Abstract
Just as social and organizational research has benefited significantly from evolutionary approaches, likewise an understanding of the evolution of teams can advance our knowledge of team formation and functioning. The current paper traces the multilevel emergence of teams as a unique type of group that evolved specially for complex task performance, outlines the evolved mechanisms that enable humans to use teams as a form of adaptive technology, and describes how teams leverage flexible structural adjustments and distinct human motives to tackle a wide range of challenges. We conclude by discussing the implications of this novel framework for team research.
Teams are among the most studied topics in organization and management research over the last four decades, a trend that continues unabated (Mathieu et al., 2017) with theoretical and methodological advancements paving the way for novel perspectives on team functioning (Chaffin et al., 2017; Cronin et al., 2011; Edmondson, 2012). This growth in team research has also taken the field to extreme environments. For example, some team scientists have recently taken their research to space, informing NASA about how astronaut teams should be managed given the long-term exposure of members to each other in tight spaces and the lack of escape mechanisms during missions (Salas et al., 2015).
While such advances have presented breakthroughs in our understanding of teams in different settings, it is important to remember that all teams continue to share basic underlying features. Indeed, as novel as such space-age teams may seem, little has changed fundamentally since the days of our evolutionary ancestors, who also had to form teams and work interdependently under resource constraints and in high-stakes environments. Early humans living in kin-based tribes on the African savannah similarly suffered from a lack of escape opportunities if collaborations with team members became contested and rife with conflict. Thus, there are important commonalities between teams working in very different environments, whether these teams are scouting the outskirts of the land, exploring the frontiers of the universe, or solving problems in a corporate office.
A consideration of the evolutionary origins of teams can lead to a better appreciation of how teams manifest and function. Evolutionary theorizing has already contributed significantly to our understanding of the closely related domain of human grouping (e.g., Brewer & Caporael, 2006; Kameda & Tindale, 2006; O’Gorman et al., 2008; Wilson, 1983). Despite the prevalence of evolutionary theory in group research, there are much less evolutionarily driven studies on teams, which is surprising because teams differ markedly from other broadly discussed human groups (Anderson & Franks, 2001; Caporael, 1997). 1 Whereas grouping can emerge relatively passively from generalized social mechanisms, the specific need to solve problems drives the formation of teams, or small groups with interdependencies between members in competencies, tasks, goals, and outcomes as well as the experience of a shared destiny (Ilgen, 1999). An ancestral hunting team, for example, had to perform; otherwise, the tribe would starve. Such tasks create shared purpose for which the best combination of individuals who could run fast, use spears, or detect prey assembled. The team does not need everyone to be good at every skill, but insofar as they can leverage each member’s expertise while working interdependently toward the end objective (e.g., a successful hunt), the team can succeed. Much can be extrapolated from these evolutionary foundations to understand teams today as well as in the future.
We open our discourse with a primer on the importance of thinking about evolved function when analyzing social and organizational phenomena. Following from the axiom that “nothing in biology makes sense except in the light of evolution” (Dobzhansky, 1973), likewise the intricacies of mind and social behavior cannot be fully understood without due consideration of the adaptive challenges they were designed for (Tooby & Cosmides, 1990). We then proceed with a conceptualization of teams as an adaptive technology used by humans to solve problems, followed by a discussion of our evolved mechanisms that enable effective teaming through multilevel evolutionary selection and flexible team structural arrangements. Through this analysis, we provide coherence to our assortment of adaptive psychological mechanisms, suggest the main factors that constrain team formation and functioning, and offer insights into when teams should be used, how teams can be optimized, and what the future of teams may look like.
The Utility of Evolutionary Theory in Social and Organizational Behavior
At first glance, our digestive system looks like a complicated mass of tissue. Analysis might discern distinct physical and sensory components, such as the gastrointestinal tract, stomach acid, and hunger pangs, and establish predictability over these components, such as the tendency for the gastrointestinal tract to move matter into the stomach through peristalsis. Many of us know these phenomena because we have learned that the system functions to process food sources for nutrition. This overarching knowledge facilitates our understanding of why certain features are in place and how they relate to one another. While this example may seem obvious to most readers, it shows that failure to appreciate evolved function would do our understanding of the human body a huge disservice. The evolutionary biologist and Eastern Orthodox Christian Theodosius Dobzhansky thus wrote in 1973 that “nothing in biology makes sense except in the light of evolution”, and indeed much of the surface-level chaos of the biological landscape falls into place only through an evolutionary lens. More broadly, the observed diversity of life—which emerges from combinations of only a few genetic letters in DNA and RNA—and its distribution throughout Earth make sense only when viewed in the context of evolution.
Many decades would pass before evolutionary thinking crossed over into mainstream social and organizational research, a delay that was partly due to the prevailing belief that the mind and body are separate (Robinson, 2003). However, it is increasingly accepted that the mind is also an evolved adaptation like any other body parts—shaped by evolution to enable the pursuit of survival and reproductive objectives. And just like our evolved physical traits, the mind is comprised of evolved psychological mechanisms (e.g., emotions, preferences, cognitive biases) that enabled early humans to survive and reproduce better (Haselton et al., 2005). As descendants of ancestors who thrived and successfully passed on the genes encoding these psychological traits, they also exist in us today (see Crawford & Salmon, 2004 for fuller discussions of evolved adaptations).
Prior to the advent of evolutionary models of human behavior, there existed a glut of disparate social theories guided by the view that either personality traits or socialization (then also widely and loosely referred to as culture) drove psychology and behavior (Tooby & Cosmides, 1992). This status quo suffered from two problems. First, although these social theories can be rich and highly descriptive, they each focus on highly specific psychological or behavioral aspects and are useful only within a particular context. For instance, early social theories explained aggression as either a dispositional male tendency shaped by gender roles (Campbell & Muncer, 1994) or a form of deviant or antisocial behavior (Kaplan, 1967). The evolutionary perspective, however, understands aggression as an offshoot of male intrasexual rivalry, which accounts for the sex difference while revealing a “young male syndrome” where violence is characteristic of men competing for mates (Farsang & Kocsor, 2016; Wilson & Daly, 1985)—a finding that would have been obscured if not for evolutionary theorizing. Social theories may also come into opposition, such as when some theories predict that humans seek to subsume under a group (Baumeister & Leary, 1995) while others argue that humans want to differentiate themselves and stand out (Snyder & Fromkin, 1980). Detailed taxonomies of these distinct social tendencies have been provided (e.g., Ellemers et al., 2002), but without an overarching framework, it is impossible to adjudicate between them, specify the conditions under which some theories would be more valid than others, or establish unforeseen linkages between them. The result of such unbounded theorizing is an excess of theories that shuffle between explanations, each with their own subjective level of plausibility and little incremental value.
