This study extends emerging theories of star performers to digital platforms, an increasingly prevalent entrepreneurial context. It hypothesizes that the unique characteristics of many digital platforms (e.g., low marginal costs, feedback loops, and network effects) produce heavy-tailed performance distributions, indicating the existence of star entrepreneurs. Using longitudinal data from an online learning platform, proportional differentiation is identified as the most likely generative mechanism and lognormal distribution as the most likely shape for distributions of entrepreneurial performance in digital contexts. This study contributes theory and empirical evidence for non-normal entrepreneurial performance with implications for scholars and practitioners of digital entrepreneurship.

这项研究将明星表演者的新兴理论扩展到数字平台，这是一个日益普遍的创业环境。它假设许多数字平台的独特特征（例如，低边际成本、反馈循环和网络效应）产生重尾绩效分布，表明明星企业家的存在。使用来自在线学习平台的纵向数据，比例分化被确定为最可能的生成机制，对数正态分布被确定为数字背景下创业绩效分布最可能的形状。这项研究为非正常创业绩效提供了理论和经验证据，对数字创业的学者和实践者具有重要意义。