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Justice in Teams

Summary and Keywords

Traditionally, justice in teams refers to a specific climate—called justice climate—describing shared perceptions about how the team as a whole is treated. Justice at the individual level has been a successful model from which to build the concept of justice in teams. Accordingly, there is a parallelism between the individual and team levels in the investigation of justice, where scholars’ concerns and responses have been very similar, despite studying different levels of construct. However, the specific particularities of teams are increasingly considered in research. There are three concepts (faultlines, subgrouping, and intergroup justice) that contribute to knowledge by focusing on particularities of teams that are not present at the individual level. The shift toward team-based structures provides an opportunity to observe the existence of dividing lines that may split a team into subgroups (faultlines) and the difficulty, in many cases, of conceiving of the team members as part of a single group. This perspective about teams also stimulates the study of the subgroup as a source of justice and the focus on intergroup justice within the team. In sum, the organizational context facilitates shared experiences and perceptions of justice beyond individual differences but also can result in potential conflicts and discrepancies among subgroups within the team in their interpretation of fairness.

Keywords: team-level justice, individual-level justice, faultlines, subgrouping, intergroup justice

Organizational theory has increasingly paid attention to the investigation of justice. The interest shown by scholars and practitioners is based on the idea that justice is a strong predictor of employee attitudes and behaviors (e.g., Colquitt et al., 2013). These outcomes lie at different levels of construct and analysis. In fact, one of the most important advances in the justice literature was the transition from an individual-level to a multilevel approach to organizational justice, where the team level has achieved a prominent status (see Li, Cropanzano, & Molina, 2015). At least three interrelated drivers explain the interest in justice at the team level: (a) the shift toward team-based structures in organizations; (b) the expansion of scientific knowledge through the multilevel perspective; and (c) the development of techniques that facilitate statistical analyses beyond the individual level.

The shift toward team-based structures in organizations has stimulated the interest in justice in teams. Although the fragmentation and distribution of simple tasks among individual workers—present in the scientific management (Taylor, 1991)—were efficient strategies for the mass production of standard products, these strategies are being questioned in an era when consumers are more sophisticated and ask for differentiated products and services. To satisfy this complex demand, organizations need multi-tasking and multi-skilled employees working in teams, based on the assumption that this way of organizing the work is better “for an environment in which flexibility, innovation and problem solving at source are important” (Lanz, Miroudot, & Nordås, 2013, p. 211). The increasingly generalized use of teams in organizations creates an ideal context for the emergence and study of justice at the team level. Team members are subjected to similar stimuli, processes, and structures. They also have more opportunities to communicate with each other than in an individual-based organization of work. This context facilitates shared experiences and perceptions of justice beyond individual differences but also can result in potential conflicts and discrepancies among subgroups within the team in their interpretation of fairness.

Regarding the second driver, the consideration of different levels in the study of justice coincides with the expansion of scientific knowledge in organizational theory, where there is general consensus about the importance of going beyond the individual level in order to better understand organizational behavior. If we seriously consider the organization from a systems approach, we cannot restrict research efforts to the individual subsystem. Relevant constructs emerge at different levels (individual, team, organization as a whole), and investigating bridges between levels of construct and analysis is an indicator of the maturity of theory and research (Kozlowski & Klein, 2000). Of course, individual differences in justice perceptions exist, but team members are also able to develop shared perceptions of justice regarding the way the supervisor and other sources of justice (e.g., the organization a whole, peers) treat the team as a whole (e.g., Naumann & Bennett, 2000; Stoverink, Umphress, Gardner, & Miner, 2014). Approaches such as symbolic interaction or the attraction/selection/attrition model, which we discuss later, help to provide theoretical arguments for the existence of team-level justice. Nevertheless, the internal dynamics of teams are complex, and different views about justice can coexist within the same team (Roberson & Colquitt, 2005).

Finally, the development of techniques and methods of conducting research has also facilitated the consideration of justice at the team level in empirical research. The individual is usually the original level for the measurement of constructs, including justice. Thus, scholars traditionally use mean ratings of measures at the individual level to obtain indicators of variables at the team level. To do so, researchers should not only have theoretical arguments but also statistical information about the existence of agreement among team members. During the past few decades, different techniques have flourished to assess the degree to which raters (e.g., team workers) assign similar judgments to an object (e.g., treatment received by the supervisor). Well-known examples of these techniques are the interrater agreement index (rwg) by James, Demaree, and Wolf (1993) and average deviation indices (AD) by Burke, Finkelstein, and Dusig (1999). Researchers are also interested in investigating cross-level effects, such as how team-level variables (e.g., team-level justice) can impact individual-level variables (e.g., individual commitment). To this end, the use of hierarchical linear models has become popularized (Raudenbush & Bryk, 2002). In addition, to capture the complex and sometimes conflictive dynamic of teams, algorithms have been developed to assess discrepancies and the potential existence of subgroups (see Meyer, Glenz, Antino, Rico, & González-Romá, 2014). Over time, all of these methodological efforts, as well as others, have facilitated adequate research on team-level justice (e.g., Molina, Moliner, Martínez-Tur, Cropanzano, & Peiró, 2015; Yang, Mossholder, & Peng, 2007).

