion of the blame assessmentprocess (Folger & Cropanzano, 2001).

The linkage between trait morality and the likelihoodof behavioral response would seem to depend on thenature of the speciWc reaction. On the one hand, highlymoral individuals are particularly likely to hold othersresponsible for their actions, as morality is associatedwith a tendency to ascribe responsibility (Zuckerman &Reis, 1978) and sanctions often follow from ascriptionsof blame (Pizarro, Uhlmann, & Bloom, 2003). Moreover,Folger et al. (2005) suggested that retribution against thesource of an injustice is itself a “moral remedy” that isconsistent with social exchange theories of interaction(Blau, 1964). Bies and Tripp (1995) went so far as todescribe revenge as a “moral imperative,” noting thatperpetrators of revenge often report a strong belief thatthey were “doing the right thing” (pp. 258–259).

On the other hand, individuals high in trait moralityshould be very resistant to the prospect of engaging incounterproductive behaviors like theft or retaliation. Indi-rect support for this assertion can be drawn from a seriesof studies by Turillo, Folger, Lavelle, Umphress, and Gee(2002). The studies gave participants the opportunity toeither self-sacriWcially punish an individual who hadexhibited unfair intentions in a past phase of the study, orself-sacriWcially reward an individual who had exhibitedfair intentions. Punishments and rewards occurred using apayout matrix, where participants chose their own payoutwhile also allocating payouts to others. Importantly, theresults of one of the studies revealed that participantsdecided to punish past transgressions only when thoseactions did not harm the payouts received by other cur-rent participants. The authors wrote, “These results sup-port our reasoning that individuals will only engage inretributive justice to punish unfairness in the past when,by doing so, they are not themselves being unfair in thepresent.” (p. 852). Because a counterproductive responsemeans “being unfair in the present,” a moral individualshould be more likely to respond to injustice with lesstask-related eVort as opposed to more overt forms ofretaliation. A reduction in performance can amount to abrand of “civil disobedience” that is relatively harmless to

others. As a result, our hypotheses for trait morality arelimited to task performance.

As with the other integrative theories, fairness theoryemphasizes the commonalities among the diVerent formsof justice rather than the diVerences. For example, thewould counterfactual considers an event’s aversiveness,with no particular importance given to whether theevent is distributive, procedural, or interactional innature (Folger & Cropanzano, 2001). The could counter-factual assesses whether other sequences of events oractions might have been feasible, again with littleemphasis on modalities of justice. However, discussionsof the should counterfactual and writings on the moralvirtue and deontic approaches to justice do seem to pri-oritize procedural and interactional justice violations(Folger, 1998, 2001; Folger & Cropanzano, 2001). Proce-dural and interactional justice rules, such as bias, ethical-ity, respectfulness, and honesty seem more “morallycharged” than distributive concepts like met expecta-tions, reward-cost proportionality, and outcome/inputratio comparisons. Indeed, in Folger’s (2001) “deonticdiVerentiation” of distributive, procedural, and interac-tional justice (pp. 22–25), he speculated that moralaccountability for justice tends to grow stronger inascending order from distributive to procedural to inter-actional (see also Turillo et al., 2002). We therefore mademoderation predictions for only the latter two dimen-sions of justice:

Hypothesis 3. Trait morality moderates the eVects of (a)procedural justice and (b) interactional justice on taskperformance, such that the relationships are stronger forindividuals high in trait morality and weaker for individ-uals low in trait morality.

Alternative approaches to moderation of justice eVects

Though the hypotheses advanced in Fig. 1 are derivedfrom the three theories that form the core of the so-called“integrative wave” of the justice literature (Colquitt et al.,2005), there are other potential approaches to the studyof moderation of justice eVects that have been used inpast research. One approach is the study of personalitytraits that are speciWcally designed to moderate justiceeVects, as in the cases of equity sensitivity (Husemanet al., 1987) and sensitivity to befallen injustice (SBI; Sch-mitt et al., 1995). Both traits might have moderatingpotential, though research on equity sensitivity is limitedto distributive justice eVects and research on SBI has yetto extend beyond the tests by Schmitt and colleagues(e.g., Schmitt & Dorfel, 1999; Schmitt et al., 1995). Wetherefore included equity sensitivity and SBI so that theirmoderating eVects could be compared to the eVects oftrust propensity, risk aversion, and trait morality.

A second alternative approach to moderation of jus-tice eVects is the Wve-factor model of personality


(Costa & McCrae, 1992; Goldberg, 1990). The “BigFive” dimensions of conscientiousness, agreeableness,neuroticism, openness to experience, and extraversionsubsume many of the narrow traits shown in Fig. 1. TheBig Five may also moderate justice eVects, as research bySkarlicki et al. (1999) showed that agreeableness andneuroticism moderated the eVects of speciWc justice com-binations. However, as Hogan and Roberts (1996)noted, broad traits are not always best suited for narrowpredictions, and the reaction to an injustice is clearly amore speciWc criterion relative to day-to-day job perfor-mance. Nevertheless, we also included the Big Five asalternative moderators of justice eVects to provide a sec-ond frame of comparison for the eVects predicted inFig. 1.

