Abstract
Teams are an important part of most organizations. As such, it is necessary that organizational leaders make a number of decisions regarding how to pay teams. In this article, prominent themes in the teams literature and the pay-for-performance literature are integrated to develop a framework of team pay-for-performance effectiveness. Using this framework as a guide, the literature on team pay-for-performance is reviewed. Important dimensions of the team pay-for-performance construct are identified, and mediating paths between these dimensions and team outcomes are clarified. This integration leads to identification and discussion of valuable areas for future work.
Keywords
Teams are a way of life in many modern organizations. Fifteen years ago, 67% of human resource (HR) professionals considered teams to be important in their organizations (McClurg, 2001), and the figure has likely increased in the interim. We have known for more than half a century that team dynamics are critical (Cartwright & Zander, 1968) but recent research has addressed this issue with renewed energy (Mathieu, Maynard, Rapp, & Gilson, 2008; Mathieu, Tannenbaum, Donsbach, & Alliger, 2014). Research has focused on many aspects of team dynamics but has devoted only sporadic attention to a fundamental aspect of team functioning, that is, how team members are paid. A recent meta-analysis (Garbers & Konradt, 2014), for example, uncovered only 30 studies on team pay-for-performance (PFP), and of these, an overwhelming majority were conducted in laboratory settings and/or using student populations. Thus, we know little about how best to pay team members to maximize team effectiveness. This is despite the existence of a robust literature on teams and a robust literature on compensation. In this article, we begin to bridge this gap by offering a theoretical integration of the two fields.
The Garbers and Konradt (2014) meta-analysis is a useful starting point for this endeavor. The study demonstrated a strong positive relationship between the use of PFP and performance in team contexts (g = 0.45). PFP had a stronger effect when equitable rather than equal allocations were made, when teams were smaller, and in teams with gender-based heterogeneity. These results are encouraging, but they raise more questions than they answer. In fact, many of the empirical relationships reported were in contrast to the hypothesized relationships. For example, PFP effectiveness in teams was predicted to be weaker when tasks were more complex, but the meta-analysis results indicated that more complex tasks were associated with greater PFP effectiveness. The meta-analysis also did not address many issues that team and compensation scholars have identified as critical, including aspects of PFP system design (e.g., intensity) and team dynamics (e.g., team motivational states). Finally, it is likely that a static view of teams yields different insights than a dynamic view. As Garbers and Konradt (2014) noted, the question of if PFP works for teams was addressed in their meta-analysis. If team PFP is to be used effectively, we must now address why it works.
In this article, we integrate the team literature and the compensation literature to develop a framework for understanding the mechanisms through which team PFP systems affect team processes and outcomes. This integration results in differentiation between PFP effects on team motivation and performance and PFP effects on team satisfaction and continued team membership. In addition, the proposed framework addresses short- and long-term effects of PFP on teams, taking into account both individual-level and team-level dynamics. We elucidate a framework that explains how teams may be changed by PFP design, helping explain why team PFP plans are not always sustainable despite positive short-term effects (Beer & Cannon, 2004).
This endeavor is important for a number of reasons. While there are recent reviews on PFP (e.g., Gerhart, Rynes, & Fulmer, 2009) and on teams (e.g., Mathieu et al., 2008), the last thorough, qualitative review of team PFP, to our knowledge, was conducted almost 20 years ago (DeMatteo Eby, & Sundstrom, 1998). In addition, team PFP is remarkably different from individual PFP, making theoretical integration particularly valuable. Team PFP has additional dimensions beyond those discussed in individual PFP research (e.g., interdependence), performance measurement for team PFP is more complicated (e.g., measures at both the individual and the team levels must be addressed), and unique team-level influences (e.g., ambient stimuli; Chen & Kanfer, 2006) and processes (e.g., motivational states and goal orientation) affect PFP in the team context. In sum, PFP in the context of teams must be differentiated from individual-level PFP. What is needed is an integration of the individual PFP and team literatures. Drawing on insights from both streams of research enables the development of a comprehensive framework for understanding team PFP as a free-standing phenomenon.
In this article, we develop an integrative team PFP effectiveness framework. We start by briefly reviewing the team and PFP literatures, focusing on issues of particular concern for team PFP. The next section presents a framework for explaining how and why team PFP affects outcomes, followed by empirical evidence bearing on the framework. The last section highlights the complexities implied in the proposed framework to elicit directions for future research.
Teams
Research uses both “group” and “team” to describe collectives in the workplace. For clarity, we primarily use the term “team.” Following the common usage, we view teams as (a) including two or more individuals, (b) having some level of interdependence, (c) sharing outcomes, and (d) being considered a defined social entity within the organization (Cohen & Bailey, 1997; Guzzo & Dickson, 1996). When describing non-interdependent collectives, we use the term “group.” We note that we concentrate on non-executive teams because the dynamics in executive teams can be quite different (e.g., Devers, Cannella, Reilly, & Yoder, 2007). In this brief overview of teams research, we focus on theory and findings, especially relevant to the development of a team PFP effectiveness framework.
Team Effectiveness Frameworks
A detailed team effectiveness framework was offered by Mathieu et al. (2008), which expanded on the well-known input → process → outcome model (e.g., McGrath, 1984; Steiner, 1972). In Mathieu et al.’s (2008) framework, inputs were nested, such that team members worked within a team. Intervening effects were subsumed under mediators, which included both processes and emergent states. Outcomes spanned multiple criteria, including behavioral and affective reactions at different levels. This framework included feedback loops, mainly between outcomes and mediators, such that outcomes affected future processes and emergent states.
Issues of team motivational dynamics were clarified by Chen and Kanfer’s (2006) framework of team motivation. This framework distinguished between two types of team inputs, that is, ambient and discretionary stimuli (Chen & Kanfer, 2006; Hackman, 1992). Discretionary stimuli operate primarily at the individual level, and “predispose individuals, but not teams, to behave in certain ways” (Chen & Kanfer, 2006, p. 253). They influence team-level processes through individual-level effects (Pearsall, Christian, & Ellis, 2010). Ambient stimuli, by contrast, operate primarily at the team level and affect both team-level and individual-level motivational processes (Chen & Kanfer, 2006). The authors also identified three primary components of team motivational processes—motivational states, goal generation, and goal striving—and described team motivation as occurring through interactive processes across levels.
Team membership dynamics were further clarified in research regarding team composition frameworks. Mathieu et al. (2014) summarized this research using four models of team membership. Specifically, the authors explained that team membership models vary on two dimensions—the approach to aggregation in the model (i.e., composition or compilation) and the focus of the model (i.e., individual or team). The ideal makeup and importance of individual-oriented ability/motivation versus team-oriented ability/motivation differed depending on the aggregation approach and the focus of the model. For instance, compositional membership models (i.e., individual contributions are aggregated to the team level) with individual focus were proposed to need individual members with high ability and motivation; team skills would be less relevant. Compilational models (i.e., individual contributions are aggregated in complex ways to understand the team level) with a team focus were proposed to need members with team skills; variation in other abilities and motivation would be expected and even desirable.
