Friends With Performance Benefits: A Meta-Analysis on the Relationship Between Friendship and Group Performance

Abstract

The current article examines if, and under which conditions, there exists a positive relationship between working with friends and group performance. To do so, using data from 1,016 groups obtained from 26 studies, we meta-analyzed comparisons of the performance of friendship groups versus acquaintance groups. Results show that friendship has a significant positive effect on group task performance (Cohen’s d = 0.31). Furthermore, this relationship was moderated by group size (i.e., the positive effect of friendship on performance increased with group size) and task focus (i.e., friendship groups performed better than acquaintance groups on tasks requiring a high quantity of output, whereas there was no performance benefit on tasks requiring a single or high-quality output). These results help to reconcile mixed findings and illustrate when friendship groups are more likely to perform better than acquaintance groups.

Keywords

friendship group performance meta-analysis relationships

People prefer the company of friends over that of strangers or acquaintances. This should not be surprising as friendships, by nature, are volitional relationships between two or more people characterized by mutual liking and positive regard. Importantly, this preference for spending time with friends applies not only to the social realm but also often extends to choices regarding with whom we choose to work. In the workplace, the benefits of working with friends are often touted (Riordan, 2013), with managers having favorable attitudes about friendships among employees in the workplace (Berman, West, & Richter, 2002). In both education and employment settings, people report greater satisfaction when they work closely with their friends (Baldwin, Bedell, & Johnson, 1997; Morrison, 2002; Winstead, Derlega, Montgomery, & Pilkington, 1995).

Despite the acknowledgment that friendships are important, and the recognition that people generally like working with friends more than strangers or acquaintances, it remains unclear whether working with a friend(s) will be necessarily beneficial for group performance. That is, simply because employees and students may enjoy working with their friends, these positive feelings may not translate to actual performance gains. One can imagine that there may be pros and cons to working with friends when it comes to performance. On one hand, there may be clear benefits associated with working with people who we know and like. On the other hand, a close affinity may detract from the required work to be successful at the task (e.g., coworkers who spend their time discussing their weekend activities/plans together instead of doing their assigned task). A review of literature shows mixed findings with regard to the question of whether groups of friends perform better or worse than groups of acquaintances. Whereas some studies have documented a positive effect of friendship on group performance (e.g., Harrison, Mohammed, McGrath, Florey, & Vanderstoep, 2003; Jehn & Shah, 1997; Shah & Jehn, 1993), other studies have not documented performance benefits of friendship groups (e.g., Andersson & Rönnberg, 1996; Nibler & Harris, 2003; Peker & Tekcan, 2009; Swenson & Strough, 2008).

In the current article, we seek to reconcile mixed findings and to better understand the relationship between friendship and group performance. Considering the mixed findings in the literature, and the potentially high degrees of variability that can arise when studying groups, a meta-analytic review can offer a more conclusive depiction of the effect of friendships on group performance. Conducting a meta-analysis helps move beyond a narrative review approach, which focuses on the number and the direction of significant findings and does not provide insight into the overall size of the relationship. Moreover, given the logistic challenges associated with recruiting existing friendship groups to the laboratory, and then comparing their performance with ad hoc acquaintance groups, it is feasible that some studies that show null findings are simply underpowered. By meta-analytically integrating studies we are able to base our conclusions upon a large number of groups, offering more reliable insight into the relationship between friendship and group performance, and the existence of potential moderators.

After introducing the construct of friendship, we describe how and why friendship may affect two processes which underlie effective group task performance: coordination and motivation. We examined coordination and motivation as two primary processes, which scholars have regularly linked to the success/failure of groups (Hackman, 2002; Steiner, 1972). Following this, we systemically integrate existing empirical findings to meta-analytically (Hedges & Olkin, 1985; Lipsey & Wilson, 2001) estimate the overall effect of friendship on group performance. We also identify task and group characteristics which we hypothesize will moderate the effect of friendship on group performance. Namely, we first test the hypothesized moderating effects of group size, task independence (i.e., high vs. low interdependence), and task focus (i.e., maximizing vs. optimizing tasks). We also conducted exploratory moderator analyses for task type (i.e., physical vs. cognitive tasks) and participant population (i.e., children vs. adults). Ultimately, by testing our theoretically derived hypotheses and exploratory analyses through meta-analytic techniques, we hope to pave the way for a clearer and deeper understanding of when and why friendships affect group performance.

Literature Review and Theoretical Background

Acquaintance and Friendship Groups

Much of the research on group performance has utilized ad hoc or acquaintance groups. A group is defined as two or more interdependent individuals who influence one another through social interaction (Forsyth, 1999). Acquaintance groups are defined as groups with limited familiarity and contact among members (Jehn & Shah, 1997). Acquaintances often do not have personally meaningful shared pasts, and do not possess deep, intimate knowledge of one another. Based on this conceptualization, participants who have just met and were introduced shortly before being assigned to work on a task together are an example of an acquaintance group. With a brief exchange that provides a minimal foundation of familiarity and ability to at least recognize one another, these individuals would no longer be complete strangers. Instead, they would qualify as acquaintances, particularly when they still have neutral rather than strong positive or negative feelings about their relationship (Schnall, Harber, Stefanucci, & Proffitt, 2008). The interpersonal aspects that distinguish acquaintances and friends are worth noting, because they can presumably create important differences in how acquaintance versus friendship groups operate and, ultimately, perform.

In contrast to acquaintances, friendships are marked by their interpersonal closeness, warmth, and mutual regard (Hartup & Stevens, 1997). Friendship groups are defined as groups with close, interpersonal ties and positive, amiable preexisting relationships (Jehn & Shah, 1997). These are voluntary relationships that require reciprocity and mutuality in the sense that two individuals must affirm their relationship to each other, and their affection must be bidirectional (Ross, Cheyne, & Lollis, 1988). Friendships often involve individuals of equal status, who, because they have chosen to care about each other, are particularly motivated to learn about each other, consider each other’s wants and desires, navigate conflicts effectively, and acknowledge the potential impact that their behaviors have on each other (Dunn, 2004). Accordingly, a defining feature of friendship is the strong proclivity for attempts of empathy, understanding, and validation.

What Makes Friendship Unique?

While much research on social relationships often examines interpersonal interaction based on economic or social exchange theories (Thibaut & Kelley, 1959), friendship does not begin with a planned agreement, statement, or announcement. For example, in business, producers rarely give products to customers without any monetary benefits in return. Therefore, people should not desire to build relationships when there are high explicit and implicit costs as compared with the potential benefits that they may earn. However, many suggest that friendships do not operate on a pure economic model of costs and benefits, but instead often utilize more complex social exchange rules that consider more than a reciprocation of benefits (Clark & Mills, 1979; Lin & Rusbult, 1995). As such, friendship is primarily based on the positive experiences of interacting and working with others.

