Characterising Open Source Co-opetition in Company-hosted Open Source Software Projects: The Cases of PyTorch, TensorFlow, and Transformers

作者：Cailean Osborne, Farbod Daneshyan, Runzhi He, Hengzhi Ye, Yuxia Zhang, Minghui Zhou · 发表于：Proceedings of the ACM on Human-Computer Interaction · 年份：2025 · DOI：10.1145/3710944 · 被引用次数：7 · 研究领域：Open Source Software Innovations、Private Equity and Venture Capital、Wikis in Education and Collaboration

Companies, including market rivals, have long collaborated on open source software (OSS) development, resulting in a tangle of co-operation and competition known as "open source co-opetition". While prior work investigates open source co-opetition in OSS projects that are hosted by vendor-neutral foundations, we have a limited understanding thereof in OSS projects that are hosted and governed by one company. Given their prevalence, it is timely to investigate open source co-opetition in such contexts. Towards this end, we conduct a mixed-methods analysis of three company-hosted OSS projects in the artificial intelligence (AI) industry: Meta's PyTorch prior to its donation to the Linux Foundation, Google's TensorFlow, and Hugging Face's Transformers. We contribute three key findings. First, while the projects exhibit similar code authorship patterns between host and external companies (~80%/20% of commits), collaborations are structured differently (e.g. decentralised vs. hub-and-spoke networks). Second, host and external companies engage in strategic, non-strategic, and contractual collaborations, with varying incentives and collaboration practices. Some of the observed collaborations are specific to the AI industry (e.g. AI model integrations), while others are typical of the broader software industry (e.g. bug fixing or task outsourcing). Third, single-vendor governance creates a power imbalance that influences open source co-opetition practices and possibilities, from the ...