The Relationship Between Perceptions of Fairness and Voluntary Turnover Among Retail Employees

The Relationship Between Perceptions of Fairness and Voluntary Turnover Among

Retail Employees1

DAVID A. JONES~ DANIEL P. SKARLICKI~ University of Calgary

Calgary, Alberta, Canada University of British Columbia

Vancouveu, British Columbia, Canada

Research on the relationship between perceived fairness and employee turnover has tended to focus on turnover intentions rather than behavior, and the few studies that have assessed actual turnover have reported inconsistent results. In the present study, we examined the interactive effects of distributive, procedural, and interactional justice on turnover among 159 retail employees. Results showed that the effect of distributive justice on turnover was stronger when interactional justice was perceived as low rather than high. Our findings also suggest that disproportionate turnover group base rates favoring stayers over leavers can affect results ofjustice turnover research.

Turnover is one of the most frequently studied criterion measures in organizational research (Mitra, Jenkins, & Gupta, 1992). This is not surprising, consider- ing the high costs to recruit, select, and train new employees (e.g., Cascio, 1982; Darmon, 1990; Hall, 198 1). Employee turnover and retention are becoming increasingly important to organizations because of periodic labor shortages that potentially reduce the availability of high-performing employees. For example, the United States unemployment rate reached a 30-year low of 4.1% in 1999 (U.S. Bureau of Labor Statistics, 2000b).

The retail sales industry employs 22.3 million people in the United States (U.S. Bureau of Labor Statistics, 2000a). Turnover is a major concern for sales organizations in particular, because their success depends on employees who sell goods and services (Darden, Hampton, & Boatwright, 1987). Sales personnel

'A portion of this manuscript was presented at the 61st annual convention of the Canadian Psy- chological Association (June/July 2000), Ottawa, Canada, and an earlier version of this manuscript was presented at the 17th annual conference of the Society for Industrial and Organizational Psychol- ogy (April 2002), Toronto, Canada. The authors thank Gary Johns, Theresa Kline, Jeff Sager, Lome Sulsky, and two anonymous reviewers for their comments on earlier drafts of this paper.

*Correspondence concerning this article should be addressed to David A. Jones, Department of Psychology, University of Calgary, 2500 University Drive, N.W., Calgary, Alberta T2N 1N4, Canada. E-mail: [email protected]

3Support for this study was provided by a Social Sciences and Humanities Research Council grant to the second author.

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Journal of Applied Social Psychology, 2003, 33, 6, pp. 1226-1 243. Copyright 0 2003 by V. H. Winston & Son, Inc. All rights reserved.

PERCEPTIONS OF FAIRNESS AND TURNOVER 1227

are the company in the consumer’s eyes (Roberts & Chonko, 1994), thus custom- ers may perceive staffing instability as a negative characteristic of the organization.

Annual turnover rates among sales employees range from 45% to 200%, which is relatively higher than in other employment sectors (Dartnell, 1996- 1997; Mason & Mayer, 1981). Moreover, high turnover rates are costly. Training a single retail employee in the United States is estimated at $463 (US. Bureau of Labor Statistics, 1995), and the overall cost of replacement has been estimated at $1,000 (Mason & Mayer, 1981). Despite these statistics, there is a paucity of turnover research conducted in retail settings (Schulz, Bigoness, & Gagnon, 1987).

One reason why people may quit their jobs is that they feel unfairly treated by their employers or supervisors (e.g., Adams, 1963). Fairness has been defined in terms of distributive (outcomes), procedural (processes and policies), and interactional (interpersonal treatment by a supervisor) justice. Despite the presence of logical arguments linking the extensive organizational justice literature to turnover, few studies have examined how the three forms of justice predict voluntary turnover behavior (Griffeth, Hom, & Gaertner, 2000). Moreover, recent theory (referent cognitions theory; Folger, 1993) and research (e.g., Skarlicki & Folger, 1997) suggests that reactions to unfairness may be understood best by consider- ing the interactive effects of justice, rather than its main effects. The primary objective of the present study is to investigate whether interactive effects of justice predict voluntary turnover among retail employees.