Friendship is also distinct from other constructs associated with liking between individuals, such as cohesion, familiarity, network density, closeness, and intimacy. For example, on the surface, cohesion may seem to be similar conceptually to friendship. While both cohesion and friendship share interpersonal intimacy among group members (Evans & Dion, 1991; Shah & Jehn, 1993), not all cohesive groups include friendships between team members. Moreover, while friendship may be considered a type of “strong tie” (Krackhardt, 1992), not all strong ties are considered friendships. A tie may be considered strong if it fulfills one or two of the elements of friendship, but friendship only exists when the relationship encompasses all three components such as liking behaviors, shared experiences, and reciprocity. As such, for the current study, we exclusively focus on examining friendships within groups, excluding groups that may be conceptualized or measured as cohesive or contain social network ties, but do not fulfill all of the required elements of friendship.

Group Processes: Friends Versus Nonfriends

It is well recognized that group processes, or the behaviors or interactions among group members, often underlie how and why some groups perform better or worse than other groups (Hackman, 2002; Ilgen, Hollenbeck, Johnson, & Jundt, 2005; Larson, 2010; Steiner, 1972). Steiner’s (1972) model of group performance suggests that groups often incur motivational or coordination process losses (i.e., where actual performance of the group is less than the anticipated performance given the individuals within the group). Building on Steiner’s framework, scholars have noted that people working together in groups may experience motivational or coordination process gains (i.e., where actual performance of the group is greater than the anticipated performance given the individuals within the group; Hackman & Wageman, 1995; Kerr & Tindale, 2004; Larson, 2010; Nijstad, 2009). Specifically, motivational process losses (or gains) may occur when individuals in a group work less (or work more) than they would if they were working alone. Likewise, coordination process losses (or gains) may occur when groups of individuals perform worse (or better) than the best individual member in the group, due to the combined effective mixture of their resources and efforts (i.e., coordination).

Below, we describe the underlying reasons for why one may anticipate an overall positive effect for motivation and coordination to occur when friends work together. Namely, we propose below that, relative to acquaintance groups, when friends work together, coordination will be improved through increased collaboration, communication, and conflict management; motivation will be increased via increased commitment, goal-setting, and goal pursuit.

Motivation

A potential difference between acquaintance and friendship groups that could have implications for group performance involves the motivation levels of members. Decades of research have documented that social loafing (Latané, Williams, & Harkins, 1979) and free-riding (Kerr, 1983) underlie reductions in motivation and harm group performance. Whereas research has identified structural factors, such as reducing anonymity or adding an incentive for good performance, to help reduce loafing, “social” factors have been documented to also affect motivation on group tasks. Consistent with the predictions of the Collective Effort Model (Karau & Williams, 1993), individuals work harder on group tasks when they identify and care about the welfare of the group (Ellemers, De Gilder, & Haslam, 2004). When individuals identify and care about the welfare of the group, they are more inclined to work particularly hard for the group in an effort to help the group accomplish its goal (Karau & Williams, 1997).

As people interact and close interpersonal ties strengthen, individuals begin to espouse aspects of each other into their senses of self (i.e., self-expansion theory; Aron & Aron, 1997). Shared goals become synonymous with own goals, and personal concern and accountability for the fate of friends rises as the concepts of self and other increasingly merge. Presuming the emotional attachments that accompany friendships carry over and apply to their task groups when friends work together, heightened commitment to the group is expected in such work settings. This is not trivial because identification with and commitment to the group elevate personal accountability and task effort (Newcomb & Brady, 1982; Tesser, Millar, & Moore, 1988), which often stimulate efforts toward helping the group perform well (Klein & Mulvey, 1995). Furthermore, work by Jehn and Shah (1997) supports this possibility, documenting that the increased commitment to friendship groups, relative to acquaintance groups, helped account for the greater performance of friendship groups.

In addition to increased commitment, friendships may facilitate goal-setting and increase persistence during goal pursuit. Because friends derive a sense of understanding, caring, and acceptance from their relationships, these positive ties inherently satisfy the need to belong (Baumeister & Leary, 1995). When confronted with challenging tasks that involve strain and possible ego-threats, the satisfaction of needs (e.g., relatedness, autonomy, competence) has been found to be an important predictor of performance because need satisfaction often fosters intrinsic motivation (Deci & Ryan, 2000). Intrinsically motivated individuals engage in work from a source of genuine interest rather than pursuit of external rewards and are energized workers who are less susceptible to exhaustion during goal pursuit (Kammeyer-Mueller, Simon, & Judge, 2016). Past work demonstrates that social cues that signal acceptance can fuel intrinsic motivation when people work together (Carr & Walton, 2014), which suggests that intrinsic motivation should be especially high when tasks are assigned to friendship groups.

The psychosocial resources that friendships offer can be energizing, as well as confidence boosting. In a psychological landscape filled with subjectivity, uncertainty, and perceptual ambiguity, the interpersonal similarity evidenced within friendships can serve as a vital source of validation and affirmation. Combined with the acceptance that accompanies friendships, these close relationships exist as a natural well-spring of self-efficacy. In fact, merely reminding participants of existing friendships decreases the perceived intensity of challenges (i.e., increases efficacy; Schnall et al., 2008). This work incorporated an established paradigm where participants were escorted to the bottom of a hill, asked to put on a backpack loaded with weights, and then provided steepness estimates of the incline in front of them. Prior research (Proffitt, Stefanucci, Banton, & Epstein, 2003) has shown that the visual perception of the physical world is systematically influenced by self-efficacy when confronting challenging tasks and threats. Specifically, to the degree self-efficacy is low (e.g., burdened with a heavy backpack while looking up at a hill), the intensity of challenges (e.g., steepness of a hill they anticipate climbing) becomes perceptually exaggerated (e.g., hills subjectively appear steeper than they objectively are).

Adopting these principles, Schnall et al. (2008) recruited pairs of friends who were walking together by the experimental location (Study 1), or primed participants to think about and visualize a friend who is important to them (Study 2), and then asked these physically burdened participants to provide steepness estimates of the hill they were facing. These judgments were compared with those of participants who were recruited while walking alone (Study 1) or primed to image an acquaintance relationship (Study 2). Results showed that the presence of friends and reminders of friendships led people to see the same hill as less steep in comparison with control participants. Importantly, from both studies, relationship closeness ratings from those in the friendship conditions were negatively related to hill steepness perceptions, indicating a positive link between efficacy and friendship ties. In a conceptual replication of this effect of friendship on efficacy, others found that the mere presence of friends (vs. being alone) led to reductions in the perceived physical formidability of a dangerous target (e.g., Fessler & Holbrook, 2013).

Supporting the possibility that friendship will be beneficial for motivation, Karau and Williams (1997) documented across two studies that groups of friends were less likely to engage in social loafing as compared with acquaintance groups. Moreover, Kerr and Seok (2011) showed that under certain circumstances (i.e., when individuals’ contributions were instrumental for the team to perform well), participants displayed motivation gains (i.e., working harder in a group than when working alone) when working with a friend as compared with an acquaintance.