Interdependence
When individuals are working within groups, the nature of their dependence on one another is important in understanding the team and the use of team PFP (DeMatteo et al., 1998; Wageman & Baker, 1997). There are two main types of interdependence—reward/outcome interdependence and task interdependence (Van der Vegt, Emans, & Van de Vliert, 1998). Reward/outcome interdependence concerns the extent to which rewards (specifically pay, in the present context) are dependent on the accomplishments of team members. Reward interdependence is a central team PFP characteristic and is discussed later.
Task interdependence refers to the way the task is completed, how the work of individual members is combined to achieve an output, and how reliant each team member is on other team members in the completion of work. Types of interdependence range from low levels, that is, pooled, to high levels, that is, intensive (Tesluk, Mathieu, Zaccaro, & Marks, 1997). Pooled interdependence refers to nearly independent work and an additive product. Intensive task interdependence is the highest level of interdependence with the team’s output relying on complex intra-team interactions (e.g., problem solving). The membership issues discussed by Mathieu et al. (2014) are likely to be influenced by task interdependence.
PFP
The literature on PFP provides a solid foundation on which to build a framework of team PFP. Two primary themes in the PFP literature—construct clarity and theoretical foundations—are highlighted below.
Construct Clarity
PFP exists when pay is based on performance factors (Gerhart et al., 2009). This definition sounds simple but is actually somewhat complex when design and implementation characteristics of PFP plans are taken into account. In a thorough review of the compensation literature, Gerhart and Rynes (2003) focused on intensity (i.e., incentive pay as a proportion of total pay; Zenger & Marshall, 2000) and measurement of the performance criterion. In a review of the team rewards literature, DeMatteo et al. (1998) focused on three reward characteristics—size, frequency, and allocation procedures. We address these dimensions to ensure comprehensiveness. Size and intensity are similar in that they both focus on the amount of pay associated with performance. Frequency has received little attention and involves a trade-off with size of reward (discussed in more detail below). Thus, intensity, size, and frequency are reviewed together. We also discuss reward interdependence because it is a fundamental concept in teams research (Van der Vegt et al., 1998; Wageman & Baker, 1997). We note that specific team PFP dimensions contribute to overall reward interdependence. The dimensions are addressed below.
Intensity/frequency
PFP can vary in intensity. For instance, a plan can base most or all of pay on performance (as in a commission system), or it can base only a small portion on performance (as in most faculty annual merit raises). The intensity of a PFP plan can exist at the individual and the team levels. For instance, at the individual level, team PFP intensity would be the proportion of an individual’s total pay based on team performance; at the team level, team PFP intensity would be the proportion of the team’s total pay based on team performance.
PFP intensity can influence the strength of employee reactions. For example, Kepes, Delery, and Gupta (2009) reported that greater performance-based differentiation in compensation across employees was associated with higher workforce performance. In another study, PFP raises were perceived positively only when they were greater than 7% for college students engaged in a coding task (Mitra, Gupta, & Jenkins, 1997). That is, 7% was the “just noticeable difference” threshold for PFP raise intensity. Recent research suggests that below-threshold raises can have substantial disutility (Mitra, Jenkins, Gupta, & Shaw, 2015).
PFP plans can also vary in frequency, which refers to the rate at which individual payments are made. Reinforcement theories suggest that, to be motivating, individual payments should be made immediately following desired behaviors (Milkovich, Newman, & Gerhart, 2014). Studies on frequency of PFP payouts are especially difficult to find (DeMatteo et al., 1998), but the existing research suggests that frequency varies and is meaningful. For example, a study on salesperson bonus payout frequency reported that firms most often pay out on an annual basis, followed by quarterly, monthly, and semi-annually, in that order (Joseph & Kalwani, 1998). The same study noted that turnover rates were lower in firms that paid bonuses annually as compared with all other payout frequencies.
While PFP frequency should make rewards more visible (DeMatteo et al., 1998; Lawler, 1971), potentially increasing their motivational power, it may also be more expensive for firms to administer PFP payouts frequently (Joseph & Kalwani, 1998). In addition, in the resource-constrained environment of most firms, increasing PFP frequency often means decreasing PFP intensity and vice versa.
Performance measurement
By definition, PFP is based on performance, but what is performance? Performance measurement lies at the heart of PFP (Gerhart & Rynes, 2003; Rynes, Gerhart, & Parks, 2005), and both compensation and performance appraisal research emphasize distinctions in performance measurement, including (a) behavior or results based, (b) objective or subjective, (c) relative or absolute, and (d) individual, team, or organization level.
Results-based measures focus on outcomes (e.g., the number of articles published; Gerhart & Rynes, 2003; Gerhart et al., 2009). Behavior-based measures focus on processes and behaviors (e.g., coming to work on time or cooperating; Gerhart & Rynes, 2003; Gerhart et al., 2009). Objective performance measures are based on hard criteria (e.g., the number of cars sold), whereas subjective measures are based on subjective ratings of performance (Lazear & Oyer, 2013). Objective measures are usually more readily available for results than for behaviors, leading to conflation of the two dimensions. But objective measures could focus on behaviors (e.g., recorded number of absences) and subjective measures could focus on results (e.g., supervisor’s ratings of performance quantity).
These distinctions are important because the performance assessment literature demonstrates that results-based, objective measures tend to suffer from criterion deficiency (i.e., measures are available typically only for a limited set of criteria). Behavior-based, subjective measures tend to suffer from criterion contamination (i.e., they encompass extraneous factors, such as the supervisor’s liking of a subordinate; Cardy & Dobbins, 1986; Cleveland & Murphy, 1992; Lazear & Oyer, 2013). Criterion deficiency can lead to dysfunctional behaviors (Holtzen & Gupta, 2014; Kerr, 1995; Lawler & Rhode, 1976; Shaw & Gupta, 2015). For example, a focus on sales volume alone can lead employees to act as “vultures” and to ignore unrewarded tasks. Results-based measures can ignore machine breakdowns and other external factors beyond the employee’s control (Gerhart et al., 2009). Criterion contamination can lead to employees focusing on impression management and other behaviors that erode effective functioning (Holtzen & Gupta, 2014; Kerr, 1995; Lawler & Rhode, 1976; Shaw & Gupta, 2015).
