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A Preliminary Investigation on the Relationships Between Personality Traits and Team Climate in a Smart-Working Development Context

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Product-Focused Software Process Improvement (PROFES 2021)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 13126))

Abstract

Developers collaborating with collective efforts in large-scale distributed software typically have different personalities that might play a central role in software development and in team climate. In this paper, we have investigated if personality traits are related to the perceived team climate of software developers (Computer Science master students) in a smart-working development context. In particular, we conducted a preliminary study with 53 master students of a Computer Science course conducting a project work during the Covid-19 pandemic. Participants were grouped into 19 distributed teams. We analyzed the correlation between personality traits and team climate factors and created a predictive model for Task Orientation using these correlations. Results suggest that the Extroversion personality trait (characteristic of social and easy-going people) is statistically significant. We also observed a (weak) positive correlation with considered team climate factors.

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Notes

  1. 1.

    Team climate refers to a shared perception among the team members of the team’s work procedures, practices, and members’ behaviors [25].

  2. 2.

    Dr. John A. Johnson, Professor of Psychology, Penn State University, Short Form for the IPIP-NEO (International Personality Item Pool Representation of the NEO PI-R\(\textregistered \)), https://bit.ly/3nHo8tK.

  3. 3.

    https://cran.r-project.org.

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Correspondence to Giuseppe Scanniello .

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Francese, R., Milione, V., Scanniello, G., Tortora, G. (2021). A Preliminary Investigation on the Relationships Between Personality Traits and Team Climate in a Smart-Working Development Context. In: Ardito, L., Jedlitschka, A., Morisio, M., Torchiano, M. (eds) Product-Focused Software Process Improvement. PROFES 2021. Lecture Notes in Computer Science(), vol 13126. Springer, Cham. https://doi.org/10.1007/978-3-030-91452-3_11

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  • DOI: https://doi.org/10.1007/978-3-030-91452-3_11

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