How Peripheral Developers Contribute to Open-Source Software Development
Abstract
Open-source software development is the next stage in the evolution of product development, particularly software products. Compared with the prevailing proprietary approaches, open-source software products are developed by co-opting external developers and prospective users. Although a core group of developers might still play a key role in the initial design and development, a notable aspect of the open-source software paradigm is the role of peripheral developers in the enhancement and popularization of the product. Peripheral developers are not formal members of the core development team. They voluntarily contribute their time and creative talent in improving the quality of the product or in popularizing the product through word-of-mouth advocacy. As volunteers, they are not subject to the traditional hierarchical controls, nor are they contractually obligated. Peripheral developers represent a novel and unique aspect of open-source software development, and there is a greater interest in tapping their potential. However, there has been limited evidence about how and when their participation has beneficial impacts. We examine how peripheral developers contribute to product quality and diffusion by utilizing longitudinal data on 147 open-source software products. Hierarchical linear modeling analysis indicates that peripheral developers make significant contributions to product quality and diffusion, especially on projects that are in the more mature stages of product development.
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Core contributors were classified using contributors' level of activity during the pretreatment period, measured by number of commits, into core contributors (top 25%) and peripheral contributors (rest 75%).
“For the conceptualization of core contributors we used contributors' level of activity during the pretreatment period, measured by the number of commits, to classify contributors into core contributors (top 25%) and peripheral contributors (rest 75%) (Setia et al. 2012, Crowston et al. 2006).”
From AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden (2025) · cites this paper as Setia et al. 2012
Core developers primarily design the overall architecture, write code, maintain control over the codebase, and guide the long-term development of the project.
“Core developers primarily design the overall architecture, write code, maintain control over the codebase, and guide the long-term development of the project”
From The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot  (2024) · cites this paper as Setia et al. 2012
Peripheral developers contribute code on a more irregular basis and tend to focus on bug fixes and incremental feature additions.
“peripheral developers contribute code on a more irregular basis and tend to focus on bug fixes and incremental feature additions (Crowston et al. 2006, Setia et al. 2012, Gousios et al. 2014).”
From The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot  (2024) · cites this paper as Setia et al. 2012
Core developers are more embedded in focal projects and maintain sustained involvement, while peripheral developers contribute more sporadically, leading to limited project familiarity.
“In the OSS community, core developers are more embedded in focal projects and maintain sustained involvement (Setia et al. 2012), while peripheral developers contribute more sporadically (Howison and Crowston 2014, Krishnamurthy et al. 2016), which leads to their limited level of project familiarity.”
From The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot  (2024) · cites this paper as Setia et al. 2012
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Hann, I.-H., Roberts, J. A., & Slaughter, S. A. (2013) · Information Systems Research · doi:10.1287/isre.2013.0474 · Cited by 97 · see citing works
The Sustainability of Polycentric Information Commons1
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“According to the expectancy value models, contributors evaluate the expectancy of the outcomes and its value to determine if they would participate in certain software projects (Atkinson 1957, Hertel et al. 2003, Setia et al. 2012).”
BackgroundMethodInfluentialXu, F., Medappa, P. K., Tunc, M. M., Vroegindeweij, M., & Fransoo, J. C. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5521379 · Cited by 2 · see citing works
Xu, F., Medappa, P. K., Tunc, M. M., Vroegindeweij, M., & Fransoo, J. C. (2025) · arXiv · doi:10.48550/arxiv.2510.10165 · Cited by 1 · see citing works
- Authors
- Setia, P., Rajagopalan, B., Sambamurthy, V., & Calantone, R.
- Affiliations
- University of Arkansas at Fayetteville (US)
- Oakland University (US)
- Michigan State University (US)
- Venue
- Information Systems Research
- Published
- 2012-03
- Volume
- 23
- Issue
- 1
- Pages
- 144-163
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W2138211899
- Cited by
- 110
- References
- 4
- Citations by year
- 2026: 10 · 2025: 10 · 2024: 2 · 2023: 9 · 2022: 11 · 2021: 6 · 2020: 14 · 2019: 9 · 2018: 6 · 2017: 4 · 2016: 6 · 2015: 7 · 2014: 10 · 2013: 4 · 2012: 2
- FWCI
- 4.29
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information Systems Research (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Open Source Software Innovations
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
- Keywords
- open source software, volunteer contributions, product quality
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