Second, social and organizational theories that lack evolutionary considerations are limited to explanations at the proximate level. That is, they describe or explain behavior at the surface without due consideration of the ultimate reasons for why those behaviors exist (Scott-Phillips et al., 2011). Theories run into problems when they do not address explanations at a fundamental level. For example, one proximate explanation for behavior that was widely used between the middle and end of the 20th century was “culture” (cf., Kenrick, 2020). That is, it was commonly reasoned that people have particular preferences or act a certain way because of the culture they come from. However, failure to rigorously unpack culture often resulted in tautology as the cultural basis of behavior is inferred from the behavior itself (van der Linden, 2016). Moreover, explanations can also become overly broad or all-encompassing when they are not bounded by more fundamental premises, causing them to explain almost anything and resulting in nothing being explained at all (Popper, 1959). Unbounded theories also create a false sense of flexibility over associated constructs. For instance, there was optimism that social ideals such as gender equality could be achieved by changing cultural notions of men and women. Yet, despite many decades of social activism, it is clear that biological sex differences underlying gender inequality are persistent beyond social perceptions and cultural definitions (Schmitt et al., 2012). Evolutionary theory overcomes these problems by focusing on the selection of traits for survival and reproduction as an ultimate explanation for psychology and behavior. In doing so, the rigor of theories is improved by establishing their deep functional basis (e.g., culture is a mechanism that propagates adaptive behaviors or knowledge within a specific ecological context) and their boundary conditions (e.g., culture is constrained by biological factors).
Beyond addressing these limitations of social and organizational theories, evolutionary approaches are also vital in explaining the emergence of complex morphologies and systems. Increasing complexity in form and function is essentially an evolutionary process where advanced or higher-order forms arise from simpler or lower-order versions due to mechanisms that enable this transition and benefits afforded to the organism while in the higher-order form (Brewer & Caporael, 2006; Buss, 1987; Szathmáry & Maynard Smith, 1995). However, much of the social and organizational sciences has inadequately addressed the dynamics that underlie complex phenomena and instead focused on static and cross-sectional relationships that are isolated from the environment in which they are embedded (cf., Cronin et al., 2011). From an evolutionary perspective, it is incomplete to say that a particular factor (e.g., male dominance) correlates with some outcome (e.g., reproductive success); instead, it is necessary to outline how outcomes manifest from those factors (e.g., dominance translates into resource acquisition ability among males, and females are attracted to males with resources; hence reproductive success is higher for dominant males and females who mate with such males). These shortcomings have been increasingly recognized by organizational scholars who study group outcomes using multilevel selection approaches (e.g., Brewer & Caporael, 2006; O’Gorman et al., 2008) and input-process-output and input-mediator-output-input models (e.g., Ilgen et al., 2005; Mathieu et al., 2000; McGrath et al., 2000).
Taken together, evolutionary theorizing can prompt a better understanding of how the various social and organizational accounts interlink under an overarching framework and encourage exploration of emergent processes. The current paper sought to illustrate how an analysis of teams through an evolutionary lens can similarly advance our knowledge of teams and generate novel team insights.
Teams as Adaptive Technology
Evolutionary analyses begin simply by asking: If a human feature appears ubiquitous, for what specific purpose might it have been designed to serve? The widespread tendency of humans to form teams suggests that adaptive challenges were in place that made teaming capacities important for survival. According to Hinsz (2015), teams serve most fundamentally as a form of technology to help humans take advantage of their innate capabilities and solve adaptive problems. The human proclivity to create and use technology is uncontroversial—indeed, our history comprises numerous technological milestones including the Stone Age, Bronze Age, Iron Age, agricultural age, industrial age, nuclear age, and information age, each one marking our adoption of new devices and means to accomplish objectives more effectively. However, long before any of these technological ages, humans were already armed with the use of teams to solve a myriad of problems. Technology is often conceived as complicated instruments or advanced machinery, but a broad definition of technology refers most fundamentally to the use of methods, materials, and devices to solve practical problems or accomplish tasks (Hinsz, 2015). From this broad view of technology, the use of teams can be regarded as a method or process for solving practical problems. In particular, teaming affords humans a means to achieve goals that they cannot accomplish (or would accomplish less efficiently) otherwise. Collaborations can be simple (e.g., one person lifting up another to reach high-hanging fruit) or complex (e.g., a group of individuals carrying out specialized roles and coordinating their efforts to run a business), but because of the significant adaptive benefits of teams, humans evolved to readily form teams, engage in teamwork, and use teams like they do for other technologies to solve problems. This proclivity is so innate that humans are born teamwork-ready—young children do not have to learn about teaming before they can engage in it (Sherif et al., 1961), and people team up often with little conscious effort required (Moreland et al., 1998).
To be sure, humans are not the only organisms capable of teaming. Nonhuman animals have been observed to organize into teams to accomplish objectives (Anderson & Franks, 2001), and impressive collaborations can arise from individual organisms simply abiding by basic decision rules. For instance, fish can achieve safety in numbers by swimming in swarms, thereby creating a general defense against predation. No higher-order concept of a swarm or desire to form swarms is needed; fish simply follow the decision rule, “if conspecifics are nearby, swim close to them”, and the emergent outcome of every fish’s individual adherence to the decision rule is a formidable swarm. Social animals can also share an understanding of task concepts and coordinate their actions to achieve desired and highly specific outcomes. In experiments where two capuchin monkeys are separated by a transparent wall with a hole through which items can be passed and one is given a sealed box of nuts while the other is given a sharp flint, they often figure out that the nuts can be reached if the flint is used to cut through the lid (De Waal, 2016). Hence, one monkey must entrust the tool to the other and hope that, after successfully opening the box, the spoils will be shared. These capuchin monkeys regularly demonstrate that they are willing to risk giving the flint away so that their counterparts can retrieve the nuts, and those with the nuts also demonstrate a willingness to hand over a fair share of nuts to their cooperative counterparts. In chimpanzees, up-and-coming males often share similar desires to usurp the aging alpha male and claim the dominant share of mating opportunities and resources (De Waal, 1996). With relatively rudimentary communication capabilities, young male chimpanzees can gang up to achieve their shared goal, and chimpanzee politics are marked by repeated cycles of this timeless struggle. Importantly, their ability to form alliances, coordinate actions, and strategize attacks clearly reflects teaming capacities.