Research on justice at the team level has largely imitated the steps that have been taken in the study of justice at the individual level, examining areas such as the dimensionality of justice, main antecedents and outcomes, and sources of justice. This strategy has led to significant advances. However, other approaches that consider the particularities of teams have significantly contributed to the knowledge and identified new paths in the study of justice at the team level. With this in mind, this article is organized as follows. First, it summarizes the transition from the individual to the team level in the study of justice in organizations. Second, it describes the parallelism between justice at the individual and team levels. Finally, it analyzes how considering unique characteristics of teams contributes to knowledge and implications for future research.

From the Individual to the Team: A Brief Summary

In general terms, organizational justice is defined as the degree to which an element of the organizational environment is perceived as fair, according to a certain rule or standard (Cropanzano, Rupp, Mohler, & Schminke, 2001). Over time, justice research has evolved from the individual level exclusively to a multilevel perspective where the team-level has acquired relevance. During this transition, topics and perspectives in the investigation of justice at the team level were similar to those studied at the individual level, but gradually more specific team-related issues have emerged. The team refers to a group of peers who coordinate their efforts to achieve shared objectives. Justice research beyond the individual focuses predominantly on this type of team. Nevertheless, other research studies considered conceptually close levels (e.g., department) where the level of integration of members is lower. In any case, researchers assume the existence of justice perceptions beyond the individual.

Justice at the Individual Level

About 50 years ago, John Stacey Adams (1965) published his influential paper, helping to establish the foundations of equity theory in understanding interpersonal relations and facilitating the transfer of justice to the investigation of organizational life. For years, justice in the workplace and equity were equivalent concepts, although scholars proposed other rules (e.g., equality) to define justice (Deutsch, 1975). Accordingly, distributive justice was prominent during the early stages of the conceptualization and research on organizational justice. Distributive justice emphasizes worker evaluations of outcome fairness. Workers consider their investments (time, effort, etc.) and benefits (promotion, salary, etc.), and they also compare their own investments and benefits with the inputs and outputs of a referent. When these ratios are balanced, the individual experiences equity feelings, while any disturbance in this balance has potentially negative effects. Workers perceiving underbenefiting situations experience anger because they can feel that others are taking advantage of them, while overbenefiting perceptions produce a sense of indebtedness (Buunk & Schaufeli, 1999). However, due to humans’ negativity bias (a special human sensitivity to negative events) (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001), some research studies have questioned the idea that negative effects of under- vs. overbenefiting perceptions are symmetrical in their magnitudes. In other words, underbenefiting perceptions have more accentuated negative effects than overbenefiting ones (Martínez-Tur, Estreder, Moliner, Sánchez-Hernández, & Peiró, 2016). Positive reactions toward advantageous inequity may even increase in workers without a process through which to become socialized in deontology (Moliner, Martínez-Tur, Peiró, Ramos, & Cropanzano, 2013) and in situations where cognitive processing is strongly limited (Van den Bos, Peters, Bobocel, & Ybema, 2006). In addition, there are low equity sensitivity individuals who are tolerant to overbenefiting situations and intolerant to underbenefiting ones (see Sauley & Bedeian, 2000).

Although the study of distributive justice remains relevant, over time, scholars have become aware that considering outcome fairness as the only way to define justice in work settings is limited. Research has also focused on procedures, introducing social elements of justice in the workplace (see Folger & Greenberg, 1985, for an early review). Workers consider not only outcomes in their evaluation of justice but also the procedures used to make decisions about the distribution of outcomes. This dimension of justice, called procedural justice, pays attention to the rules underlying the implementation of procedures (Thibaut & Walker, 1975). In his influential categorization of rules, Leventhal (1976, 1980) argued that fairness increases when procedures are consistently applied, correctable, free from bias, representative of all parties, and consistent with ethical standards. The distinction between outcomes and procedures has been a challenge for scholars. Usually, distributive justice has been associated with outcome-oriented concerns, while procedural justice is more relation-oriented, indicating that the recipient is a respected member of the organization (Blader & Tyler, 2005). Researchers have explored the role of both types of justice in the nomological network. For example, according to the two-factor model (see Gilliland & Chan, 2001), procedural justice is especially related to system-referenced variables (e.g., commitment), whereas distributive justice is closely associated with personal-referenced variables (e.g., pay satisfaction). However, this duality probably simplifies the motivations that underlie organizational justice. As Cropanzano and Rupp proposed (2002), individuals also act fairly for moral reasons because they view this behavior as the “right thing to do” (Cropanzano & Rupp, 2002, p. 268).