Method

Sample

Participants were 238 undergraduates from a large,southeastern university recruited from an introductorymanagement course. Females composed 45% of the sam-ple. In exchange for participation, participants weregiven course credit and earned a $5 cash prize.

Procedure

Upon entering the laboratory, participants wereseated at one of Wve tables. Each table had a pen holdercontaining seven expensive-looking pens. The tableswere arranged so that participants’ views of one anotherwere obstructed during the session. The experimenterprovided a cover story, informing participants that thepurpose of the study was to validate assessment toolsthat would be used in the future hiring of research assis-tants. Included in these assessment tools were a proof-reading task and a reading comprehension task, andparticipants were told that their performance on the Wrst

of these (the proofreading task) would determinewhether they would receive a $5 cash prize. Participantswere told that around 66% of the participants wouldperform well enough to receive the cash prize. Thisinstruction ensured that all participants began the exper-iment with the same expectations for being rewarded.

Participants were then told that they could choose apen to use during the study and that they could keep thepen they chose. They were then given seven minutes tocomplete the proofreading task, which contained a pas-sage describing various types of work groups (e.g., for-mal, informal, virtual). Next, the experimenter informedparticipants that he would leave the room to grade thetasks and then would return to give the participantsfeedback on their performance. During the gradingperiod, participants completed a questionnaire assessingthe Big Five, risk aversion, trust, and equity sensitivity,which contained the following instructions: “This ques-tionnaire assesses various aspects of your personal andgeneral attitudes. Please answer the questions in eachsection as honestly as you can.” Unless otherwise noted,all items on all questionnaires utilized a 5-point scale,where 1DStrongly Disagree and 5DStrongly Agree.

After 10 min, the experimenter called each partici-pant individually to another room to deliver the justicemanipulations. Procedural, distributive, and interac-tional justice were then manipulated by the experi-menter via eight possible statements, resulting in a2£ 2£ 2 between-subjects design with participantsrandomly assigned to conditions. Table 1 provides theexact wording of the justice manipulations. The proce-dural manipulation varied Leventhal’s (1980) accuracyand consistency criteria for justice in a manner similarto Van den Bos, Bruins, Wilke, and Dronkert (1999).Interactional justice was manipulated using the inter-personal justice subfacet, which captures the sincerityand respectfulness of authority communication (Col-quitt, 2001; Greenberg, 1993a). The remainder of thismanuscript uses the interpersonal justice label in theinterest of precision. SpeciWcally, the manipulation var-

Table 1Summary of justice manipulations

Justice dimension Level Text of manipulation

Procedural High In the past, I’ve always graded the whole proofreading task in order to be as accurate and consistent as possible. So I took the time to carefully grade all the paragraphs that you corrected.

Low In the past, I’ve always graded the whole proofreading task in order to be as accurate and consistent as possible. I didn’t do that here though. I Wnished grading everyone else’s but ran out of time on yours, so I just graded the last paragraph.

Interpersonal High I understand that students are very busy, and there’s a lot of other things you could be doing right now besides helping us out. We really appreciate your time. Thanks a lot.

Low Whatever. I don’t give a damn whether you get paid or not. That’s the way it is. I’ve got better things to do than grade these things.

Distributive High Anyway, (from that one paragraph/based on those paragraphs) I have determined that you should be paid.Low Anyway, (from that one paragraph/based on those paragraphs) I have determined that you should not be

paid.


ied the respect and rudeness components of the con-struct (Bies & Moag, 1986). Distributive justice wasmanipulated by meeting or not meeting participants’expectations about the receipt of the $5 reward, similarto the approach used by Greenberg (1993b) and Vanden Bos, Wilke, Lind, and Vermunt (1998b). Partici-pants were either paid immediately, thereby meetingexpectations, or were told they would not be paid,thereby failing to meet expectations.

Next, participants were given 10 min to complete areading comprehension test, which served as the measureof task performance. This test consisted of a short pas-sage describing carpal tunnel syndrome followed byeight questions which required participants to examinethe speciWc details and main points of the passage toobtain the correct answers. Using reading comprehen-sion as a measure of task performance is appropriate inthis context because the test was designed to be largelyeVort-driven as opposed to ability-driven. The questionswere not diYcult but did require a careful perusal of thepassage on the part of the participant. SpeciWcally, weincluded a brief paragraph at the end of the passage thatcorrected previous statements. To answer the questionscorrectly, participants had to take the time to carefullyread the entire passage. Participants then completed aWnal questionnaire that contained items for the manipu-lation checks, sensitivity to befallen injustice, and traitmorality.

Near completion of the Wnal questionnaire, the experi-menter interrupted and stated: “Um, I have to make aphone call. When you guys are done just leave your ques-tionnaire on your desk and you’re free to go. Oh, also: Iknow I read from the script earlier that you could keepthe pen, but we’re running some more sessions and itlooks like we’re getting a little low. So, if you would notkeep the pen I’d appreciate it.” The experimenter then leftthe room, giving participants the opportunity to take pensfrom the pen holder. The set up of the room preventedparticipants from being able to access the pen containersof others, so they could only take pens from their individ-ual pen holder. When participants exited the room, theexperimenter asked each one to wait for the others. Onceall had exited, the experimenter then brought the partici-pants into another room to debrief them about the truenature of the experiment. Finally, participants who didnot receive the $5 during the study were paid.

