The effect of teammate personality on team production

Hancock, Stacey; Hill, Andrew

doi:10.1016/j.labeco.2022.102248

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…2. Conscientiousness is confirmed by past research [24] to have a positive association with team performance. Teams with organized, dependable, and hardworking members tend to outperform others.…”

Section: Team Performance and Ffm Dimensionssupporting

confidence: 58%

“…Aggregate data of the distribution of students is depicted in Table 1. We compared the results to a study on the effect of teammate personality on team production [24]. Our observed average for conscientiousness stands at 0.69, exceeding the 0.59 reported in the referenced study.…”

Section: Ffm Datamentioning

confidence: 58%

“…• Incorporate at least one student with high conscientiousness (student max (c) ) in each team, as suggested by [24]. This approach triggers a beneficial "conscientiousness shock," improving team dynamics.…”

Section: Team Formation Algorithmmentioning

confidence: 99%

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A Data-Driven Approach to Team Formation in Software Engineering Based on Personality Traits

Vasiljević,

Lavbič

2023

Preprint

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Collaboration among individuals with diverse skills and personalities is crucial in producing high-quality software. The success of any software project depends on the team’s cohesive functionality and mutual complementation. This study introduces a data-centric methodology for forming Software Engineering (SE) teams centred around personality traits. Our study analyzed data from an SE course where 157 students in 31 teams worked through four project phases and were evaluated based on deliverables and instructor feedback. Using the Five Factor Model (FFM) and a variety of statistical tests, we determined that teams with higher levels of extraversion and conscientiousness and lower neuroticism consistently performed better. We examined team member interactions and developed a predictive model using extreme gradient boosting. The model achieved a 74% accuracy rate in predicting inter-member satisfaction rankings. Through graphical explainability, it underscored incompatibilities among members, notably those with differing levels of extraversion. Based on our findings, we introduce a team formation algorithm using Simulated Annealing (SA), built upon the insights from our predictive model and additional heuristics.

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Section: Team Performance and Ffm Dimensionssupporting

confidence: 58%

Section: Ffm Datamentioning

confidence: 58%