Both personality and social identity predict perceived software team productivity: A survey study
Journal article, 2026

Context: Prior work has studied how personality or social identity separately relate to software team productivity, but no study has compared them as predictors within the same model.
Objective: We investigate which factors from personality (Big Five) and social identity (Collective Self-Esteem) best predict perceived team productivity in software development, and whether both constructs contribute. Method: We surveyed 71 software professionals, measuring Big Five personality traits (Mini-IPIP), Collective Self-Esteem (Luhtanen and Crocker scale), and self-assessed team productivity. We used multiple linear regression with backward elimination.
Results: Predictors from both constructs survived backward elimination. Agreeableness was the strongest predictor of perceived team productivity, followed by Public Collective Self-Esteem and Membership Esteem, with Neuroticism predicting productivity negatively. Intellect/Openness sat near the inclusion threshold and should be read as tentative given the lenient alpha. The retained model explains roughly a third of the variance in perceived team productivity.
Conclusion: Personality and social identity are complementary predictors of software team productivity. The three strongest predictors come from both constructs, suggesting practitioners should attend to both individual traits and group identification when composing and managing teams.

Software team productivity

Personality

Collective self-esteem

Social identity

Regression

Big five

Author

Karim Abdeldayem

Student at Chalmers

Karam Khatib

Student at Chalmers

Lucas Gren

University of Gothenburg

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Information and Software Technology

0950-5849 (ISSN)

Vol. 197 108196

Subject Categories (SSIF 2025)

Software Engineering

Applied Psychology

Sociology

DOI

10.1016/j.infsof.2026.108196

Related datasets

Survey [dataset]

URI: https://zenodo.org/records/20034765

More information

Latest update

5/29/2026