Abstract
Companies, including market rivals, have long collaborated on the development of open source software (OSS), 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., hardware-software optimizations or 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 host company's singular decision-making power (e.g., the risk of license change) to their community involvement strategy (e.g., from over-control to over-delegation). We conclude with recommendations for future research.
Abstract (translated)
企业，包括市场竞争对手，长期以来在开源软件（OSS）的开发上进行了合作，形成了一个被称为“开源共竞”（open source co-opetition）的合作与竞争交织的局面。虽然之前的研究调查了由中立基金会托管的OSS项目中的这种“开源共竞”，但我们对单一公司托管和管理的OSS项目中的这种情况了解甚少。鉴于这些项目的普遍性，是时候在这样的背景下研究开源共竞了。为此，我们采用混合方法分析了人工智能（AI）行业中三个企业托管的OSS项目：Meta的PyTorch（捐赠给Linux基金会之前）、Google的TensorFlow和Hugging Face的Transformers。我们的研究贡献了三项关键发现。 首先，尽管这些项目的代码作者模式在托管公司与外部公司之间相似（80%/20% 的提交量），但合作结构有所不同（例如，去中心化网络与枢纽和辐条式网络）。其次，托管公司和外部公司在战略、非战略及合同基础上进行合作，其激励机制和协作实践各不相同。其中一些观察到的合作关系特别针对AI行业（如硬件-软件优化或AI模型集成），而另一些则属于更广泛的软件行业的常见做法（如修复错误或外包任务）。第三，单一供应商的治理模式造成了权力失衡，这影响了开源共竞的做法和可能性，从托管公司唯一的决策权（例如，更改许可证的风险）到其社区参与策略（例如，从过度控制转向过度委托）。 我们最后提出了一些对未来研究的建议。
URL
https://arxiv.org/abs/2410.18241
