Learning Through Crowdfunding

Gilles Chemla and Katrin Tinn
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Gilles Chemla: DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique

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Abstract: We develop a model in which 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 preordering a new product. Learning from the crowdfunding sample creates a valuable real option because firms invest only if updated expectations about total demand are 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. Although 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.

Keywords: Reward-based crowdfunding; moral hazard; real options; uncertainty (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (26)

Published in Management Science, 2020, 66 (5), pp.1783-1801. ⟨10.1287/mnsc.2018.3278⟩

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Journal Article: Learning Through Crowdfunding (2020)
Working Paper: Learning through Crowdfunding (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03342460

DOI: 10.1287/mnsc.2018.3278

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