Coordination

Effective coordination of group members depends on group members being able to share and integrate relevant information with one another, along with the awareness of what others know (Thomas, DeScioli, Haque, & Pinker, 2014). Inefficiencies and coordination losses commonly documented show that group members’ lack of information exchange often underlies coordination problems (Kerr & Tindale, 2004; Steiner, 1972). Importantly, when individuals communicate more effectively, and are better at understanding one another’s preferences, groups are less likely to experience problems with coordination (Deutsch, 1973).

The defining features of friendship help explain why interpersonal similarity promotes affiliation and why relationship processes often function to strengthen commonalities (Byrne, 1971; Pilialoha & Brewer, 2006). Friendships often form between individuals who share interests, attitudes, core values, backgrounds, and traits (Berscheid & Reis, 1998), making communication between parties easier and also preferred (vs. discourse with those who are not like-minded). Friends’ heightened ability and willingness to communicate with each other provide an initial basis for the expectation that performance from friendship groups will be superior to that of acquaintance groups. This is founded on the notion that group performance is in part a function of the ability of members to coordinate their resources and actions effectively (Steiner, 1972). So, group performance increases to the extent that members are willing and able to communicate and share task-relevant information, provide critical evaluations, integrate knowledge and ideas into tangible plans, and monitor and adjust ongoing actions accordingly (Larson, 2010). In addition, as compared with acquaintances, friends may have a greater awareness as to what each member already knows (i.e., sharing common knowledge). Thomas et al. (2014) have highlighted that effective coordination between teammates can be dependent on knowing what your partner already knows. As alluded to, these processes are expected to occur more frequently in friendship versus acquaintance groups for a variety of reasons.

Group members who hold similar values or beliefs, and who understand, accept, and validate one another (e.g., friends), should communicate more efficiently, effectively, and openly. As a result of the cognitive consistency and social acceptance that have been established, coordination losses should be relatively mild when friends work together. Conversely, when members are unaware of or hold different values (e.g., nonfriends) and struggle to establish common ground and consensus, the incongruity of perspectives is likely to undermine coordination and performance. These outcomes may also suffer when members who endorse conflicting views are not willing to take perspectives nor be conciliatory, or when aversion to conflict or criticism generates reluctance in members to share ideas and useful information. To be clear, this is not to say that conflict will necessarily be less frequent in friendship versus acquaintance groups, or even that conflict is something that should always be avoided. Rather, given the contrasts between acquaintances and friends, the types of conflict and extent to which they interfere with group performance are presumed to differ across group types. For example, when group members hold competing viewpoints that pertain to the task (i.e., task conflict), disagreement can lead to mounting tensions. When members feel a lack of voice and respect from their group, this perceived violation of social contracts may negate the desire to engage in self-restraint (Colquitt, Scott, Judge, & Shaw, 2006). In such cases, task conflict can spill over into the relationship domain and heighten interpersonal friction and incongruities (i.e., relationship conflict). When relationship ties are fragile, and interpersonal differences versus similarities are salient, decreases in the ability and willingness to work collectively are then likely to hinder group performance (Jehn & Mannix, 2001; Yang & Mossholder, 2004).

In contrast, when arousal from conflict is situated within a psychologically safe environment, divergent and critical forms of thinking can be adopted (Nemeth, 1986). So friendship groups with established interpersonal foundations of trust and acceptance (vs. acquaintance groups) may, in particular, have the ability to garner the positive aspects of task conflict (e.g., divergent thinking, consideration of diverse perspectives) while effectively containing any sources of spillover that could accentuate relationship conflict (Simons & Peterson, 2000; Tidd, McIntyre, & Friedman, 2004). Thus, task conflict may be less likely to negatively affect the performance of friendship groups because friends (vs. acquaintances) can more tactfully challenge each other, and the resultant sharing and consideration of varied perspectives could benefit downstream performance (Peterson & Behfar, 2003).

Despite the strong rationale underlying why friendship should aid in both coordination and motivation processes, we suspect that, at times, friendship groups may be prone to coordination losses which can detract from optimal performance. Namely, although we have proposed that friendship groups should be better coordinated than acquaintance groups, the positive aspects of a friendship group (i.e., increased trust and positivity toward one another) can potentially harm their potential to effectively coordinate information and differing perspectives. When teammates need to identify and discuss conflicting opinions to identify a correct solution, group members need to put aside relationship concerns in favor of focusing on the task. As such, in part of their desire to have a positive relationship, it is conceivable that friendship groups may be more susceptible to conformity pressures that prompt unwanted confirmation biases, ultimately creating narrow and overconfident mind-sets. These qualities could prematurely limit the searching for and sharing of information, and reduce the drive to think critically and carefully. For instance, Loyd, Wang, Phillips, and Lount (2013) found that people working with similar teammates (i.e., shared political affiliation) were more concerned about getting along with their partner and less willing to engage in constructive task conflict, as compared with those working with dissimilar teammates. When performance depends on the integration of diverse perspectives, increased concerns over having a harmonious relationship ultimately can reduce performance of groups of like-minded people (Loyd et al., 2013). Despite this possibility being a clear threat to friendship groups, Hogg and Hains (1998) found that friendship in groups was associated with reduced symptoms of groupthink as compared with acquaintance groups. Examinations of group discussions showed that friendship was associated with reduced consensus seeking and deference to the leader, along with an increase in a discussion of facts and request for information from other group members.

Although concerns over maintaining a positive relationship may possibly hinder effective communication and information exchange, we ultimately see the motivational benefits along with other communication benefits detailed above to outweigh the potential negatives when predicting whether or not friendship will be beneficial for performance. Given that past work shows a positive relationship between efficacy and performance (e.g., Bandura & Locke, 2003), the combined ability of friendships to increase efficacy, motivation, and coordination provides a theoretical foundation for the following prediction:

Hypothesis 1: Groups composed of friends will perform better than groups composed of nonfriends.

Moderating Variables on the Effect of Friendship on Group Performance

Consistent with contingency-based models of behavior (e.g., Galbraith, 1973; Lawrence & Lorsch, 1967), we anticipate there to be contextual factors that will moderate the hypothesized positive relationship between friendship and group performance. Namely, whereas we have proposed that friends’ abilities to minimize coordination and motivation losses help foster the proposed differences in performance between friendship and acquaintance groups, contextual features that involve either the task or group can make the reliance on these processes more or less important in predicting performance. Specifically, we focus on variables commonly used to categorize tasks and groups as potential moderators: task interdependence, group size, and task focus (i.e., maximizing vs. optimizing).

Task interdependence

Task interdependence describes the extent to which group members need to interact and depend on one another for tasks to be performed effectively (Van de Ven & Ferry, 1980). For example, group tasks that are low in interdependence allow members to perform separate functions individually and later pool their efforts into an aggregate response. Tasks which require low levels of interdependence are common in workplace settings (e.g., Lount & Wilk, 2014) whereby a team needs to reach a certain goal but the work is largely conducted by independent actors (e.g., team members working toward reaching a team-level sales quota). Other group tasks involve increasing amounts of interdependence and may require group members to engage in more sequential (i.e., contribution of one member needs to be shared for other members to complete their responsibilities) or reciprocal (i.e., contributions are shared and further developed jointly in an ongoing, back-and-forth fashion) interactions (Thompson, 1967). Highly interdependent tasks often occur when a discussion and information sharing is required for group members to reach a decision (e.g., a selection committee making a hiring decision).