In addition to distributive and procedural justice, Bies and Moag (1986) proposed the existence of a third dimension of justice called interactional justice. This justice facet captures the quality of the treatment the worker receives from others. This proposal stimulated a debate about the differentiation between procedural and interactional justice. Some scholars suggested that interactional justice does not have an independent status because it only describes the social component of procedural justice (e.g., Tyler & Bies, 1990), while other researchers argued for a distinction between procedural and interactional justice, indicating that they present differential correlations with criterion variables (see Cropanzano et al., 2001). Some authors even refined the structure of organizational justice by proposing a four-factor model (Greenberg, 1993). Greenberg indicated that interactional justice could be divided into two justice dimensions: interpersonal and informational justice. Interpersonal justice describes the quality of the treatment (e.g., dignity), whereas informational justice refers to the information provided (e.g., the degree to which decisions are explained and justified). Relevant empirical evidence supported the four-factor model by demonstrating that individuals are able to distinguish among the four justice dimensions (Colquitt, 2001) and by observing that each dimension has a different nomological status (Colquitt, Conlon, Wesson, Porter, & Ng, 2001).

The differentiation between specific dimensions is still persistent in the literature (e.g., Johnson, Lanaj, & Barnes, 2014). However, an increasing number of scholars question whether using the different facets exclusively is beneficial to improving knowledge, and they also propose the consideration of overall justice (e.g., Lind, 2001). Ambrose and Schminke (2007) indicated that overall justice offers a better representation of the way individuals perceive justice than discrete facets do. It helps to evaluate the total effect of justice on outcomes, and it provides a more parsimonious approach to justice. These researchers also argued that although workers differentiate between different dimensions of justice, the overall justice perception is the direct driver of final reactions. Ambrose and Schminke (2009) confirmed this argument by testing the mediating role of overall justice in the relation between specific justice dimensions (distributive, procedural, and interactional) and employee attitudes.

One way to deal with this debate about justice dimensions vs. overall justice is to explore the connection between justice and outcomes and the extent to which justice dimensions differ in their predictive power. In the first meta-analysis about organizational justice, Colquitt et al. (2001) did not confirm the predominance of only one justice dimension (e.g., distributive justice) over the rest of the justice facets in predicting several relevant outcomes (e.g., job satisfaction, organizational commitment, evaluation of authority, organizational citizenship behavior, withdrawal, performance). By contrast, their findings partially supported the two-factor model. Distributive justice showed stronger relationships with some personal-referenced outcomes (e.g., outcome satisfaction) than procedural justice did, while procedural justice had stronger links to several system-referenced outcomes (e.g., organizational commitment) than distributive justice. Colquitt et al. (2001) also observed that interpersonal or informational justice predominates (due to its interpersonal character) over procedural justice in predicting agent-referenced outcomes (e.g., citizenship behaviors directed at the supervisor). In a more recent meta-analysis, Colquitt et al. (2013) proposed two routes from justice dimensions (distributive, procedural, interpersonal, and informational) to performance and citizenship behaviors. Based on social exchange theory and a cognitive approach to human behavior, in the first route, the effects to justice dimensions were channeled through several indicators of social exchange quality (trust, organizational commitment, perceived organizational support, and leader-member exchange). By contrast, the second route establishes state affect (positive and negative) as the mediator between justice dimensions and outcomes. The authors found partial empirical support for these two routes.

Thus, the investigation of individuals’ justice experiences has mainly been characterized by exploring the dimensionality of justice, the analysis of the role of overall justice in understanding individual interpretations of justice and their consequences, and the differential effects of justice dimensions on relevant outcomes (performance, commitment, etc.). To some extent, this research at the individual level has inspired the efforts at the team level.

The Birth and Early Stages of Justice at the Team-Level

During the past 15 years, and parallel to the investigation of the individual-level construct, research on team-level justice has strongly emerged (e.g., Rupp, Bashshur, & Liao, 2007). Although there are antecedents (Mossholder, Bennett, & Martin, 1998), the seminal effort to delimitate team justice has been attributed to Naumann and Bennet (2000). These authors focused on the well-established procedural justice dimension in introducing the concept of justice climate. More specifically, they defined procedural justice climate as “a distinct group-level cognition about how a work group as a whole is treated” (Naumann & Bennet, 2000, p. 882). From that time on, many research papers have taken the team level into consideration. This is based on the idea that justice is associated with a collective identity beyond the individual. In fact, fairness positively affects the activation of interdependent identity (Johnson & Lord, 2010). In their recent review, Li et al. (2015) identified 46 relevant papers that used justice climate as a construct beyond the individual level. Of them, 21 referred to the team (or work group) level explicitly, while 17 additional studies considered a conceptually close level (department, work-unit, etc.). Other levels of construct and analysis (e.g., organization as a whole, alliances) have been used infrequently. Focusing on papers reviewed by Li et al. (2015) that used justice at the team or similar levels (work-group, work-unit, department, etc.), 30 of them considered procedural justice, 11 assessed interactional justice or some of its specific facets (interpersonal and/or informational justice), 8 evaluated distributive justice, and 4 recent papers used some version of overall justice. According to this analysis, we can conclude that research on justice in teams has considered procedural justice to be the critical dimension, given the connection between this justice dimension and the particularities of teams. According to the relational model (Lind & Tyler, 1988), team members are very sensitive to the procedural treatment they receive as a team because the group satisfies identity needs and develops norms about fairness. Consequently, unfair procedural treatment directed toward any member of the team is also considered an offense to the team as a whole (Tyler & Lind, 1992). Roberson and Colquitt (2005) also considered that procedural justice is the most influential dimension in the emergence of justice at the team level, due to its visibility and the common existence of formal procedural practices across teams. Despite the predominance of procedural justice, other justice dimensions have also been considered in the investigation of team-level justice, and statistical analyses related to data aggregation revealed that teams are able to share perceptions about distributive (e.g., Moliner et al., 2005, pp. 105–106), interactional (e.g., Spell & Arnold, 2007, pp. 735–736), and overall (Priesemuth, Arnaud, & Schminke, 2013, p. 241) justice. The construction of justice climate can emerge across justice dimensions through different mechanisms. For example, social interaction and exchange of information among team members can occur in different types of justice events—including distribution of resources, procedures, and interpersonal treatment received by the supervisor/manager—facilitating a shared view of different justice dimensions (see Spell & Arnold, 2007). Approaches to understanding the emergence of justice at the team level are discussed later.

