Learning Through Crowdfunding

We develop a model where reward-based crowdfunding enables firms to obtain a reliable proof of concept early in their production cycle: they learn about total demand from a limited sample of target consumers pre-ordering a new product. Learning from the crowdfunding sample creates a valuable real option as firms invest only if updated expectations about total demand is sufficiently high. This is particularly valuable for firms facing a high degree of uncertainty about consumer preferences, such as developers of innovative consumer products. Learning also enables firms to overcome moral hazard. The higher the funds raised, the lower the firms' incentives to divert them, provided third-party platforms limit the sample size by restricting campaign length. While the probability of campaign success decreases with sample size, the expected funds raised are maximized at an intermediate sample size. Our results are consistent with stylized facts and lead to new empirical implications