业务
营销
产业组织
计算机科学
微观经济学
知识管理
经济
作者
Leela Nageswaran,Yu Kan,Uttara M Ananthakrishnan
出处
期刊:Management Science
[Institute for Operations Research and the Management Sciences]
日期:2025-10-16
标识
DOI:10.1287/mnsc.2023.01928
摘要
E-commerce retailers often need to make inventory decisions for new products under high uncertainty. We study a new business practice of using crowdvoting, wherein a retailer first seeks input from customers on the desirability of the product and then bases the purchasing decision on their votes. We collaborated with a subscription-based apparel rental platform and obtained a proprietary data set comprising the platform’s products and users. We leverage the staggered introduction of crowdvoting in different product categories to identify whether and, if so, by how much the adoption of crowdvoting improves business performance. We find that, after the adoption, both short- and long-term rental outcomes increase. We also uncover several mechanisms that drive this improvement. We find that the platform uses the wisdom of the crowd to make better inventory depth decisions, and the products are inherently a better match with users’ tastes. Moreover, we find that brands bought through crowdvoting are more likely to be newer brands compared with items that are bought solely through expert input. In other words, the diversity of the brands carried on the platform also improves. We also find that voters become more engaged with the platform: they post more reviews and are less likely to cancel their subscription after participating in crowdvoting. Our results have important implications for retailers who may be considering similar crowd-based strategies to improve their decision making. This paper was accepted by Victor Martínez-de-Albéniz, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01928 .
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