Therefore, the use of the team level plays a main role in the current justice research, coinciding with the generalization of groups in organizations. Research efforts have followed two main directions. First, scholars have elaborated theoretical arguments and found empirical evidence to understand how shared perceptions of justice emerge at the team level. Second, research has explored the impact of team-level justice on relevant outcomes.

Regarding theoretical foundations, justice at the team level is clearly linked to the long research tradition on organizational climate. During the first decades of the 20th century, Kurt Lewin and colleagues investigated the impact of social climates or atmospheres—introducing different kinds of leadership—on behaviors and attitudes of team members (Lewin, Lippitt, & White, 1939). They assumed an interactionist approach to human behavior, where both the person and the situation are simultaneously considered. Building on this contribution by Lewin and colleagues, the climate concept was introduced into organizational psychology. The influential review by James and Jones (1974) facilitated this incorporation of the climate concept into the research agenda. These scholars distinguished between objective characteristics of the organizational context and interpretations people make of that context. Objective characteristics were considered as independent variables with significant consequences for worker perceptions. Accordingly, a top-down investigation was carried out, with worker interpretations mediating the relationship between objective contexts and individual-level outcomes (see Kozlowski & Klein, 2000). James and Jones also recommended differentiating between “climate regarded as an organizational attribute and climate regarded as an individual attribute” (James & Jones, 1974, p. 1108). This suggestion has had a strong influence on climate research in teams and organizations. Following the proposal by James and Jones, an increasing number of scholars have investigated the existence of homogeneity among organizational members in their climate perceptions, describing an emergent property of teams and organizations beyond the individual level (see Ostroff, Kinicki, & Tamkins, 2003).

In addition, one of the relevant advances in climate research has been the proposal of specific climates. In the early stages of climate research, scholars concentrated their efforts on molar dimensions. Over time, however, researchers have introduced several different specific climates associated with organizational or team goals (e.g., service, safety, innovation). As Schneider, Wheeler, and Cox (1992) indicated, “strategically focused climate measures produce stronger relationships with specific organizational outcomes than less-focused measures” (p. 705). A specific climate emerges because the topic in question is relevant to the organization or the team (Dietz, Pugh, & Wiley, 2004). Therefore, different specific climates can exist in the organization simultaneously (Martínez-Tur, Tordera, Peiró, & Potocnik, 2011; Schneider, White, & Paul, 1998). With this in mind, Naumann and Bennet (2000, p. 882) tested the existence of justice climate as a new specific climate, focusing on the procedural justice dimension. To do so, they used the three mechanisms proposed by Schneider and Reichers (1983) to understand the creation of climates: (a) the symbolic interaction approach; (b) the attraction/selection/attrition (ASA) model; and (c) the structuralist approach.

