Employing a prosocial perspective, this study examines how crowdfunders' prosocial motivation influences their lending decisions on international crowdfunding platforms, addressing the global challenge of poverty alleviation. We posit that prosocially motivated crowdfunders, concerned about economic inequality and others' well-being, are more likely to lend to poorer borrowers to minimize inequality and improve welfare. Analyzing a large dataset from Kiva.org with machine learning techniques, we find that higher prosocial motivation indeed leads to the lending choice of poorer borrowers across borders. However, cultural distance weakens this relationship by creating cognitive and emotional barriers, while crowdfunders' platform experience and women-owned businesses strengthen it. These findings highlight how digital platforms enable prosocial motivations to cross national borders in poverty-reduction efforts, while revealing barriers and enablers in cross-border lending. Our study contributes to the international business literature by introducing a prosocial perspective to digital platform research and advancing methodological approaches through machine learning. For practitioners, we suggest strategies to enhance prosocial crowdfunding platforms' effectiveness, including cultural bridge-building initiatives, leveraging experienced users as mentors, and highlighting women-owned businesses. Policymakers can use these insights to create frameworks maximizing prosocial crowdfunding's impact on poverty alleviation.

本研究采用亲社会视角，研究了众筹者的亲社会动机如何影响他们在国际众筹平台上的贷款决策，以应对全球扶贫挑战。我们假设，出于亲社会动机的众筹者，关心经济不平等和他人福祉，更有可能向较贫穷的借款人提供贷款，以最大限度地减少不平等并改善福利。使用机器学习技术分析来自 Kiva.org 的大型数据集，我们发现更高的亲社会动机确实会导致较贫穷的借款人跨境选择贷款。然而，文化距离通过制造认知和情感障碍来削弱这种关系，而众筹者的平台体验和女性拥有的企业则加强了这种关系。这些发现突出了数字平台如何使亲社会动机在减贫工作中跨越国界，同时揭示了跨境贷款的障碍和推动因素。我们的研究通过将亲社会视角引入数字平台研究并通过机器学习推进方法论，为国际商业文献做出了贡献。对于从业者，我们建议提高亲社会众筹平台有效性的策略，包括建立文化桥梁的举措，利用经验丰富的用户作为导师，以及突出女性拥有的企业。政策制定者可以利用这些见解来创建框架，以最大限度地发挥亲社会众筹对扶贫的影响。