(A)typical Spillover? How ChatGPT’s Release Reshaped Venture Funding Across Categories

Abstract

Legitimacy spillovers suggest that the extraordinary success of some entrepreneurial ventures can benefit others, particularly those with shared category membership. But is shared category membership necessary to reap these benefits? And do all ventures within a category benefit equally? Drawing on entrepreneurial finance, categorization, and organizational identity theories, we argue that a venture’s ability to leverage legitimacy spillovers depends on its organizational atypicality. Using Crunchbase data on over 200,000 startups, we analyze how ChatGPT’s release influenced funding for 10,000 AI ventures. To provide a benchmark, we apply coarsened exact matching to identify 10,000 closely similar ventures outside the AI category based on characteristics such as region, size, age, and number of categories. Our results show that while AI ventures saw positive funding effects from ChatGPT’s release, these effects diminished with increasing atypicality. Conversely, matched non-AI ventures, despite their similar profiles, experienced stronger funding benefits as their atypicality increased. Our study nuances the role of category affiliation in determining the effectiveness of legitimacy spillovers: Not only may spillovers manifest differently for new ventures based on atypicality, but they can also effectively ‘spill’ outside the successful venture’s categorical boundaries.

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