Optimal homing policy of the manufacturer facing competing platforms: the effect of selling formats

Abstract

This paper explores the optimal homing policy of a manufacturer who sells products through two competing platforms: a traditional online platform and a social commerce platform. The social platform can choose to operate with reselling or agency selling format. Through analysis, we first find that the manufacturer’s optimal decision regarding whether to single- or multi-home and the social platform’s optimal decision regarding whether to adopt reselling or agency selling format depend mainly on the intensity of the downstream competition and the platforms’ market sizes. Specifically, the manufacturer prefers single-homing if the competition intensity is relatively low and the traditional platform’s market size is relatively large. When the competition intensity increases (decreases), the agency selling (reselling) format is always the social platform’s preferred choice. Next, we find that the manufacturer is less likely to choose multi-homing (single-homing) and the social platform is more likely to select agency selling (reselling) format when the traditional platform serves as a marketplace rather than a reseller. Finally, numerical studies show that the manufacturer’s and the platforms’ preferences for selling modes are always misaligned. However, an all-win situation is achieved with the pure agency selling mode when the competition intensity is relatively high.

KEYWORDS:

• Homing policy
• platform competition
• selling format
• social commerce
• game theory

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, Wen Zhang, upon reasonable request.

Notes

1 https://www.statista.com/statistics/379046/worldwide-retail-e-commerce-sales/.

2 https://www.imarcgroup.com/social-commerce-market.

3 https://influencermarketinghub.com/social-commerce-platform/#toc-11.

4 https://www.statista.com/statistics/1231944/.

5 https://school.jinritemai.com/doudian/web/article/106833.

6 https://www.sohu.com/a/473961952_120228837.

7 https://baijiahao.baidu.com/s?id=1733147313859407461&wfr=spider&for=pc.

8 https://douyinec.com/.

9 https://influencermarketinghub.com/social-commerce-stats/#toc-17.

10 https://douyinec.com/content?id=113988.

Additional information

Funding

This work was supported by National Natural Science Foundation of China: [Grant Numbers: 72271109, 72201110].

Notes on contributors

Xujin Pu

Xujin Pu is currently a professor in School of Business, Jiangnan University. He received the Ph.D. degree from University of Science and Technology of China, Hefei, China. His research interests are main focus on agricultural supply chain management and platform operations management. His research results have been published in Omega, European Journal of Operational Research, Journal of Retailing and Consumer Services, Managerial and Decision Economics, etc.

Zhenzhen Wang

Zhenzhen Wang is currently a postgraduate student at the School of Business, Jiangnan University. Her main research directions include supply chain management and platform economy.

Wen Zhang

Wen Zhang is currently a lecture in School of Business, Jiangnan University. He received the Ph.D. degree in 2021 from University of Science and Technology of China, Hefei, China. His research interest is operations management. His research results have been published in Production and Operations Management, Annals of Operations Research, Transportation Research Part E: Logistics and Transportation Review, Computers in Human Behaviour, etc.