PLATFORM OR WHOLESALE? A STRATEGIC TOOL FOR ONLINE RETAILERS TO BENEFIT FROM THIRD-PARTY INFORMATION

• 成果类型: Article
• 署名作者: Kwark, Young; Chen, Jianqing; Raghunathan, Srinivasan
• 署名单位: State University System of Florida; University of Florida; University of Texas System; University of Texas Dallas
• 刊物名称: MIS QUARTERLY
• ISSN/ISSBN: 0276-7783
• 发表日期: 2017
• 页码: 763-+
• 关键词: word-of-mouth; consumer reviews; product reviews; MARKETS; uncertainty; COMPETITION; QUALITY; differentiation; ECONOMICS; internet

摘要

Online retailing is dominated by a channel structure in which a retailer either buys products from competing manufacturers and resells to consumers (wholesale scheme) or lets manufacturers sell directly to consumers on its platform for a commission (platform scheme). Easy access to publicly available third-party information such as product reviews that facilitate consumers' purchase decisions is another distinctive and ubiquitous characteristic of online retailing. We show that retailers can use the upstream pricing scheme, wholesale or platform, as a strategic tool to benefit from third-party information. Information on the quality dimension homogenizes consumers' perceived utility differences between competing products and increases the upstream competition, which benefits the wholesale-based retailer but hurts the platform-based retailer. Information on the fit dimension, in constrast, heterogenizes consumers' estimated fits to the products and softens the upstream competition, which hurts the wholesale-based retailer but benefits the platform-based retailer. Consequently, when the precision of the third-party information is high (low), a retailer can benefit from third-party information by adopting the wholesale (platform) scheme if the quality dimension plays a dominant role and by adopting the platform (wholesale) scheme if the fit dimension is dominant. Furthermore, the effect of precision improvement on the retailer's profit depends on the pricing-scheme choice and the relative importance of quality and fit attributes in consumers' evaluations of products. For instance, when the fit dimension is dominant, increasing the precision can hurt the wholesale-based retailer but benefit the platform-based retailer.