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To syndicate or not: a replication and extension about the influence of business angels’ personality traits on syndication using Twitter data

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Abstract

Personality traits can determine business angels’ decision to engage in syndication (i.e., co-investing with other investors). We conduct a quasi-random replication of Block et al. (J Bank Finance 100:306–327, 2019), who document an influence of the Big 5 personality traits on syndication. We employ a machine learning-based approach to operationalize business angels’ personality traits in a comprehensive sample of 4449 investments made by 1241 US business angels. Our main analysis underlines that personality traits determine syndication behaviour but highlights that different measurement tools may produce different results. We extend these findings by conducting complementary analyses that further nuance the relation between personality and syndication in business angel investing. These further analyses consider interaction effects between business angels’ personality traits and sociodemographic characteristics (e.g., gender, age, and investment experience). We also apply a closed-language tool to measure personality-related variables. Overall, our findings highlight the importance of replication studies in entrepreneurship research, especially when tools leveraging artificial intelligence are used.

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Data availability

Most of the datasets generated and analysed are proprietary, so that the authors are not at liberty to share them. However, the datasets and analyses that are not proprietary are available from the authors upon reasonable request.

Notes

  1. While we refer to “personality traits” throughout this study, synonyms include “personality-related factors”, “psychological traits”, “attributes”, or “characteristics”.

  2. In a robustness check, we additionally control for the business angels’ emotional tone. The results (Table A1, appendix) underline the robustness of our main findings.

  3. We also note that the Big 5 traits generated from Receptiviti when we applied the tool in November 2023 differ from those obtained by Block et al. (2019). Apart from differences in the underlying sample of business angels and tweets, Receptiviti’s algorithms have likely changed over the years, making a comparison with the scores obtained by Block et al. (2019) difficult.

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  1. Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, 29, Avenue John F. Kennedy, 1855, Luxembourg, Luxembourg

    Angela Altmeier & Christian Fisch

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  1. Angela Altmeier
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  2. Christian Fisch
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AA: Conceptualization, Methodology, Investigation, Data Curation, Writing—Original Draft, Writing—Review & Editing, Project administration; CF: Conceptualization, Methodology, Writing—Review & Editing, Project administration, Supervision.

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Correspondence to Angela Altmeier.

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Table A1 Robustness check: logistic regression analysis that includes emotional tone as an additional control variable
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Altmeier, A., Fisch, C. To syndicate or not: a replication and extension about the influence of business angels’ personality traits on syndication using Twitter data. Manag Rev Q (2024). https://doi.org/10.1007/s11301-024-00410-7

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