Exploring the team dynamic learning process in software process tailoring performance: A theoretical perspective

Abstract

Purpose

Software process tailoring (SPT) is a knowledge- and learning-intensive activity in which a software project team customizes its software development processes to accommodate project particularities. Because SPT critically influences how a project is conducted, SPT performance should be investigated, but the extant literature lacks investigations into how team knowledge mechanisms and team environments contribute to SPT performance. To fill this gap, this study looks into a team's absorptive capacity (AC) and combines a transactive memory system (TMS) and team climate inventory (TCI) to develop a theoretical research model to facilitate the understanding of SPT performance.

Design/methodology/approach

This paper is a conceptual study that uses the propositional methodology with a focused review of existing literature pertaining to SPT, AC, TMS and TCI to develop a theoretical model to foster SPT performance. Because this study is conceptually established, further empirical research and studies are also suggested.

Findings

The proposed model provides guidance for firms conducting SPT. It also contributes to future research aiming to empirically understand the mechanisms behind the identified team-based knowledge and environmental enablers in the dynamic team learning process that lead to superior SPT performance.

Originality/value

The proposed model provides a fresh look at the dynamic capabilities theory in SPT and innovatively identifies a team's dynamic learning process to show how a team can conduct effective SPT through AC and facilitated by TMS. Environmental climates characterized by vision, participative safety, task orientation and support for innovation act as positive moderators in promoting the team dynamic learning process.

Citation

Lee, J.-C. and Chen, C.-Y. (2020), "Exploring the team dynamic learning process in software process tailoring performance: A theoretical perspective", Journal of Enterprise Information Management, Vol. 33 No. 3, pp. 502-518. https://doi.org/10.1108/JEIM-07-2019-0202