Team Faultline Measures

Abstract

Team faultlines-hypothetical dividing lines based on member attributes that split a team into relatively homogeneous subgroups-influence team processes across contexts, as recent meta-analytic findings show. We review the available faultline measures with regard to their properties and identify several limitations, including dealing with more than two subgroups. We thus propose a new cluster-based approach, average silhouette width (ASW), that identifies the number of subgroups and subgroup membership. We then compare the measures with 1,400 simulated teams with varying properties and investigate their factor structure and their behavior under missing values. We also investigate the predictive validity of the measures with data from real work teams. Results show that different measures respond to different team features in different ways but that most of them load on two correlated factors. Taken together, the ASW measure had the most favorable attributes and was the only measure that accurately determined subgroup membership in the presence of more than two subgroups. We discuss limitations and further research opportunities pertaining to faultline measures and provide software for calculating all investigated measures at http://www.groupfaultlines.org.The labor market has become more heterogeneous: Globalization, outsourcing, increased workforce mobility, demographic changes, an increased percentage of women in previously male-dominated jobs, and an increased internationalization of education are only some of the factors contributing

Intergroup friendship and children's intentions for social exclusion in integrative classrooms: the moderating role of teachers' diversity beliefs

“…Based on findings from organizational research on team diversity, we argue that the teacher's beliefs about the value of diversity in the classroom are an important contextual moderating factor for the relationship between pupils' intergroup contact and their tendencies to socially exclude others based on social categories. These assumptions are in line with research on faultlines, hypothetical dividing lines splitting groups into relatively homogeneous subgroups (e.g., Meyer & Glenz, 2013;Thatcher & Patel, 2011. Prior findings show that such splits between subgroups need not necessarily be detrimental in the presence of pro-diversity beliefs (Homan, van Knippenberg, van Kleef, & De Dreu, 2007).…”

When and why hierarchy steepness is related to team performance

“…Regression results revealed that there were no three-way interactions between status hierarchy steepness, task complexity, and mean status that significantly predicted team conflict or team performance (lowest B = −.07, p = .17 for the conflict types separately; B = −.05, p = .27 for the combined team conflict scale, and B = .06, p = .37 for team performance). In the second model, we tested whether our hypothesized relations would change when Meyer and Glenz's (2013) average silhouette width (ASW) faultline measure of status-based subgroups was added as a second moderator. We calculated this measure based on our status variable and a constant using the asw.cluster package in R. Yet, the three-way interactions between status hierarchy steepness, task complexity, and the ASW fault line measure did not significantly predict team conflict or team performance (lowest B = −.02, p = .81 for the conflict types separately; B = −.01, p = .86 for the combined team conflict scale, and B = .04, p = .70 for team performance).…”

That’s not my place: The interacting effects of faultlines, subgroup size, and social competence on social loafing behaviour in work groups

“…The effects of faultlines have been mainly attributed to self-categorization theory (Meyer & Glenz, 2013;Thatcher & Patel, 2012;Lau & Murnighan, 2005), which assumes that the salience of social categories depends on their normative fit (i.e., to the extent to which they are meaningful), their cognitive accessibility, and their comparative fit (Turner, Hogg, Oakes, Reicher, Wetherell, 1987). Comparative fit is the extent to which similarities and differences are perceived as a division into social categories: A target is perceived as different if it belongs to a rater's outgroup.…”

“…There are several ways of calculating faultline measures, but overall, the average silhouette width (ASW) measure (Meyer & Glenz, 2013) is the most robust and versatile method (Meyer & Glenz, 2013;Meyer et al, 2014). As none of the groups under investigation was larger than seven members, we restricted it to detecting two subgroups to restrict the number of isolates (i.e., subgroups of size 1).…”

“…Still, six individuals were classified as individual isolates by the ASW algorithm, which we control for in the analysis. The calculations were performed with the asw.cluster package for faultline calculation (Meyer & Glenz, 2013) in R (R Development Core Team, 2013), which also delivers the member-tosubgroup association for each team member. The average subgroup size was 3.44, SD = 1.13.…”