Of importance, task interdependence determines the degree to which members need to collaborate and coordinate to produce desirable task outcomes (Kelly & McGrath, 1985; Steiner, 1972), with higher interdependence necessitating more frequent and effective communication and coordination attempts. Under such settings, the coordination benefits associated with friendship groups should help provide an advantage over acquaintance groups. As such, friends (vs. nonfriends) should be predisposed to work more effectively with one another, so the impact of friendship on group performance should be pronounced when task interdependence is high. However, for tasks requiring low levels of interdependence, the benefits of friendship groups should be less pronounced. When there are minimum requirements for coordination to help facilitate performance, acquaintance groups should be just as equipped to effectively communicate and coordinate actions as friendship groups. Thus, we predict the following:

Hypothesis 2: Task interdependence moderates the positive relationship between friendship and group performance, such that the positive relationship will be stronger when task interdependence is high compared with low.

Task focus

A common way to distinguish group tasks is on a basis of the criteria that are used to evaluate performance. Steiner (1972) has argued that the task focus is one such important dimension. Maximizing tasks require a focus on production, distance, or time (Baron & Kerr, 2003; Laughlin, 2011), and criteria for evaluating performance are often quantity-based (with higher amounts representing superior performance). For instance, a group tasked with generating as many ideas as possible to help solve a problem would be performing under a maximizing task focus. Optimizing tasks require a focus on the quality of output (Baron & Kerr, 2003; Laughlin, 2011), and criteria for evaluating performance are often based on the generation of a correct or optimal answer (or degree of closeness to these standards). For instance, a group tasked with generating a single correct solution to solve a problem would be performing under an optimizing task focus.

Performance on maximizing (relative to optimizing) tasks is likely to improve to the extent that group members are willing to exert effort and sustain their drive and task focus over time. As previously mentioned, the willingness to expend energy on behalf of the group should be positively related to members’ commitment to the group (Klein & Mulvey, 1995), and the willingness to sustain high levels of effort over time should be positively related to intrinsic interest (Deci & Ryan, 2000) and self-efficacy (Vroom, 1964) levels. Similarly, on maximizing tasks, as compared with optimizing tasks, group members are able to typically see how their efforts are translating into greater performance. This awareness that greater persistence is being associated with greater performance should be particularly rewarding to friendship groups where greater value is placed upon the benefit of a successful outcome (Karau & Williams, 1993). On optimizing tasks, where people are often tasked with working toward a single correct solution, there is often less feedback directly linking efforts to performance along the way. Thus, we anticipate that the proposed benefits of friendship on group performance will be especially pronounced on maximizing tasks (i.e., ones that focus on quantity-based outcome) because group members should be motivated to promote and pursue the collective welfare (Karau & Williams, 1997; Kerr & Seok, 2011), and intrinsically motivated to perform for the sake of enjoyment and derived satisfaction. Thus, we predict the following:

Hypothesis 3: Task focus will moderate the relationship between friendship and group performance, such that the positive relationship will be stronger on tasks that are maximizing versus optimizing.

Group size

As group size increases, so do the challenges groups face in avoiding threats to performance (Steiner, 1972). Across a variety of tasks, group size has been found to affect performance (Bray, Kerr, & Atkin, 1978; Hackman & Vidmar, 1970; Wheelan, 2009). Namely, an inherent challenge of larger groups is the threats to individual member motivation and the ability of group members to effectively communicate and coordinate information. Larger sized groups display greater motivation losses (e.g., Ingham, Levinger, Graves, & Peckham, 1974; Karau & Williams, 1993; Latané et al., 1979) and poorer group decision making (e.g., Lu, Yuan, & McLeod, 2012; Mullen, 1983) than smaller sized groups. With that said, the literature on the negative effect of group size on coordination and motivation has largely been based on ad hoc acquaintance groups. In line with our central assumptions that groups of friends are anticipated to communicate and coordinate more effectively and to be more motivated than nonfriends, increased group size may not hamper their performance to the same degree as groups of nonfriends. For instance, with regard to motivation losses, whereas feelings of anonymity often increase as group size increases, such negative effects should be less pronounced in a setting where everyone knows one another. Moreover, the value associated with performing well, a central ingredient to working hard on group tasks, may suffer much more as group size increases with acquaintances, but may be less affected (or even increased), as a group of friends grows larger in size. With regard to coordination and communication problems associated with larger groups, the added comfort and acceptance provided by friendships within a group may make people more willing to speak up and contribute their unique inputs, despite the group size. Moreover, the lack of familiarity among group members may only serve to exacerbate threats to group performance (e.g., conformity pressure) which occur as group size increases (Asch, 1951; Bond, 2005). Accordingly, it is possible that the positive effects of friendships may be even exacerbated in larger groups where members are all friends with one another. Taken together, we anticipated that the difference in performance between friendship and acquaintance groups will be more pronounced among larger (vs. smaller) groups. Specifically, we predict the following:

Hypothesis 4: Group size will moderate the effect of friendship on group task performance, such that the positive relationship will be stronger for larger groups as compared with smaller groups.

Exploratory Moderators of Group Performance

In addition to task interdependence, task focus, and group size, we also sought to explore whether other characteristics (e.g., cognitive vs. physical tasks) and population (e.g., children vs. adults) may moderate the relationship between friendship and group performance. Group tasks can differ in the degree to which they require members to utilize more cognitive versus physical skills. Cognitive tasks (e.g., decision making, brainstorming tasks) often involve memory retrieval, problem solving, idea generation, and/or judgment and decision making. Arguably, positive performance outcomes on cognitive tasks are associated with members’ abilities to know what and when to communicate, the development of insights and ideas through the coordinated integration of information and resources, and deliberate and divergent forms of thinking. In contrast, tasks that are primarily physical in nature (e.g., lifting/moving heavy objects, sports and exercise activities) can also contain coordination demands but are not typically centered on verbal communication. On one hand, one may anticipate that friendship groups should perform better than acquaintance groups on cognitive tasks given such tasks often involve extensive verbal communication. On the other hand, on physical tasks one may anticipate that friendship groups may feel more comfortable operating within a close interpersonal space with their fellow group members, and thus, members may be less preoccupied and concerned about violating norms of physical contact and distance while executing a task.