The third performance measurement distinction concerns relative versus absolute measurement. Absolute measures assess performance against a standard (e.g., a score of 80 on a 100-point scale) and relative measures assess performance against that of other ratees (e.g., the highest-ranked student, the best employee, the highest performing team). The performance level of other ratees is relevant for relative measures but not for absolute measures (Aguinis, 2013).
The level at which performance is measured also varies (Gerhart et al., 2009). Pay can be based on the performance of individuals (Jenkins, Mitra, Gupta, & Shaw, 1998), teams (Garbers & Konradt, 2014), and/or organizations (e.g., profit sharing; Doucouliagos, 1995). Our focus is on team PFP, and we necessarily address team-level measurement, although measurement at other levels can also be relevant.
Allocation rules
Regardless of the level at which performance is measured, pay is ultimately allocated to individuals. When performance is measured at an aggregate level, rules for allocating pay to individuals must be developed (Conroy, Gupta, Shaw, & Park, 2014). The most prominent allocation rule categorization was developed by Leventhal (1976) and Deutsch (1975). Two pay allocations are prominent in work teams, equality (i.e., same for all) and equity (i.e., differentiated based on individual contribution). Because individual allocation is nested within teams, the effects of different allocation criteria must be considered.
Reward interdependence
The issue of reward interdependence was raised under the teams literature review. Reward interdependence maps onto the allocation rule and performance measurement dimensions (Garbers & Konradt, 2014). The lowest level of reward interdependence occurs when performance is measured at the individual level and pay is allocated at the individual level as well. Greater reward interdependence is observed when reward pools are determined by team performance, but individual pay is determined equitably across individual performance. The greatest reward interdependence occurs when performance is measured at the team level, and individual allocations are made equally, that is, only team performance is relevant. Garbers and Konradt (2014) reported stronger performance effects for individual allocations than for team-level equality allocations. Increasing intensity of team PFP also increases reward interdependence (Harrison, Price, Gavin, & Florey, 2002).
Theoretical Foundations
Compensation research distinguishes between two different mechanisms through which PFP influences outcomes—an incentive mechanism that motivates the behaviors that are rewarded, and a sorting mechanism that influences who is attracted to and retained by the pay system (Cadsby, Song, & Tapon, 2007; Dohmen & Falk, 2011; Gerhart & Rynes, 2003; Lazear, 2000; Trevor, Reilly, & Gerhart, 2012). Many individual-level theories explain these effects, of which two are especially applicable here.
Expectancy theory (Porter & Lawler, 1968; Vroom, 1964) is a robust theory for explaining the individual-level incentive effects of PFP plans (e.g., Conroy et al., 2014; Lawler, 1971). According to this theory, individuals are motivated by the combination of their perceptions of expectancy, instrumentality, and valence. PFP is most likely to be effective in motivating performance (i.e., having an incentive effect) when individuals believe that they can perform (i.e., high expectancy), performance will be rewarded (i.e., high instrumentality), and the rewards are desirable (i.e., high valence; for example, Bamberger & Belogolovsky, 2010; Lawler, 1971; Schwab, 1973; Van Eerde & Thierry, 1996).
Equity theory (Adams, 1965) explains perceptions of fairness and satisfaction and is useful in understanding sorting effects—satisfied members are more likely to stay with the organization or the team (Williams, McDaniel, & Nguyen, 2006). According to equity theory, people compare their own perceived outcome (e.g., pay)/input (e.g., performance, seniority) ratios with the outcome/input ratios of relevant others. To the extent that these ratios are equivalent, people feel fairly treated, are satisfied and less likely to exit (Williams et al., 2006).
PFP system design is expected to influence expectancy theory components (particularly instrumentality perceptions, for example, Bamberger & Belogolovsky, 2010), thereby exhibiting incentive effects. It is also expected to influence equity theory components, thereby exhibiting sorting effects (e.g., Bloom & Michel, 2002; Cadsby et al., 2007).
A Framework of Team PFP Effectiveness
The team PFP effectiveness framework presented in Figure 1 provides an integration of the Mathieu et al. (2008) framework with the input dimensions and theoretical incentive/sorting mechanisms identified in PFP research.
Team PFP effectiveness framework.
Inputs
Team PFP can act both as a discretionary and as an ambient stimulus (Chen & Kanfer, 2006), depending on its design. That is, team effectiveness is influenced by both individual-level and team-level effects of team PFP design. The major dimensions of team PFP were identified above—intensity, frequency, performance measurement, allocation, and reward interdependence. Inputs focus on these dimensions as applied to teams. From a practical perspective, intensity, frequency, performance measurement, and allocation are all decisions that must be made when a team PFP system is designed.
Team PFP is necessarily based on team performance. As noted, the performance appraisal literature is replete with the diverse criteria used to measure performance (Neely, Gregory, & Platts, 1995). The precise criteria used to measure team performance are important because they specify what is valued by the organization and what will be rewarded. In interpreting research results, then, it is important to remember that all performance measures are not equivalent. Furthermore, performance measurement is a multi-level concern in the context of team PFP. Team performance must be measured, and when equity allocations are used, individual performance must be measured.
We note that performance measurement (individual and/or team level), PFP intensity, and allocation determine reward interdependence (i.e., the “degree to which outcomes for individual members depend on outcomes for their team”; Harrison et al., 2002, p. 1033). In other words, reward interdependence involves the extent to which team members influence each other’s outcomes (Wageman & Baker, 1997). Some research isolates intensity, some isolates allocation, and some conflates them into a general reward interdependence. Because of the emphasis reward interdependence has received in prior work, we maintain a distinction here, including reward interdependence in the framework and reviewing work targeting questions of reward interdependence. Still, it is important to note that these dimensions are not entirely distinct.
Mediators
Drawing on the incentive and sorting effects described in the compensation literature, primary mediators of the team PFP and team performance relationship can be identified as performance behaviors based on incentive effects and membership based on sorting effects. Team PFP can be expected to affect the behaviors of members by motivating employees to perform at higher levels; it can also affect team composition by attracting and retaining certain kinds of employees.
Performance-related behaviors are expected to be influenced by motivational dynamics. At the individual level, expectancy theory explains how team PFP dimensions could influence motivation. For example, as intensity increases, valence of the pay outcome of performing is expected to increase, leading to higher motivation for individuals (Conroy et al., 2014; Gupta, Conroy, & Delery, 2012). Performance measurement and allocation affect behaviors because what is deemed “performance” in the expectancy equation will depend on what is measured and rewarded (e.g., if collaboration is rewarded, collaboration should increase). These effects should be particularly notable as PFP intensity increases, as PFP intensity will influence the valence of the outcome. Frequency can be expected to increase the visibility of the reward, strengthening expectancy theory perceptions and increasing effort as the reward gets closer (Asch, 1990; Lawler, 1971). Reward interdependence should affect the extent to which individuals are motivated toward team or individual performance. From the perspective of team motivation models (i.e., Chen & Kanfer, 2006), the motivational states, generation of and striving toward individual and team goals, will depend on the reward interdependence.