While examples of teaming among nonhuman animals are numerous and certainly impressive, human teams are arguably more formidable and capable of tackling diverse and complex problems that require cooperation over extended periods of time. On the one hand, human teams are highly effective simply because they consist of humans, who have greater cognitive and problem-solving capabilities than animals at the individual level. On the other hand, humans have evolved psychological features that enable teams to extend beyond the sum total of their individual human capabilities (Steiner, 1972). Even if not everyone knows how to tackle a problem, all it takes is for one individual to know how to do so and critical information can be disseminated so that team members can work together toward solving the problem. The ability to transmit information intergenerationally also enables humans to work on long-term problems that outlive themselves (Tam, 2015). And when it is not clear how a problem can be overcome, teams have multiple minds to come up with solutions. These psychological features enable humans to form and work in highly effective teams, thereby establishing teams as a powerful adaptive tool in our technological repertoire.
Despite the clear adaptive functions of teams, the team literature has yet to produce a thorough account of teams from an evolutionary perspective. This oversight is disconcerting as many of the commonly yet disparately studied team topics, such as teams as problem-solving devices and the various team processes and outcomes, can be synthesized within an evolutionary framework. We also believe that part of the reason for the lack of evolutionary team frameworks is the tendency to view teams like groups, for which a mature evolutionary research agenda already exists (e.g., Brewer & Caporael, 2006; Conradt & Roper, 2003; Kameda & Tindale, 2006; O’Gorman et al., 2008). Hence, it is worth noting at the outset that although teams and groups share many commonalities, they have important differences. In contrast to groups, whose members are relatively homogeneous and passive consumers of the structure in which they operate, teams have higher levels of interdependence among members across various dimensions, including task interdependence, centralized decision-making, outcome interdependence, spatial interdependence, and temporal interdependence (Hollenbeck et al., 2012). By extension, this interdependence produces perceptions of a shared history and future, or perceptions of shared fate (Hackman, 2011), which enable teams to reconfigure their workload allocations, structure, and decision-making processes as the team sees fit (Bunderson & Boumgarden, 2010). With this research gap in mind, we aimed to provide an account of teams that demonstrates the utility of evolutionary theorizing and sheds light on the unique features of teams that differentiate them from groups. Having said that, commonalities between teams and groups necessitate the use of arguments from the group literature whenever they apply to teams.
Evolutionary Processes and Adaptive Mechanisms that Enable Effective Teaming
An evolutionary account of teams requires first an understanding of how humans evolved to form groups, without which teaming arrangements cannot exist. In this section, we expound on the emergence of groups through multilevel selection processes and the various ways that human groups configure themselves. From these grouping proclivities, we describe how teams arise as a unique group that specializes in problem-solving and elucidate the adaptations that not only facilitate teamwork but also enable teams to achieve high levels of performance and effectiveness.
Multilevel Evolutionary Theory
In 1987, Leo Buss spearheaded an account of group-level selection that went against the dominant view of individual or “selfish gene” selection held by his evolutionary contemporaries. In brief, it had been argued that group selection could not work because any organism that had variants that cared more for the group than itself would be outcompeted by variants that were more selfish (cf., Wilson, 1983). Noting the limitations imposed by this narrow view on the study of group dynamics, Buss argued that biologists had taken complex multicellular life for granted as the multicellular individual itself attests to higher-order levels of selection. Indeed, multicellularity exists because initially self-replicating units found ways to consolidate and organize themselves. Mitochondria, for instance, are cellular structures that were initially autonomous units until they merged with and became dependent upon replicating cells. Such consolidations confer significant adaptive benefits as they enable lower-order entities such as mitochondria to exploit the environment in a manner that would otherwise be unavailable if they had remained disordered. Hence, advantages that exist at levels beyond that of the individual (whatever the individual unit is—mitochondria, human, or otherwise) may select for mechanisms that enable individuals to overcome barriers to organization and gain those benefits.
The shift from selfish gene-based selection models of evolution to multilevel evolutionary models brought to light the dynamic factors that are associated with transitions from lower-order to higher-order forms (Jablonka, 1994; Szathmáry & Maynard Smith, 1995). At a morphological level, the eye represents the evolution of photo sensors into more advanced forms that conferred greater benefits by detecting light stimuli at higher resolutions. In turn, the rest of the organism co-evolves with these enhanced visual acuities, such as the ability to detect prey from afar in birds or the development of reading capabilities in humans. In mating dynamics, an assortative mating equilibrium, or the aggregate tendency for individuals with similar mate values to pair up, occurs from all actors in a mating market pursuing the highest quality mates (Simão & Todd, 2003). Subsequently, as being similarly matched affords benefits such as relationship stability, psychological mechanisms like love and partner idealization co-evolve to facilitate those emergent outcomes (Murray et al., 1996). These insights can similarly be applied to understand how human groups form as well as the psychological adaptations that co-evolve with grouping.
Group Emergence from a Multilevel Evolutionary Perspective
From a multilevel evolutionary perspective, higher-order organizational forms are aggregate entities that emerge through forces that operate not on the aggregate entity per se but on the lower-order entities that make up the aggregate (Brewer & Caporael, 2006). Such self-organizing processes are argued to be non-purposive; “rather, the eventual higher order structure is an unintentional, yet inevitable, by-product of lower order processes” (Schaller & Latané, 1996, p. 65). Hence, people need not be conscious of any downstream, higher-order outcomes of their individual behaviors (e.g., judgments, decisions, preferences), and these higher-order outcomes also need not serve as reasons for any intentional enactment of those behaviors. Yet, through the individualistic pursuit of lower-order preferences that are coincidentally conducive to higher levels of organization, individuals can end up in groups and reap the benefits that are only available in a grouped state. These benefits may then exert a selective force on the lower level psychological mechanisms that enable individuals to organize. Multilevel evolutionary theory therefore provides an elegant framework of group formation without invoking the questionable argument that individuals evolved to act “for the good of the group” (Wilson & Wilson, 2008, p. 380).
Selective pressures at different levels work in concert to drive grouping in humans (see Figure 1). Benefits must exist at the higher or group level for grouping to exert selective pressure on constituent individuals. As the natural environments inhabited by our evolutionary ancestors were often impoverished and unforgiving, group living served as a buffer between individuals and the natural habitat, thereby affording a better chance of survival to individuals belonging to groups. Moreover, many adaptive tasks that early humans had to undertake, including hunting prey, finding shelter, acquiring ecological knowledge, and monitoring for predators or enemies, were better performed as a group (Jarvenpa, 1977).
Multiple selective pressures at lower and higher levels of organization.