Integrative theory traits

Trust propensityWe measured trust propensity using 5 items from the

International Personality Item Pool (2001). The itemsincluded: “I trust others,” “I trust what people say,” “Iam wary of others (R),” “I suspect hidden motives inothers (R),” and “I distrust people (R).” CoeYcient � forthis scale was .81.

Risk aversionRisk aversion was also assessed using 6 items from

the International Personality Item Pool (2001). Itemsincluded: “I enjoy being reckless (R),” “I take risks (R),”“I seek danger (R),” “I seek adventure (R),” I wouldnever go hang-gliding or bungee jumping,” and “I wouldnever make a high risk investment.” CoeYcient � for thisscale was .82.

Trait moralityThis trait was measured using 6 items from the Inter-

national Personality Item Pool (2001). The itemsincluded: “I would never cheat on my taxes,” “I turn myback on others (R),” I scheme against others (R),” “I actat the expense of others (R),” “I respect the privacy ofothers,” and “I respect authority.” CoeYcient � for thisscale was .86.

ConWrmatory factor analysisWe conducted a conWrmatory factor analysis on the

measures of the three integrative theory traits to deter-mine whether the items seemed to be tapping three dis-tinct constructs. We included a reverse-wording factorwith loadings on the items worded in the opposite direc-tion from the majority of the scale, given that responsesto these sorts of items can be inXuenced by carelessrespondents (Schmitt & Stults, 1985). The trait moralityscale was balanced in wording, so the items reXecting alack of morality were loaded onto the wording factor.We also allowed the errors for the two “I trustƒ” itemsto covary as their item similarity resulted in an observedcorrelation signiWcantly higher than the model repro-duced correlation. The results of a three-factor modelprovided an acceptable Wt to the data (�2 (108)D174.50;CFID .954; RMRD .048; RMSEAD .052). The loadingsfor the three personality factors were all statistically sig-niWcant and averaged as follows: trust propensity (.62),risk aversion (.63), and trait morality (.59). The correla-tions among the three latent variables were moderate inmagnitude, with an absolute average of .25. Takentogether, these results support the assertion that thescales are measuring three distinct factors.

Alternative moderators

Equity sensitivityWe measured equity sensitivity using the 5-item scale

developed by King and Miles (1994). Participants wereasked to divide 10 points between two opposing state-ments by “giving the most points to the choice that ismost like you and the fewest points to the choice that isleast like you.” All Wve items began with the phrase “Inany organization I might work for:” An example item is“It would be more important for me to (A) get from theorganization or (B) give to the organization.” Theinstrument was scored by adding items reXecting


Entitledness; thus high scores represent a high sensitivityto perceived underreward. The potential range of scoreswas zero to 50. CoeYcient � for this scale was .77.

Sensitivity to Befallen injusticeWe measured SBI using the 10-item scale developed

by Schmitt and Maes (2000). A sample item is: “It both-ers me when others receive something that ought to bemine.” CoeYcient � for this scale was .87.

Big Five dimensionsWe measured the Wve-factor model using the Big Five

Inventory (BFI; John, Donahue, & Kentle, 1991), withdimensions as follows: neuroticism (eight items, e.g., “Ican be moody,” �D .86), extraversion (eight items, e.g., “Ihave an assertive personality,” �D .89), openness toexperience (10 items, e.g., “I am curious about manythings,” �D .86), agreeableness (nine items, e.g., “I have aforgiving nature,” �D .75), and conscientiousness (eightitems, e.g., “I do a thorough job,” �D .80).

Outcome measures

Task performanceTask performance was assessed by scoring each par-

ticipant’s answers to the reading comprehension test.Task performance ranged from a possible score of zero(no correct answers) to eight (all answers correct).

Counterproductive behaviorWe measured counterproductive behavior by the

number of pens taken from each participant’s penholder upon leaving the experiment (pen holders heldseven pens in total). Counterproductive behaviorranged from 0 (no pens taken) to 3 (the maximumnumber of pens taken by a participant). The act of tak-ing a pen when asked not to do so likely taps twodiVerent counterproductive behaviors that range inseverity. At its most severe, taking a pen represents aform of theft. At its least severe, taking a pen repre-sents a form of intentional noncompliance with anauthority Wgure.

Manipulation checks

We assessed whether participants perceived the jus-tice manipulations as intended using three items for eachdimension of organizational justice. The procedural jus-tice items included “The grading procedures used on theproofreading task seemed accurate.” (�D .94). The inter-personal justice items included “The experimenter spoketo me with sincerity and respect.” (�D .97). The distribu-tive justice items included “I received the $5 reward forthe proofreading task.” (�D .96). We also veriWed thatthe manipulations aVected perceptions of fairness byincluding the following four-item global fairness percep-

tions scale (e.g., “In general, this was a fair experiment”)(�D .96).