The symbolic interaction approach argues that the team creates the ideal context for the emergence of shared views. Members pertaining to a specific team have more opportunities for social interaction with each other than with members of other teams. This social interaction allows members of a team to develop similar interpretations of organizational life. Naumann and Bennet (2000) used team cohesion to test this proposal because, in cohesive teams, members present high levels of interaction with each other and mutual influence. Naumann and Bennet (2000) confirmed this hypothesis, observing that cohesion is positively and significantly related to the level of agreement on procedural justice within teams. Other quite similar arguments and approaches have also been considered to support the existence of justice climate, also focusing on the exchange of information and experiences. Degoey (2000) referred to cognitive and emotional contagion processes, where social interaction again plays a critical role. When information is ambiguous and emotionally charged, members of the same team tend to interact and exchange information in order to reduce the ambiguity by creating a shared interpretation among team members. Whitman, Caleo, Carpenter, Horner, and Bernerth (2012) and Li et al. (2015) used social information processing (SIP) to argue that workers from the same team or unit level discuss justice events, facilitating agreement in their interpretations. Roberson (2006) argued that teams activate sense-making in the creation of justice climate. Sense-making “is a process of social construction in which individuals interpret and explain their experiences, which become rationalized and objectified, thereby influencing individuals’ view of reality” (Roberson, 2006, p. 178). Because it is not easy to access objective information, the sense-making process helps team members to exchange information and create a consensual view of justice. Whitman et al. (2012), based on fairness heuristic theory (FHT), interpreted this sense-making process as a collective heuristic (or shortcut), where team members search for justice signals through interaction, allowing a shared interpretation of authorities’ behavior. Despite the different labels and perspectives, the final argument of all these approaches is similar: team members are motivated to discuss organizational life, including justice, and in doing so they create consensus about justice. Roberson (2006) found empirical evidence supporting this proposal. Teams that participated in discussions about their collective experiences and extended this discussion over time presented high agreement about procedural and distributive justice dimensions.

The ASA model (Schneider, 1987; Schneider, Goldstein, & Smith, 1995) can be summarized as the following process: workers are attracted to others who have similar physical characteristics, personality traits, education level, etc.; selection processes in organizations also tend to incorporate people with similar characteristics; and workers who do not fit the predominant profile are more likely to try to leave the organization. Subsequently, the model predicts that teams evolve toward homogeneity over time. Therefore, it is reasonable to expect that when teams are composed of similar members, shared justice perceptions are likely to emerge. Naumann and Bennet (2000) predicted that (un)fair events directed toward similar peers can be extended to the other team members, creating consensual views about (in)justice. Degoey (2000) suggested that people are more willing to share information and experiences about justice with colleagues who are similar, facilitating similar perceptions. Colquitt, Noe, and Jackson (2002) argued that diversity in teams increases internal discrepancies in the perception, interpretation, and evaluation of reality, including justice events. Empirical evidence supporting the expected positive relationship between homogeneity and shared perceptions of justice at the team level is mixed (Colquitt et al., 2002; Naumann & Bennet, 2000). Thus, it is likely that third factors play a role in the way homogeneity/heterogeneity impacts shared perceptions of justice. For example, socialization can be a successful organizational strategy to create similar mental models (see Li et al., 2015), reducing the effects of diversity on justice climate, even in heterogeneous groups.

The structuralist approach has received less attention than symbolic interaction approaches and the ASA model. According to structuralism (Schneider & Reichers, 1983), the mere exposure to similar policies, practices, and procedures facilitates shared climates because recipients are subjected to the same stimuli. Naumann and Bennet (2000) transferred this argument to the emergence of procedural justice climate. They assumed that supervisors are climate engineers. If supervisors are visible in implementing policies and delivering justice, uniformity in procedural justice perceptions among team members is likely to increase. Naumann and Bennet confirmed this hypothesis: supervisors’ visibility in managing the team was positively related to team members’ agreement in terms of procedural justice.

All these theoretical approaches (symbolic interaction, contagion, SIP, FHT, ASA, and structuralism) suggest that the creation of justice climate at the team level can follow different routes: interaction and exchange of information and experiences among team members; uniform composition of the team; and exposure to similar stimuli in organizations. These theoretical proposals and empirical evidence were necessary prerequisites to taking further steps. Once the existence of justice at the team level was confirmed as an emergent property beyond individual differences, relationships between justice climate in teams and other variables could be investigated. Whitman et al. (2012) carried out a meta-analysis that helps to understand the impact of justice climate on a number of outcomes. In general, they found moderate-to-substantial relations with four criteria that are relevant in team effectiveness: attitudes (e.g., satisfaction, commitment); processes (e.g., citizenship behaviors, cooperation); withdrawal (e.g., absenteeism, turnover intentions); and performance (e.g., customer satisfaction, financial performance). The magnitude of these relationships is higher when the level of the referent (in the formulation of items) is collective—“we”—compared to the individual referent in items—“I”—and when the level of analysis is the team (as opposed to the organization as a whole). Whitman et al. (2012) also observed that distributive justice at the team level has the strongest relation with performance, while interactional justice has the strongest link to processes. These differential results allowed them to propose that instrumental vs. relational motives have a role in the impact of team-level justice on outcomes. The instrumental model proposes that people value justice as a way to achieve economic and material benefits (Thibaut & Walker, 1975). Accordingly, high distributive justice at the team level stimulates the combined effort of team members, maximizing team performance and achieving rewards, which explains the strong association between distributive justice and performance at the team level. By contrast, Whitman et al. (2012, p. 784) attributed the strong relationship between interactional justice at the team level and processes (e.g., citizenship behaviors) to relational motives. When supervisors/managers treat team members adequately, teams are motivated to display helping behaviors and cooperation.

