Fixed Fee or Proportional Fee? Contracts in Platform Selling Under Asymmetric Information

ABSTRACT

In platform selling, platforms commonly charge third-party sellers a commission fee, which affects sellers’ decision making and platforms’ contract choice. This study explores this choice where a platform privately knows the market size and intends to signal to a seller. We aim to provide researchers and platform-selling practitioners insights into contract and information strategies. The result shows that the fixed-fee contract leads to either a costly or a costless signaling scenario. In costly scenarios, the high-demand platform must downward distort the fixed rent to distinguish itself from the low-demand platform. This distortion results in a different consensus on two players’ contract preference when the commission rate in the proportional-fee contract is exogenous. Under symmetric information, consensus is achieved only on the proportional-fee contract. However, in asymmetric information settings, this consensus may arise on fixed-fee contracts if market uncertainty is high. Furthermore, the comparison of information strategies reveals that players can reach an agreement on both the information-sharing strategy and the proportional-fee contract under certain conditions. When the platform endogenously determines the commission rate, this decision making can also signal demand type, and only the proportional-fee contract leads to a win–win outcome.

KEY WORDS AND PHRASES:

• Platform selling
• asymmetric information
• signaling game
• contract choice
• online platforms
• commission fees

Acknowledgments

We thank the editor-in-chief, Professor Vladimir Zwass, and two anonymous reviewers for their constructive comments and suggestions. This work is supported by the National Natural Science Foundation of China, no. 72102163, and the Humanities and Social Sciences Youth Foundation, Ministry of Education of China, no. 20YJC630037.

Disclosure Statement

No potential conflict of interest was reported by the authors.

Supplementary information

Supplemental data for this article can be accessed on the publisher’s website

Additional information

Notes on contributors

Jun Wang

Jun Wang ([email protected]) is an associate professor at the School of Management Science and Engineering, Tianjin University of Finance and Economics, China. He earned his PhD in management science and engineering from Tianjin University. Dr. Wang’s principal research interests include electronic commerce and supply chain management. His work has been published in Journal of Cleaner Production, Operational Research, and other journals.

Qian Zhang

Qian Zhang ([email protected]) is a graduate student at the School of Management Science and Engineering, Tianjin University of Finance and Economics, China.

Pengwen Hou

Pengwen Hou ([email protected]; corresponding author) is a lecturer at the Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, China. His research addresses supply chain management and blockchain. He has published in many journals, including Production and Operations Management, European Journal of Operational Research, Transportation Research Part E: Logistics and Transportation Review, IEEE Transactions on Systems Man Cybernetics: Systems, and International Journal of Production Economics. Dr. Hou’s research was supported by the National Natural Science Foundation of China.