Results

Manipulation checks

A MANOVA with the three manipulation checkscales as dependent variables revealed signiWcant maineVects for all three manipulations (FD903.40, p < .001,for distributive justice; FD36.24, p < .001, for interper-sonal justice; FD 10.10, p < .001, for procedural justice)with no interaction eVects. ANOVA results showed thatthe distributive manipulation had a strong eVect on thedistributive check (FD2724.93, p < .001, �2D .92, MD4.67 vs. 1.21) and weaker eVects on the procedural(FD20.85, p < .001, �2D .08, MD3.17 vs. 2.50) and inter-personal checks (FD23.03, p < .001, �2D .09, MD 3.99 vs.3.33). The interpersonal manipulation had a strong eVecton the interpersonal check (FD 92.65, p < .001, �2D .29,MD 4.25 vs. 2.84), a weaker eVect on the proceduralcheck (FD6.13, p < .01, �2D .03, MD 2.99 vs. 2.58), andno eVect on the distributive check (FD .12, pD .73,�2D .00, MD 2.77 vs. 2.85). The procedural manipulationhad a strong eVect on the procedural check (FD 30.56,p < .001, �2D .12, MD3.20 vs. 2.36), a weaker eVect onthe interpersonal check (FD10.42, p < .001, �2D .04,MD 3.89 vs. 3.33), and no eVect on the distributive check(FD .40, pD .53, �2D .00, MD2.84 vs. 2.76). All threemanipulations also inXuenced global perceptions of fair-ness, explaining a total of 17% of the variance (FD 16.07,p < .001). Unique eVects were as follows: distributive jus-tice (BD .67, p < .001), procedural justice (BD .28,p < .05), and interpersonal justice (BD .54, p < .001).

The ANOVA results above indicate some spillover,with a manipulation of one form of justice aVectingchecks of another, which is likely due to attemptingorthogonal manipulations of variables that are so highlycorrelated on a perceptual level (Cohen-Charash &Spector, 2001; Colquitt et al., 2001). However, the degreeof spillover does not seem serious enough to impair anunambiguous evaluation of the experiment’s results(Perdue & Summers, 1986). The F values for theintended eVects were 53 times stronger than the F valuesfor the unintended eVects, and the �2 values for theintended eVects were 12 times stronger than �2 values forthe unintended eVects. Nevertheless, we statistically con-trolled for all spillover by partialling out the contaminat-ing variance from each justice manipulation. Forexample, we partialled out the shared variance betweenthe procedural manipulation and the interpersonalcheck by regressing the latter onto the former and usingthe residual as the new procedural manipulation vari-able. This process resulted in a completely “clean” set ofANOVA results. We should emphasize that this form of


statistical control did not alter the tests of any of ourhypotheses but is presented here to provide as clear apicture of our results as possible.

Results for integrative theory traits

Table 2 provides the descriptive statistics and zero-order correlations among the variables. The moderatedregressions used to test our hypotheses are shown inTable 3. The Wrst two steps assess the main and interac-tive eVects of the justice manipulations, which did nothave main or interactive eVects on task performance,with the main eVects falling within the conWdence inter-vals from Colquitt et al.’s (2001) meta-analytic review.The justice manipulations did have signiWcant main andinteractive eVects on counterproductive behavior, con-sistent with past research (Greenberg, 1990, 1993b,2002), with the procedural and distributive manipula-tions reducing counterproductive behavior (though thelatter eVect only approached signiWcance at p < .07). Theinteraction eVects showed that the combination of lowprocedural justice and either low interpersonal or lowdistributive justice created particularly high counterpro-ductive behavior levels. The third step of the regressionsassesses the main eVects of the three personality traits,with none reaching statistical signiWcance.

The fourth step of the regressions enters thejustice£personality product terms used to test thehypotheses. Consistent with the recommendations ofCohen, Cohen, West, and Aiken (2003), we mean-cen-tered all moderators before computing the productterms. The set of justice£personality product termsexplained signiWcant incremental variance in both taskperformance and counterproductive behavior. Hypothe-sis 1a and b predicted stronger eVects for procedural andinterpersonal justice on task performance and counter-

productive behavior when trust propensity was low. Theinterpersonal justice£ trust propensity interactionapproached signiWcance for task performance, with thepattern in the predicted direction (p < .07, see Fig. 2).Though not predicted, the results also revealed a similarinteraction with distributive justice for task performance(p < .06, see Fig. 2). A signiWcant interpersonal justice£ trust propensity interaction was also observed forcounterproductive behavior, but was opposite to

Table 3Moderated regression results for trust propensity, risk aversion, andtrait morality

Note. nD 238. �R2 values may not sum exactly to R2 values due torounding error.¤ p < .05, two-tailed.

¤¤ p < .10, two-tailed.

Regression step Task performance Counterproductive behavior

R2 �R2 � R2 �R2 �

1. Procedural Justice (PJ) .00 .00 .05 .05¤ .05¤ ¡.19¤

Interpersonal Justice (IJ) .02 ¡.08Distributive Justice (DJ) .00 ¡.12¤¤

2. PJ£ IJ .01 .01 ¡.05 .10¤ .06¤ .20¤

PJ£ DJ ¡.04 .15¤

IJ£ DJ ¡.09 .07

3. Trust Propensity .03 .02 .00 .11¤ .01 ¡.02Risk Aversion .11 .04Trait Morality ¡.10 ¡.06

4. PJ£Trust Propensity .12¤ .09¤ ¡.01 .23¤ .12¤ ¡.11IJ£Trust Propensity ¡.14¤¤ ¡.21¤

DJ£Trust Propensity ¡.14¤¤ ¡.05PJ£Risk Aversion .14¤ ¡.22¤

IJ£Risk Aversion ¡.05 ¡.19¤

DJ£Risk Aversion ¡.06 ¡.08PJ£Trait Morality ¡.11 .11IJ£Trait Morality .25¤ ¡.02DJ£Trait Morality .24¤ ¡.00

Table 2Descriptive statistics and zero-order correlations

Note. n D 237. SBI D Sensitivity to Befallen Injustice.¤ p < .05, two-tailed.