Organizational Justice and Turnover

Early organizational justice research concentrated on distributive justice: people’s perceptions of fairness regarding outcomes such as pay or promotion. Adams (1963) proposed that individuals determine outcome fairness by comparing themselves to a referent other regarding their ratios of inputs (i.e., contri- butions to the organization) to outcomes received. A second focus of justice research has been procedural justice: the perceived fairness of the processes that determine an employee’s outcomes (Lind & Tyler, 1988). Procedures are seen as more fair when they are based on accurate information and the input of all affected parties (also termed process control); are consistent, without bias, and ethical; and include opportunity for appeal (Leventhal, Karuza, & Fry, 1980; Thibaut, & Walker, 1975). More recently, justice scholars have focused on interactional justice: the perceived fairness of interpersonal treatment by organizational leaders (Bies & Moag, 1986). Interactional justice perceptions are affected by whether employees are treated with sensitivity, dignity, and respect, and whether explanations are provided for outcomes (Colquitt, Conlon, Wesson, Porter, & Ng, 2001; Folger & Bies, 1989).

1228 JONES AND SKARLlCKl

We propose that there at least two reasons why each form of justice predicts voluntary turnover. First, Randall, Cropanzano, Bormann, and Birjulin (1 999) suggested that organizations can be viewed as marketplaces in which people trade their talents and motivation in return for both tangible (e.g., pay) and intangible rewards (e.g., fair treatment, dignity, and respect). According to social exchange theory (Blau, 1964) and the norm of reciprocity (Gouldner, 1960), a mutual reciprocation of benefits often occurs during social interactions. Put sim- ply, people tend to reciprocate benefits received. Thus, individuals who perceive that they are fairly treated may reciprocate by continued employment.

Second, it is plausible that employees who perceive unfairness may quit their jobs in an attempt to obtain fairer treatment in another organization. In response to perceptions of low distributive justice, employees may leave to end the inequity (Adams, 1963) or to obtain fairer outcomes in another organization. More- over, Folger (1993) suggested that perceptions of unfair procedures and interpersonal treatment could signal a lower likelihood of organizationwide fairness and fair interpersonal treatment in the future, respectively. Hence, employees may be motivated to leave and to seek a fairer alternative.

To date, however, justice-turnover research has reported inconsistent results. Some studies have found support (e.g., Hendrix, Robbins, Miller, & Summers, 1998; Sager, 199 l), whereas others have shown a lack of support for one or more aspects of justice predicting turnover (e.g., Aquino, Griffeth, Allen, & Hom, 1997; Dittrich & Carrell, 1979). We propose that these mixed results may be a result of theoretical and methodological issues; namely, focusing on main effects rather than the theoretically based interactions among the three forms of justice, and the use of disproportionate turnover group base rates.

Interactive Justice Effects

Theory and research suggest that justice main effects may not tell the whole fairness-turnover story. Brockner and Wiesenfeld (1 996) argued that empirical and conceptual models of organizational justice that ignore interactive justice effects are potentially committing a specification error. According to referent cognitions theory (RCT), resentment and reactions to unfairness are predicted by the combination of outcome severity (i.e., distributive justice) and inappropriate treatment in terms of procedural or interactional justice (Folger, 1993). The degree of distributive justice has less of an impact on employees’ work attitudes and behaviors when they find it difficult to envision the achievement of a more positive outcome obtained through alternative procedures or treatment. Employees are particularly resentful about unfair outcomes that are associated with procedures or a leader’s behavior when the latter is deemed to be purposeful or intended (Folger & Cropanzano, 1998). Thus, resentment and turnover are highest when low distributive justice is combined with either low procedural or low interactional justice.


Considerable support exists for the interactive effects of perceived justice on work attitudes and behavior (for a review, see Brockner & Wiesenfeld, 1996), including studies of turnover intentions (Brockner, DeWitt, Grover, & Reed, 1990; Garonzik, Brockner, & Siegel, 2000; Greenberg, 1994; Magner, Welker, & Johnson, 1996; Schaubroeck, May, & Brown, 1994). Only one study (Randall & Mueller, 1995) examined whether an interactive justice effect predicts actual turnover, but the results showed that the Distributive Justice x Procedural Justice interaction was nonsignificant.

