Discovering Potential Founders Based on Academic Background

Arman Arzani, Marcus Handte, Matteo Zella, Pedro José Marrón

2023

Abstract

Technology transfer is central to the development of an iconic entrepreneurial university. Academic science has become increasingly entrepreneurial, not only through industry connections for research support or transfer of technology but also in its inner dynamic. To foster knowledge transfer, many universities undergo a scouting process by their innovation coaches. The goal is to find staff members and students, who have the knowledge, expertise and the potential to found startups by transforming their research results into a product. Since there is no systematic approach to measure the innovation potential of university members based on their academic activities, the scouting process is typically subjective and relies heavily on the experience of the innovation coaches. In this paper, we study the discovery of potential founders to support the scouting process using a data-driven approach. We create a novel data set by integrating the founder profiles with the academic activities from 8 universities across 5 countries. We explain the process of data integration as well as feature engineering. Finally by applying machine learning methods, we investigate the classification accurracy of founders based on their academic background. Our analysis shows that using a Random Forest (RF), it is possible to successfully differentiate founders and non-founders. Additionally, this accuracy of the classification task remains mostly stable when applying a RF trained on one university to another, suggesting the existence of a generic founder profile.

Paper Citation

in Harvard Style

Arzani A., Handte M., Zella M. and José Marrón P. (2023). Discovering Potential Founders Based on Academic Background. In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS; ISBN 978-989-758-671-2, SciTePress, pages 117-125. DOI: 10.5220/0012156200003598

in Bibtex Style

@conference{kmis23,
author={Arman Arzani and Marcus Handte and Matteo Zella and Pedro José Marrón},
title={Discovering Potential Founders Based on Academic Background},
booktitle={Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS},
year={2023},
pages={117-125},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012156200003598},
isbn={978-989-758-671-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS
TI - Discovering Potential Founders Based on Academic Background
SN - 978-989-758-671-2
AU - Arzani A.
AU - Handte M.
AU - Zella M.
AU - José Marrón P.
PY - 2023
SP - 117
EP - 125
DO - 10.5220/0012156200003598
PB - SciTePress