Variable M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1. Procedural Justice .00 .49 —2. Interpersonal Justice .00 .49 ¡.09 —3. Distributive Justice .00 .48 ¡.08 ¡.12 —4. Trust Propensity 3.79 .54 .05 .01 ¡.05 —5. Risk Aversion 3.08 .66 ¡.00 .12 .08 .09 —6. Trait Morality 4.15 .46 .04 .10 .00 .47¤ .40¤ —7. Equity Sensitivity 22.45 6.12 ¡.06 .07 .04 ¡.23¤ .08 ¡.22¤ —8. SBI 2.92 .65 .11 ¡.01 .06 ¡.32¤ .07 ¡.21¤ .19¤ —9. Conscientiousness 4.04 .53 ¡.03 .02 ¡.03 .35¤ .09 .40¤ ¡.28¤ ¡.12 —

10. Agreeableness 3.84 .50 ¡.05 .06 ¡.03 .51¤ .12 .43¤ ¡.24¤ ¡.28¤ .28¤ —11. Neuroticism 2.80 .73 .08 ¡.05 ¡.03 ¡.45¤ .17¤ ¡.17¤ .11 .39¤ ¡.33¤ ¡.34¤ —12. Openness 3.64 .67 ¡.08 .07 ¡.08 .16¤ ¡.10 .17¤ ¡.12 ¡.14¤ .21¤ .23¤ ¡.13¤ —13. Extraversion 3.58 .72 ¡.01 ¡.10 ¡.01 .41¤ ¡.10 .14¤ ¡.14¤ ¡.05 .20¤ .22¤ .24¤ .13¤ —14. Task Performance 6.17 1.42 .05 .01 ¡.00 .03 .05 ¡.05 .09 ¡.04 .07 .08 ¡.14 .10 .03 —15. Counterproductive Behavior .10 .30 ¡.18¤ ¡.05 ¡.10 ¡.03 ¡.04 ¡.10 .06 .07 ¡.12 ¡.02 .03 ¡.01 ¡.08 ¡.01


predictions. The eVect of interpersonal justice on coun-terproductive behavior was stronger for trusting individ-uals. Neither of the procedural justice interactionsreached statistical signiWcance.

Fig. 2. Justice £ trust propensity interactions for task performance andcounterproductive behavior.

High Trust Propensity

Low Trust Propensity




Interpersonal Justice


Tas

k P

erfo

rman

ceT

ask

Per

form

ance

Co

un

ter

pro

du

ctiv

e B

ehav

iou

r

Distributive Justice


High Low

High Low

High Low

7.75

7.00

6.25

5.50

4.75

7.75

7.00

6.25

5.50

4.75

0.40

0.30

0.20

0.10

0.00

Hypothesis 2a–c predicted stronger eVects for proce-dural, interpersonal, and distributive justice on task per-formance and counterproductive behavior when riskaversion was high. The procedural justice£ risk aversioninteraction was signiWcant for both task performanceand counterproductive behavior, with the patterns in thepredicted direction (see Fig. 3). A signiWcant interper-sonal justice £ risk aversion interaction was alsoobserved for counterproductive behavior, again in thepredicted direction (see Fig. 3). In all three cases, thebeneWcial eVects of fair treatment were stronger for indi-

Fig. 3. Justice£ risk aversion interactions for task performance andcounterproductive behavior.

High Risk AversionLow Risk Aversion



High Low

High Low

High Low

7.75

7.00

6.25

5.50

4.75

0.40

0.30

0.20

0.10

0.00

0.40

0.30

0.20

0.10

0.00


Procedural Justice

Procedural Justice

Tas

k P

erfo

rman

ceC

ou

nte

r p

rod

uct

ive

Beh

avio

ur

Co

un

ter

pro

du

ctiv

e B

ehav

iou

r


viduals who were highly risk-averse. Contrary to predic-tions, neither of the distributive justice interactions wassigniWcant.

Hypothesis 3a and b predicted stronger eVects forprocedural and interpersonal justice on task perfor-mance when trait morality was high. The interpersonaljustice£ trait morality interaction was signiWcant fortask performance, with the pattern in the predicteddirection (see Fig. 4). Though not predicted, the resultsalso revealed a similar interaction with distributive jus-tice for task performance (see Fig. 4). In both cases, theeVects of fair treatment on task performance were morepositive for individuals high in trait morality. Contraryto predictions, the procedural justice interaction was notstatistically signiWcant.

Results for alternative approaches to moderation of justice eVects

Table 4 provides the moderated regression results forequity sensitivity and SBI. The Wrst two steps reproducethe justice manipulation results from Table 3. The thirdstep examines the main eVects of the two traits, and nei-ther had signiWcant eVects. The fourth step examines thejustice£personality product terms, and the step was not

Fig. 4. Justice £ trait morality interactions for task performance.

