回归不连续设计
生态系统
资源(消歧)
集合(抽象数据类型)
业务
营销
环境经济学
计算机科学
经济
生态学
医学
计算机网络
病理
生物
程序设计语言
标识
DOI:10.1177/00018392231204839
摘要
Startup accelerators, which aim to improve the set of choices representing a startup’s entry strategy, have become increasingly influential in both regional development and the strategies of individual startups. This article explores an accelerator’s impact on startup performance and whether that impact varies substantially by features of the startup’s founding environment. Leveraging data from a leading startup accelerator, I use a regression discontinuity framework to hold startup quality constant so that I can compare the performance of admitted startups to those that do not make the cut, and I examine whether any observed performance differentials are driven by accelerator admission and by characteristics of the startup’s earlier environment. I find evidence that startups from better pre-accelerator environments experience stronger gains from accelerator admission. I also find evidence of home bias, as local startups have a stronger treatment effect. These results provide evidence of ecosystem effects whereby the impact of one organizational sponsor in an ecosystem is strongly moderated by other features in the ecosystem. The findings help to explain the concentration of accelerator programs in already successful entrepreneurial ecosystems and reveal how such programs may interact with founding environments to complement resource abundance or magnify prior resource inequalities.
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