Although benefits exist at the higher-order state, they exert an insufficient force on grouping. Without lower-order mechanisms that make individuals stay grouped, the costs of grouping will outweigh its benefits. For instance, creating and maintaining bonds between individuals can be effortful, and individuals living in groups are vulnerable to conflicts due to differing interests (Korsgaard et al., 2014) and exploitation by free riders (Bowles & Gintis, 2011). As such hindrances create disincentives to grouping and undermine group integrity, the group context becomes an adaptive problem in which barriers to grouping or problems caused by grouping itself must be solved. We describe five mechanisms that co-evolved to reduce the costs of grouping and enable humans to attain the benefits associated with groups:
Need to belong
The need to belong is one of the strongest human needs and manifests as an instinctive motive to be close to others and form interpersonal relationships (Baumeister & Leary, 1995). Group formation can occur from the satisfaction of this simple need when people act out their individual desires to form bonds, interact, and be in close proximity with others. In turn, these individuals, now grouped together, can then gain the higher level benefits made accessible by their interactions and togetherness. This need is so strong that people are hypersensitive to being socially excluded. One study found that participants who were exposed to ostracism cues reported feeling emotional distress, physical pain, and even sensations akin to death (Spoor & Williams, 2007). Research on human motivation also demonstrates that the need to belong underlies self-regulatory processes that dictate both the implicit and explicit pursuits of life goals (DeShon & Gillespie, 2005). These findings emphasize the importance of being valued as a group member for survival.
In-group identification
Once humans are grouped, group identity keeps individuals bonded by enabling them to see each other as similar (Brewer, 1993). An offshoot of in-group identification is the tendency for people to view others either as part of the in-group or as out-group individuals, which is responsible for stark differences in people’s social attitudes and approaches. A relatively benign expression of in-group bias is the expectation that in-group members are good and can be trusted, but in its more malignant form, group identification underlies people’s aggressive actions against out-groups (Hertel & Kerr, 2001; Tajfel & Turner, 1986). The experience of comradeship among in-group individuals and hostility against out-group individuals co-evolved under the selective context of intergroup competition, which is another basis for grouping as being part of a strong group negates the threat of other groups.
Generalized exchange systems
As individuals enter into prolonged states of grouping, adaptations are required to facilitate exchanges between individuals. Groups wherein members invest in others without knowing whether the investment will be reciprocated require elaborate coordination mechanisms and exchange rules (Flynn, 2005). However, as negotiating the rules of exchange for every interaction is time consuming and costly, negotiated exchanges are suboptimal. Requiring beneficiaries to reciprocate past favors may also be suboptimal if they are not in a position to reciprocate or the group would benefit more from other value-creating activities performed by them instead. Generalized exchange systems go beyond negotiated or reciprocal exchanges by compelling all group members to assist others, regardless of whether the other person has accrued a net positive balance through past investments into the group. In other words, generalized exchange systems require group members to invest in others without knowing if, from whom, and when they will receive this investment in kind. Generalized exchange systems are superior to negotiated or reciprocal exchange systems because they are not only more efficient but also reinforcing of solidarity and identification with the group (Willer et al., 2012). Importantly, generalized exchange systems are only possible if individuals are willing to invest in the face of uncertain reciprocation. The need to belong and in-group identification make such investments under uncertainty possible as group members define part of their identity through group membership, and the more interdependent group members are, the more likely that generalized norms of exchange will benefit individual members and the group as a whole.
Free rider suppression
Although collective action carries adaptive benefits for individual members, “participation in group activity is often described as a sacrifice of personal utility” because of a trade-off between cooperative behaviors that serve group interests and selfish, individualistic behaviors that undermine the group (Kameda et al., 2011, p. 76). As groups form, opportunities to free-ride on those who are willing to fulfill their social obligations inevitably present themselves (Olson, 1965). The crux of this social dilemma is that the payoff to an individual group member is less when he or she cooperates than if he or she acted as a free rider, despite the overall group welfare being larger when all members cooperate than when nobody cooperates (Camerer, 2003). Hence, group stability and cooperation require free rider suppression mechanisms that make the benefits of collective action outweigh those of free-riding and non-cooperation. While such mechanisms can operate by either increasing the benefits of cooperation or reducing the benefits of free-riding, the latter has been found to be not only more effective but necessary, particularly by making free riding costly through sanctioning and reputation systems (Bowles & Gintis, 2011). For example, punishments through expensive fines for polluting the environment or jail terms for committing robbery decrease the likelihood that people will take advantage of group membership at the expense of others. Incurring a reputation as a free rider is also detrimental to one’s group membership and subsequent welfare as it leads to ostracism or expulsion, thereby protecting the integrity of the group. Indeed, studies show that group contributions deteriorate over time in the absence of punishment (e.g., Camerer, 2003; Herrmann et al., 2008). By disincentivizing free-riding and upholding norms of cooperation, people are more likely to act in ways that sustain the group and make group membership beneficial for all.
Collective action heuristics
Grouping may also be costly if group members are unable to reach consensus over collective action. One heuristic that groups utilize is the majority rule, which may have evolved because of its efficiency compared to other decision-making alternatives (Hastie & Kameda, 2005). In particular, the majority rule delivers high levels of decision accuracy despite requiring as little cognitive and social effort as simply following any random member. Especially for problems that require a survey of diverse opinions or the agreement of group members, majority rule quickly generates an informed collective decision and commitment to the decision. Social animals have also been observed to follow this democratic approach. Gorillas vote on where to go based on callings, and when they reach a consensus of approximately 65% among adults, the entire group starts to move in the direction of the consensus (Conradt & Roper, 2003). From observations of group decision-making in the Mae Enga tribe in New Guinea, Boehm (1996) noted that majority rule was highly instrumental as it allowed members to feel that their opinions mattered and promoted acceptance of group decisions at the same time.
The tendency for humans to enter into hierarchies and follow leaders functions as another collective action heuristic. By giving up some autonomy to the group under the rule of a leader, group members can minimize conflict and quickly achieve alignment in direction and strategies (Van Vugt & Ahuja, 2010). In ancestral contexts, leaders typically emerged from young males who rose the ranks to become the alpha, and this process often involved outmuscling rivals, participating in and leading hunts and invasions, and protecting the group. As these capabilities were pertinent to dealing with harsh natural environments and the threat of enemy tribes, survival benefits could be gained by going along with physically formidable leaders. This heuristic has persisted into modern times as corporations seem to prefer hiring taller and dominant-looking men as managers and CEOs (Spisak et al., 2011). By following these collective action heuristics, individuals in groups can overcome differences, align themselves, and act cohesively as a unit.
In summary, multilevel evolutionary theory specifies that groups emerge from the simultaneous allure of higher-order benefits and support of lower-order mechanisms that facilitate and reduce the costs of grouping. Importantly, the theory does not state that individuals are driven by any explicit desire to organize into groups. Instead, simple processes that operate on individuals produce sufficient social glue to keep people grouped, grease relations between individuals, and minimize costs associated with cooperation. In turn, individuals who can maintain themselves in a collective state may then reap the benefits that are accessible only to groups, which further provides an evolutionary impetus that selects for the lower level processes responsible for grouping.
