Modeling the Competitive Content Service Market from the Perspective of Consumer Preferences: A Game Theory Approach

Deploying interaction-intensive AI-generated content (AIGC) services on mobile edge networks enables mobile AIGC to deliver personalized, high-quality content efficiently and cost-effectively. These services are designed to automatically generate content based on user inputs or requirements, positioning mobile AIGC as a promising solution for content creation in immersive and dynamic Metaverse environments. However, the current implementation of edge devices as AIGC Service Providers (ASPs) suffers from a lack of incentives, which impedes the sustainable delivery of high-quality edge AIGC services. This paper tries to design an incentive strategy by investigating the competition relationship among AIGC service providers (ASPs) as a Duopoly Game, which mathematically describes the competition among ASPs based on their service quality, cost, and prices. In this content service market, social planners issue policies to improve social welfare while providers maximize their profits according to the consumption preference of users. This consumption preference of consumers is described as consumer preference model to capture consumers' demands for different QoS services when different content service providers serve them simultaneously. The simulation shows that 1) competition among providers will produce more differences on content service quality than social regulation will bring; 2) more social welfare may be engendered by the competition among different ASPs.