Furthermore, the participant population (i.e., children vs. adults) is another potential moderator that warrants examination. It is possible that children derive more comfort from friendship groups compared with adults. Past work shows that children find the experience of working with friends more positive than do adults, partly due to the fact that children tend to engage in such collaborations more frequently (Miell & MacDonald, 2000; Newcomb & Brady, 1982). Moreover, children may have an increased aversion toward working with strangers or nonfriends as compared with adults (Greenberg & Marvin, 1982). However, children may make friends much quicker than adults and may experience a sense of closeness to another similar aged group member as compared with two adults meeting one another for the first time (Ladd, 1990). As such, it is an open question for what, if any, impact participant population (i.e., children vs. adults) might have on the relationship between friendship and group performance.

Method

Literature Search and Sample of Studies

To acquire articles for possible inclusion, we searched for empirical studies examining the effect of friends (vs. acquaintances) on group performance. Specifically, studies across multiple disciplines were searched using various online databases (ABI/Inform, Business Source Complete, ERIC, JSTOR, PsycINFO, ScienceDirect, Google Scholar, Web of Science, Wiley Online Library). We searched for a combination of various keywords, such as friends*, friendship*, team task performance, group task performance, team performance*, friend/acquaintance, and friend/stranger. We also searched for articles that relate to structural ties (e.g., cohesion, affective ties, density, intimacy, familiarity) or group size (e.g., “dyads” and “group/team”).

To be thorough in our ability to identify studies applicable to analyses, we also examined journals and conference proceedings across the fields of social psychology and organizational behavior (e.g., Academy of Management Journal, Administrative Science Quarterly, Group Dynamics, Group Processes and Intergroup Relations, Journal of Applied Psychology, Journal of Experimental Social Psychology, Journal of Management, Journal of Organizational Behavior, Journal of Personality and Social Psychology, Organization Science, Organizational Behavior and Human Decision Processes, Personality and Social Psychology Bulletin, Personnel Psychology, Small Group Research, and Social Psychology and Personality Science). Moreover, given the interdisciplinary relevance of our research questions, a search of articles published from outlets pertaining to education was also conducted (e.g., Child Development and Psychology in the Schools).

Inclusion Criteria for Studies

There were several criteria to warrant inclusion in analyses. First, we focused only on empirical research that employed participants from established friendships, and also included nonfriends/acquaintances as a comparison group. We excluded studies that employed partners in a cohesive group (Zaccaro & Lowe, 1988; Zaccaro & McCoy, 2006),¹ and romantic couples (Wegner, Erber, & Raymond, 1991), and studies where friendship was manipulated via a scenario methodology (Perry-Smith, 2014).

Second, to maintain a clear focus on group performance, studies were only included if task performance was reported. Studies that only reported outcomes tangentially related to task performance were excluded (i.e., satisfaction: Mendelson & Kay, 2003; Riordan & Griffeth, 1995; job involvement: Berndt & Keefe, 1995; Birch & Billman, 1986; engagement: Sharabany & Hertz-Lazarowitz, 1981; cooperation: Hanham & McCormick, 2008; and fairness: Austin, 1980; Pataki, Shapiro, & Clark, 1994).

These criteria yielded 24 papers, which presented the findings from 26 unique studies, thereby resulting in our ability to code 26 statistically independent effect sizes (Table 1). Outlier analysis was conducted with Huffcutt and Arthur’s (1995) sample-adjusted meta-analytic deviance approach. No outliers were identified, and thus, all 26 independent effect sizes were included in our analyses.

Table 1.

Summary of All Studies Included in the Meta-Analysis.

Author(s)	Effect size (d)	SE	Sample characteristics^a			Work features^b	Task type
Author(s)	Effect size (d)	SE	n	Population	Group size	(TI; TF; TT)	Task type
Andersson (2001)	0.75	0.30	48	1	2	2; 1; 2	Picture recall
Andersson and Rönnberg (1995), Experiment 1	−0.03	0.45	20	2	2	1; 1; 2	Word recall
Andersson and Rönnberg (1995), Experiment 2	0.24	0.32	40	2	2	1; 1; 2	Detail recall
Andersson and Rönnberg (1996)	0.02	0.32	40	2	2	1; 1; 2	Semantic and episodic recall
Andersson and Rönnberg (1997)	0.65	0.30	48	2	2	2; 1; 2	Word recall
Azmitia and Montgomery (1993)	0.31	0.34	36	1	2	1; 2; 2	Problem solving
Bos, Buyuktur, Olson, Olson, and Voida (2010)	1.26	0.49	20	2	9	1; 1; 2	Shape-building computer task
Brennan and Enns (2015)	−0.12	0.33	37	2	2	1; 2; 2	Target recognition
Gruenfeld, Mannix, Williams, and Neale (1996)	−0.20	0.30	46	2	3	1; 2; 2	Hidden profile
Harrison, Mohammed, McGrath, Florey, and Vanderstoep (2003)	1.04	0.32	43	2	3	1; 1; 2	Problem solving
Hope, Ost, Gabbert, Healey, and Lenton (2008)	−0.26	0.41	24	2	2	1; 1; 2	Word recall
Jehn and Shah (1997)	0.66	0.28	53	2	3	2; 1; 1	Model building
Karau and Williams (1997), Experiment 1	0.34	0.52	15	2	2	2; 1; 1	Typing
Karau and Williams (1997), Experiment 2	0.20	0.33	38	2	2	2; 1; 2	Idea generation
Kerr and Seok (2011)	0.44	0.31	44	2	2	2; 1; 1	Physical persistence
Krylow (2008)	0.14	0.30	46	2	3	1; 2; 2	Hidden profile
Kutnick and Kington (2005)	−0.07	0.33	36	1	2	1; 2; 2	Scientific reasoning
Miell and MacDonald (2000)	0.65	0.46	20	1	2	1; 2; 2	Music composition
Newcomb and Brady (1982)	0.68	0.27	60	1	2	1; 1; 2	Problem solving
Nibler and Harris (2003)	0.14	0.20	100	2	5	1; 2; 2	Problem solving
Peker and Tekcan (2009)	−0.40	0.38	29	2	3	2; 1; 2	Word recall
Shah and Jehn (1993)	0.56	0.46	20	2	3	2; 1; 1	Model building
Swenson and Strough (2008)	−0.20	0.25	66	1	2	1; 2; 2	Problem solving
Thompson (2016)	0.73	0.38	30	2	2	2; 1; 1	Physical persistence
Van Dick, Stellmacher, Wagner, Lemmer, and Tissington (2009)	0.18	0.32	39	2	3	2; 1; 2	Idea generation
Voida, Bos, Olson, Olson, and Dunning (2012)	1.44	0.53	18	2	8	1; 1; 2	Shape-building computer task

Note. Positive effect sizes indicate that subjects who worked with friends perform better than strangers. Effect size d = Cohen’s d effect size (unbiased/standardized).

n = Number of groups in a study; Population: Sample’s age (1 = children, 2 = adults); Group size: Number of subjects in a group.

TI = Task Interdependence: High (1) vs. Low (2); TF: Task Focus: Maximizing (1) vs. Optimizing (2); TT = Task Type: Physical (1) vs. Cognitive (2); Task: Description of Task.

