An Empirical Study of the Dynamic and Differential Effects of Prefunding

Xiahua Wei, Ming Fan, Weijia You and Yong Tan

Production and Operations Management, 2021, vol. 30, issue 5, 1331-1349

Abstract: This study investigates the dynamic and differential effects of prefunding on reward‐based crowdfunding markets plagued by information asymmetry. Prefunding, an innovative feature in crowdfunding, enables founders to share project information with potential backers before fundraising begins. By collecting and analyzing daily project‐level panel data from one of the world's largest crowdfunding platforms, we found that projects with the prefunding feature were more likely to succeed in reaching their funding goals and the effects of prefunding on the amount of funds raised remained positive and significant over time. In probing why this occurred, we used text analyses and revealed that the mechanisms driving the funding premium were the specific types of prefunding information shared between founders and potential backers (volume, length, and sentiment). Furthermore, in examining the sources of funds, we found that prefunding information first attracts funding from regular backers, followed by lottery backers. This herding behavior creates two intertwined funding streams—a primary and a secondary—for prefunding projects. Finally, using counterfactual decomposition analysis, we identified the types of projects that benefited the most from prefunding and found that prefunding democratizes funding outcomes. These findings and insights into information sharing, herding, and differential effects of prefunding contribute to the OM‐IS research on operational designs of reward‐based crowdfunding platforms that serve early‐stage ventures in online environments with minimal informational oversight and regulations.

Date: 2021
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