Adaptive Core Grouping Configurations
The ways by which human groups structure themselves vary according to specific adaptive contexts. Noting consistencies in how individuals ranging from traditional hunter-gatherers to modern scientists formed groups, Caporael (1997) proposed four core configurations of human grouping, each one aimed at addressing a particular adaptive context, and highlighted the psychological processes that co-evolved within each context. Specifically, humans routinely organize into dyads, task groups, bands, and macrobands—each with their own set of evolved processes for the tasks they confronted. Dyads are for mating, infant-mother interaction, and close friendships where human capabilities support microcoordination, including emotional contagion, mimicry, and somatic synchronicity. Task groups, which organize around a small number of individuals, are used to execute tasks in dynamic environments that carry a degree of unpredictability and require specialized skills or flexible decision-making, such as foraging and hunting. During engagement in task groups, human capabilities function to coordinate cognition and action among members to enhance groupwork and performance. Bands comprise 30 to 50 individuals (6–10 families), which are the smallest self-sustaining units of domestic life. Adaptive tasks such as childrearing, the formation of task groups, and accumulation of detailed knowledge of the local habitat were carried out by bands where collective identity and social norms evolved to promote cohesiveness among members. Macrobands, which consist of multiple bands, are the only organizational form that do not require regular face-to-face interactions. Instead, macrobands are formed seasonally for a short period of time by congregating bands through common linkages such as ethnicity and linguistic affinity. Group identification allows constituents of a macroband to maintain depersonalized relationships with others by virtue of universal membership and facilitate efficient trades of goods between people.
Jarvenpa and Brumbach’s (1988) observations of the Chipenwyan Indians, a hunter-gather community, provide a useful description of how these core configurations enable humans to address a variety of adaptive problems. Endowed with abundant food and favorable weather during summer, different tribes aggregate and form a temporary yet concentrated regional gathering (i.e., the macroband) in which they engage in intense socializing, renew extended family bonds, and reaffirm themselves as members of the Chipenwyan community. As the weather cools, groups of five to ten families (i.e., bands) head toward home dwelling sites known as winter staging communities. From late September until May the following year, the staging community forms, dispatches, and supports winter hunting groups comprising three to five men from different households (i.e., task groups) that embark on trips spanning multiple weeks to hunt for food and fur. These configurations are also present in modern organizations. Relationships exist between coworkers (dyads), teams form to tackle specific tasks (task groups), departments manage the day-to-day functions of multiple teams (bands), and all of these activities occur within the organization as a whole (macroband).
Teams as a Specialized Configuration for Dynamic Problem Solving
While most of the abovementioned configurations function to deal with recurrent and predictable problems that existed throughout human evolutionary history (e.g., mating, childrearing, group living), task groups are uniquely specialized to enable humans to address novel, unpredictable, or dynamic challenges. The task groups that Caporael identified in her assessment of hunter-gatherer societies correspond notably with teams that are studied in the team literature, which are often defined as small groups of individuals who interact cooperatively and adaptively in the pursuit of shared task goals (Cannon-Bowers et al., 1993). Task groups also contain the key interdependent elements of teams, in particular clearly defined roles and responsibilities where members contribute relevant knowledge and skills, which differentiate this particular organizational form from larger groupings characterized by group member homogeneity and interchangeability. Thus, as collective units that exist specially to perform complex tasks, task groups or teams are essentially the sharpest tool in the shed—called upon to leverage their high levels of problem-solving effectiveness and accomplish tasks where the other configurations do not suffice.
Evolved Mechanisms for Team Formation and Functioning
Like all other organizational entities, teams also emerge from multilevel selective pressures at higher and lower levels. As one particular type of human group, teams are similarly facilitated by grouping mechanisms such as the need to belong, free rider suppression, and group decision-making heuristics, which enable team members to feel connected to one another, derive shared identity, and act collectively (Rink & Jehn, 2010). However, the higher-order motive that specifically demands the team entity is the need to solve dynamic problems that require effective decision-making and coordination among constituent individuals. Therefore, these problem-solving benefits are accessible only when processes that operate on individual team members enable them to not only band together but also perform well together. More specifically, teams require mechanisms that enable members to work interdependently and maximize each member’s capabilities so that task objectives can be achieved. Accordingly, the psychological processes identified by organizational scientists that facilitate teamwork can be viewed as evolved mechanisms for effective coordination and decision making that enable humans to gain the adaptive benefits of teaming. We consider the following well-studied team mechanisms:
Distributed cognition
Teams expand their cognitive capacity when members are assigned specialized roles for the encoding, processing, and retrieving of different information (Hinsz et al., 1997). Like the human brain where unique information can be stored in different places and retrieved for further processing whenever needed, team members’ unique knowledge and skills can be utilized for specific task demands. That is, beyond the meta-knowledge of individuals (i.e., knowing what I know), distributed cognition as the meta-knowledge of teams (i.e., knowing who knows what) allows members to recognize and exploit the cognitive caliber of teammates. A study on human groups tasked with assembling transistor radios found that 30 minutes of group interaction on the task was enough for teams to form meta-knowledge such that they could coordinate their efforts more efficiently and outperform individuals working alone (Moreland et al., 1998). Other social animals have similar characteristics. Observations of teamwork between capuchin monkeys, for example, indicate that they can understand the knowledge of others, use this knowledge to modify their behaviors, and maximize rewards (De Waal, 2016). However, humans are especially unique in that they routinely engage in cognitive coordination to work on different parts of a problem—a capability that undergirds our capacity to leverage functional role specialization, engage in division of labor, and tackle ever more complex tasks (Hollenbeck et al., 2002).
Shared task representations
Team members can develop “sharedness” heuristics, which serve as a unifying framework to efficiently integrate distributed members’ cognitions (Tindale & Kameda, 2000). While distributed cognition affords greater access to a large pool of information, this poses a challenge to the aggregation of different information from members, and teams that fail to resolve this overload of varying information are likely to flounder in task performance. Sharedness biases operate as fast and frugal cognitive devices for individuals in groups. In particular, teams possess cognitive heuristics such as shared information bias which allow consolidated decisions to be quickly formed based on team members’ diverse informational contributions (Stasser, 1999). Evidence for shared task representations date as far back as to the prehistoric era. For example, the Lascaux cave paintings are a preserved record of hunting groups in coordinated action during the Upper Paleolithic or Late Stone Age and may represent team goal-setting and strategic planning with detailed directions of arrows and spears onto the bodies of common targets (e.g., big cats, bison), akin to the maps and drawing boards used by military officials as they deliberate their next course of attack (Bataille, 2005). By creating shared mental models within the team, the coordination of unique expertise afforded by team members is further enhanced (Cannon-Bowers et al., 1993).
