Selling formats and platform information sharing under manufacturer competition

Author:

Li Xue1ORCID,Tong Shilu2,Cai Xiaoqiang3ORCID,Chen Jian4ORCID

Affiliation:

1. International Business School Beijing Foreign Studies University Beijing China

2. Shenzhen Finance Institute School of Management and Economics, The Chinese University of Hong Kong Shenzhen China

3. Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology The Chinese University of Hong Kong, Shenzhen Research Institute of Big Data Shenzhen China

4. Research Center for Contemporary Management Key Research Institute of Humanities and Social Sciences at Universities, School of Economics and Management, Tsinghua University Beijing China

Abstract

AbstractOnline retail platforms have increasingly utilized big data technologies to gather demand information, which is then shared with upstream manufacturers employing various selling modes, including a hybrid format that encompasses both direct and indirect selling. Previous studies have suggested that platforms should refrain from sharing demand information with manufacturers engaged in indirect selling. In this study, we present a game‐theoretic model to examine the factors influencing the online platform's decision to share information with an indirect selling manufacturer and under what conditions. Our initial analysis, considering exogenous selling formats in the base model, reveals that the platform's information sharing behavior is primarily influenced by selling format structures, commission fee rates, and competition intensity. The platform always has an incentive to share information with direct selling manufacturers; however, under a hybrid selling format, information sharing with indirect selling manufacturers may occur, particularly when both the commission fee rate and competition intensity are relatively high. We extend our investigation to explore the platform's optimal format‐dependent information sharing behavior, accounting for manufacturers' endogenous selling format decisions, and demonstrate the robustness of our main findings from the base model. Overall, our research offers valuable insights and guidelines to assist online platforms in making informed decisions about their information sharing practices.

Funder

National Natural Science Foundation of China

Science, Technology and Innovation Commission of Shenzhen Municipality

Publisher

Wiley

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