ProjektEntrepreneurial Overconfidence – Advice Taking and Seeking
Grunddaten
Titel:
Entrepreneurial Overconfidence – Advice Taking and Seeking
Laufzeit:
01.01.2018 bis 30.06.2019
Abstract / Kurz- beschreibung:
Entrepreneurial startups are a crucial source of innovation (e.g., Acs and Audretsch, 1988). Venture capital funds (VCs) fuel the innovative activity by financing these startups (Samila and Sorenson, 2010; Kortum and Lerner, 2000). This makes VCs an important object of economic research. Extant research not only highlights the importance of VC funding for startups and innovation but also focuses on VCs’ advice. VCs’ advice to their startups distinguishes VCs from other investors. It serves as a vital resource and makes startups successful (Kerr, Lerner, and Schoar, 2014). This success depends on the startups’ willingness to search for and take the VC’s advice. However, the entrepreneurs who run these startups are known to be highly overconfident (Åstebro et al., 2014; Puri and Robinson, 2013) and specific aspects of overconfidence might hamper the willingness to take advice. Yet, we know little about how entrepreneurs seek and take advice and how entrepreneurial overconfidence affects this behavior.
The present project targets this question. First, we explore the degree to which entrepreneurs in IT-startups seek and take advice. Second, we investigate the impact of entrepreneurial overconfidence on how they take and seek advice. In so doing, we disentangle different forms of overconfidence (overestimation, overprecision, overplacement, see Moore and Healy, 2008; Benoît, Dubra, and Moore, 2015) and especially focus on overplacement and its incidence in startup teams. A special feature of our research project is the longitudinal nature of the dataset that we will build. This allows tracking changes in overconfidence over time (Merkle, 2017) and gives us the opportunity to rely on previous responses for comparing advice taking between different types of advisors (experts, managers, and peers). More specifically, we propose a longitudinal study based on a 12 months survey with 120 entrepreneurs and 100 employees as control group in Spain, UK, and Germany. In the survey, we track advice seeking and taking behavior and overconfidence of the participants each quarter. Hence, we aim at a panel size of 220 quarterly observations, i.e., 880 in total.
Our findings will inform the entrepreneurial finance literature on overconfident entrepreneurs, and the strategy literature on how VCs can manage these entrepreneurs in terms of seeking and taking advice. Further, understanding how to stimulate advice taking in entrepreneurs matters to VC managers and will increase the success rate of startups. Based on scientific findings obtained in our project, we will develop best practice approaches with our cooperation partners. The present project, however, is not only useful for the development of best practice approaches, but it is also informative to basic research on the psychology of advice seeking and taking. Existing research investigated influences of the task difficulty or the expertise of the advice giver. At the present stage, however, there is no research that links advice seeking and taking to person variables. Moreover, there is a lack of research tracing advice taking propensity over time. Hence, we are focusing for the first time on the interplay of person and situation variables in the advice taking domain.
The present project targets this question. First, we explore the degree to which entrepreneurs in IT-startups seek and take advice. Second, we investigate the impact of entrepreneurial overconfidence on how they take and seek advice. In so doing, we disentangle different forms of overconfidence (overestimation, overprecision, overplacement, see Moore and Healy, 2008; Benoît, Dubra, and Moore, 2015) and especially focus on overplacement and its incidence in startup teams. A special feature of our research project is the longitudinal nature of the dataset that we will build. This allows tracking changes in overconfidence over time (Merkle, 2017) and gives us the opportunity to rely on previous responses for comparing advice taking between different types of advisors (experts, managers, and peers). More specifically, we propose a longitudinal study based on a 12 months survey with 120 entrepreneurs and 100 employees as control group in Spain, UK, and Germany. In the survey, we track advice seeking and taking behavior and overconfidence of the participants each quarter. Hence, we aim at a panel size of 220 quarterly observations, i.e., 880 in total.
Our findings will inform the entrepreneurial finance literature on overconfident entrepreneurs, and the strategy literature on how VCs can manage these entrepreneurs in terms of seeking and taking advice. Further, understanding how to stimulate advice taking in entrepreneurs matters to VC managers and will increase the success rate of startups. Based on scientific findings obtained in our project, we will develop best practice approaches with our cooperation partners. The present project, however, is not only useful for the development of best practice approaches, but it is also informative to basic research on the psychology of advice seeking and taking. Existing research investigated influences of the task difficulty or the expertise of the advice giver. At the present stage, however, there is no research that links advice seeking and taking to person variables. Moreover, there is a lack of research tracing advice taking propensity over time. Hence, we are focusing for the first time on the interplay of person and situation variables in the advice taking domain.
Beteiligte Mitarbeiter/innen
Leiter/innen
Fachbereich Wirtschaftswissenschaft
Wirtschafts- und Sozialwissenschaftliche Fakultät
Wirtschafts- und Sozialwissenschaftliche Fakultät
Startup Center
Außenstellen und sonstige zentrale Einrichtungen
Außenstellen und sonstige zentrale Einrichtungen
Mathematisch-Naturwissenschaftliche Fakultät
Universität Tübingen
Universität Tübingen
Fachbereich Psychologie
Mathematisch-Naturwissenschaftliche Fakultät
Mathematisch-Naturwissenschaftliche Fakultät
Graduiertenkolleg: Statistische Modellierung in der Psychologie (SMiP)
Graduiertenkollegs
Graduiertenkollegs
Fachbereich Wirtschaftswissenschaft
Wirtschafts- und Sozialwissenschaftliche Fakultät
Wirtschafts- und Sozialwissenschaftliche Fakultät
Lokale Einrichtungen
Fachbereich Wirtschaftswissenschaft
Wirtschafts- und Sozialwissenschaftliche Fakultät
Universität Tübingen
Universität Tübingen
Fachbereich Psychologie
Mathematisch-Naturwissenschaftliche Fakultät
Universität Tübingen
Universität Tübingen
Geldgeber
Köln, Nordrhein-Westfalen, Deutschland