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Groups rarely use the unique knowledge of their members when making decisions, focusing instead on knowledge that members have in common. This tendency to neglect the expertise of group members severely limits the effectiveness of group decision making. Previously, this problem has been addressed by showing that groups will pool task-relevant information and make effective decisions if members have knowledge of each other's expertise. However, these studies are generally limited because they disregard why people use each other's expertise once they are aware of it. The current study uses expectancy theory to investigate this issue and to link motivation to information exchange in groups. Results of a hidden profile study involving 40 groups indicated that expectancy motivation drives groups to use expertise awareness, exchange more unique information, and thus solve a hidden profile problem correctly.

The large increase in the average sample size of team studies published in premier management journals over the past decade is concerning. A strict focus on large samples suppresses the study of many teams, particularly less prominent ones; for example, teams in small or medium-sized enterprises, teams in unique contexts, teams containing underrepresented minorities, and teams adopting new technologies. It also impedes our collective understanding of teams by devaluing work relying on philosophies of science that do not prioritize large samples. Large samples allow positivists to establish relationships between constructs. Yet, contextualized, rich data from as few as just one team can help constructivists uncover lived experiences or could be studied by critical realists to identify mechanisms underlying social systems of active agents. In this paper, we review how these three philosophies of science view sample size, addressing how and when small samples are beneficial. Importantly, research from all three traditions is necessary to build an in-depth, practical understanding of teams. We also describe five specific ways small sample research can contribute to team science and lay out four general recommendations for assessing the value of sample size in team research. Throughout, we maintain that scientific progress is collective and pluralistic. A sole reliance on large samples threatens this goal.

Richard Kettner-Polley and Charles Gavin founded Small Group Research ( SGR) to present research, build theory, and generally advance the study of small groups by combining insights from multiple disciplines. Currently, we evaluate the extent to which this interdisciplinary mission has been upheld over time. To do this, we apply the perspective and tools of big data analytics to the nearly 3 million words that span the 829 articles that comprise the SGR corpus from February 1990 to June 2017. Keyword analysis, ontological ordering, and interdisciplinary content analyses identify intriguing patterns and detect latent trends. Our results speak to the consistent interdisciplinarity of SGR while identifying opportunities for further development and more complex disciplinary integration in research on small groups.

Groups must leverage their members' diverse knowledge to make optimal decisions. However, the gender composition of a group may affect this ability, particularly because solo status female members (one female grouped with males) are generally allocated lower status than their male counterparts, so their knowledge is more likely to be ignored. Whereas most previous work suggests ways solo status women can increase their status; instead, we propose that groups communicate better when men give their female teammate appropriate respect. We examine this in mixed-gender groups working on a hidden profile task while wearing wireless EEGs to measure live neural activity. We find that groups who solve the problem correctly are more likely to contain majority male members with more approach-oriented mindsets, operationalized as neural alpha asymmetry, as they respect their female teammate more. Thus, we provide evidence that neural activity is partially responsible for whether mixed-gender groups make optimal decisions.

PurposeThe purpose of this paper is to expand the nomological network of a relational efficacy construct, transpersonal efficacy, and examine its effect on attitudes and behaviors important for team performance. The authors identify several antecedents to transpersonal efficacy, including task interdependence, agreeableness and conscientiousness. The authors also find that transpersonal efficacy is related to relational attitudes and behaviors in teams.Design/methodology/approachThis study consists of an online cross-sectional survey completed by participants representing a wide range of occupations, team types, contexts and industries. Participants reported on their working relationships with team members and various behavioral outcomes. Participants used the Occupational Information Network (O*NET) to describe their teammates' job requirements and to evaluate each teammate's ability to complete required tasks. Confirmatory factor analysis and structural equation modeling were used to test hypotheses.FindingsFindings suggest that people in highly interdependent teams have more confidence in their teammates. Further, transpersonal efficacy predicts relationship, task and process conflict when controlling for team task interdependence and virtualness, along with individual differences including agreeableness and conscientiousness. Transpersonal efficacy also contributes to the prediction of relationship conflict beyond the explained variance of collective efficacy.Originality/valueThis paper contributes to our understanding of individuals in teams by using social cognitive theory, expectancy theory and uncertainty reduction theory as a base for predicting the value of transpersonal efficacy in driving relational team behaviors. The authors uniquely consider efficacy as an interpersonal construct that is related to individual behaviors and attitudes that target specific teammates, rather than the team as a whole.

At its 50-year milestone, we assess the Small Group Research ( SGR) corpus to reflect on the development of group research over the past half century. To do this, we examine the evolution of the corpus's context and content. We examine its context by assessing its impact, which journals it communicates with, and the internationality of its authors. We examine its content—the topics discussed in its articles—using keyword clustering and co-occurrence network analysis. We identify 10 research communities and track their relationships over the four editorial periods associated with the SGR corpus (lagged 2 years for influence): 1970–1981, 1982–1991, 1992–2010, and 2011–2019. Our analyses indicate that the global and local study of group dynamics has fluctuated over time and that phenomenologically based topics connect theoretical topics and stimulate theoretical development. We also provide three criteria to identify communities and topics of group research most likely to benefit from future integration.