Exploring the Effectiveness of Open-Source Donation Platform: An Empirical Study on Opencollective

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Shuoxiao Zhang, Enyi Tang, Xinyu Gao, Zhekai Zhang, Yixiao Shan, Haofeng Zhang, Ziyang He, Jianhua Zhao, Xuandong Li
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Abstract

In recent years, with the development of the open-source community, various open-source donation platforms have emerged. These platforms effectively alleviate the financial pressures faced by open-source projects through diversified funding sources and flexible donation methods. As one of the most representative open-source donation platforms, Opencollective has garnered widespread attention from both the open-source community and academia. Although Opencollective claims to provide more funding opportunities for open-source projects, the extent to which it effectively addresses the financial challenges faced by these projects remains unclear. While there have been studies on the effectiveness of traditional donation models, research on the effectiveness of emerging donation platforms such as Opencollective is still limited. Given that a large number of open-source projects are urgently seeking donations, understanding the effectiveness of donations through Opencollective is crucial for these projects. To address this gap, we have made an early step in this direction. This paper conducts a comprehensive study on the effectiveness of donations through the Opencollective, employing a combination of quantitative and qualitative analysis and identifies the following key findings: (1) Opencollective attracts a diverse group of participants, including individual donors, sponsors, contributors, and project managers, with individual donors constituting the largest group. Most donations are concentrated in the range of $5 to $10, indicating that the platform largely relies on small but frequent donations from individuals. (2) Only about 26.61% of open-source projects receive donations through Opencollective, with approximately 64.38% of these projects receiving a total donation amount of less than $50,000. The likelihood of receiving donations increases with project scale, maturity and the number of stars. Among projects that have received donations, larger projects with stronger social media promotion, greater attention and more issues are more likely to receive additional donations. (3) The positive impact of donations on project development and spend activities is significant only in the short term, with no notable long-term effects. In contrast, donations do not have a significant short-term impact on community engagement. Although the long-term effect is slightly positive, it is not statistically significant. (4) The main shortcomings of Opencollective include insufficient project management and collaboration features, inadequate user experience and interface design, high transaction fees, and a lack of transparency in fund allocation and usage. Our findings provide significant theoretical support and practical recommendations for the effectiveness of emerging donation platforms and the sustainable development of open-source projects.

Abstract Image

探索开源捐赠平台的有效性:基于Opencollective的实证研究
近年来,随着开源社区的发展,各种开源捐赠平台应运而生。这些平台通过多元化的资金来源和灵活的捐赠方式,有效缓解了开源项目面临的资金压力。Opencollective作为最具代表性的开源捐赠平台之一,受到了开源社区和学术界的广泛关注。尽管Opencollective声称为开源项目提供更多的融资机会,但它在多大程度上有效地解决了这些项目面临的财务挑战仍不清楚。虽然对传统捐赠模式的有效性进行了研究,但对Opencollective等新兴捐赠平台的有效性研究仍然有限。鉴于大量的开源项目迫切需要捐赠,了解通过Opencollective捐赠的有效性对这些项目至关重要。为了弥补这一差距,我们已经朝这个方向迈出了早期的一步。本文采用定量分析和定性分析相结合的方法,对Opencollective的捐赠有效性进行了全面研究,得出以下主要结论:(1)Opencollective吸引了包括个人捐赠者、发起人、贡献者和项目经理在内的多元化参与者群体,其中个人捐赠者构成了最大的群体。大多数捐款集中在5美元到10美元之间,这表明该平台在很大程度上依赖于小额但频繁的个人捐款。(2)只有约26.61%的开源项目通过Opencollective获得捐赠,其中约64.38%的项目获得的总捐赠金额低于5万美元。接受捐赠的可能性随着项目规模、成熟度和星级的增加而增加。在接受捐赠的项目中,更大的项目,社交媒体推广力度更大,关注度更高,问题更多,更有可能获得额外的捐赠。(3)捐赠对项目开发和支出活动的积极影响仅在短期内显著,长期影响不显著。相比之下,捐赠对社区参与没有显著的短期影响。虽然长期效果略显积极,但在统计学上并不显著。(4) Opencollective的主要缺点是项目管理和协作功能不足,用户体验和界面设计不完善,交易费用高,资金分配和使用缺乏透明度。研究结果为新兴捐赠平台的有效性和开源项目的可持续发展提供了重要的理论支持和实践建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Software-Evolution and Process
Journal of Software-Evolution and Process COMPUTER SCIENCE, SOFTWARE ENGINEERING-
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10.00%
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109
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