The 'Experts' in the Crowd: The Role of Experienced Investors in a Crowdfunding Market
To Appear in MIS Quarterly
66 Pages Posted: 30 Apr 2013 Last revised: 10 Dec 2018
Date Written: May 26, 2018
Using a data set on individual investments in an online crowdfunding platform for mobile applications, this study examines whether an early investor’s experience within the platform serves as credible signals of quality for the other investors in the crowd and if so under what conditions. We find that early investors with experience – particularly, investors with app development experience and investors with app investment experience - have a disproportionate influence on later investors in the crowd. Investors with app development experience who are likely to have a better knowledge of the product are found to be more influential for “concept apps” (apps in the pre-release stage), while investors with app investment experience with a better knowledge of market performance are found to be more influential for “live apps” (apps that are already being sold in the market). Our findings show that the majority of investors in this market – the crowd – although inexperienced in this market, are rather sophisticated in their ability to identify and exploit nuanced differences in the underlying expertise of the early investors – signals that align well with their informational needs at different stages of a venture. In examining the ex-post performance of apps, we find that apps with investments from investors with experience are positively associated with ex-post app sales. More importantly, we find that these investors with experience indeed have the ability to select better apps, making their investment choices credible signals of quality for the crowd. Contrary to popular perceptions of crowdfunding platforms as substitutes for traditional expert-dominated mechanisms, our findings indicate that the participation by individuals with experience can be beneficial to these markets.
Keywords: crowdfunding, investor experience, quality signals, information asymmetry, herding, market design
JEL Classification: D81, L15, L86
Suggested Citation: Suggested Citation