INDIVIDUAL SELECTION ABILITY IN CROWDINVESTING

INDIVIDUAL SELECTION ABILITY IN CROWDINVESTING Nico Zeiner, University of Mannheim, Chair of Organization and Innovation 3rd year of enrolment; expected final date: 2020; nico.zeiner@uni-mannheim.de Analyzing the performance of early-stage investors and their ability to build winners has a long tradition in the entrepreneurial finance literature (Baum and Silverman, 2004; Colombo and Grilli, 2010; Bertoni et al., 2011, 2013; Chemmanur et al., 2011; Puri and Zarutskie, 2012; Croce et al., 2013). Professional investors, such as Venture Capitalists, take on the risk of financing early stage start-ups hoping that at least some start-ups turn out to be blockbusters (Sahlman, 1990). To reduce the inherent high risk of failure, professional investors do not only provide financial resources but also act as scouts and coaches (Baum and Silverman, 2004). One could argue that investor performance requires both selecting the most promising start-ups and providing the necessary management expertise. However, professional investors are often selected by start-ups. Hence, professional investors, who have been successful in the past typically have access to qualitatively better start-ups, which are also likely to perform better in the future (Nanda et al., 2018). Overall, the performance of early-stage investors is hard to disentangle from the performance of the start-up, because of the selection mechanisms and the management and coaching activities of professional investors (Bertoni et al., 2011). Literature on the selection ability of early-stage investors is scarce. Most of the studies only investigate how investors select start-ups, without exploring whether these criteria actually reflect the underlying quality of a start-up (Baum and Silverman, 2004). This study investigates the selection ability of early-stage investors in the context of crowdinvesting, an alternative financing channel for entrepreneurs that gained substantial interest in both academia and practice (Hornuf and Schwienbacher, 2017). Crowdinvesting allows private investors without (visible) experience to invest in start-ups (Ahlers et al., 2015). In comparison to professional investors, crowdinvestors are not entitled to any participation rights to issue management instructions. Due to this concentrated property rights structure, the performance of the crowdfunded start-up is largely independent from the expertise of the crowd. Hence, the performance of the individual crowdinvestor depends on his ability to select startups that turn out to be successful investments over time. From a policy perspective, it is important to understand the crowd at the individual level of the investor, as there have been many concerns about the participation of private individuals in a market characterized by a high risk of failure. Therefore, it is important to understand how individual crowdinvestors actually perform over time in order to derive adequate regulations for their protection. In the context of crowdfunding and crowdinvesting, investors differ considerably in terms of the timing of their contribution to a campaign and the amount of money they invest (Kuppuswamy and Bayus, 2017; Hornuf and Schwienbacher, 2018; Vismara, 2018; Wick and Ihl, 2018). Therefore, we are interested in exploiting the variance within the crowd with regard to the timing and amount of investments to analyze if these characteristics actually explain an investor’s selection ability. Whereas early investors effectively screen signals to assess the underlying quality of the start-up, later investors might lack knowledge to evaluate the fundamental value of a start-up observe and interpret early investments as a signal of certification. In addition, individuals contributing significantly more money to campaigns invest more effort in their due diligence than investors contributing small amounts of money (e.g. Vismara, 2018). We use a unique dataset containing investment-level information on all crowdinvestors on Companisto, the leading crowdinvesting platform in Germany. In total, the dataset consists of 8,108 investors with 41,513 investments in 74 campaigns from June 2012 to April 2018. Due to the specific data structure, we apply survival analysis techniques. Overall, this study shows that the individual selection ability of crowdinvestors reflects the heterogeneity within the crowd with regard to their investment behavior. Results indicate that investors contributing early to a campaign and investing higher amounts of money have a higher likelihood of experiencing an exit. For example, investors contributing within the second half of a campaign have a 14% lower likelihood of experiencing an exit than investors contributing before 50% of the funding goal is reached.