Leadership
As an extension of the group heuristic to follow key figures, leadership is another important mechanism that facilitates coordination among team members, particularly when there are significant barriers to spontaneous teamwork. For instance, teams may consist of members who are culturally or functionally diverse, leading to deficiencies in shared understanding of the task or one another’s capabilities (Cronin & Weingart, 2007). Leaders help to overcome such coordination obstacles by providing direction so that the team can proceed without members having to spend time resolving differences between them or acquiring full knowledge of the task. Moreover, team effectiveness can be enhanced when teams act according to the decisions of knowledgeable or competent individuals, thus serving as supporting agents that enable the team to function according to the capabilities of the best individuals (Belbin, 2003; Hollenbeck et al., 1995).
Leveraging Belongingness and Distinctiveness
An especially unique feature of teams as task-driven, problem-solving groups is that they are able to co-opt the mechanisms of various adaptive group arrangements and expand their capabilities. As units that sit in the middle of the various core configurations in terms of size, teams are able to leverage both the microcoordination features of dyads and the benefits of larger group sizes. Further reflecting this unique feature of teams, people can also achieve higher levels of effectiveness through teams when they utilize team settings to satisfy their evolved needs for belongingness and distinctiveness (Brewer, 2003). We had earlier discussed the need to belong as an underlying mechanism of group formation. At the same time, in the struggle for social status and resources, humans evolved to be individualistic and opportunistic (Hilbe & Sigmund, 2010). As an extension of these self-oriented motives, people perceive themselves in terms of their distinctive features and strive to exercise their individual autonomy (McGuire et al., 1978; Snyder & Fromkin, 1980). Teams serve as a means for people to pursue these often countervailing needs. On the one hand, emphasizing the team over individual members evokes perceptions of a cohesive unit in which team members are all pulling into the same direction, with little friction but also little consideration of individual needs. Such an arrangement promotes feelings of togetherness, the experience of a shared fate, and salient interactions with other team members. On the other hand, emphasizing individual members over the team satisfies the need to feel unique and distinguished (Snyder & Fromkin, 1980). Research shows that people achieve better well-being, functioning, and productivity when they satisfy both group and individual needs and experience an optimal level of distinctiveness (Brewer, 1993, 2003), and teams can function as a vehicle through which individuals pursue both of these needs, often simultaneously.
Team structural arrangements determine the extent to which the identity of the team or the identity of individual members is emphasized. At one end of the spectrum, tightly coupled teams that use functional structures, collective rewards, centralized leadership, and synchronous, face-to-face communication intensify connections among members and the salience of the team such that team characteristics dominate over individual members (Hollenbeck et al., 2012; Hollenbeck & Spitzmuller, 2012; Johnson et al., 2006; Spitzmuller & Park, 2018). The advantage of such tight coupling resides in the seamlessness with which team members work together, enabling teams to operate with reduced coordination issues. At the other end of the spectrum, loosely coupled teams that use divisional structures, competitive rewards, and decentralized decision-making emphasize the autonomy of individual members (Hollenbeck et al., 2012; Johnson et al., 2006; Spitzmuller & Park, 2018). When team members are decoupled from each other, the characteristics of individual members strongly influence the unit. Just as group orientation is adaptive for individual and team functioning, the need for individuality and distinctiveness can also be adaptive. Indeed, individuals can be a source of inspiration for teams when they deviate from established practices and group norms. Such non-conforming actions include voice behaviors (Van Dyne & LePine, 1998), dissent (Nemeth, 2018), proactivity (Crant, 2000), and innovation (West & Anderson, 1996). Furthermore, although team norms and cohesiveness enhance coordination, this can produce uniformity in perception and thinking and preclude the team from new ideas and flexible behavior. Conversely, individuals who are less tightly coupled into a team’s social relationships may establish connections with individuals outside the team more easily. Such boundary spanners are crucial conduits to the team environment as they develop social capital that can be crucial for subsequent team adaptation to changes in the environment (Marrone, 2010).
Studies show that teams respond to extreme experiences by gravitating toward their opposite, resulting in a tendency to oscillate between tight and loose structures (Hollenbeck et al., 2015). For example, if a team was characterized by high centralization, shared rewards, and high interdependence among team members, the team is likely to eventually demand structures that de-emphasize order and affirm individuality. Hence, teams have an in-built mechanism to respond to changes in their environment by adjusting the tightness of coupling and varying the extent to which belongingness or distinctiveness is emphasized. By simultaneously allowing individuals to satisfy both needs, teams enable their members to achieve not only optimal distinctiveness but also higher levels of task effectiveness through harnessing the potential of both human motives. Reflecting the pursuit of these various benefits, most teams settle on a moderate degree of order among team members as an equilibrium (Hollenbeck & Spitzmuller, 2012).
Discussion
The current paper sought to address the absence of evolutionary theory in the team literature and highlight its utility for the scientific study of teams. In particular, we showed that an evolutionary framework can integrate the many team factors that are often studied disparately (e.g., teams as problem-solving units, team psychological processes, team structural flexibility) and provide fundamental explanations for their emergence. By looking at the adaptive benefits conferred by teams, answers to many “why” questions become evident, such as why teams form and why particular psychological processes and organizational peculiarities are often found with teams. In short, the team literature stands to gain substantially from evolutionary considerations.
Further Implications and Directions of an Evolutionary Team Science
Through the evolutionary perspective, we elucidated the mechanisms that enable teams to function as an effective technology for humans to solve problems. However, technologies have their limitations depending on how they are designed and their suitability to the task environment. Hence, by understanding their underlying mechanisms, we can foresee the limits of teams and also think of ways to optimize the use of teams. In addition, a consideration of the fundamental aspects of teams can allow us to surmise what the future of teams may be.
Are teams always good?
An appreciation of the evolved mechanisms needed for teaming provides clues as to how or when teams may not be up to task. For instance, teams whose members do not share an understanding of the task or each other’s roles are unlikely to perform well. Being cognizant of how team and group mechanisms malfunction will also help in anticipating team ineffectiveness. For example, effective coordination among team members hinges on group mechanisms that promote cohesiveness (e.g., need to belong) and collective action (e.g., majority rule). Such mechanisms may skew the team from correct decisions if factors that undermine accurate judgments are present, such as misinformation or uncertainty (Yong et al., 2020). Strong cohesiveness when there is a large margin for error can be problematic especially when members with differing opinions fail to speak up because they are reluctant to oppose the majority view (Nemeth, 2018). Leadership mechanisms may also lead teams astray when members elect leaders according to stereotypical traits like height and dominance, which may be useful in ancestral settings but are less relevant today (Brescoll, 2016). The instinct to identify physically formidable males as leaders can undermine team effectiveness when other capable individuals (particularly females) with relevant traits such as task-based abilities are overlooked. Lastly, the core configurations model suggests that teams have an optimal size. As teams get larger and members feel that their contributions are dispensable, contributions to team performance may decrease (Latané et al., 1979).
