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Assortment Optimization with Customer Choice Modeling in a Crowdfunding Setting

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  • Fatemeh Nosrat

Abstract

Crowdfunding, which is the act of raising funds from a large number of people's contributions, is among the most popular research topics in economic theory. Due to the fact that crowdfunding platforms (CFPs) have facilitated the process of raising funds by offering several features, we should take their existence and survival in the marketplace into account. In this study, we investigated the significant role of platform features in a customer behavioral choice model. In particular, we proposed a multinomial logit model to describe the customers' (backers') behavior in a crowdfunding setting. We proceed by discussing the revenue-sharing model in these platforms. For this purpose, we conclude that an assortment optimization problem could be of major importance in order to maximize the platforms' revenue. We were able to derive a reasonable amount of data in some cases and implement two well-known machine learning methods such as multivariate regression and classification problems to predict the best assortments the platform could offer to every arriving customer. We compared the results of these two methods and investigated how well they perform in all cases.

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  • Fatemeh Nosrat, 2022. "Assortment Optimization with Customer Choice Modeling in a Crowdfunding Setting," Papers 2207.07222, arXiv.org.
  • Handle: RePEc:arx:papers:2207.07222
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    References listed on IDEAS

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    1. Belleflamme, Paul & Omrani, Nessrine & Peitz, Martin, 2015. "The economics of crowdfunding platforms," Information Economics and Policy, Elsevier, vol. 33(C), pages 11-28.
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    4. Jacob Feldman & Huseyin Topaloglu, 2015. "Bounding Optimal Expected Revenues for Assortment Optimization under Mixtures of Multinomial Logits," Production and Operations Management, Production and Operations Management Society, vol. 24(10), pages 1598-1620, October.
    5. Paat Rusmevichientong & David Shmoys & Chaoxu Tong & Huseyin Topaloglu, 2014. "Assortment Optimization under the Multinomial Logit Model with Random Choice Parameters," Production and Operations Management, Production and Operations Management Society, vol. 23(11), pages 2023-2039, November.
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