We propose that the team PFP input characteristics will influence the type of employees who are attracted to the organization (represented by the input → sorting arrow) and who choose to stay over time (represented by the outcome → sorting feedback loop; Schneider, Goldstein, & Smith, 1995). We focus on membership dimensions representing individual differences that have been particularly relevant in prior PFP and team research, specifically ability, team orientation, and entitlement (e.g., Fisk, 2010; Mathieu et al., 2014; McClurg, 2001).
An application of equity theory (Adams, 1965) clearly demonstrates that team PFP inputs will influence perceptions of fairness in the team. For example, intensity and frequency are likely to influence perceptions of outcomes, that is, how much is paid and how often; performance measurement and allocation rules are likely to influence perceptions of inputs, that is, what types of inputs are rewarded and whether distinctions are made across individuals in such rewards. As equity theory is perceptual, individual differences in perceptions of one’s own ability, team orientation, and entitlement can be expected to influence assessments of fairness regarding team PFP; this, in turn, should affect who remains with the team and, thus, the composition of the team. Sorting also influences incentive dynamics as higher ability should lead to higher expectancy (i.e., beliefs that effort will lead to performance; Lawler, 1971) in the motivational equation, team-oriented individuals may value team-focused behaviors, and feelings of entitlement could be related to lower levels of effort (Fisk, 2010).
Outcomes
Outcomes can be examined at the individual, team, and organizational levels. This article is focused on teams, and outcomes are examined at the team level. But team outcomes may result from an aggregation of individual outcomes (e.g., individual performance levels can be totaled to the team level), or they can occur at the team level (e.g., coordination among team members results in higher team-level performance). In addition, outcomes can be behavioral and attitudinal (Mathieu et al., 2008). For example, a team could have average performance but high morale. This distinction is important to the extent that morale influences future group membership and behaviors. Thus, both performance and attitudinal outcomes are included in Figure 1, as are feedback loops to performance behaviors and membership. We also note that a feedback loop from outcomes to inputs is included because team PFP input characteristics (e.g., measurement, intensity) can change over time as a result of prior performance episodes.
Team Context
The list of contextual variables that could influence an individual or a team is practically infinite. For brevity, we included one issue to illustrate contextual effects—task interdependence—because it is central to team PFP (DeMatteo et al., 1998). Task interdependence is representative of the level of reliance of team members on each other to complete work. The form of membership characteristics and aggregation and the most important behaviors for team PFP to be effective are likely to depend on task interdependence.
Empirical Support
Research on the effect of the initial introduction of team PFP has shown an increase in productivity ranging from 9% to 20% (Jones, Kalmi, & Kauhanen, 2010), but questions remain regarding how this effect occurs. This section summarizes the extant research in Figure 1. Our review is organized by input dimensions and mediating processes, enabling identification of the areas where sufficient research exists and the areas in dire need of further empirical work.
Team PFP Inputs → Incentive Dynamics → Outcomes
As shown in Figure 1, team PFP characteristics affect team motivational processes, and more specifically team motivational states, goal generation, and goal striving. They also affect individual motivational processes. These motivational processes then affect team outcomes.
Intensity/frequency
A few studies have clarified the motivational effects of PFP intensity. In an experimental study using undergraduate business students as subjects, Guthrie and Hollensbe (2004) reported that higher intensity team PFP (200% of base pay) resulted in student teams setting more difficult goals than did weaker intensity team PFP (50% of base pay). In addition, the high PFP intensity groups had higher goal commitment and team performance as compared with a fixed pay condition. Harrison et al. (2002) reported higher levels of collaboration in student teams as the percentage of the final course grade based on a team project increased. Shaw, Duffy, and Stark (2000) found that individual performance, measured as peer ratings, in student teams increased as the percentage of the individual’s course grade based on team performance increased. Scott and Tiessen (1999) studied a variety of organizations and reported higher team performance when team performance carried a greater weight in individual compensation. Taken together, these studies support the influence of intensity on team-level motivational dynamics.
Extrapolating the effects of PFP to a higher level, a positive relationship between group PFP intensity and firm performance was established in a sample of South Korean firms (Kim, Sutton, & Gong, 2013). This study was primarily at the firm level, such that group PFP intensity was operationalized as payments based on team, group, and company-level performance as a percentage of total base pay. Group PFP intensity was positively related to both objective and subjective firm performance measures, with employee empowerment moderating the effect. Increases in group PFP intensity were especially effective at influencing firm performance when team empowerment practices were in place (Kim et al., 2013). In essence, these results suggest that PFP intensity has a positive relationship with firm performance outcomes, at least partially through increased individual and team motivation.
Little empirical research could be located regarding team PFP frequency, but one particularly interesting study addressed team PFP frequency in the context of call centers (Liu & Batt, 2010). Frequency was measured based on worker reports of how often supervisors used group-based rewards, including cash and non-cash rewards. Frequency was related to improvements in an objective measure of individual performance (i.e., call handling times). In addition, group performance increased as rewards were more frequent along with increased coaching (Liu & Batt, 2010). It is possible that it is not frequency alone, but rather frequency interacting with other elements, such as team PFP intensity, that affects motivational processes. This issue is addressed further in a later section.
Performance measurement
Performance measurement distinctions are rarely discussed in the context of team PFP, as team research, especially in laboratory settings, has focused primarily on objective, results-based performance measures. For example, team performance has been measured as number of points earned (Barnes, Hollenbeck, Jundt, DeRue, & Harmon, 2011; Pearsall et al., 2010) and number of words created (Guthrie & Hollensbe, 2004). Field research has often used financial results as the performance measure (Kerrin & Oliver, 2002; Park & Kruse, 2014). By contrast, two field studies used behavioral measures—the extent of safety-based team PFP lowered workplace injuries in a study of 48 firms across multiple industries (Lauver, 2007) and the extent to which peer-appraised behavior measures determined rewards was positively related to individual and team performance in self-managed manufacturing teams (Stewart, Courtright, & Barrick, 2012).
One recent paper addressed multiple performance measurement issues within a group setting. Specifically, Belogolovsky and Bamberger (2014) placed individuals into workgroups that lacked task interdependence and manipulated subjective/objective and relative/absolute measurement of performance. The authors also manipulated pay openness/secrecy. When pay was secret and based on relative performance as compared with other group members, PFP perceptions, similar to instrumentality perceptions, were low. Furthermore, when pay was based on objective rather than subjective performance measures, PFP perceptions were positively related to individual performance. These findings suggest that within-group relative and subjective performance measures may be less effective for individual performance in groups. It does not tell us specifically about complex tasks as the task and its measurement were relatively concrete in a low task interdependence context.
