This dissertation primarily address scholarly conversations on (1) communication strategy in entrepreneurial pitches and (2) the inclusivity of women in entrepreneurship, in both formal and informal early-stage financing settings. Empirically, I employ machine learning algorithms to analyze large unstructured data, including texts, images, and videos of entrepreneurs collected from publicly accessible websites like YouTube and Kickstarter. I also refer to large scale archival database of funding deal records from Crunchbase. Recognizing the challenge in quantifying subtle nonverbal cues within entrepreneurial pitches, my dissertation began with a comprehensive review of coding tools used in published social science papers, complemented by practical applications to 50 accelerator pitch videos. This study wraps up with targeted algorithm suggestions for facial and vocal analysis, alongside a qualitative discussion about emotional disclosure in accelerator pitches of successful entrepreneurs. Transitioning from methodological exploration to practical application, the next study analyzed 183 pitch videos to uncover gender differences in the evaluation of nonverbal emotional neutrality in the crowdfunding context. I observed that gender-conforming expressions of emotion tend to be favored over non-conforming ones among informal investors. Building on these insights about gender difference in early-stage financing evaluation, the third study examines a potential solution to early-stage funding access of female entrepreneurs. Contrary to the implications of gender homophily between female investors and entrepreneurs, I find that the representation of female-founded startups securing initial funding rounds decreased when a female venture capitalist is involved, in states with heightened public attention post Elizabeth Holmes scandal. Overall, this dissertation critically explores gender and entrepreneurship, focusing on the subtle cues that may benefit women in pitch evaluations and substantial challenges they face in securing early-stage financing.

Subtle Cues and Substantial Challenges in Early-Stage Financing: Essays on Pitch Evaluation and Women in Entrepreneurship

MAO, JIONGNI
2025

Abstract

This dissertation primarily address scholarly conversations on (1) communication strategy in entrepreneurial pitches and (2) the inclusivity of women in entrepreneurship, in both formal and informal early-stage financing settings. Empirically, I employ machine learning algorithms to analyze large unstructured data, including texts, images, and videos of entrepreneurs collected from publicly accessible websites like YouTube and Kickstarter. I also refer to large scale archival database of funding deal records from Crunchbase. Recognizing the challenge in quantifying subtle nonverbal cues within entrepreneurial pitches, my dissertation began with a comprehensive review of coding tools used in published social science papers, complemented by practical applications to 50 accelerator pitch videos. This study wraps up with targeted algorithm suggestions for facial and vocal analysis, alongside a qualitative discussion about emotional disclosure in accelerator pitches of successful entrepreneurs. Transitioning from methodological exploration to practical application, the next study analyzed 183 pitch videos to uncover gender differences in the evaluation of nonverbal emotional neutrality in the crowdfunding context. I observed that gender-conforming expressions of emotion tend to be favored over non-conforming ones among informal investors. Building on these insights about gender difference in early-stage financing evaluation, the third study examines a potential solution to early-stage funding access of female entrepreneurs. Contrary to the implications of gender homophily between female investors and entrepreneurs, I find that the representation of female-founded startups securing initial funding rounds decreased when a female venture capitalist is involved, in states with heightened public attention post Elizabeth Holmes scandal. Overall, this dissertation critically explores gender and entrepreneurship, focusing on the subtle cues that may benefit women in pitch evaluations and substantial challenges they face in securing early-stage financing.
22-gen-2025
Inglese
WILLIAMS, CHARLES FREDERICK
Università Bocconi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/190395
Il codice NBN di questa tesi è URN:NBN:IT:UNIBOCCONI-190395