How to make teams good?
A strength of evolutionary theory is its focus on fundamental mechanisms. Hence, when undesired outcomes occur, interventions adopting an evolutionary approach are likelier to get at the root causes rather than merely dealing with superficial symptoms (Li et al., 2020). When applied to teams, it is clear that mechanisms at the lower levels must be addressed, such as ensuring that team members share a common understanding or that teams comprise the right mix of members with the required knowledge or skill sets. This suggestion may seem obvious, but organizations often try to create teams in a top-down manner (e.g., forcing a group of individuals who do not identify with one another to work together) while neglecting the bottom-up, supportive mechanisms needed for teams to function well. Thus, the evolutionary perspective recommends a “back to basics” approach to ensure that teamwork-conducive processes are in place, such as getting members to feel a sense of belonging, identify with one another, and have sufficient team meta-knowledge. Team members may also lose motivation when the team becomes too big or is highly cohesive and members get along well with one another (Karau & Williams, 1993). Based on our understanding of team structural flexibility as a unique adaptive trait of teams, such motivational losses can be counteracted with adjustments emphasizing individuality and distinctiveness, such as divisional structures, competitive rewards, and decentralized decision-making, which reaffirm individual autonomy and personal responsibility in the team.
The evolutionary perspective also affords suggestions for futuristic teams such as astronaut teams. If all teams, no matter how old or new, are bound by evolutionary principles, then their opportunities and pitfalls, no matter how unprecedented, will remain predictable. A team of astronauts, who must execute highly technical tasks while co-existing in close proximity for a long time, may thus benefit from the timeless lessons of tribal hunting teams that similarly had to venture into the unknown, perform under pressure, and remain stuck with each other. Hunting teams have strong kinship ties and identification with a larger collective, which make members feel united, bound to common purpose, and cooperative. Hunting teams also have shared task representations and distributed expertise across members, which raise the likelihood of effective performance. As hunts are often high-stakes situations due to the danger of the activity and consequences for the tribe should they fail, hunting team members must be competent and know everyone’s roles well. Although a leader may generally orchestrate the team, members exercise high levels of autonomy so that the team can make fast and accurate decisions. These insights are useful for astronaut teams that must perform in stressful conditions for long periods. It will be important that the team is well bonded so that conflicts are minimized at the outset and actions can be better coordinated. Distributed expertise and shared understanding will be vital not only for executing tasks effectively but also for enhancing appreciation of each other’s value to the mission (Kanas et al., 2010). To balance against the interdependent nature of the team, structures that emphasize autonomy and individuality (e.g., decentralized decision-making) may allow members to feel unique and significant in the loneliness of space. Despite the alien conditions that astronauts find themselves in, they are still very much human beings under their spacesuits (Boyd et al., 2009). Thus, conditions that accentuate team members’ individual identities while keeping them focused on the collective objective can help to remind everyone that they are all in this together.
When are teams good?
Like any other forms of technology, it may sometimes pay greater dividends to use teams at the right time rather than to force their usage. Teams are well-equipped to work on tasks where they can utilize their greater information pooling capacities to rapidly achieve high levels of situational awareness (Hinsz, 2015; Kameda & Tindale, 2006). When faced with unexpected changes in the environment, teams afford members more courage through group solidarity to continue exploration as well as the cognitive apparatus through distributed storage of information and shared mental models to process diverse information. Shared information biases are particularly adaptive when members have access to diverse information and the division of roles and expertise is clear (Stasser, 1999), thereby enhancing the ability of teams to anticipate and respond to changes in volatile environments (Sunstein & Hastie, 2015). Thus, insofar as teams are not too large that motivation loss sets in, teams allow members to check and balance each other’s personal biases and judgment errors, leading to more accurate and reliable decision patterns over time (Hinsz, 2015). Airline cockpit crews are a good example of how teams are well-suited for complex tasks in dynamic environments (Ginnett, 1990). By assigning tight role boundaries with specific knowledge and skill sets to each member, a group of cockpit crew (i.e., captain, first officer, flight engineer, head flight attendant, and assistant flight attendants) who are initially unacquainted can proceed easily after a short briefing session. Such standardized team coordination allows airline crews to successfully complete their routine flight journeys and prepares them to deal with complexities from unexpected problems encountered during flights.
The future of teams
Evolutionary approaches emphasize the boundary conditions of human nature and thus stand in contrast to other perspectives that marvel at the seemingly infinite capabilities of humans. As aptly stated by the zoologist Desmond Morris, man is “in danger of being dazzled” by the “dramatic progression that led him, in a mere half million years, from making a fire to making a space-craft”—under the sheen of these undoubtedly remarkable achievements, “he is still very much a primate. (‘An ape’s an ape, a varlet’s a varlet, though they be clad in silk or scarlet.’) Even a space ape must urinate” (Morris, 1967, p. 15). As such, it is worth returning to how we began this paper—by putting so-called futuristic teams in perspective. Importantly, these teams can operate because the psychological processes that enable teaming are still very much able to function. As advanced technologies enable team mechanisms to work beyond the limits imposed by nature, modern teams undoubtedly appear impressive and have a sci-fi touch to them. Today’s computing tools enable team members to process information faster while cloud systems enhance distributed and shared cognition with larger pools of real-time data, information, and knowledge. The way we work as teams today, geographically dispersed all around the world, would be unthinkable to people who lived before the internet age. Hence, teams of the future may manifest beyond what is imaginable today, but they will go only as far as the problems they are tasked with and the mechanisms that facilitate teaming can continue operating on individual members with their human needs and limitations.
The COVID-19 crisis that has swept the world since the beginning of 2020 has also generated an intense discussion on the future of virtual teamwork. Some organizations such as Twitter and WeWork have announced that all of their employees will continue to work from home after the end of the pandemic, making virtual teamwork a necessity. While we do not question the merits of such decisions per se, our evolutionary approach suggests that reductions in face-to-face contact and spatial interdependence would have to be counterbalanced by emphasizing other tightness elements, such as task interdependence, centralization of decision-making processes, or outcome and reward interdependence. Only then will team members experience the sense of belongingness that is needed for cooperation to emerge and virtual teams to be effective.