Relative and absolute measurement in teams is a particularly interesting consideration when team PFP is used. When relative measures (e.g., forced distributions; McGregor, 2006) are used for individual employees, competition among employees is more likely, because to score well on the measure, the employee must outperform peers. This competition may be more functional when work is independent rather than interdependent. Certainly, when relative measures are used across teams, between-team competition and within-team cooperation are more likely (Bornstein, 2003). This issue also bears on PFP allocation practices. Equity allocations with relative measures may be particularly prone to dysfunctional competition such as sabotage within teams (Bose, Pal, & Sappington, 2010).
Research also suggests that team PFP performance measurement is an issue when feedback loops from outcomes to inputs are taken into account. As performance increases, the cost of payouts increases, and performance increases can lead to changing performance standards (Murphy, 2000). For example, in the Hewlett–Packard case described by Beer and Cannon (2004), managers changed performance standards when payouts from the plan were high. Managers felt that high payouts indicated that standards were set too low. In essence, over time, performance standards, at least in objective, results-based contexts, are likely to increase with successful performance of teams.
Changing standards may appear to make sense to continue to see improvement in performance through team goal setting and striving. However, research on performance standards in PFP contexts suggests that these adjustments may be biased. For example, Bol, Keune, Matsumura, and Shin (2010) reported that managers used discretion in setting sales performance targets for shipping stores and assigned easier targets to higher status store managers. Changes in the standards associated with a PFP plan can vary across teams and individual team members. These inconsistencies across time (changing standards) and across units (altering standards differently across teams and individuals) are likely to affect instrumentality perceptions negatively, weakening employee perceptions that performance will be rewarded over the long term.
A dynamic perspective, then, suggests that a team PFP plan may be successful initially at motivating team performance, but that this effect can erode as performance standards change, especially if changes are implemented inconsistently. Most of what we know about changing performance standards is based on objective and results-based plans. It would be particularly intriguing to isolate the performance measure for pay allocations (i.e., absolute/relative, subjective/objective, results/behavior) and study the effects of changes in these measures over time. McClurg (2001) reported that managers’ satisfaction with team rewards was weakened by the constant need to update the plans; it would behoove scholars to understand these updates.
It may be especially important that employees understand and commit to the team PFP system for it to be effective in motivating individuals and teams. This can occur by engaging employees in the performance measurement process. For example, Boning, Ichniowski, and Shaw (2007) reported that team PFP was especially likely to increase productivity in environments characterized by high complexity. Employees in this study participated in the development of the PFP system and performance targets. The increases in productivity were, at least partly, attributable to increases in flexibility and initiative among employees.
One lesson is clear—the specific performance measure that is used determines the kinds of behaviors displayed in teams. Thus, the design of a team PFP system must devote special attention to the specification of performance indicators on which PFP is based.
Allocation
This element refers to the extent to which team PFP is distributed to members equally versus equitably (i.e., based on individual contributions). Equally distributed PFP is more likely to serve as an ambient stimulus (Pearsall et al., 2010). Although equality-based distributions are sometimes advocated in team contexts (e.g., Pfeffer, 1998; Pfeffer & Langton, 1993), the Garbers and Konradt (2014) meta-analysis reported higher performance in teams when equity-based distributions were used compared with equality-based distributions. It is likely that the preferable distribution approach varies depending on other considerations.
Basic theories of motivation suggest that the equality/equity distinction is important for goal selection and goal-directed behavior. For example, it is reasonable to assume that team goals are more important under equality allocation; individual goals should be at least as important as team goals under equity allocation (DeMatteo et al., 1998; Kerr, 1995). This argument is supported by two studies that reported cooperation and helping were higher under equality than under equity allocation (Bamberger & Levi, 2009; Rack, Ellwart, Hertel, & Konradt, 2011).
As different allocations result in differential goal emphasis (team goals under equality, team and individual goals under equity), and as equality allocations promote cooperation (Rack et al., 2011), this research points to the superiority of each allocation rule depending on the relative importance of team versus individual goals and, by extension, task interdependence of the team context. For example, if the aggregation of individual contributions is sufficient to measure team performance (e.g., pooled interdependence), equity rules are certainly more likely to be conducive to team performance; if the aggregation of individual contributions is not sufficient and the focus is entirely team level (e.g., intensive interdependence), equality rules may be more conducive to team performance outcomes.
Research also suggests that the history of allocation complicates the effects of team PFP inputs. Johnson et al. (2006) reported the influence of pay based on individual performance versus based entirely on team performance (i.e., equality allocation). While this was not a pure test of team PFP because individual performance distributions did not involve a team performance component, the study does have interesting implications for understanding allocation effects as equity aligns more with an individual focus and equality more with a team focus. The authors found that when individual-focused allocations were switched to team-focused allocations, information sharing was lower, leading to lower performance (measured as accuracy), than when team-focused allocations were used without such history. This finding was later replicated (Beersma et al., 2009).
Reward interdependence
This factor concerns the extent to which members depend on the team for their rewards. It is generally accepted that alignment between team task interdependence and reward interdependence is important (DeMatteo et al., 1998; Wageman, 1995; Wageman & Baker, 1997). For example, in a field experiment conducted on a sample of service technicians, team performance was highest when there was alignment between task and reward interdependence at the extremes (i.e., pure individual or pure group interdependence; Wageman, 1995). Results of this study also indicated that work motivation was highest in individual reward conditions, speaking to the role of instrumentality in motivational processes. Wageman and Baker (1997) manipulated reward interdependence using three conditions—pay was based only on self-performance, pay was based on an equal weight of self- and partner-performance, and pay was based on self- and partner-performance with a heavier weight on self-performance. The highest performing pairs were those with high task and high reward interdependence; this finding supports the importance of alignment between reward and task interdependence.
More recent work focuses on specific behaviors that reward interdependence may encourage. In an experimental study of undergraduates, Johnson et al. (2006) reported an increase in information sharing under cooperative conditions (where winning teams won a cash prize) as compared with competitive conditions (where winning individuals won a cash prize, and it was almost impossible for members of the same team to win the prize). Knight, Durham, and Locke (2001) reported that under team incentives, subjects were more willing to take risks if goals were difficult. Other goal-striving behaviors have been shown to be encouraged by higher levels of reward interdependence, including helping (higher when pay was based entirely on team performance than when pay was based on a combination of individual and team performance; Barnes et al., 2011), peer monitoring (a group-based PFP plan compared with an individual PFP plan; Welbourne & Ferrante, 2008), and coordination (as described above for Johnson et al., 2006, cooperative conditions compared with competitive conditions; Beersma, Homan, Van Kleef, & De Dreu, 2013). With respect to performance outcomes, Beersma et al. (2003) reported that teams in cooperative reward conditions performed better in terms of accuracy, whereas teams in competitive reward conditions performed better in terms of speed.