Regarding interactive results, Li et al. (2015) concluded in their review that justice at the team level interacts with environmental and employee personality variables in predicting outcomes. In addition, they observed that the literature, based on the individual level, connects justice climate to leadership and organizational changes. A few papers have tested the link from servant, ethical, and transformational leadership to justice at the team level. Leaders focusing on follower development (servant leadership) and the ability to inspire the followers to contribute to the organization’s mission (transformational leadership) increase procedural justice at the team level, whereas ethical leaders increase interactional justice in teams. Li et al. (2015) also analyzed some research studies about change process fairness, a team-level construct that describes the fairness of change processes in organizations. In general, findings indicate that, under some circumstances, the fairness of change processes helps to understand changes and how they are interpreted within the organization.

In sum, during the past decade researchers have introduced the concept of justice climate, and the team level has had a prominent status. Interestingly, theoretical arguments and statistical findings have supported the existence of an emergent reality beyond individual perceptions. In addition, the connection between justice at the team level and critical outcomes and processes has legitimated justice in teams as a relevant construct.

The Parallelism Between Individual and Team Levels

Many research studies on justice in teams have assumed an isomorphic structure across levels and analogous relationships with outcomes at both individual and team levels. This general picture describes a parallelism between the individual and team levels in the investigation of justice, where scholars’ concerns and responses have been very similar, despite studying different levels of construct. This parallelism is summarized in different aspects below.

  • The interest of researchers in the dimensionality of justice has been transferred from the individual to the team level. Although the research in teams began with procedural justice (Naumann & Bennet, 2000) and this dimension remains predominant, the literature about justice at the team level has progressively incorporated the other dimensions. Several theoretical models (symbolic interaction, contagion, SIP, FHT, ASA, and structuralism) make it possible to support the existence of identical justice dimensions across levels, creating an isomorphic perspective where the dimensionality of justice at the individual level is transferred to the team level. Even the concern for overall justice, initiated at the individual level, was recently transferred to the team level (e.g., Priesemuth et al., 2013).

  • This parallelism can also be observed in the prediction of outcomes, comparing the meta-analysis by Colquitt et al. (2001) at the individual level and the meta-analysis by Whitman et al. (2012) about justice climate. The magnitudes of the relationships between justice and relevant outcomes were similar at the individual and team levels: “the patterns of the relationships at the unit level appear to be either similar or slightly greater in magnitude than the individual-level relations” (Whitman et al., 2012, p. 784). In addition, Whitman et al. (2012) also observed parallelisms with the individual level in the differential relations between justice dimensions and outcomes, supporting the two-factor model: “These findings are in line with individual-level research (e.g., Colquitt, 2001) … that has suggested that instrumental and relational motives play a role in the different construct relations” (p. 784). Thus, scholars explore analogous relationships with outcomes for justice at the individual level and justice at the team level.

  • Most of the papers about justice in teams use the traditional sources of justice existing in research studies at the individual level. Thus, measures in papers ask team members about their perceptions of the degree to which an external authority—usually the supervisor/manager or the organization as a whole—treats the team adequately (e.g., Moliner et al., 2005).

  • The parallelism is again present in the investigation of leadership as a relevant antecedent of justice. The tradition at the individual level (e.g., Pillai, Scandura, & Williams, 1999) was transferred to the first research studies on leadership as a predictor of collective justice (see Ehrhart, 2004, for research at the department level).

  • Scholars also transferred the study of the role of justice in organizational changes from the individual to the team level (see Li et al., 2015, p. 146). More specifically, the investigation of procedural justice in organizational changes at the individual level (e.g., Brockner et al., 1994) has been translated into the team-level construct called change process fairness climate (Caldwell, Herold, & Fedor, 2004; Herold, Fedor, & Caldwell, 2007) to understand worker reactions to organizational changes.

This parallelism between the individual and team levels is logical. Scholars have used the individual level as a successful model from which to build the concept of justice at the team level. Additionally, justice at the team level is able to predict worker behaviors after controlling for justice at the individual level (e.g., Naumann & Bennet, 2000). Thus, the predictive power has increased with the incorporation of justice at the team level. Nevertheless, future research can produce qualitative changes by considering what is unique about or specific to teams.

Particularities of Justice at the Team Level: Implications for Future Research

Research may benefit from the consideration of particularities of justice in teams that are not present at the individual level. Some research efforts have focused on these particularities, showing new ways to make contributions to the existing knowledge. Accordingly, two promising areas of research are proposed: (a) faultlines and subgrouping and (b) intergroup justice.

Beyond Justice Climate Strength: Faultlines and Subgrouping in Teams

One exciting research area in team-level justice is justice climate strength. Whereas justice climate refers to the level of justice perceived by a team, justice climate strength describes the level of agreement within the team with regard to the treatment team members receive. Again, Naumann and Bennet (2000) were responsible for introducing this concept in the justice literature. Some scholars have focused on factors that explain strength (agreement). As mentioned above, all these efforts (e.g., Colquitt et al., 2002; Naumann & Bennet, 2000; Roberson, 2006) helped to establish justice at the team level as a construct with an independent status. It was assumed that teams were subjected to circumstances (e.g., information exchange) that facilitated agreement. Thus, it can be concluded that climate at the team level exists as an emergent property beyond individuals.