Given our focus on group task performance, all analyses were conducted at the group level. Altogether, the final sample included 1,016 groups (3,467 individuals), yielding 26 independent effect sizes.

Coding of Study Characteristics

Following steps detailed by Lipsey and Wilson (2001), a coding scheme was developed for relevant study features and moderators. For each study, we coded (a) study characteristics (i.e., date of publication, number of subjects in the study, participant population, that is, children or adults), and (b) group features and task characteristics (i.e., level of task interdependence, task focus, task type, group size,² and description of the task).

To maintain statistical independence of data, when more than one performance variable was reported from a study, a single effect size was selected and coded. In cases where multiple measures of performance on a single task were available from a study, we selected the most objective performance measure to reduce rater bias (De Jong, Dirks, & Gillespie, 2016; Mesmer-Magnus & DeChurch, 2009). When the multiple performance measures of differing tasks were reported, when there was no difference in the level of objectivity for performance outcomes, we randomly selected a single performance measure (Lipsey & Wilson, 2001). Two graduate student coders read the papers and independently provided ratings of the described characteristics for each of the studies. In the instances of disagreement between coders, resolution was attempted via discussion (e.g., Kong, Dirks, & Ferrin, 2014). If consensus was still not reached, the second author joined the discussion until agreement was achieved. Cohen’s (1968) Kappa was calculated to assess interrater reliability of coding variables. A Cohen’s Kappa of 90.6% was obtained, indicating a high degree of interrater agreement (Landis & Koch, 1977).

Computation of Effect Sizes

For each study, the unstandardized mean difference approach (Lipsey & Wilson, 2001) was used to calculate effect sizes by comparing the means of outcome measures for experimental (e.g., friendship group performance) and control (e.g., acquaintance group performance) groups. Because effect sizes using the unstandardized mean differences approach can be biased due to small sample sizes, we computed Cohen’s d as an overall effect size from each study and then converted it to a standardized mean difference (Cohen, 2013). Cohen’s d = 0.20 is considered to be a small effect size, d = 0.50 to be medium effect size, and d = 0.80 to be large effect size (Cohen, 2013). The standardized mean differences were derived by the pooled standard deviation to adjust sample size bias (Hedges & Olkin, 1985). This procedure helps to minimize the upward biases of effect sizes when sample sizes from individual studies are small. Thus, we used unbiased (i.e., standardized) mean differences effect sizes and derived weighted mean effect sizes from the inverse variance weight calculation (Hedges & Olkin, 1985). The inverse variance weight gives more weight to the overall analysis to effect sizes that are more reliably estimated (Lipsey & Wilson, 2001).

Analysis of Effect Sizes

To test an overall relationship between friendships on group performance among the coded studies, we conducted a random-effects analysis. The analyses were conducted in SPSS with a Restricted Maximum Likelihood (REML) approach using syntax provided by Lipsey and Wilson (2001). The random-effects approach attempts to make unconditional inferences that go beyond the studies that are analyzed and are an increasingly advocated approach for studies where the goal is to generalize the results beyond the studies included in the analysis (Lipsey & Wilson, 2001; Raudenbush, 2009; Vevea & Coburn, 2015).

To conduct moderator analysis on categorical variables (i.e., task interdependence, task focus, task type, and population), we used a random-effects categorical model, analogous to an ANOVA. Following Hedges and Olkin (1985), a homogeneity Q statistic was computed to test the homogeneous distribution of the effect sizes. The significant between-group variance statistic (Q_b), which identifies the possible existence of a moderator(s), indicates that the mean effect size across groups differs by coded variables. A significant Q_w statistic indicates within-group homogeneity of effect sizes in ANOVA and also indicates the appropriateness of the categorical variable to explain the heterogeneity across the effect sizes (Lipsey & Wilson, 2001). We also calculated the variance (τ²) and the standard deviation between the studies in true effects (τ) in a random-effects model to estimate the heterogeneity variance within each subgroup (Borenstein, Hedges, Higgins, & Rothstein, 2009). Furthermore, we also computed and report the I² statistic (Higgins & Thompson, 2002), which is used to help quantify the degree of heterogeneity. The I² statistic indicates the percentage of variation in point estimates derived from between-study heterogeneity rather than sampling error, where .25 = low heterogeneity, .50 = moderate heterogeneity, and .75 = high heterogeneity.

To conduct moderator analysis on continuous variables (i.e., group size), using SPSS syntax provided by Lipsey and Wilson (2001), we used a random-effects meta-regression approach. The meta-regression approach is analogous to an ordinary least squares (OLS) regression. However, the meta-regression approach is adapted for meta-analysis by incorporating study-specific weighting into the analysis (Lipsey & Wilson, 2001).

Last, we also conducted several analyses to examine the potential impact of publication bias (i.e., the file-drawer problem). To assess publication bias, we utilized a number of different techniques using Comprehensive Meta-Analysis software (Version 3.0; Borenstein, Hedges, Higgins, & Rothstein, 2014). This software evaluated the publication bias by funnel plots (i.e., a scatterplot of each effect size against its standard error), Egger’s test of regression (Egger, Smith, Schneider, & Minder, 1997), and Begg’s rank correlation test (Begg & Mazumdar, 1994). We also conducted Duval and Tweedie’s (2000) “Trim and Fill” analysis, which is based on the assumption that a complete set of possible studies will be normally distributed around a true mean. The method seeks to trim outlying studies, fill in estimated studies, and then recalculate a newly estimated overall effect size if publication bias is detected.

Results

Main Effect: Friendship and Group Task Performance

The overall effect of friendship on group performance was significant and positive: Cohen’s d = 0.31; k = 26; 95% confidence interval (CI) = [0.15, 0.48], indicating that friendship groups performed better than acquaintance groups, supporting Hypothesis 1. Table 2 presents results for both the overall main effect and the categorical moderator analyses.

Table 2.

Effects of Friendship on Group Performance With Between- and Within-Homogeneity Tests Across Hypothesized/Exploratory Categorical Variables (Random-Effects Model).

Variables	k	Effect size (d)	95% CI	Homogeneity tests
Variables	k	Effect size (d)	95% CI	Q(b)	Q(w)	I ²
Overall effect of friendship (H1)	26	0.31	[0.15, 0.48]		40.97*	38.98
Theory-relevant moderators
Task interdependence (H2)				1.50
High	16	0.24	[0.05, 0.43]		21.67	30.78
Low	10	0.43	[0.18, 0.67]		6.71	0.00
Task focus (H3)				10.54**
Maximizing	18	0.46	[0.30, 0.62]		25.70	33.85
Optimizing	8	0.04	[−0.16, 0.24]		4.73	0.00
Exploratory variables
Task type				2.22
Physical	5	0.57	[0.19, 0.94]		0.49	0.00
Cognitive	21	0.26	[0.09, 0.42]		27.14	26.31
Population				0.01
Children	6	0.32	[0.01, 0.64]		5.71	12.43
Adults	20	0.31	[0.12, 0.49]		21.20	10.38

Note. Positive effect size indicates that friendship groups performed better than acquaintance groups; k indicates the number of independent samples. CI = confidence interval.

p < .05. **p < .01.