In an experimental study of U.S. undergraduates, Blazovich (2013) examined differences in efforts exerted toward helping the team versus efforts exerted for oneself, depending on the pay structure. Individual effort improved in both individual PFP and team PFP with equality allocation conditions as compared with fixed payments, whereas team effort improved only in the team PFP condition. This study provides support for the influence of reward interdependence as an ambient influence on the team, affecting goal generation and striving processes. It is worth noting that the Blazovich (2013) study did not use actual cash for all participants; rather, participants earned points which were then used for a cash prize lottery. Those with more points had a greater chance of winning the prize. Furthermore, effort exertion was not real effort but an effort choice made by participants. Regardless, across multiple studies, the evidence is pretty clear that reward interdependence promotes team-focused goal-striving behaviors.
There is also research suggesting that reward interdependence can influence how teams handle diversity. In a study using an undergraduate sample, reward interdependence (increasing team PFP intensity with equality allocations) increased collaboration, which in turn mitigated the negative effects of surface-level diversity and accentuated the negative effects of deep-level diversity on team social integration (i.e., cohesion, satisfaction, and enjoyment of the team experience; Harrison et al., 2002). In the context of retail sales, Chan, Li, and Pierce (2014) reported that work ability heterogeneity was associated with positive performance outcomes in team-based pay contexts, but not in individual-based pay contexts. Taken together, this research supports the idea that team PFP, specifically reward interdependence, is effective at moving teams beyond at least surface-level differences.
Team PFP Inputs → Sorting Dynamics → Outcomes
In addition to motivational and behavioral effects, team PFP can affect team membership through the attraction and retention of different kinds of members. We review support for this mediating path here. There is little work isolating team PFP intensity and frequency. Thus, we review performance measurement, allocation, and reward interdependence.
Performance measurement
In terms of individual-level membership effects of PFP, research indicates that high-performing individuals working in groups are affected by the PFP measurement system. Belogolovsky and Bamberger (2014) reported an increase in intentions to continue among high performers when performance measurement was objective rather than subjective. This was related to high performer perceptions that pay was tied to performance (i.e., instrumentality perceptions). Similarly, Fong and Shaffer (2003) found better attitudes about group PFP when employees saw tighter connections between performance and pay.
In general, this suggests that team attitudes and effectiveness can be enhanced by systems with clear performance measurement. This effect may be attributable to perceptions of fairness in comparing equity ratios. In a field study of employees at a non-union production facility, Dulebohn and Martocchio (1998) reported that attitudinal outcomes were better when employees understood the team PFP system and believed it to be effective. Another study reported that, at the firm level, group and organizational PFP had a positive relationship with job satisfaction and organizational commitment; the relationship was strongest for firms with high levels of human capital (Park, 2012). Relating attitudinal effects to instrumentality perceptions, Guthrie (2000) reported a positive relationship between firm size and turnover among firms using collective PFP plans. He suggested that instrumentality perceptions were likely to be clearer in smaller rather than in larger teams (operationalized as firms).
At the team level, Bandiera, Barankay, and Rasul (2013) reported that when individuals had the power to choose their teams, introducing team tournament PFP schemes (i.e., PFP with only one team winning, such that relative team-level performance measurement determined rewards) led to workers entering teams that were similar in ability. Worker performance increased, with effects being driven by top performer productivity. This suggests that outcomes of team PFP may depend partially on performance measurement due to team sorting dynamics.
Allocation
Research suggests that the ability and team orientation of team members may be influenced by allocation rules. Kuhn and Yockey (2003) examined, among other things, preference for team versus individual PFP among undergraduates. As an equity-based distribution mimics individual PFP, in that the compensation for an employee is (at least partly) determined by individual performance, the Kuhn and Yockey (2003) study is informative regarding allocation rules and membership. Subjects reported the attractiveness of job postings with varied pay policies. The authors found that (a) subjects preferred PFP to fixed pay when pay was individually based rather than collectively based, but (b) collectively based PFP was more acceptable to subjects who preferred teamwork, and (c) subjects higher on self-efficacy preferred PFP if it was individually based or small team based. These results suggest that people with higher levels of self-efficacy prefer individual to team PFP, but that this effect can be ameliorated by team orientation.
People with stronger team orientation are more likely to be attracted to, and retained by, team PFP with equality distributions (DeMatteo et al., 1998). For example, Kirkman and Shapiro (2000) reported higher receptivity to team PFP among employees high in collectivism. Fong and Shaffer (2003) found employees in Hong Kong (a more collectivistic society) to be more satisfied with team PFP than employees in the United States (a more individualistic society). Equity-based allocations, which are more individually oriented, are preferred by individualistic people, and equality-based allocations by more team- or collectivistic-oriented people (Brewer & Gardner, 1996; Earley & Gibson, 1998; Kirkman & Shapiro, 2000; Shaw et al., 2000; Shaw, Duffy, & Stark, 2001).
In this context, the negative relationship between ability and team reward attitude (i.e., “an individual’s general evaluation of receiving rewards based on the performance of the team”; Shaw et al., 2001, p. 904) is interesting, as it indicates that people with lower ability (Shaw et al., 2001) and lower past performance (Haines & Taggar, 2006) score higher on team reward attitude. Presumably, high team performance requires members with both team orientation (Bell, 2007) and high ability (Schmidt & Hunter, 1998), but the negative relationship between these two individual differences suggests that finding such individuals may be challenging.
Reward interdependence
If a team PFP plan involves only a small part of an individual’s pay being based on team performance (low PFP intensity) and/or allocation being based on individual performance (equity allocation), those who dislike team PFP are unlikely to be affected substantially by the reward and less likely to be deterred from membership. But when a large part of an individual’s pay is based on team performance (high PFP intensity) and/or the allocation is equality based, much stronger membership effects can be expected. The studies discussed above (e.g., Kirkman & Shapiro, 2000; Kuhn & Yockey, 2003) provide evidence of the preferences individuals have across team and individual PFP plans.
The dynamic nature of the framework shown in Figure 1 implies that the effects of reward interdependence on team membership could be amplified over time. If a PFP plan is set up to be highly reward interdependent for only one “performance episode” (Marks, Mathieu, & Zaccaro, 2001; Mathieu & Button, 1992), team membership may change very little as a result. PFP plans set up to be highly reward interdependent for multiple performance episodes are more likely to have membership effects. Individuals who are averse to team PFP have more time to consider alternatives, should experience the poor-fitting PFP system repeatedly, and thus be more likely to seek and find alternative employment, changing the membership of the team.