Some Caveats
Multilevel evolutionary theory has been hotly debated for decades (Kramer & Meunier, 2016; Wilson, 1983). Some camps stress the centrality of second-order social dilemmas in multilevel selection and argue for the relevance of free rider suppression mechanisms such as altruistic punishment over other mechanisms (Bowles & Gintis, 2011). From this view, mechanisms such as the need to belong would constitute only an individual-level or ordinary selection explanation (e.g., belonging to a group simply reduces the risk of predation). The second-order problem is that even though grouping and successful team performance (through grouping and teaming mechanisms) bring benefits to members, free riders are better off as they receive benefits of team performance without contributing to it, and striving to eliminate free riders by punishing them still allows non-punishers (second-order free riders) to enjoy higher fitness than punishers, and so on.
Approaches that focus on second-order social dilemmas emphasize costs to cooperative group members and assume that group returns are linear in individual contributions (Dawes, 1980). However, the approach we adopt considers grouping costs that exist not only after grouping but also before grouping. Inclinations to be close to and identify with one another provide the motivation to come together and stay grouped, and if there was no benefit from being grouped (i.e., the higher level benefit), those inclinations (i.e., lower level mechanisms) would not be selected for. Moreover, some researchers have downplayed the centrality of the free rider problem in organizational dynamics. For instance, Kameda et al. (2011) argued that when people collaborate, productivity usually increases with group size, but the relationship is not always linear. The authors provide an example: “If one is camping with a group of 10 people, there are much larger benefits from the first and perhaps second person staying awake to warn the other campers about approaching bears than there are from the ninth and 10th campers, whose contributions generate virtually zero marginal benefits, staying awake” (p. 77). Using agent-based simulations that assume, more realistically, decreasing marginal group production as a function of aggregate individual contributions, Kameda et al. demonstrated that groups can stabilize and achieve high levels of performance with majority-plurality decision rules even if free riding is not sanctioned.
We do not suggest from these findings that free riding should be seen as trivial, but instead adopt a more moderate or perhaps broader stance that considers free riding as one among several other organizational problems, each requiring its own adaptive solution. While providing a comprehensive comparative analysis of the various perspectives of multilevel selection is beyond the scope of the current paper, we hope that acknowledging these diverse perspectives allows our work to be better situated in the literature and encourage further discussions in the field.
Suggestions for Further Research
The integrative nature of evolutionary theory makes it tempting to address the many linkages that are possible between team science and other psychological domains, but space constraints make such an endeavor impossible. More importantly, it is hoped that the current analysis provides firm foundations for further inquiry. One example is the linking of team and personality domains through an evolutionary lens. Because “dark” personality traits (e.g., narcissism, psychopathy, machiavellianism; Paulhus & Williams, 2002) are often detrimental at an interpersonal or dyadic level, they may have evolved not so much because of individual-level benefits (people incur costs when they cooperate with narcissists, and narcissists also incur costs when they are in turn punished for narcissistic behavior), but because they confer significant advantages at the team level. The first and second authors are currently examining the impact of dark personalities on team functioning and have noted that narcissistic members are motivated by competition and perform well under pressure, thereby contributing significantly to team performance in competitive inter-team contexts. Multilevel evolutionary theory also suggests that new insights in team personality composition may be revealed by looking at how team members vary their behaviors as a function of different grouping configurations.
Our list of group and team mechanisms is far from exhaustive. The literature includes many other important psychological processes that are well-documented to facilitate grouping behavior and team performance, such as trust (Hilbe & Sigmund, 2010), social norms (Tam, 2015), and communication (Salas et al., 2008). Many of these mechanisms overlap considerably as they work in concert to enable humans to organize and coordinate, but further research delineating how they work according to their evolved function promises deeper insights. For instance, larger collectives often enforce rules of cooperation in order for reciprocity norms to work (cf., Guererk et al., 2006). Must teams do the same to be effective? Our evolutionary analysis suggests that moderate coupling is both prescriptive and normative—teams converge on moderate levels of coupling without external enforcement or sanctioning due to the adaptiveness of such structures for team functioning. But to what extent do settings that require higher levels of coupling, interdependence, and cohesiveness among team members emerge naturally? And to what extent can they survive without enforcement mechanisms that reward cooperative team members and penalize rule breakers? Further research along these lines will prove to be illuminating.
Evolutionary arguments often surface to explain why organizations prefer tall, male, and physically strong leaders. There is no shortage of praise for the bold and courageous actions of leaders—often at the expense of tempered action—which perpetuate the myth of the strong man (Van Vugt & Ahuja, 2010). Similarly, the recent resurgence of populist leaders around the world appears to reiterate the human need for strong leadership. The persistence of such accounts raises the question of how and when humans are able to set aside archaic conceptualizations of teams, leadership, and member roles. Research that investigates the factors that move us toward more enlightened accounts of team functioning and leadership, such as life history and developmental experiences (Safra et al., 2017) or organizational interventions from an evolutionary perspective (Colarelli, 1998), would go some way toward addressing these questions.
A longstanding explanation for group formation is coalitional warfare, which proposes that intergroup threat is the primary reason for between-group selection to overcome the within-group selection that undermines group formation (Alexander, 1979). The multilevel evolutionary perspective argues instead that although intergroup conflict may create some impetus for humans to form groups, it is not required; the benefits of organization also include safety against harsh natural elements and solving problems through teamwork. That said, there are several other alternative evolutionary accounts that are worth considering, such as costly signaling (Gintis et al., 2001), biological market theory (Noë & Hammerstein, 1994), and prestige- versus dominance-based perspectives (Henrich & Gil-White, 2001). In all likelihood, careful evolutionary analyses will uncover coherence rather than conflict between these alternative theories and the one presented in this paper.
Lastly, revisiting the universalities between hunting teams, space teams, and other teams tasked with exploring new frontiers suggests that the erosion of teamwork can be proactively curtailed by evolutionarily enlightened measures, such as forging strong bonds between members through kinship (e.g., seeing each other as family) or collective identity (e.g., tapping on our common humanity). This is particularly important since interventions, such as the placement of psychologists onboard expedition missions to care for team members when they experience loneliness or other forms of psychological distress, mostly reflect a reactive approach. Moreover, rather than overemphasizing novelty when trying to understand new-age teams, which often prompts the search for new hypotheses of teamwork that are overly idiosyncratic and for which data are non-existent, we suggest that looking into our evolutionary past and focusing on common fundamental features affords a more grounded approach to formulating team hypotheses and pre-emptive measures that cultivate good team practices from the bottom up.
Conclusion
The current paper represents a novel foray into the development of an evolutionary framework for the study of teams through which the various mechanisms that underlie teams and their evolutionary processes can be better understood. Echoing Dobzhansky, this endeavor reveals that teams also make far greater sense in the light of evolution. By recognizing teams for what they most fundamentally are—an adaptive technology that has aided the survival of our species—we may better appreciate their place in the human condition.
Footnotes
Acknowledgements
We thank Dr. Norman P. Li and Hui Si Oh for their valuable comments and assistance on drafts 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.
