Learning Through Crowdfunding

Gilles Chemla () and Katrin Tinn
Additional contact information
Gilles Chemla: Imperial College Business School, London SW7 2AZ, United Kingdom; Centre for Economic Policy Research, London EC1V 0DX, United Kingdom.; Centre National de la Recherche Scientifique, Paris Sciences et Lettres, Paris 75016, France

Management Science, 2020, vol. 66, issue 5, 1783-1801

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; learning; uncertainty (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (32)

Downloads: (external link)
https://doi.org/10.1287/mnsc.2018.3278 (application/pdf)

Related works:
Working Paper: Learning Through Crowdfunding (2020)
Working Paper: Learning through Crowdfunding (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:66:y:2020:i:5:p:1783-1801

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().