Thinking about these effects on team performance over time suggests that task interdependence of the team and the aggregation model most relevant to team performance may be moderating factors with regard to the membership effects of team reward interdependence. When team focus is most important (e.g., teamwork considerations are critical; Mathieu et al., 2014) and task interdependence is intensive (Tesluk et al., 1997), the membership changes caused by reward interdependence are desirable for team performance. When an individual focus is more important (e.g., individual considerations are critical; Mathieu et al., 2014) and task interdependence is pooled (Tesluk et al., 1997), the membership changes caused by high levels of reward interdependence are likely to be more detrimental to performance.
Complexities and Research Directions
The framework and the empirical evidence suggest that some clear linkages—PFP intensity, performance measurement, allocation, and reward interdependence—can have substantial effects on performance behaviors and membership in teams, and these in turn affect individual and team performance. It clearly demonstrates that much more research is needed regarding the effects of team PFP plans on individual and team functioning and outcomes. The typical questions that have been asked so far are whether using team PFP plans works better than not using team PFP plans, and whether using team PFP plans works better than using individual PFP plans in team settings. But these questions are just the start. What we must ask now is how team PFP plans can be designed for maximum effectiveness, what characteristics of team functioning are critical in the design of team PFP plans, what outcomes are most affected by team PFP plans, and so on. Both theoretical and empirical advancements are critical in addressing these questions. The relationships outlined in Figure 1 provide a framework for future research. In this section, we use the framework and the existing empirical evidence to identity five major themes for the next steps in team PFP research. Unresolved tensions provide the underpinnings of these themes.
PFP Input Dimensions
The evidence suggests that team PFP intensity increases lead to increases in motivation and behaviors aligned with rewards. Yet, higher PFP intensity may also stimulate dysfunctional behaviors (Holtzen & Gupta, 2014; Lawler & Rhode, 1976). Dysfunctional behaviors in team settings include destructive competition, undermining, and lack of cooperation. These behaviors are especially likely when within-team relative performance measures are in place. Lawler and Rhode (1976) argued that many dysfunctional consequences can be reduced through the development of systems that include all relevant aspects of performance.
As noted, performance measures can suffer from deficiency and contamination. Objective, results-based measures are attractive as a means to avoid contamination, but often these measures are deficient. If PFP intensity is high, deficient measures are particularly likely to trigger dysfunctional behaviors, with employees attending to only those performance dimensions that are measured and rewarded. For example, social loafing is a danger for team PFP (Karau & Williams, 1993). But social loafing can occur only when individual behaviors are not incorporated into the performance measurement, pointing to the importance of including both team and individual dimensions. The performance measurement system must thus create a delicate balance among indicators of performance that minimize deficiency and contamination. Work that investigates the various distinctions we have identified in this article (i.e., results/behavior, objective/subjective, and absolute/relative) and the interaction of these distinctions with other input dimensions (e.g., intensity) can help us understand this balance.
A PFP input dimension that is likely to interact with other PFP input dimensions, but has been practically ignored in prior research, is frequency. It was noted earlier that there is a trade-off between frequency and intensity. As research on frequency versus intensity is quite sparse, evidence-based conclusions are difficult. Still, this trade-off should be weighed carefully in PFP plan design as team motivation and membership may change depending on the emphasis on frequency versus intensity. For example, feelings of entitlement can develop when rewards are frequent, especially in conjunction with the measure(s) used to determine payout. Fisk (2010) noted that when performance measurement is lenient, rewards are most likely to be associated with excessive entitlement (“when an individual’s desire for outcomes exceeds what is considered socially normative based on the nature of his or her inputs,” Fisk, 2010, p. 103). Similarly, if frequent rewards are distributed using equality rules, individuals, especially low performers, may begin feeling entitled to rewards. Thus, frequent rewards used with equality rules and lenient performance measurement systems would be more likely to represent conditions favorable to the development of feelings of entitlement. Highly entitled teams are likely to be less motivated by future use of team PFP, suggesting that goal-setting and goal-striving behaviors may degrade over time. In short, the available evidence suggests that frequency most likely interacts with other PFP components to determine effectiveness; this offers a fruitful avenue for research.
Incentive Versus Sorting Dynamics
The use of team PFP plans can entail trade-offs among sorting and incentive effects. For example, equity-based allocation may lead simultaneously to higher motivation and more individualistic team members. How should these competing outcomes be weighed in a decision to use team PFP? Logically, an assessment of the effectiveness of team PFP plans should be confined to only those outcomes on which the PFP is based—if pay is based on quantity of output, only quantity of output should be affected by the PFP system, for example. But this is a limited perspective, as secondary effects are likely to occur, and some secondary effects could work at cross-purposes. For example, motivation may be high initially and lead to higher performance, but membership may change substantially.
Some evidence suggests that higher performing and higher ability people prefer individual PFP, whereas lower performing, lower ability people prefer team PFP (Haines & Taggar, 2006; Shaw et al., 2001). This is another critical area for research as membership changes can have a significant influence on performance outcomes (Lazear, 2000). Work on team PFP input design could resolve this dilemma. For example, team PFP with equity-based allocations promotes both team performance (the PFP pool is determined by team performance) and individual performance (each member’s performance determines his or her share of the pool). Serendipitously, this approach would also address social loafing (individual performance is measured and rewarded; Karau & Williams, 1993) and criterion deficiency, as measuring both team and individual performance could result in more complete record of performance.
In addition, while the evidence shows that higher performers or members with higher ability react differently to equity versus equality allocation, a team could be homogeneous or heterogeneous in terms of ability and individual contributions (Mathieu et al., 2014). This leads to some interesting research questions. Should an equity allocation be used in homogeneously high-performing teams and an equality allocation in homogeneously low-performing teams? Are equity or equality distributions better in heterogeneous teams? Understanding how membership and motivation effects differ across levels is a critical area for investigation.
Levels
Team research is nicely nested at a meso-level between organizations and individuals. This placement creates both challenges and opportunities. It highlights the fact that team research must address cross-level issues in a way that micro- and macro-research can ignore more easily. For example, while strategic HR management research needs to cross only one level, that is, between organizations and individuals, teams research entails crossing at least two levels, that is, between teams and individuals and between teams and organizations.
The strategic management research in general, and strategic HR management research in particular, tends to emphasize the importance of fit between strategic, organizational-level preferences and HR policies and practices. Not surprisingly, this has been the focus of much strategic HR management research (Delery & Doty, 1996; Schuler & Jackson, 1987). This emphasis should be beneficial to team PFP research as well. For example, do team PFP plans work equally effectively in autocratic versus participative organizations? Are team PFP plans equally effective in organizations with differing structures, such as flatter versus taller organizations? Some of the arguments concerned above fit between different HR policies. For example, the team PFP system and the performance measurement system must be consistent for maximum benefit. Cross-level issues entail a careful assessment, not just within the level but across the organization and the team.
