Attracting the Right Crowd under Asymmetric Information: A Game Theory Application to Rewards-Based Crowdfunding

• Published in: Mathematics (Basel) Vol. 9; no. 21; p. 2757
• Main Authors: Jiménez-Jiménez, Francisca, Alba-Fernández, Maria Virtudes, Martínez-Gómez, Cristina
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2021
• Subjects: asymmetric information; Asymmetry; conditional process analysis; Consumers; Crowdfunding; Empirical analysis; Entrepreneurial finance; Entrepreneurs; entrepreneurship; Food science; Funding; Game theory; Hypotheses; Moral hazard; price discrimination; Profits; Regression analysis; signaling; Social networks; Startups; Success; Variables
• ISSN: 2227-7390; 2227-7390
• DOI: 10.3390/math9212757

In this paper, we investigate rewards-based crowdfunding as an innovative financing form for startups and firms. Based on game-theory models under asymmetric information, we test research hypotheses about the positive effects of two main campaign features: funding target and number of rewards. Furthermore, we examine how and when these characteristics are effective in attracting crowdfunders, by signaling high-quality projects (target) and by pricing according to backers’ preferences (rewards). Conditional process analysis is applied to a dataset of 1613 projects launched on the Spanish platform Verkami from 2015 to 2018. As expected, our study shows that market size is positively influenced by the target and the number of rewards, separately. Further analysis gives some interesting findings. Firstly, we find significant and positive mediating roles of social networks (in the relationship between target and market size) and of backers’ preferences (between rewards and market size). Secondly, the main orientation of a campaign, commercial or social, is relevant to explain previous relationships. While high funding targets are more effective in commercial projects, a high number of rewards is more effective in the social projects. This research provides new insights into the design of optimal crowdfunding, with theoretical and empirical implications.