Accelerator cohort social network structure and startup performance

Abstract

Accelerators have become a widespread means of supporting entrepreneurs and their startups. Yet, deductive empirical research explaining and predicting peer effects in startup accelerator cohorts is wanting. Following queues from the theoretical and qualitative literatures, we hypothesize and find that higher performing cohorts have more connections between peer startups. This suggests that beyond merely acting as brokers, accelerators enable potentially valuable peer effects. However, as the dark side of density literature suggests, we also hypothesize an inverse curvilinear relationship between cohort peer network density and likelihood that a cohort will produce at unicorn. We approximate the intra-cohort social network structures of 1537 startups comprising 154 Techstars cohorts using their activity on Twitter. We find that there exists an upper limit to the impact of cohort network density on performance, after which any further increase becomes negative.

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