It is also important to examine the cross between the individual and the team. An important issue to address is whether the effects of PFP plans can simply be aggregated from the individual to the team. It likely depends on whether team performance is the sum of individual performance or is a gestalt or synergistic combination of individual contributions that makes team performance greater than the sum of individual performance. With respect to membership, evidence shows that team PFP plans affect employee attitudes, such as preferences (Kuhn & Yockey, 2003) and receptivity (Kirkman & Shapiro, 2000), and that these and other attitudes are prone to contagion (Barsade, 2002). This raises the possibility that team attitudinal reactions can also be greater than the sum of individual attitudinal reactions.
We distinguished between performance and membership responses at the team and the individual level, but going forward, team PFP research must extend further. For instance, evidence suggests that collectivistic employees fare better under equality allocations and individualistic employees fare better under equity allocations. Teams are likely to have many different kinds of employees. What proportion of collectivistic individuals is necessary before equality distributions make sense? Collectivism is just one individual characteristic. What distribution of personality characteristics is ideal? Should organizations be urged to tailor selection systems to dovetail with the PFP systems in use for teams? These issues of fit between employees and compensation systems in team settings are fertile fields of research.
Furthermore, in this article, we implicitly take the stance that successful implementation of team PFP will have firm-level benefits. But research on human capital and utility has shown that returns on investments in pay depend on organization-level contextual factors, such as the variance in individual and/or team performance and the importance of individual and team performance to firm profitability (Klaas & McClendon, 1996; Park & Kruse, 2014). Park and Kruse (2014) reported a stronger group PFP and firm financial performance relationship as firm-level innovation increased. Likewise, microselection utility research (e.g., Schmidt & Hunter, 1983) emphasizes the importance of incorporating the relative payoffs from high versus low individual performance. When SDy (the standard deviation of performance in dollars) is high, HR practices are much more likely to affect firm performance. Research investigating these and similar organization-level contextual variables can provide a more complete picture of the contexts in which team PFP can improve firm performance.
Dynamism
Although most research adopts a static approach to studying team PFP, team PFP plans are likely to be ongoing in work organizations. As the input–mediator–outcome process plays out with performance as the outcome, the resulting performance serves as the input for employee reactions to the PFP system. As noted, if employees do really well under the system and payouts are large, the organization may raise the standard used to compute payouts (Beer & Cannon, 2004; McClurg, 2001; Murphy, 2000). Even assuming that other aspects of the PFP system remain intact, it is likely that employee reactions the second time around will be less positive—the change in measurement could promote distrust. In other words, the Year 1 success serves as the history and guides employee responses in Year 2. Studying Year 2 dynamics while ignoring Year 1 history is likely to provide a distorted view of the effects of team PFP plans. In addition, as the PFP system plays out in Year 1, employees learn what is actually rewarded rather than what the organization says it rewards. Wright and Nishii (2013) distinguished among intended, actual, and perceived HR practices. If employees perceive consistency across intended and actual practices as they work under the PFP system, the intended effects of the PFP system are more likely to materialize. Inconsistency, however, will jeopardize the intended effects (e.g., politics-based pay; Kepes et al., 2009). Payouts from team PFP can also affect the composition of the team. Members who are dissatisfied with the payout could leave the team, and new members with different orientations could enter. This also suggests that the dynamics that materialize within the team in Year 2 will be different from those in Year 1.
Another result of the end of a performance episode that may feed into pay inputs in the next performance episode is the dispersion created by payouts. If payouts are equity based, then pay dispersion within the group should increase. Even with equality-based allocations, pay dispersion could be influenced if the allocation mechanism is a percentage of pay when there are different starting salaries among team members. There is a vast literature on pay dispersion (see, for example, Conroy et al., 2014; Shaw, 2014 for reviews) that has interesting implications for team dynamics over time.
An additional temporal concern focuses on the stage of team development (DeMatteo et al., 1998). It is quite possible that a team PFP system appropriate for one stage of team development becomes quite problematic in another stage of team development. A team PFP system that encourages training and learning could be quite beneficial early in a team’s development but become superfluous as the team matures. How is this phenomenon addressed as teams change composition due to leaving of members? Comprehensive exploration of the interactions between team developmental stage and the priorities of the PFP system could answer these questions.
For empirical research to address these temporal dynamics, it would be most valuable to move beyond short-term laboratory settings. Longitudinal field studies, field experiments, and/or experimental simulations are essential. Computer simulations of long-term team dynamics could provide a useful avenue for this research.
Team Pay Basics
In the eagerness to advance knowledge, we sometimes forget what we do not know about the basics. We reviewed the body of research that explicates team PFP. But PFP is usually a supplement and, for many employees (and teams), PFP constitutes only a small part of the paycheck. By far, the larger component of an employee’s pay tends to consist of base pay. Hardly any team pay research has concerned itself with team base pay.
Many years ago, Gupta and Jenkins (1991) criticized the use of job-level base pay in team settings. That is, the biggest portion of an employee’s pay follows the industrial revolution recommendation of paying the job, not the person. This traditional job evaluation approach investigates the skill, effort, responsibility, and working conditions of the job and derives a commensurate pay level based on these factors. Nowhere in this assessment are team skills, team responsibilities, team effort, or any team essentials addressed. With the growing popularity of teams, the traditional job evaluation approach may be anachronistic.
If teams, rather than jobs, are a fundamental unit in organizational life, then team evaluation must supplant job evaluation as the determinant of base pay. Supporting this view, Mathieu et al. (2014) recommended “a new type of job analysis” (a fundamental building block to base pay systems) that recognizes teams as a central concept (p. 144), and Conroy and Gupta (2011) began to explicate the features of team evaluation. Much more still needs to be done. Base compensation may not be as exciting as PFP, but without a proper base compensation system, the effectiveness of the team PFP system will likely erode.
Conclusion
The use of team PFP is complex. The study of team PFP is arguably even more complex. But this area of study offers fabulous opportunities for scientific theory and practice. Knowledge of team PFP plans is still in its infancy. Teams are here to stay, however, and we should do what we can to make them better. Rather than being daunted by our nebulous understanding of team PFP, we have identified a myriad avenues for research because such a rich opportunity of potential research questions is available. It is up to us as scholars to rise to the challenge. It is truly an exciting time to be a team PFP researcher.
Footnotes
Acknowledgements
The authors would like to thank Lucy Gilson, two anonymous reviewers, and Emilija Djurdjevic for feedback provided during the development of this article.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research and/or authorship of this article.
Associate Editor: Lucy Gilson