Disproportionate Base Rates

Although predicting actual behavior has advantages over behavioral intentions, which are discussed in more detail later, one potential drawback is that the analyti- cal strategy changes from predicting a continuous to a dichotomous variable. For example, the reduction in variance in the criterion can heighten the possibility of a Type I1 error. Moreover, imbalanced cell sizes, which arise from low turnover base rates, can result in weak empirical links between attitudes and turnover (Hom & Griffeth, 1995). Thus, for any given relationship with a dichotomous criterion, increasingly unequal group sizes will lower the strength of the observed relationship (i.e., range restriction). To address this, turnover researchers have developed formulas to correct for unbalanced leaver and stayer base rates to reflect a 50-50 split (Bass & Ager, 1991; Kemery, Dunlap, & Griffeth, 1988; Steel, Shane, & Griffeth, 1990). Some scholars (Williams, 1990; Williams & Livingstone, 1994), however, caution against the use of such statistical corrections because there are often real and setting-specific reasons for the unbalanced base rates.

Statistical pundits suggest that statistical strategies such as discriminant function analysis and logistic regression can be useful for predicting dichotomous outcomes (for a review, see Tabachnick & Fidell, 1996). Logistic regression, for example, identifies the best linear combination of predictors to maximize the likelihood of obtaining an observed outcome frequency. Thus, rather than comparing the relative means between participants or estimating variance in a criterion, logistic regression uses a function of predictors and their interactions to estimate group membership (i.e., stayers vs. leavers). Based on outcomes that are known, logistic regression calculates the percentages of cases that a given function of predictors correctly classifies into group membership. Moreover, logistic regression can be usehl for comparing whether the linear combination of predictors is better (i.e., a higher percentage of correct classification) at predicting one classification group (e.g., leavers) than another (e.g., stayers).

There is reason to expect, however, that imbalanced cells can lead researchers to make incorrect inferences regarding their results. Specifically, imbalanced cells can bias classification findings in favor of the larger cells. Sager (1991), for example, examined fairness predictions within a sample favoring stayers (3: l),


and found that the percentage of correct classification was higher for stayers than for leavers. Similarly, Jones (1998) used logistic regression analysis to analyze data from a disproportionate sample that favored stayers (1 1 : 1) and found that classification accuracy was higher for stayers (97%) than for leavers (38%). Jones concluded that procedural fairness is a better predictor of who would remain than who would leave the organization. This result, however, might have occurred because the logistic regression function was constructed to maximize classification accuracy for the entire sample-a sample in which the majority of employees did not turnover.

Imbalanced cell sizes can be particularly problematic when examining interactive fairness effects on turnover. Specifically, RCT proposes that interactive justice effects will predict resentment and negative workplace behaviors (i.e., those who leave) better than positive behaviors (i.e., those who stay). In the Randall and Mueller (1 995) study discussed earlier, the justice interaction that theoretically should help predict who will leave the organization was tested in a sample in which the majority of people remained (i.e., 149 stayers and 13 leavers).

Indeed, unequal cell sizes are a common occurrence in fairness-turnover research. In five of six justice-turnover studies that reported the group sizes, there were substantial differences in the number of stayers versus leavers, reflecting a low base rate for those who left: approximately 8 leavers versus 142 stayers (Aquino et al., 1997); 8 leavers versus 136 stayers (Hom, Griffeth, & Sellaro, 1984); 42 leavers versus 464 stayers (Jones, 1998); 13 leavers versus 149 stayers (Randall & Mueller, 1995); and 24 leavers versus 72 stayers (Sager, 1991; for an exception, see Hendrix et al., 1998, with 42% of 310 who left). We reasoned that a sample with a relatively equal and naturally occurring ratio of leavers to stayers might permit a more appropriate test of justice theory predictions.

Turnover Intentions Versus Behavior

A vast majority of previous studies of justice and turnover have focused on turnover intentions and withdrawal cognitions, rather than turnover behavior (e.g., Alexander & Ruderman, 1987; Dailey & Kirk, 1992; Konovsky & Cropanzano, 199 1 ; Masterson, Lewis, Goldman, & Taylor, 2000; Miceli, Jung, Near, & Greenberger, 199 1 ; Sujak, Parker, & Grush, 1998; Sweeney & McFarlin, 1997). Predicting turnover intentions is important because, for example, they also are related to the withdrawal of citizenship behaviors (e.g., Chen, Hui, & Sego, 1998). Nonetheless, researchers (e.g., Newman, 1974; Tett & Meyer, 1993) have questioned the use of turnover intention as a surrogate for actual behavior, as has occurred in previous justice research (Roberts, Coulson, & Chonko, 1999).

