Personnel Turnover and Team Performance

Levine, John M.; Moreland, Richard L.; Argote, Linda; Carley, Kathleen M.

doi:10.1037/e500262012-001

Cited by 14 publications

(7 citation statements)

References 120 publications

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“…Previous literature reported on the negative impact of turnover on team cognition and performance (Levine and Choi, 2004;Levine et al, 2005), and its costs for the company and society (Graef and Hill, 2000;Garman et al, 2005). Software engineering-specific literature has also shown that developers' turnover harms software development projects (Bass et al, 2018;Nakatsu and Iacovou, 2009;Hall et al, 2008).…”

Section: Developers' Turnover and Disengagementmentioning

confidence: 99%

Will You Come Back to Contribute? Investigating the Inactivity of OSS Core Developers in GitHub

Calefato,

Gerosa,

Iaffaldano

et al. 2021

Preprint

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Several Open Source Software (OSS) projects depend on the continuity of their development communities to remain sustainable. Understanding how developers become inactive or why they take breaks can help communities prevent abandonment and incentivize developers to come back. In this paper, we propose a novel method to identify developers' inactive periods by analyzing the individual rhythm of contributions to the projects. Using this method, we quantitatively analyze the inactivity of core developers in 18 OSS organizations hosted on GitHub. We also survey core developers to receive their feedback about the identified breaks and transitions. Our results show that our method was effective for identifying developers' breaks. About 94% of the surveyed core developers agreed with our state model of inactivity; 71% and 79% of them acknowledged their breaks and state transition, respectively. We also show that all core developers take breaks (at least once) and about a half of them ( 45%) have completely disengaged from a project for at least one year. We also analyzed the probability of transitions to/from inactivity and found that developers who pause their activity have a 35 to 55% chance to return to an active state; yet, if the break lasts for a year or longer, then the probability of resuming activities drops to 21-26%, with a 54% chance of complete disengagement. These results may support the creation of policies and

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Section: Developers' Turnover and Disengagementmentioning

confidence: 99%

Will You Come Back to Contribute? Investigating the Inactivity of OSS Core Developers in GitHub

Calefato,

Gerosa,

Iaffaldano

et al. 2021

Preprint

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show abstract

“…For example, teams may grow accustomed to functioning with a particular trait configuration, making the entry of a new team member with distinctive traits a highly novel event (Joardar et al, 2007; Kammeyer-Mueller et al, 2011; Phillips et al, 2009). However, when teams are given information about an incoming team member’s traits in advance, they tend to perform better (Levine et al, 2005), suggesting that providing team members with information about what to expect can reduce the novelty of a team membership change event. Furthermore, there is some evidence to suggest prior experience with team membership change can improve team performance by reducing the novelty of additional membership change events (Ahmed et al, 2019; Huckman & Staats, 2011; Huckman et al, 2009).…”

Section: Advancing Future Research On Team Membership Change “Events”mentioning

confidence: 99%

Team Membership Change “Events”: A Review and Reconceptualization

Trainer

Jones

Pendergraft

et al. 2020

Group & Organization Management

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Driven by views of teams as dynamic systems with permeable boundaries, scholars are increasingly seeking to better understand how team membership changes (i.e., team members joining and/or leaving) shape the functioning and performance of organizational teams. However, empirical studies of team membership change appear to be progressing in three largely independent directions as researchers consider: (a) how newcomers impact and are impacted by the teams they join; (b) how teams adapt to member departures; or (c) how teams function under conditions of high membership fluidity, with little theoretical integration or consensus across these three areas. To accelerate an integrative stream of research on team membership change, we advance a conceptual framework which depicts each team membership change as a discrete team-level “event” which shapes team functioning to the extent to which it is “novel,” “disruptive,” and “critical” for the team. We use this framework to guide our review and synthesis of empirical studies of team membership change published over the past 20 years. Our review reveals numerous factors, across conceptual levels of the organization, that determine the strength (i.e., novelty, disruptiveness, criticality) of a team membership change event and, consequently, its impact on team functioning and performance. In closing, we provide propositions for future research that integrate a multilevel, event-based perspective of team membership change and demonstrate how team membership change events may impact organizational systems over time and across levels of observation.

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“…Turnover refers to team members entering or leaving a workgroup or organisation, which often is associated with changes of performance and expertise (e.g. Levine, Moreland, Argote, and Carley 2005 ). These changes may have positive effects on performance, for instance when newcomers are highly skilled, but also may be negative if it disturbs a team's steady state (Levine et al 2005).…”

Section: Introductionmentioning

confidence: 99%

When Does a Newcomer Contribute to a Better Performance? A Multi-Agent Study on Self-Organising Processes of Task Allocation

Zoethout¹,

Jager²,

Molleman³

2010

JASSS

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This paper describes how a work group and a newcomer mutually adapt. We study two types of simulated groups that need an extra worker, one group because a former employee had left the group and one group because of its workload. For both groups, we test three conditions, newcomers being specialists, newcomers being generalists, and a control condition with no newcomer. We hypothesise that the group that needs an extra worker because of its workload will perform the best with a newcomer being a generalist. The group that needs an extra worker because a former employee had left the group, will perform better with a specialist newcomer. We study the development of task allocation and performance, with expertise and motivation as process variables. We use two performance indicators, the performance time of the slowest agent that indicates the speed of the group and the sum of performance of all agents to indicate labour costs. Both are indicative for the potential benefit of the newcomer. Strictly spoken the results support our hypotheses although the differences between the groups with generalists and specialists are negligible. What really mattered was the possibility for a newcomer to fit in.

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Personnel Turnover and Team Performance

Cited by 14 publications

References 120 publications

Will You Come Back to Contribute? Investigating the Inactivity of OSS Core Developers in GitHub

Will You Come Back to Contribute? Investigating the Inactivity of OSS Core Developers in GitHub

Team Membership Change “Events”: A Review and Reconceptualization

When Does a Newcomer Contribute to a Better Performance? A Multi-Agent Study on Self-Organising Processes of Task Allocation

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