Single- and Double-Loop Learning

ACM SIGMIS Database: the DATABASE for Advances in Information Systems(2020)

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摘要
Free/Libre Open Source Software (FLOSS) developers often make a single contribution to a project and then no more, making project management difficult. To improve understanding around why developers leave, this work explores the relationship between FLOSS developer motivations and their attitudes and behavior related to projects. In particular, we add insight to the current understanding of these issues by proposing single- and double-loop learning as intervening mechanisms that connect developer motivations to outcomes and thereby help clarify when developer motivations have negative and positive impacts for the project. We test our hypotheses in a sample of 132 FLOSS developers. We find that intrinsic motivations (motivation to learn) and social motivations (motivation to collaborate) positively influence single- and double-loop learning while extrinsic motivations negatively impact both types of learning. We further find that single- and double-loop learning have differential impacts on contribution to the focal project and other projects. While single-loop learning is associated with lower turnover intentions, double-loop learning is associated with higher turnover intentions. Implications of our findings for research and management are provided in the discussion.
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