The incentives for information sharing in online retail platforms

Qinjia Zhong, Jianjun Wang, Zongbao Zou and Xiaofan Lai

Transportation Research Part E: Logistics and Transportation Review, 2023, vol. 172, issue C

Abstract: Compared with the traditional brick-and-mortar retail industry, e-commerce has numerous advantages in the collection of consumer demand information, and big data technology can help online platforms forecast accurate demand information from the collected data, which can then be used to improve business operations. To investigate the incentives for sharing the forecast information with or without platform encroachment, this paper establishes stylized analytical models in an e-commerce setting consisting of a manufacturer, an online platform and a third-party retailer (as a reseller). Depending on whether the online platform encroachment happens or not, we consider two different platform operation modes, namely, the mode without platform encroachment where only the third-party retailer sells products, and the mode with platform encroachment where both the online platform and the third-party retailer sell products. Our analysis shows that when the online platform does not encroach, it has no incentives to share forecast information with the manufacturer, but always has incentives to share forecast information with the third-party retailer. Interestingly, when the online platform encroaches, the online platform may share forecast information, depending on the level of substitutability between products and commission rate charged by it, either only with the third-party retailer, or with both the manufacturer and the third-party retailer, or with none of them.

Keywords: Platform retailing; Information sharing; Demand uncertainty; Co-opetition (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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DOI: 10.1016/j.tre.2023.103050

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