Other scholars have been interested in examining the role of justice climate strength in models for predicting justice outcomes. Some studies have explored the mediating role of justice climate strength in the relationship between leadership and outcomes (e.g., Ogunfowora, 2013). It was assumed that leaders would have an influence on justice climate strength (e.g., through variability in their behaviors) that could be translated, in turn, into outcomes. Strength has also been considered as a moderator. Colquitt et al. (2002) observed that relationships between the justice climate level and outcomes (absenteeism and team performance) were stronger in teams with high justice agreement. They interpreted this effect of strength according to the fairness heuristic (shortcut). When strength is high, the heuristic is shared among members and the justice climate level is automatically translated into outcomes. By contrast, in teams where strength is low, members have to reconcile perspectives, and this reduces the effects of justice climate on outcomes. Similarly, based on the situational strength concept, Moliner et al. (2005) proposed that agreement increases consistency in affective responses, influencing the predictability of units’ average burnout. They confirmed that the link from interactional justice climate to team exhaustion is higher for high interactional justice strength than for low interactional justice strength.

High or low strength is a particularity of teams that contribute to knowledge, avoiding the parallelism with the individual level. However, behavior within teams is complex and cannot be limited to the level and strength of justice climate. For example, different subgroups can exist within the same team. Since the first scientific studies on organizational theory, this phenomenon has been identified and described (e.g., Henderson & Mayo, 1936, pp. 407–408). The shift toward team-based structures in organizations may facilitate shared perceptions within numerous teams, but, paradoxically, this shift toward teams also provides an opportunity to observe their complexity and the difficulty, in many cases, of conceiving of the team members as part of a single group. Changes related to workforce mobility, globalization, and the specialization of team members are factors that may be increasing diversity within teams, creating adequate conditions for subgrouping (Meyer et al., 2014). The incorporation of virtual technologies in teams also has an influence. Electronic communication allows instantaneous exchanges among team members across time and space, but it reduces their direct and shared experiences (Jarvenpaa, Knoll, & Leidner, 1998). The generalized use of teams, combined with high levels of diversity and the use of information and communication technologies, creates conditions for subgrouping within teams because of faultlines. Although the faultline concept comes from geography (intersection between two tectonic plates), Lau and Murnighan (1998) adapted it to the study of teams. Thus, they referred to faultlines as “hypothetical dividing lines that may split a group into subgroups based on one or more attributes” (Lau & Murnighan, 1998, p. 328).

An increasing number of scholars are interested in faultlines and the subgrouping phenomenon. Although some research studies have created subgroups through experimental conditions in the lab (Rico, Sánchez-Manzanares, Antino, & Lau, 2012), most efforts have been conducted in the field. Research increasingly explores multiples characteristics or attributes of teams simultaneously in understanding faultlines (e.g., Thatcher, Jehn, & Zanutto, 2003) rather than evaluating just one demographic characteristic. In addition, there are different measures of faultlines to diagnose the potential existence of subgroups in a real context (Meyer et al., 2014). Using a measure or another depends on the research question. For example, the Fau measure (Thatcher et al., 2003) of faultlines assumes the existence of two well-differentiated subgroups, while the ASW measure (Meyer & Glenz, 2013) helps to detect multiple subgroups.

Some researchers have analyzed factors that can explain the existence of faultlines and subgroups within teams. In their review, Roberson and Colquitt (2005) referred to member diversity, leader-member exchange (LMX), and dispersion. Member diversity usually reduces communication in teams, and communication between dissimilar team members tends to be infrequent, not reciprocated, and weak. Diversity can also facilitate differentiated functions and roles within teams, hindering communication between members with different statuses and facilitating subgrouping. In line with the LMX theory, leaders distribute resources according to the contribution of each team member. High- vs. low-quality relations between the leader and team members can create subgroups (e.g., core vs. peripheral team members). Finally, dispersion also facilitates the emergence of subgroups because the physical proximity that allows formal and spontaneous interaction is limited within the team. Other research efforts have focused on understanding the effects of faultlines and subgroups. In general, a detrimental impact of faultlines on team-level outcomes (performance, satisfaction, etc.) is observed, and it is accentuated if team members actively perceive the faultline (see Thatcher & Patel, 2011, 2012, for meta-analyses). The main theoretical argument used to understand the negative effects of faultlines is related to categorization and social identity approaches. Each group within the team perceives the members of other groups as pertaining to a different social category, hindering the necessary cooperation, especially if the categories are salient for team members (Thatcher & Patel, 2011). In line with this argument, González-Roma and Hernández (2014) observed that subgrouping in a team climate of support from the organization increases team conflict and reduces communication quality within teams, after controlling for climate level and climate strength. Faultlines and climate strength are different—although related—concepts. Strength assumes uniformity, reflecting variability in agreement within the team. In contrast, faultlines assume non-uniformity, describing the existence of different sub-groups within the team (see González-Roma & Hernández, 2014, p. 1044). Regarding justice, research is at the starting point. Bezrukova, Spell, and Perry (2011) investigated the influence of faultlines on coping with injustice. Spell, Bezrukova, Haar, and Spell (2011) found, using a sample from 42 teams, that faultlines moderated the relationships between distributive justice, task conflict, and role conflict.