Moreover, as shown in Table 2, there was significant heterogeneity among effect sizes (τ² = 0.13; τ = 0.36; Q(w) = 40.97; p = .02), suggesting that it is likely that there are moderators of the main effect (Hedges & Olkin, 1985; Lipsey & Wilson, 2001). Further supporting evidence of heterogeneity, I² statistic indicated a low-to-moderate degree of heterogeneity, 38.98% (Higgins, Thompson, Deeks, & Altman, 2003).

Hypothesized Moderator Analyses

To examine whether the benefit of friendship on group performance would be more pronounced for highly interdependent tasks (Hypothesis 2), we conducted a categorical moderator analysis. Results did not support Hypothesis 2, as the level of task interdependence did not significantly moderate the effect of friendship on group task performance (Q_b = 1.50, p= .22). In other words, the benefit of friendship on group performance did not differ between levels of task interdependence. Friendship groups were documented to perform better than acquaintance groups on both high interdependent tasks (d = 0.24; k = 16; 95% CI = [0.05, 0.43]) and low interdependence tasks (d = 0.43; k = = 10; 95% CI = [0.18, 0.67]).

We next tested whether the benefit of friendship on group performance would be more pronounced on maximizing than optimizing tasks (Hypothesis 3). When comparing the two different types of task focus, moderator analyses yielded a significant difference, Q_b = 10.54, p = .001, supporting Hypothesis 3. Namely, task focus was a boundary condition for the positive effects of friendship on group performance, with a significant positive relationship occurring for performance on maximizing tasks (d = 0.46, k = 18, 95% CI = [0.30, 0.62]) but not for performance on optimizing tasks (d = 0.04, k = 8, 95% CI = [−0.16, 0.24]). Put another way, these results indicate that friends perform better when working on maximizing tasks as compared with optimizing tasks.

To test our prediction that the benefit of friendship would be more pronounced as group size increased (Hypothesis 4), we conducted a continuous moderator analysis (Table 3). Supporting Hypothesis 4, the meta-regression analysis yielded a positive and significant effect of group size on group performance (b = 0.11, SE = 0.05, k = 26, 95% CI = [0.003, 0.216], R² = .15). This positive relationship indicates that the benefits of friendship on group performance became larger as group size increased.

Table 3.

Continuous Model for Effect Sizes (Random-Effects Model).

Predictor	Linear regression
Predictor	b	SE	95% CI
Group size (H4)	0.11	0.05	[0.003, 0.216]
R ²	.15

Note. b = unstandardized regression coefficient; CI = confidence interval.

Exploratory Moderator Analyses

We next examined what impact, if any, task type would have on the relationship between friendship and group performance. A categorical moderator analysis did not show a difference in how friends versus nonfriends groups perform across physical and cognitive tasks (Q_b = 2.22, p = .14). Friends performed significantly better than nonfriends groups when working on a physical task (d = 0.57; k = 5; 95% CI = [0.19, 0.94]) and on a cognitive task (d = 0.26; k = 21; 95% CI = [0.09, 0.42]).

Last, we also conducted an exploratory moderator analysis for participant population (children vs. adults). The relationship between friendship and group performance did not differ between populations (Q_b = 0.01, p = .93). Friends performed better than nonfriends in both groups of children (d = 0.32, k = 6, 95% CI = [0.01, 0.64]) and groups of adults (d = 0.31, k = 20, 95% CI = [0.12, 0.49]).³

Publication Bias Analyses

In addition to the overall main effect analysis and moderator analysis, we used multiple techniques to examine the potential impact of publication bias. First, we conducted Egger’s regression analysis (Egger et al., 1997) and Begg’s rank correlation test (Begg & Mazumdar, 1994) to statistically test for publication bias. Neither Egger’s regression test, p = .10, nor Begg’s rank correlation approach, p = .19, yielded evidence that publication bias affected the results. We next conducted Duval and Tweedie’s (2000) Trim and Fill analysis and found no adjustment for missing studies. That is, the Trim and Fill method imputed no “missing studies,” and yielded an observed point estimate of d = 0.31 (95% CI = [0.15, 0.48]), which was identical to the value from our random-effects analysis. Taken together, these results suggest that publication bias is unlikely to account for our findings.

Discussion

The current findings offer a generalizable view of the link between friendship and group performance, and provide additional evidence that reliably depicts conditions that moderate this effect in substantive ways. Overall, the proposed main effect describing the benefits of friendship on group performance was supported, and despite the mixed nature of the prior literature, our results indicate that there are performance benefits associated with friendship, which are generalizable across a variety of task characteristics and populations.

The relative performance superiority of friendship groups can be interpreted through a variety of explanations, none of which are mutually exclusive. Integrating theory and past research, we speculated that the benefits of friendship groups may stem from their members’ heightened abilities to coordinate resources and actions through shared knowledge and effective communication, and elevated levels of motivation. Some of these presumed characteristics of friendship groups have been documented in individual research studies (e.g., Harrison et al., 2003; Jehn & Shah, 1997), and the robust nature of main effect that we report is consistent with the notion that friendships allow members to bring to the table many of the group dynamics and processes that underlie productivity and effective performance.

Interestingly, while the relative performance advantage of friendship groups was found to be stable, the magnitude of benefits from this type of group composition effect did not occur uniformly. As hypothesized, we found support for the expectation that task focus (i.e., maximizing vs. optimizing tasks) and group size moderated the positive effect of friendship on performance. Our general depiction of friendship groups as social contexts that intensify commitment, self-efficacy, and intrinsic motivation also provides bases for understanding the relative performance superiority of friendship groups when tasks are maximizing versus optimizing. Maximizing tasks often require effortful persistence under conditions of strain, where workers have to continuously combat unwanted conditions like fatigue and potential boredom from behavioral redundancy. Because performance on maximizing tasks are largely a function of members’ abilities to self-regulate, our research suggests that friendship groups offer psychosocial resources that can ameliorate these aversive forces, namely, those that we used to describe friendship groups. Moreover, it is worth noting that friendship groups were not found to outperform acquaintance groups on optimizing tasks. This highlights an important boundary condition for the purported benefits of friendship for group performance, and one that has important practical implications for managers and practitioners alike. As such, on optimizing tasks, where success is based on a group’s ability to effectively coordinate, share information, and figure out a correct solution, friendship groups do not appear to have an advantage over ad hoc groups. In addition, on optimizing tasks, it may also be the case that motivation is a much less critical component for success as compared with its impact on maximizing tasks. Although our meta-analysis does not provide evidence on why friendship groups do not outperform nonfriends groups on optimizing tasks, we suspect that optimizing tasks may increase relational concerns which can accompany certain types of relationships between team members (Loyd et al., 2013) and ultimately limit the benefits of working with friends.