Table 4Moderated regression results for equity sensitivity and sensitivity toBefallen Injustice

Note. n D 238. �R2 values may not sum exactly to R2 values due torounding error.¤ p < .05, two-tailed.


Regression step Task performance

Counterproductive behavior

R2 �R2 � R2 �R2 �



2. PJ£ IJ .01 .01 ¡.05 .10¤ .06¤ .20¤

PJ£ DJ ¡.04 .15¤

IJ£ DJ ¡.09 .07

3. Equity Sensitivity .03 .02 .11 .12¤ .01 .04SBI ¡.08 .11

4. PJ£ Equity Sensitivity .05 .02 ¡.01 .15 .03 ¡.13IJ£ Equity Sensitivity .10 .06DJ£Equity Sensitivity ¡.01 ¡.07PJ£ SBI ¡.06 ¡.06IJ£ SBI ¡.08 .02DJ£ SBI ¡.09 ¡.01

Table 5Moderated regression results for Big Five dimensions

Note. n D 238. �R2 values may not sum exactly to R2 values due torounding error.¤ p < .05, two-tailed.


Regression step Task performance

Counterproductive behavior

R2 �R2 � R2 �R2 �



2. PJ£ IJ .01 .01 ¡.05 .10¤ .06¤ .20¤

PJ£ DJ ¡.04 .15¤

IJ£ DJ ¡.09 .07

3. Conscientiousness .04 .03 .01 .13¤ .02 ¡.12Agreeableness .02 .01Neuroticism ¡.15 .01Openness .08 ¡.01Extraversion ¡.02 ¡.08

4. PJ£ Conscientiousness .10 .06 .00 .20¤ .07 .05IJ£ Conscientiousness .00 ¡.10DJ£Conscientiousness ¡.03 .04PJ£ Agreeableness ¡.07 ¡.13IJ£ Agreeableness ¡.15 ¡.18DJ£ Agreeableness .04 ¡.09PJ£ Neuroticism .04 .00IJ£ Neuroticism ¡.03 ¡.04DJ£ Neuroticism ¡.06 ¡.10PJ£ Openness ¡.00 .06IJ£ Openness .18 .05DJ£ Openness .01 .02PJ£ Extraversion .05 .10IJ£ Extraversion ¡.04 .02DJ£ Extraversion .02 .07


signiWcant for either task performance or counterpro-ductive behavior. Table 5 presents the moderated regres-sion results for the Wve-factor model. As with the otherpersonality traits, the third step of the regressionsrevealed no main eVects of the Big Five dimensions ontask performance or counterproductive behavior. Thefourth step examines the justice£personality productterms, and the step was not signiWcant for either taskperformance or counterproductive behavior.

Discussion

Taken together, our results illustrate that the integra-tive theories that have emerged within the justice litera-ture over the past Wve years can be fruitful sources ofpotential moderators of justice eVects. Although fairnessheuristic theory, uncertainty management theory, andfairness theory were not created for the express purposeof identifying personality moderators, the traits exam-ined here Xow neatly from the core propositions of eachtheory. The signiWcant interactions for trust propensity,risk aversion, and trait morality were observed acrosstypes of justice, supporting the replicability of the eVects.With the exception of trait morality, the interactionswere also observed for both task performance and coun-terproductive behavior. The task performance eVects arenotable, as the interactions help to clarify the inconsis-tent results in past studies of justice and performance(Cohen-Charash & Spector, 2001; Colquitt et al., 2001).

Of the moderators examined in our study, risk aver-sion yielded the most promising results, as it ampliWedthe beneWcial eVects of both procedural and interper-sonal justice. Indeed, it was the only trait examined inour study that altered procedural eVects. Risk aversionwas also the only trait that moderated both task perfor-mance and counterproductive behavior eVects in the pre-dicted manner. In contrast, risk aversion did not alter theeVects of distributive justice on either task performanceor counterproductive behavior. Although uncertaintymanagement theory deemphasizes the diVerences amongthe justice dimensions (Lind & Van den Bos, 2002; Vanden Bos & Lind, 2002), it may be that distributive justiceis less relevant to the management of uncertainty thanprocedural or interpersonal justice because it is moreepisodic, particularly when referenced to a one-time out-come or decision event.

With regards to trust propensity, given that justice isused as a proxy for trust, we reasoned that justice wouldhave less value to individuals who trusted “by default,”instead taking on more importance to the dispositionallysuspicious. Indeed, our results showed that the eVects ofinterpersonal and distributive justice on task perfor-mance were more positive for individuals lower in trustpropensity. Those eVects aside, two other aspects of ourtrust propensity results were contrary to predictions.

First, trust propensity failed to moderate procedural jus-tice eVects on either task performance or counterproduc-tive behavior, which is somewhat surprising becausemany procedural justice rules (e.g., consistency, bias sup-pression, and ethicality) overlap conceptually with theintegrity dimension of trustworthiness (Leventhal, 1980;Mayer et al., 1995). It may be that trust propensitywould emerge as a signiWcant moderator of proceduraljustice eVects in Weld settings, where long-term relation-ships are prevalent. Second, the eVects of interpersonaljustice on counterproductive behavior were actuallystronger for individuals high in trust propensity, oppo-site to the task performance results. This result may beakin to Wndings by Brockner, Tyler, and Cooper-Schnei-der (1992) that individuals who were highly committedto an organization experienced greater negative reac-tions as a result of unfair treatment than those less com-mitted. That is, “the higher they are, the harder they fall”(Brockner et al., 1992). However, given that the resultsfor task performance were in the opposite pattern, ratherthan non-signiWcant, this explanation may not be ade-quate. Future research is needed to provide insight intoexplaining these conXicting results.