The investigation of faultlines and subgrouping in teams offers additional relevant input to future research on justice at the team level in at least two ways. First, the adequate identification and assessment of faultlines within teams, based on justice perceptions, is a necessary step. Fortunately, in other research areas, scholars have developed different algorithms and guidelines for choosing the right measure combination (Meyer et al., 2014). These efforts can facilitate an optimal starting point for the identification of faultlines associated with justice perceptions. Second, there are theoretical arguments to propose and test models where faultlines and subgrouping play a role (Roberson & Colquitt, 2005). For example, differential or asymmetrical LMX can produce subgroups based on justice interpretations that, in turn, influence team effectiveness. This type of research can contribute to the knowledge by considering unique aspects of teams.

Beyond Peer Justice: Inter-Group Justice

As mentioned above, most papers about justice in teams have followed the literature at the individual level to define sources of justice (see Li et al., 2015). For this reason, the typical source of justice considered in team-level justice is an external authority (supervisors/managers and the organization as a whole). However, Cropanzano and colleagues initiated the study of an aspect that is specific to and significant for groups: peer justice. Instead of looking for the source of justice in an external authority, they focused on the nature of teams by investigating how team members who cooperate in the achievement of common goals treat each other. In fact, they defined peer justice as a “shared perception regarding how individuals who work together within the same unit and who do not have formal authority over each other judge the fairness with which they treat one another” (Cropanzano, Li, & Benson, 2011, p. 568). In this first empirical study of this topic, they validated the peer justice construct and found two mediating effects. First, peer justice is related to citizenship behaviors via interpersonal team processes (cohesion, efforts, and interpersonal support in the team). Second, peer justice is associated with team performance through communication, coordination, and contribution of team members. The main contribution of a second empirical study (Li, Cropanzano, & Bagger, 2013) was structural. These authors found that the best way to represent peer justice (and justice climate) is through a hierarchical two-level model. The first-order factors were the three typical justice dimensions (distributive, procedural, and interactional), whereas the second-order factor was overall justice. Recently, Molina et al. (2015) investigated peer justice and justice climate in a cross-level relationship between teams and customers in the health care industry. They observed that both justice climate and peer justice are related to customers’ quality of life through service quality delivered by teams. However, two different routes were identified. Justice climate improved customers’ quality of life through functional service quality (efficiency of the team in delivering the core service), whereas peer justice followed a relational service quality route (emotional benefits above and beyond the core service).

Although research on peer justice is in its infancy, it makes it possible to study aspects that are genuinely associated with the internal life of teams and can stimulate future initiatives in research. The continuity in the study of peer justice will provide advances in justice research, but future research can also make significant progress by questioning the universality of certain principles underlying peer justice research. Peer justice assumes a shared perception among team members about how they treat one other, with variability in the agreement in terms of strength. However, this uniformity is not universal in teams. The identification of faultlines and subgroups within the team (González-Roma & Hernández, 2014; Thatcher & Patel, 2011) forces us to consider non-uniform realities where different subgroups and significant faultlines exist. Peer justice also assumes that teammates do not have formal authority over each other. Nevertheless, faultlines provide an informal structure (Lau & Murnighan, 2005), and the existence of subgroups can also describe informal differences in the status of team members (Roberson & Colquitt, 2005). Taken together, these perspectives about teams stimulate the study of the subgroup as a source of justice and the focus on intergroup justice within the team. At least two relevant topics can be investigated. First, future research could study the quality of the relationships among subgroups (fair, unfair, and neutral)—considered as a relational property—and their antecedents and effects. For example, a previous history of offenses can create a negative spiral affecting the quality of relationships between subgroups that translates into mutual unfair treatment between the parties. Second, interesting asymmetries can be investigated in the way subgroups treat one another. For instance, differences in roles and status are not only precursors of subgrouping (Roberson & Colquitt, 2005), but they could also produce power asymmetry and differential perceptions about the treatment each subgroup receives from the other subgroups in the team.


During the past 15 years, research has produced relevant contributions to understanding justice at the team level. This construct has achieved an independent status in the literature, and scholars have studied its dimensionality and clarified some of its connections with antecedents and outcomes. This progress has been inspired largely by research conducted at the individual level. It is reasonable to expect that this parallelism between the individual and team levels will remain. However, there is also a growing interest in aspects that are unique to teams, with the potential to promote a qualitative change that distinguishes justice in teams from the individual approach. Contributions to knowledge about justice in teams can follow different routes. One of them would be the interrelations with the individual level, but another fruitful path would be to focus the research on the particularities of teams.

Further Reading

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