Although turnover intentions predict turnover, the relationship is less than perfect. First, people’s underlying motives for their intentions are not necessarily based on dissatisfaction with the organization (Vandenberg & Nelson, 1999).


Second, employees may want to quit or intend to quit, but remain at work because they may feel they do not have the skills to obtain alternative employment (Mone, 1994). Employees are often reluctant to leave because certain commitments (e.g., feelings of obligation toward the organization) bind them to their current position, and because the costs associated with leaving are perceived as high (Meyer & Allen, 1997). Sager and Menon (1 994), for example, found that sales personnel can intend to quit, yet they remain indefinitely employed. Finally, because both justice perceptions and turnover intentions are measured using self-report, the results may be affected by common method variance. Thus, although justice perceptions indeed predict turnover intentions, fairness may not necessarily predict turnover behavior,

In the present study, we propose that focusing on actual turnover provides a stronger test of the fairness-turnover relationship than would a study of turnover intentions. Furthermore, predicting actual turnover rather than a surrogate measure of turnover intention increases construct and internal validity (Keaveney, 1992), has more relevance for organizations, and avoids the potential disadvan- tage of using self-reports for both predictor and criterion measures (i.e., common method bias).

Hypotheses

Hypotheses 1 and 2 were derived from RCT The theoretically based interactions between the forms of justice predict turnover incremental to their main effects. Hypothesis 3 was based on our discussion of the impact of unequal turnover base rates on the results of justice-turnover research.

Hypothesis I. The relationship between distributive justice and turnover is stronger when interactional justice is low rather than high.

Hypothesis 2. The relationship between distributive justice and turnover is stronger when procedural justice is low rather than high.

Hypothesis 3. In a randomly drawn subsample with unequal turnover base rates favoring stayers (3: l), the percentage of leavers who are correctly classified is lower than in an equal base rate subsample.

Method

Participants

Participants were 177 employees from a large retail chain in western Canada. The sample included merchandisers, cashiers, and departmental salespeople. All employees volunteered to participate. Some (n = 18) participants were excluded


because they were either dismissed by the organization or had fewer than 30 days of tenure at the time of the justice measures. Of the remaining 159, 75 were female and 84 were male, and the mean tenure and age were 25.5 months and 29.6 years, respectively.

Measures

We obtained self-reports of distributive, procedural, and interactional justice. The response scale for all of the justice variables was a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strong& agree). Items were averaged to form each justice measure. Higher scores represented greater perceived fairness than did lower scores.

Distributive justice. We measured distributive justice with three items that asked participants about the perceptions of their pay: “I believe that I am being rewarded fairly here at work”; “I believe that the base pay I receive is fair”; and “I believe that the overall pay I receive is fair.” As is common in organizational justice research (Skarlicki & Folger, 1997), the focus of distributive justice was on perceptions of fairness regarding wages because pay was likely a relevant outcome to retail employees.

Procedural justice. We measured procedural justice with four items based on the rules of procedural justice (Leventhal et al., 1980). Items were adapted from Folger and Konovsky (1989), and each item began with “Do you believe there are processes currently in place that . . . ?” and the items read “make sure that information used for decisions is accurate and complete”; “make sure all parties affected by a company decision are represented in the decision”; “make sure that information upon request and explanations are provided to employees regarding company decisions”; and “make sure that [the company] is informed about employees’ needs in order to make fair decisions.”

lnteractionaljustice. We measured interactional justice with four items that assessed whether procedures were enacted properly by the managers, based on measures used in previous research (Folger & Bies, 1989; Moorman, 199 1). Each item began with “Do you believe that your supervisor. . . ?’ and the items read “considers your viewpoint, needs, and concerns when making decisions”; “provides you with timely feedback about issues that concern you”; “treats you with dignity and respect”; and “shows concern for your rights as an employee.”

We conducted an exploratory factor analysis on the fairness items using max- imum likelihood extraction and oblique rotation. The three forms of fairness emerged as three distinct factors. The pattern matrix showed that all items loaded on their intended factors (ranging from .66 to .95), and no items cross-loaded. The three factors explained 65.4% of the total item variance.