The third moderator examined in our study was traitmorality. Using a trait-based form of the variable drawnfrom trait models of personality (de Raad et al., 1992;Hofstee et al., 1992), we found that the eVects of inter-personal and distributive justice on task performancewere more positive for individuals high in trait morality.In contrast, trait morality did not moderate the eVects ofprocedural justice on task performance, contrary to ourpredictions. Folger (2001) argued that the moralaccountability of justice tends to grow in ascendingorder from distributive to procedural to interactional.Thus, although distributive justice does have moral rele-vance (Folger, 1998, 2001), one would have expected theprocedural interaction eVects to be stronger than the dis-tributive. It may be that our Wndings might have diVeredhad we manipulated procedural rules that were moremorally charged than accuracy and consistency, such asbias suppression or ethicality (Leventhal, 1980).

To gauge the signiWcant eVects for risk aversion, trustpropensity, and trait morality, we explored two alterna-tive approaches to moderation of justice eVects. First, weexamined two traits introduced by justice scholars:equity sensitivity and SBI. Both traits failed to moderatethe eVects of justice, and their moderating eVects weremuch weaker than those of the three integrative theorytraits. However, it should be noted that equity sensitivitywas never intended to moderate the eVects of proceduralor interpersonal justice. Similarly, the content of SBI, asmeasured using Schmitt and Maes’s (2000) scale, isdecidedly distributive in nature, with the “befallen injus-tice” usually consisting of others receiving more ofsomething of value. It therefore remains unclear howrelevant SBI is to procedural and interpersonal justice.


Second, we investigated the traits of the Big Five; how-ever, results were weaker compared to the results for thethree integrative theory traits, with the justice£Big Fiveproduct terms explaining less variance in the outcomesoverall. Although Skarlicki et al.’s (1999) results foundsigniWcant interactions with Big Five variables, theirresults involved three-way interactions rather than thetwo-way eVects explored in our study. Still, it is notablethat 6 years have passed since Skarlicki et al.’s (1999)study was published without further published work onjustice£Big Five interactions. It may be that such workhas been conducted but yielded non-signiWcant results,creating a potential Wle drawer problem.

Practical implications

Our results oVer a number of practical implications.Task performance and counterproductive behaviorclearly are important outcomes in any organization, asboth impact bottom-line costs. Our results add to pastresearch linking justice dimensions to those behaviors(Greenberg, 1990, 1993b, 2002; Konovsky & Cropanz-ano, 1991; Van den Bos et al., 1996). Inaccurate andinconsistent procedures, disrespectful interpersonaltreatment, and unexpectedly low rewards impactedcounterproductive behavior and task performance,though often in an interactive rather than main eVectfashion.

Although justice principles can be trained (e.g., Skarl-icki & Latham, 1996), training initiatives often failbecause of a lack of awareness of speciWc person andorganizational variables that impact training eVective-ness. The “person analysis” phase of the training needsassessment is used to identify participant characteristicsthat make training more or less eVective, whereas the“organization analysis” explores contextual variablesthat can do the same. Our results could inform the per-son analysis, suggesting that justice training interven-tions would have particularly strong eVects when theleaders participating in the training oversee units withpredominantly suspicious, cautious, and moral individu-als. However, organizations do not typically collect dataon trust propensity, risk aversion, and trait morality, andit would be diYcult to characterize an entire unit on suchpersonality traits. Our results might therefore inform theorganization analysis, as justice trainers could considercontextual cues that trigger or amplify concerns aboutdistrust, uncertainty, or moral issues.

Limitations

As in many laboratory studies, the framing of instruc-tions, the sequence of measurement, and the timing ofmeasurements could impact the generalizability ofresults. For example, Harrison, McLaughlin, andCoalter (1996) showed that measures that reference fair-

ness concepts are susceptible to scale ordering and con-text eVects. Our personality measures, some of whichthemselves referenced justice concepts, may be suscepti-ble to such biases. Context eVects could also haveaccounted for the small amount of manipulation spill-over that occurred among the justice manipulationchecks. Although we removed this contamination byresidualizing the aVected manipulations, a proceduralremedy is usually preferred over a statistical one. Inaddition, our distributive justice manipulation variedfulWllment of expectations rather than outcome/inputratio comparisons. Although expectation fulWllmentmatches Blau’s (1964) conceptualization of distributivejustice and has been used extensively in past research(Greenberg, 1993b; Van den Bos et al., 1998b), that typeof manipulation may have constrained equity sensitiv-ity’s eVects, given that it is based on Adams’s (1965)theorizing.