With regard to the greater benefit of friendship on performance as group size increased, we propose that these benefits stem from friendship groups’ ability, relative to acquaintance groups, to limit the threats to motivation and coordination which increase with group size. Studies have regularly documented that motivation and coordination problems decrease the effectiveness of larger groups, often leading practitioners and group scholars to conclude that group size needs to be limited. Our findings suggest that friendships between group members may be an important caveat to consider as group size increases. Namely, larger groups of friends may not succumb to the same motivation and coordination threats which limit the performance of larger ad hoc groups. It is important to recognize that our findings only focused on the performance of these groups, and we cannot show which process(es) underlies these differences.

Taken together, the results from our meta-analysis confirm the relative performance superiority of friendship groups and provide informative details about the conditions under which this effect is especially likely to occur. The current findings add to the large literature on the array of benefits that surround close relationships, but help to extend this area by emphasizing the benefit of friendships on task performance, rather than the ways in which friendships promote the psychological or physical well-being of a given individual. In this way, the current findings have implications relevant to work settings. For example, our results suggest that it may be advisable to facilitate friendship development during team building or corporate training, to encourage employees socialize with teams, and to perhaps explicitly recognize the value of socioemotional leaders.

Last, this work helps inform possible reasons for mixed findings in the literature. In addition to identifying that optimizing tasks are a boundary condition, we identified other moderators which affected the positive relationship on performance. Considering that our significant effects ranged from “small” to “medium” in size, it may be the case that some of the null effects in the prior literature are attributable to underpowered studies. Given the logistic challenges associated with bringing groups of friends to the lab and then comparing them with the performance of acquaintance ad hoc groups, the average sample size of groups that were included in the typical study in this meta-analysis was not large (M = 39.08). We suspect that the number of groups being studied in the typical study may have made it difficult to detect significant effects given the variability and overall small to medium effect sizes observed. As such, future work examining the impact of friendship on group performance may require larger samples than those typically examined in prior studies to be best equipped to detect significant effects.

Limitations and Future Directions

We believe the results of this meta-analysis are important for a number of reasons. In recent years, concern about the validity and reliability of individual research publications has been intensifying, along with a growing appreciation for the value of replication research. The numerous advantages that meta-analyses offer over single publications and replication studies for documenting the robustness of effects are particularly salient in the present climate, and calls for increased use of such analyses have been raised (Fabrigar & Wegener, 2016; Stroebe, 2016). We believe that this work provides an exemplary and timely response to such calls in part given that prior research on friendship and group performance has commonly relied upon small sample sizes and, as a literature, has yielded mixed findings.

As with any work though, the current study is not without limitations. For our meta-analysis, some of these are particularly reflective of the construct we chose to study. For instance, one possible limitation concerns the relatively low number of aggregated independent studies (i.e., independent effect sizes). The current analysis included effect sizes from 26 independent studies, which may seem low in comparison with other published meta-analyses. However, we suspect that the logistical challenges that are involved in recruiting groups of intact friends, and the need to form appropriate ad hoc groups for purposes of comparison, fostered the modest number of existing studies.

Although the study of friendships and group performance is important to advance, research that involves either, and nonetheless research that incorporates both, is challenging to conduct because of the need to access and obtain sets of participants who meet the necessary criteria. For these reasons, the sample sizes of studies that involve group-level outcomes can be relatively small, as a multitude of applicable participants are required to produce a single datum point. To address these obstacles, some researchers may simply accept the use of small sample sizes, choose to rely on scenario-based methods, or create imagined friendships and groups through the use of priming. As mentioned in the “Method” section, we chose not to include the latter two cases in our meta-analysis. Thus, within the empirical research that utilized intact friendship groups and interacting group members who performed a collective task, the average sample sizes per study were small. This can raise concerns that the overall effect size of a meta-analysis may be upwardly biased (Hedges, 1981; Lipsey & Wilson, 2001), but given the methodological obstacles that researchers of friendship groups face, we strongly believe in the merits of a meta-analysis to characterize more reliable and replicable depictions of group phenomena over a single study, and believe this is consistent with the current call for such publications.

Given the potential for friendship ties to produce a range of interesting and applicable effects, the directions for future research are many. For instance, with the presumed ability of friendship ties to induce numerous types of commitment and motivation, outcomes such as satisfaction (Winstead et al., 1995), intentions to leave the group (Riordan & Griffeth, 1995), and prosocial behaviors could be measured and compared across group types. Although we expect that communication processes are enhanced within friendship groups, friends clearly enjoy socializing. Therefore, it is conceivable that friendship groups display performance superiority when they are granted ample time for task completion, yet perform rather poorly when faced with challenging time constraints that require a strict task focus. The social exchange rules that govern friendships can also differ, and it is conceivable that these and other norms exert interesting and informative effects on how friends think, feel, and behave when they work together.

Last, we believe this work has implications for managers and practitioners interested in how to compose workgroups. A common concern among those who are responsible for forming groups (e.g., teachers and managers) may be that having people work with their friends will lead to lower performance as group members may be more interested in enjoying their time together rather than focusing on performing the task at hand. Although we suspect there are likely individuals who may be inclined to encourage one another to take it easy when working with friends, our results show there are clear performance benefits associated with working with friends. In addition, for teams composed of acquaintances as compared with teams composed of friends, there may need to be more attention given to rules that help teams overcome the potential limitations associated with motivation and coordination threats. We have suggested that these threats are more pronounced in acquaintance groups than friendship groups. As such, acquaintance groups may benefit greater from actions aimed at reducing threats to motivation (e.g., making individual performance contributions visible) and those that can improve coordination/communication (e.g., assigning a devil’s advocate). Moreover, consistent with the oft-stated phrase, “The more the merrier,” composing larger groups of friends seems to only enhance this benefit. With that said, a remaining question is how many group members or what proportion of the group needs to be friends with one another for such benefits to occur? Future work will be needed to answer these questions, and we see unpacking the dynamics of larger friendship groups, and their possible compositions, as being an important and worthwhile area for future work which will have basic and applied contributions.

Conclusion

Given the ubiquitous employment of groups and teams across domains in life, it is important to acknowledge the relative performance advantages of friendship groups so that groups can be composed more effectively through consideration of such relevant variables. The current findings contribute to the group composition literature by featuring effects from variables that are interpersonal (e.g., friendship ties) rather than intrapersonal (e.g., individual differences, expertise level) in nature. To advance the literature on group performance, it is critical to integrate interpersonal concepts because close ties often develop from group work, and these meaningful relationships are likely to produce a cascading range of effects on how group members think, feel, and behave. In the current article, we hoped to stimulate increased interest in variables with an interpersonal nature by summarizing ways in which the close and unifying bonds that exist between persons can positively affect the performance of a collective.

Footnotes

Acknowledgements

The authors thank Fabrizio Butera, Sarah Doyle, Howard Klein, Ray Noe, and two anonymous reviewers for their helpful feedback on earlier versions 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, authorship, and/or publication of this article.

Notes

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