Control measures. Career stage is often related to turnover and has been oper- ationalized as a combination of tenure and age (Cohen, 1991). As is common in


Table 1

Descriptive Statistics, Correlations, and Cronbach ’s Alphas for Al l Study Variables

Variable M SD 1 2 3 4 5

1. Tenure 25.52 39.70 -

2. Age 29.55 9.30 .31*** - 3. Distributive justice 2.60 1.03 -.05 -.02 (.94) 4. Procedural justice 3.09 0.73 .02 . l l .43*** ( 3 2 ) 5. Interactionaljustice 3.80 0.82 -.01 .OO .15 .22** (.87) 6. Turnover 0.44 0.50 -.38*** -.29** -.19* . l l . l l

Note. Point-biserial correlations were calculated for turnover. Cronbach’s alphas are reported in parentheses for the justice scales. Tenure refers to the number of months employed in the organization at the time of the justice measures. *p<.OS. **p<.Ol. ***p<.OOl.

turnover research (Griffeth et al., 2000), both age and tenure were related to turnover group membership in our sample (Table l), thus we controlled for both variables. Tenure was obtained from company records, and age was assessed through self-report.

Turnover: Turnover status (89 stayers coded 0, and 70 voluntary leavers coded 1) was obtained from store records 10 months after the justice measures were taken. This time frame was consistent with previous research (e.g., 9 months, Sager, 1991; 11 months, Dittrich & Carrell, 1979).

Procedure

Questionnaires were administered during company time in an onsite board- room. A cover letter from the storeowner highlighted that the voluntary responses were confidential and were to be used for research purposes only.

Results

The descriptive statistics, correlations, and Cronbach’s alphas for the variables are presented in Table 1. Table 2 shows the results of the sequential logistic regression analysis. We entered age and tenure as control variables in Step 1. We entered the individual justice effects in Step 2 and the two justice interaction terms in Step 3. After Step 3, the model’s pseudo R2 (Aldrich & Nelson, 1984) was .48, and correct classifications were made for 73.0% and 67.1% of the stayers and leavers, respectively.


Table 2

Results of Hierarchical Logistic Regression Analysis Predicting Turnover Group Membership

~ ~~ ~ ~

x2 model

improve Variable ment p S E B Wald pr

Step 1 Tenure

Age Step 2

Distributive justice Procedural justice Interactional justice

Distributive Justice x Proce-

Distributive Justice x Interac-

Step 3

dural Justice

tional Justice

-0.03** .01 10.22 -.19 -0.17 .10 3.14 -.07

13.49** -0.60** .20 8.98 -.I9 0.72* .31 5.52 .13 0.26 .23 1.25 .OO

4.48

-0.27 .26 1.12 .OO

0.48* .25 3.86 .10

Note. p r = partial correlation. *p < .05. **p < .01.

In Step 2, Wald’s tests of the regression coefficient showed that the individual effect of interactional justice was not significant, but both distributive and procedural justice predicted turnover group membership incremental to age, tenure, and the other individual justice effects. Contrary to our expectations, higher procedural justice was associated with a greater likelihood of leaving the organization.

In Step 3, the two-way interaction of distributive and interactional justice was a significant predictor of turnover above and beyond all other effects in the model. We created high and low interactional justice groups comprised of participants whose scores were 1 SD above and below the mean, respectively, and tested the simple distributive justice effects while controlling for age, tenure, and procedural justice (Bonferroni corrected a = .025). The relationship between distributive justice and turnover group membership was nonexistent in the high interactional justice group (partial correlation was .OO; p = 0.01, II = 27). In contrast, distributive justice significantly predicted turnover group membership in the low interactional justice group in which the partial correlation between


Table 3

Percentage of Correct Predictions for Stayers and Leavers in Two Subsamples and in the Full Sample

Sample

Turnover group Unequal Equal Full

Stayers 88.8% 66.7% 73.0% n = 89 n = 60 n = 89

Leavers 38.7% 73.3% 67.1% n=31 n=60 n=70

distributive justice and turnover was -.29 (p = -2.52, n = 23). Thus, Hypothesis 1 was supported. The distributive by procedural justice interaction was not significant; hence, Hypothesis 2 was not supported.

To test Hypothesis 3, the same method of entry was used for two randomly generated subsamples to demonstrate the implications of using unbalanced turnover base rates (equal: n = 60, n = 60; unequal favoring stayers: n = 89, n = 3 1) . Table 3 shows that after Step 3, the percentage of correct classifications for leavers in the unequal base rate subsample (38.7%) was lower than in the equal subsample (73.3%); thus, Hypothesis 3 was supported.

