Next Article in Journal
What Drives VOD Purchases in Mobile TV Services? Exploring Utilization, Motivations, and Personality Traits
Next Article in Special Issue
COVID-19 and Supply Chain Disruption Management: A Behavioural Economics Perspective and Future Research Direction
Previous Article in Journal
From Fake Reviews to Fake News: A Novel Pandemic Model of Misinformation in Digital Networks
Previous Article in Special Issue
An Explainable Artificial Intelligence Approach for Multi-Criteria ABC Item Classification
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Optimal Recommendation Strategies for AI-Powered E-Commerce Platforms: A Study of Duopoly Manufacturers and Market Competition

1
School of Management, Tianjin University of Technology, Tianjin 300384, China
2
School of E-Commerce and Logistics, Beijing Technology and Business University, Beijing 100048, China
3
Labovitz School of Business and Economics, University of Minnesota Duluth, Duluth, GA 55812, USA
*
Authors to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 1086-1106; https://doi.org/10.3390/jtaer18020055
Submission received: 5 May 2023 / Revised: 27 May 2023 / Accepted: 5 June 2023 / Published: 7 June 2023

Abstract

Artificial intelligence-powered recommendation systems have gained popularity as a tool to enhance user experience and boost sales. Platforms often need to make decisions about which seller to recommend and the strength of the recommendation when conducting recommendations. Therefore, it is necessary to explore the recommendation strategy of the platform in the case of duopoly competition. We develop a game model where two competing manufacturers sell products through an agency contract on a common platform, and they can decide whether or not to provide recommendations to the manufacturers. Our highlight lies in the endogenous recommendation strength of the platform. The findings suggest that it is optimal for the platform to offer recommendation services when the commission rate is high. The platform also prefers to only recommend one manufacturer in the market with low or high competition, but it prefers to recommend both manufacturers in moderately competitive markets. From the view of manufacturers, they can benefit from the recommendation service as long as the commission rate is not too low. Moreover, recommending only one manufacturer consistently yields stronger recommendations compared to recommending multiple manufacturers. However, the impact of recommendation on prices is influenced by the commission rate and product substitutability. These results have significant implications for platform decision making and provide valuable insights into the trade-offs involved in the development of recommendation systems.
Keywords: recommendation strategy; platform operations; duopoly competition; pricing strategies; product substitutability recommendation strategy; platform operations; duopoly competition; pricing strategies; product substitutability

Share and Cite

MDPI and ACS Style

Zhou, C.; Li, H.; Zhang, L.; Ren, Y. Optimal Recommendation Strategies for AI-Powered E-Commerce Platforms: A Study of Duopoly Manufacturers and Market Competition. J. Theor. Appl. Electron. Commer. Res. 2023, 18, 1086-1106. https://doi.org/10.3390/jtaer18020055

AMA Style

Zhou C, Li H, Zhang L, Ren Y. Optimal Recommendation Strategies for AI-Powered E-Commerce Platforms: A Study of Duopoly Manufacturers and Market Competition. Journal of Theoretical and Applied Electronic Commerce Research. 2023; 18(2):1086-1106. https://doi.org/10.3390/jtaer18020055

Chicago/Turabian Style

Zhou, Chi, He Li, Linlin Zhang, and Yufei Ren. 2023. "Optimal Recommendation Strategies for AI-Powered E-Commerce Platforms: A Study of Duopoly Manufacturers and Market Competition" Journal of Theoretical and Applied Electronic Commerce Research 18, no. 2: 1086-1106. https://doi.org/10.3390/jtaer18020055

APA Style

Zhou, C., Li, H., Zhang, L., & Ren, Y. (2023). Optimal Recommendation Strategies for AI-Powered E-Commerce Platforms: A Study of Duopoly Manufacturers and Market Competition. Journal of Theoretical and Applied Electronic Commerce Research, 18(2), 1086-1106. https://doi.org/10.3390/jtaer18020055

Article Metrics

Back to TopTop