How Founders Evaluate VCs: A GPT-Based Extraction of Value-Criteria from Online VC Reviews

Conference Paper
Academy of Management Proceedings 2025(1), 18846
Authors

Oliver Specht

Jonas Wilinski

Jürgen Christopher Thiesen

Christoph Ihl

Published

January 1, 2025

Doi

10.5465/AMPROC.2025.18846abstract

Abstract
Venture Capital (VC) investments positively impact startup success, enhancing operational performance through factors like collaboration and value-added services. While research on investment decisions primarily focuses on investors’ selection criteria and decision-making processes, our study addresses the gap in founders’ perspective. Using Generative Pre-Trained Transformers (GPT) for text classification on a dataset of 8,561 online VC reviews, we extract 9,229 unique value-criteria from founders’ perspectives. A text-embedding cluster method categorizes these criteria into 26 categories. By analyzing additional startup lifecycle data, we determine which value-criteria are crucial at different startup stages. Our findings reveal that investors’ “general social skills” are the most important value-criteria across all startup stages, while more mature startups prioritize more self-serving criteria focused on growth and long-term relationships. Additionally, we observe that founders mostly fulfill the value-criteria by investors, with “general advice” being particularly well-executed.

Research

© Anne Gärtner

  • Conference Paper
  • 2025
  • Vol. 2025(1)
  • DOI

Authors

Oliver Specht, Jonas Wilinski, Jürgen Christopher Thiesen, Christoph Ihl

Abstract

Venture Capital (VC) investments positively impact startup success, enhancing operational performance through factors like collaboration and value-added services. While research on investment decisions primarily focuses on investors’ selection criteria and decision-making processes, our study addresses the gap in founders’ perspective. Using Generative Pre-Trained Transformers (GPT) for text classification on a dataset of 8,561 online VC reviews, we extract 9,229 unique value-criteria from founders’ perspectives. A text-embedding cluster method categorizes these criteria into 26 categories. By analyzing additional startup lifecycle data, we determine which value-criteria are crucial at different startup stages. Our findings reveal that investors’ “general social skills” are the most important value-criteria across all startup stages, while more mature startups prioritize more self-serving criteria focused on growth and long-term relationships. Additionally, we observe that founders mostly fulfill the value-criteria by investors, with “general advice” being particularly well-executed.

Tags

Venture Capital Founders NLP GPT