Discussion

We proposed that the interactive effects of justice would account for variance in turnover incremental to its main effects. We also tested whether imbalanced cell sizes, a methodological artifact endemic to previous justice turnover research, affected our findings.

We found support for the distributive justice by interactional justice effect on turnover group membership. Consistent with RCT, the negative relationship between distributive justice and turnover was stronger when interactional justice was low than when it was high, and the likelihood of leaving was maximized when both distributive justice and interactional justice were low. Moreover, our results suggest that perceptions of high interactional justice can offset the delete- rious effects of low distributive justice on voluntary turnover. It is also noteworthy that the main effect of interactional justice on turnover was not significant, but that it was related to turnover when considered simultaneously with distributive justice. These findings illustrate the importance of moving beyond individual justice effects and examining the RCT-based interactions to predict organizational behavior.


The distributive justice by procedural justice interaction did not explain significant variance in the turnover measure. Moreover, contrary to our expectations, higher procedural justice was associated with a greater likelihood of leaving. This finding should be interpreted cautiously, however, because procedural justice was a significant predictor of turnover only when procedural justice was tested incremental to the other predictors in the model (the zero-order point- biserial correlation between procedural justice and turnover was nonsignificant). To assess whether this finding influenced the observed interactive effect of interactional justice by distributive justice on turnover, we removed the procedural justice effects (both individual and interactive) from the model post hoc and found that the results for Hypothesis 1 were unchanged. We also tested the procedural justice by distributive justice interaction after removing all interactional justice effects from the model, and our conclusions remained unchanged.

An important question raised by our results is under what conditions perceptions of high procedural justice might be related to higher turnover. Brockner, Magner, and Magner (2000) proposed that people sometimes use procedural fairness information to make causal attributions for their outcomes. When people believe that a poor outcome resulted from a fair procedure, they are more likely to make an internal attribution (e.g., “I must deserve the poor outcome because the procedure was fair”), which can result in lower self-esteem (Schroth & Shah, 2000; Van den Bos, Bruins, Wilke, & Dronkert, 1999). In contrast, with unfair procedures, a person is able to protect his or her self-esteem by making an external attribution for a poor outcome (e.g., “The procedure was flawed, thus the outcome is not indicative of my worth as an employee”). Leaving an organization may be one way to avoid the threat to one’s self-esteem that can result from the combination of poor outcomes with fair procedures.

The self-esteem explanation we just described is based on the internal- external locus distinction (Brockner et al., 2000), which is one of three primary dimensions proposed to underlie causal attribution (e.g., Anderson, Krull, & Weiner, 1996). An alternative explanation is related to a second causal dimension, stability, which is purported to predict people’s expectations for future events (e.g., Weiner, 1986). Unfair procedures provide little information about the future predictability of outcomes (Brockner & Wiesenfeld, 1996). In contrast, if an employee believes that poor outcomes are determined by fair procedures, then the cause might be seen as stable, which may indicate that outcomes will remain low over time. Thus, people may leave to avoid poor outcomes in the future.

It is noteworthy that in the present study, the mean distributive justice rating ( M = 2.60) was the only fairness measure that participants rated below the midpoint of the scale. Anecdotally, several employees indicated that they felt under- paid relative to employees in other retail stores (68.6% of our sample rated distributive justice at or below the scale midpoint). Assuming that the low distributive justice ratings reflect employees’ belief that their pay was relatively


low, the perception that fair procedures resulted in low pay may have led to a greater likelihood of voluntary turnover.

Given the attribution-based arguments and the distribution of perceptions of pay fairness, however, one might expect an interaction between distributive justice and procedural justice, such that the propensity to leave was maximized when people perceived lower distributive justice and higher procedural justice. The lack of such an interaction, however, may be a result of two different interactive patterns canceling each other out: the RCT prediction (turnover is maximized when procedural justice and distributive justice are low), and the causal attribution prediction (turnover may occur when there is low distributive justice and high procedural justice).

