Vol.127, No.1, 2021, pp.291-307, doi:10.32604/cmes.2021.014347
OPEN ACCESS
ARTICLE
Dynamic Pricing Model of E-Commerce Platforms Based on Deep Reinforcement Learning
  • Chunli Yin1,*, Jinglong Han2
1 College of Economics and Administration, Tonghua Normal University, Jilin, 130000, China
2 Department of Administration Section, Tonghua Normal University, Jilin, 130000, China
* Corresponding Author: Chunli Yin. Email:
(This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
Received 19 September 2020; Accepted 12 November 2020; Issue published 30 March 2021
Abstract
With the continuous development of artificial intelligence technology, its application field has gradually expanded. To further apply the deep reinforcement learning technology to the field of dynamic pricing, we build an intelligent dynamic pricing system, introduce the reinforcement learning technology related to dynamic pricing, and introduce existing research on the number of suppliers (single supplier and multiple suppliers), environmental models, and selection algorithms. A two-period dynamic pricing game model is designed to assess the optimal pricing strategy for e-commerce platforms under two market conditions and two consumer participation conditions. The first step is to analyze the pricing strategies of e-commerce platforms in mature markets, analyze the optimal pricing and profits of various enterprises under different strategy combinations, compare different market equilibriums and solve the Nash equilibrium. Then, assuming that all consumers are naive in the market, the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed. By comparing and analyzing the optimal pricing and total profit of each enterprise under different strategy combinations, the subgame refined Nash equilibrium is solved. Finally, assuming that the market includes all experienced consumers, the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.
Keywords
Deep reinforcement learning; e-commerce platform; dynamic evaluation; game model; pricing strategy
Cite This Article
Yin, C., Han, J. (2021). Dynamic Pricing Model of E-Commerce Platforms Based on Deep Reinforcement Learning. CMES-Computer Modeling in Engineering & Sciences, 127(1), 291–307.
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