Addressing OSS Community Managers’ Challenges in Contributor Retention

2025-09-22

ACM Transactions on Software Engineering and Methodology

AI Summary

This study addresses the lack of predictive tools for open-source software (OSS) community managers to proactively identify and mitigate contributor attrition, a gap left by existing approaches that predominantly rely on post-hoc analysis. Adopting the design science research paradigm, the authors integrate semi-structured interviews, multi-vocal literature reviews, community surveys, and iterative build-and-evaluate cycles to develop and validate a web-based prototype system enabling early risk diagnosis and intervention. Field evaluations in two OSS communities yielded key insights into retention challenges and effective strategies, leading to an actionable framework that embeds predictive analytics into managerial practice. The resulting system significantly enhances intervention efficiency while reducing managerial burden, offering both theoretical and practical contributions to sustaining OSS communities.

Technology Category

• Data Mining & Knowledge Management: Anomaly/Outlier Detection
• Multiagent Systems: Distributed Problem Solving
• Humans and AI: Crowd Sourcing and Human Computation

Application Category

• Social Networks and Social Media: Socio-technical web-based systems
• Web Mining and Content Analysis: Community question answering
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Open-source software (OSS) community managers face significant challenges in retaining contributors, as they must monitor activity and engagement while navigating complex dynamics of collaboration. Current tools designed for managing contributor retention (e.g., dashboards) fall short by providing retrospective rather than predictive insights to identify potential disengagement early. Without understanding how to anticipate and prevent disengagement, new solutions risk burdening community managers rather than supporting retention management. Following the Design Science Research paradigm, we employed a mixed-methods approach for problem identification and solution design to address contributor retention. To identify the challenges hindering retention management in OSS, we conducted semi-structured interviews, a multi-vocal literature review, and community surveys. Then through an iterative build-evaluate cycle, we developed and refined strategies for diagnosing retention risks and informing engagement efforts. We operationalized these strategies into a web-based prototype, incorporating feedback from 100+ OSS practitioners, and conducted an in situ evaluation across two OSS communities. Our study offers (1) empirical insights into the challenges of contributor retention management in OSS, (2) actionable strategies that support OSS community managers’ retention efforts, and (3) a practical framework for future research in developing or validating theories about OSS sustainability.

Problem

• contributor retention
• open-source software
• community management
• disengagement prediction
• OSS sustainability

Innovation

• contributor retention
• predictive analytics
• design science research
• open-source software sustainability
• community management