Paper Number
ECIS2026-2840
Paper Type
SP
Abstract
Entrepreneurial exit is typically celebrated as a marker of success, yet its psychological consequences for founders remain underexplored. Drawing on hope theory, identity theory, and social capital research, we examine how exiting a startup affects entrepreneurs’ well-being and how their network structure moderates this effect. We combine qualitative interviews with large-scale digital trace data from Crunchbase and Twitter/X. We identify founders, their acquisition dates, and a 6-month window of pre- and post-exit tweets to measure mood via sentiment analysis, depression-signal detection, and topic modeling. We further construct founder-level mention networks to assess structural and relational dimensions of network structure prior to exit. Our proposed model tests whether exit predicts declines in founder well-being and whether strong online networks buffer these effects. This study advances research on entrepreneurial exit and online social networks by revealing the hidden emotional costs of successful exits and highlighting the protective role of high-quality networks.
Recommended Citation
Krijestorac, Haris and Gerges-Yammine, Rand, "Who Am I Without My Startup? Entrepreneurial Exit, Mental Health, and The Role Of Online Networks" (2026). ECIS 2026 Proceedings. 22.
https://aisel.aisnet.org/ecis2026/gen_track/gen_track/22
Who Am I Without My Startup? Entrepreneurial Exit, Mental Health, and The Role Of Online Networks
Entrepreneurial exit is typically celebrated as a marker of success, yet its psychological consequences for founders remain underexplored. Drawing on hope theory, identity theory, and social capital research, we examine how exiting a startup affects entrepreneurs’ well-being and how their network structure moderates this effect. We combine qualitative interviews with large-scale digital trace data from Crunchbase and Twitter/X. We identify founders, their acquisition dates, and a 6-month window of pre- and post-exit tweets to measure mood via sentiment analysis, depression-signal detection, and topic modeling. We further construct founder-level mention networks to assess structural and relational dimensions of network structure prior to exit. Our proposed model tests whether exit predicts declines in founder well-being and whether strong online networks buffer these effects. This study advances research on entrepreneurial exit and online social networks by revealing the hidden emotional costs of successful exits and highlighting the protective role of high-quality networks.
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