Other limitations center on the measures of some ofour variables. Van den Bos et al. (1998a) showed thatknowledge of trust moderated the eVects of justice, withjustice being more impactful when trust was uncertain.Our measure of trust propensity is incapable of separat-ing trust uncertainty from trust valence, as suspiciousindividuals may either be uncertain about the trustwor-thiness of others or be certain that trustworthiness islacking. In addition, our measure of counterproductivebehavior could be interpreted in two ways: as intentionalnoncompliance with authority (one of the less seriousforms of the construct) and outright theft (one of themore serious forms of the construct). Our results forcounterproductive behavior may therefore fail to gener-alize to contexts where the retaliation is clearly serious innature (e.g., theft of actual money).

Finally, the most serious limitation of our study cen-ters on our trait morality measure. Recall that we choseto deWne morality as an intersection of high agreeable-ness and high conscientiousness (Hofstee et al., 1992).However, there are some interpretational ambiguitiesin trait models, mostly due to the presence of measure-ment error. For example, the adjectives “conscien-tious” and “agreeable” do not themselves fall squarelyon the circumplex poles used to deWne those respectiveBig Five factors. Such ambiguities may hinder the con-struct validity of adjectives like “morality” that resideat the intersection of the conscientiousness and agree-ableness poles. Although future work can clarify manyof these issues, there remains a limited amount ofresearch on the Big Five circumplex. Moreover, it isimportant to note that Hofstee et al.’s (1992) modeldoes not focus on morality per se, instead describing alarge number of traits that represent blends of multipleBig Five factors.

It is also important to note that the results for our cir-cumplex form of morality cannot be generalized to otherforms of the construct, such as a Kohlbergian stage


approach. As stated previously, a trait approach diVersfrom a stage approach in that the former emphasizesdiVerences across individuals while the latter emphasizesdiVerences within individuals over time (Walker, 2002).However, it may be that stage models such as Kohl-berg’s would also be useful for examining moderatingeVects of justice (for an example, see Greenberg, 2002).Future researchers utilizing such an approach wouldbeneWt from using appropriate stage measures such asthe DeWning Issues Test 2 (Rest, Narvaez, Thoma, &Bebeau, 1999).

Suggestions for future research

Perhaps the most fruitful area for future research con-cerns one additional limitation of our study. Our concep-tual model in Fig. 1 includes three diVerent mechanismsthrough which personality traits could moderate justiceeVects: sensitivity to justice concerns, deliberate rumina-tion on justice information, and likelihood of behavioralresponse. Our study did not assess those mechanisms,however. It therefore remains an empirical questionwhether those mechanisms do explain moderation eVectsat all, or whether only one or two of the processes is neces-sary for interactions to emerge.

Although our study was fairly comprehensive in itscoverage of multiple justice dimensions and its inclusionof several personality traits, some gaps in our coveragehighlight other areas for future research. For example,the “belief in a just world” may be relevant to the shouldcounterfactual and to the mechanisms in Fig. 1. It maybe that individuals with strong just world beliefs attendmore to justice because they, like moral individuals, aremore concerned with fairness in general. However, itmay also be that individuals with strong just worldbeliefs attend less to issues of fairness because theybelieve that things will “work out” in the end.

Future research should also explore personality mod-erators in conjunction with the other sub-facet of interac-tional justice: informational justice. We did not includeinformational justice in the present study for both practi-cal and conceptual reasons. Practically speaking, includ-ing informational justice would have doubled the numberof experimental conditions in an already complex study.Conceptually, we felt that some of our personality traitswere more relevant to interpersonal justice, given that it ismorally charged and holds special relevance to the integ-rity and benevolence forms of trustworthiness (Folger,2001; Mayer et al., 1995). However, informational justiceis germane to the could and should portions of fairnesstheory (Folger & Cropanzano, 2001; Shaw, Wild, &Colquitt, 2003) and its eVects could be moderated bytraits that capture the likelihood of asking “why?” ques-tions (e.g., curiosity, need for cognition).

Future research should also explore personality mod-erators of the two-way justice interactions often

observed in the justice literature. Skarlicki et al.’s (1999)results showed that neuroticism and agreeableness mod-erated the interaction between distributive and interac-tional justice, while Hagedoorn et al.’s (2002) showedthat just world beliefs moderated the interactionbetween distributive and procedural justice. Such workallows justice scholars to assess the generalizability ofsuch interactions across personality types. It may be thatmore complex interactions could help explain some ofthe unexpected patterns in our two-way results. Forexample, some of the interactions were symmetric innature, with fair treatment resulting in lower perfor-mance or more counterproductive behavior at certainpersonality patterns. Although such patterns are surpris-ing in the context of two-way interactions, they maymake more sense in conjunction with higher-order inter-action patterns.

Finally, it is important to point out that the interac-tions observed in our study could be interpreted in adiVerent way—that justice dimensions moderate therelationships between personality traits and counter-productive behavior and task performance. The signiW-cant product terms can be interpreted in either fashion,as can the plots represented in the Wgures. It may bethat organizational justice can be used to clarify incon-sistent behavioral eVects within the trust propensity,risk aversion, or morality literatures. For example,unfair treatment may be relevant to the principle oftrait activation (e.g., Tett & Gutterman, 2000), withfairness violations creating situational cues thatenhance the likelihood of trait expression. To ourknowledge, the justice dimensions have rarely been castas moderators in past research, leaving open a poten-tially fruitful area for future theorizing and empiricalstudy.

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