The distribution of scores on perceived pay fairness predominantly represents different degrees to which distributive justice was perceived as unfair. It is pos- sible that the relationship between distributive justice and turnover did not depend on the level of procedural justice (i.e., the interaction was nonsignificant) because for employees with low outcome fairness, whether procedural justice was perceived as high (attributions) or low (RCT) resulted in little difference in the likelihood of turnover. Moreover, there might have been too few employees with high distributive justice perceptions to observe a simple procedural justice effect within fair distributive justice. Although highly speculative, our finding of a positive effect of procedural justice on turnover might indicate that the attribution processes were operating for more people or to a greater extent than the procedural justice-based RCT processes. Future research is needed to determine when the attribution and RCT-based interactive patterns are most likely to oper- ate, and whether these interactive patterns can cancel each other out.

Staying and leaving are inversely related. However, the decision to leave or to stay with an organization is not necessarily influenced by the same antecedents (Hom & Griffeth, 1995). Jones (1998) proposed that fairness predictions are more accurate for stayers because the decision to leave is affected by both the desire to leave (i.e., perceived unfairness) and the ease of leaving (e.g., labor market conditions). When we analyzed a subsample with disproportionate base rates favoring stayers, the stayers were more accurately classified than were the leavers. However, rates of correct classification were similar for stayers and for leavers in both the equal subsample and in the full sample used in our hypothesis testing. Thus, the present study contributes to our understanding of the justice- turnover relationship by showing that perceived fairness not only predicts those who stay, but also can predict those who leave. Our results also demonstrate the importance of examining a balanced proportion of leavers to stayers to allow for optimal tests of the research questions.

The present study design does not permit us to make causal inferences, although the temporal order of the data collection allows us to rule out the possibility that leaving the organization caused perceptions of unfairness. Also,


the turnover variance was restricted to those who left within 10 months before the justice measures were taken. This time frame was somewhat artificial because, given enough time, all employees will leave the organization (Hendrix et al., 1998). Future research may benefit from the use of time-phased longitudinal designs.

The practical implication of this research is that organizations facing financial constraints may not be able to change the perceived fairness of outcomes such as pay. However, fair treatment by organizational leaders may be a cost-efficient method to reduce voluntary turnover (Aquino et al., 1997). One way of increasing interactional justice is through leader training (Skarlicki & Latham, 1996). In light of the significant interaction effects found in the present study, managerial fairness training may be highly relevant for retail organizations in which employees typically receive relatively low wages.

Recent conceptual research has proposed that employees’ attributions of blame are an important aspect of their fairness perceptions (e.g., Folger & Cropanzano, 1998). Studies have found that different forms ofjustice can predict at least three different types of outcomes: personal, system, or leader-referenced (Byrne & Cropanzano, 2000). Research (e.g., Masterson et al., 2000; Sweeney & McFarlin, 1993) has suggested that distributive justice is a relatively stronger predictor of personal-referenced outcomes (e.g., pay and job satisfaction), whereas procedural justice is a relatively stronger predictor of system-referenced outcomes (e.g., organizational commitment), and interactional justice is a relatively stronger predictor of leader-referenced outcomes (e.g., citizenship behavior toward the supervisor). Our research suggests that instead of attempting to determine which aspect of justice is the strongest predictor of voluntary turnover behavior or intention (e.g., Roberts et al., 1999), it may be more fruitful to consider how the justice aspects work together interactively to predict turnover. Thus, we propose that voluntary turnover may act as a combination of person, system, and leader-referenced outcomes.

Building on our findings, one important question for future research is whether interactional justice is stronger than procedural justice in moderating the distributive justice-turnover relationship. Folger and Cropanzano (1998) proposed this conclusion based on the tendency for people to make causal attributions for unfair treatment. Given that an unfavorable outcome has occurred, it is often unclear whether the procedure associated with it was intentional and purposeful. In contrast, when unfavorable outcomes are accompanied by low interactional justice, there is relatively less ambiguity as to the source and the intention of the supervisor. Furthermore, attributions of harmful intention can be deflected by a decision maker through an excuse, justification, or fair interpersonal conduct. Stated differently, attributions of ill will may follow more directly from an evaluation of a supervisor (i.e., interactional justice) than of a procedure (i.e., procedural justice). To our knowledge, however, researchers have not


investigated whether interactional or procedural justice is a stronger moderator of the relationships between distributive justice and relevant outcomes. The role of attributions of harmful intent to justice theory warrants future study.

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The Relationship Between Perceptions of Fairness and Voluntary Turnover Among Retail Employees

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