Herding in Equity Crowdfunding

Abstract

Do equity crowdfunding investors rationally or irrationally herd? We build a model of rational information aggregation where both informed and uninformed investors arrive sequentially and rationally choose whether and how much to invest. We compare the predictions of the model to several alternative models of irrational herding and no herding, and test those predictions using data on all investments on a leading European equity crowdfunding platform. We show empirically that the size and likelihood of a pledge is causally affected by the size of the most recent pledge, and by the time elapsed since the most recent pledge. These results are consistent with rational information aggregation, and inconsistent with naïve herding, independent investments, and common information shocks. However, there is still room for negative information cascades to occur. Implications for platform design and regulatory actions are discussed.

Success drivers of online equity crowdfunding campaigns

“…Campaigns with a larger number of early investors are more likely to become successful, possibly because early investments send a signal of trust and confidence to prospective later investors and because early investors may contribute to the word-of-mouth around the campaign (Lukkarinen et al, 2016;Vismara, 2018a;Vulkan et al, 2016). Furthermore, the size of previous investments is a positive predictor of subsequent investment activity at campaign level, as large investments may send a signal that the investor possesses such knowledge of the campaign that others do not (Hornuf and Schwienbacher, 2018;Vulkan et al, 2016;Åstebro et al, 2018). Similarly, the amount of time that has passed since the most recent investment has a negative effect on the likelihood and size of investment, as an absence of investments can 29 be indicative of a lack of investors who would possess good private signals of the campaign (Åstebro et al, 2018).…”

“…Although unanimity among research findings exists regarding the influence of several campaign features such as campaign videos (Li et al, 2016;Vismara et al, 2017), minimum investment size (Hornuf and Schwienbacher, 2017;Lukkarinen et al, 2016), and campaign updates (Angerer et al, 2017;Block et al, 2018b;Hornuf and Schwienbacher, 2018;Li et al, 2016), venture characteristics such as previous funding from experienced investors (Kleinert et al,. 2018;Mamonov and Malaga, 2018), as well as herding behavior (Hornuf and Schwienbacher, 2018;Vismara, 2018a;Vulkan et al, 2016;Åstebro et al, 2018), contradictory results prevail as well. For example, it remains unclear whether campaign duration (Lukkarinen et al, 2016;Piva and Rossi-Lamastra, 2018;Vismara, 2018), the portion of equity retained by the entrepreneurs (Ahlers et al, 2015;Ralcheva and Roosenboom, 2016;Vismara, 2016), or intellectual property rights (Ahlers et al, 2015;Kleinert et al 2018;Piva and Rossi-Lamastra, 2018;Ralcheva and Roosenboom, 2016) influence funding success.…”

Subjective Norms and Intention- A Study of Crowdfunding in India

“…Pan, & Liu, (2018) stated that strong motivation to comply with referent groups will lead to the high inclination to participate in equity crowdfunding projects. Astebro et al (2018) concluded that early contributors gather and disseminate information to their referent groups which encourage other contributors to invest. Shneor and Munim (2019) studied the reward-based crowdfunding and proposed that factors like attitude, self-efficacy, and subjective norms have a direct relationship with the contribution behavior.…”

How lead investors build trust in the specific context of a campaign

“…Amateur investors typically lack the experience and capability to perform extensive due diligence (Ahlers et al 2015;Agrawal et al 2015). Bernstein et al (2017) found that existing lead investors seem to have little influence on follow-on investors' screen decisions, whilst other studies suggested that follow-on investors herd after professional investors (Astebro et al 2017). Such inconsistent findings, based mainly on evidence recorded in a platform, suggest a need to investigate the unobservable decision-making processes of ECF investors and gather in-depth evidence from multiple sources.…”

“…Consequently, a wide range of determinants have been identified: expertise and experience possessed by founding entrepreneurs (Ahlers et al, 2015), their social networks (Vismara, 2016), equity retention (Vismara, 2016), updates (Block et al, 2018), and behaviours of professional investors (Vismara, 2018;Bernstein at al., 2017). These studies have employed a signalling theory to examine what signals from the entrepreneurs and venture determine the likelihood of online campaign success (Ahlers et al, 2015), with the exception of Vismara (2018) and Astebro et al (2017). The literature are currently dominated by quantitative studies.…”