Title: Social network analysis: unveiling the joint investment patterns of shark tank entrepreneurs

Authors: Nasser Shahrasbi; Tai-Yin Chi; Paul A. Beckman

Addresses: Department of Information Systems, San Francisco State University, San Francisco, CA, USA ' Department of Information Systems, San Francisco State University, San Francisco, CA, USA ' Department of Information Systems, San Francisco State University, San Francisco, CA, USA

Abstract: This research illustrates an important application of social network analysis in the entrepreneurship and venture capital domain. Using secondary data from the shark tanks TV show and graph analysis, our research unveils patterns in sharks' investment decisions that are not apparent using other methods like statistical analysis. Our network analysis over multiple seasons of the show reveals that the number of single investments increased almost perfectly linearly over time while double investments decreased mostly linearly, implying that most sharks (investors) find more value in investing solely than jointly with other investors. Our results also show that one particular shark (Mr. Kevin O'Leary) invested jointly (versus individually) at a much higher rate than the other Sharks. We hypothesise that this may have been attributed to his experience in financial investments and risk management, which resulted in taking more financial risks than other investors. We discuss how these results were not possible to obtain without relying on social network analysis and graph theory.

Keywords: social network analysis; venture capital; entrepreneurship; joint investing; graph theory; shark tank.

DOI: 10.1504/IJESB.2024.139619

International Journal of Entrepreneurship and Small Business, 2024 Vol.52 No.4, pp.431 - 449

Received: 18 Sep 2021
Accepted: 03 Mar 2022
Published online: 05 Jul 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article