Item Type |
Journal paper
|
Abstract |
Investors increasingly use machine learning (ML) algorithms to support their early stage investment decisions. However, it remains unclear if algorithms can make better investment decisions and if so, why. Building on behavioral decision theory, our study compares the investment returns of an algorithm with those of 255 business angels (BAs) investing via an angel investment platform. We explore the influence of human biases and experience on BAs’ returns and find that investors only outperformed the algorithm when they had extensive investment experience and managed to suppress their cognitive biases. These results offer novel insights into the role of cognitive limitations, experience, and the use of algorithms in early stage investing. |
Authors |
Blohm, Ivo; Antretter, Torben; Siren, Charlotta; Wincent, Joakim & Grichnik, Dietmar |
Research Team |
IWI6, Crowdsourcing, CCC |
Projects |
Blohm, Prof. Dr. Ivo; Wincent, Prof. Ph.D Joakim & Malmström, Malin
(2019)
Learning Algorithms for Discrimination Free Innovation Funding Activities
[fundamental research project]
|
Journal or Publication Title |
Entrepreneurship Theory and Practice |
Language |
English |
Subjects |
business studies information management |
HSG Classification |
contribution to scientific community |
HSG Profile Area |
Global Center for Entrepreneurship + Innovation |
Refereed |
Yes |
Date |
July 2022 |
Publisher |
Wiley-Blackwell SSH |
Number of Pages |
38 |
ISSN |
1042-2587 |
Publisher DOI |
https://doi.org/10.1177/1042258720945206 |
Depositing User |
Corinne Metzger-Wyder
|
Date Deposited |
06 Oct 2020 11:51 |
Last Modified |
08 Nov 2022 15:10 |
URI: |
https://www.alexandria.unisg.ch/publications/261136 |