Analyzing the game pricing mechanism of data assets: Theoretical evidence considering market structure and competitive characteristics

The trade of data assets is increasingly serving as a central impetus for economic progress. By implementing the strategy of “data assetisation”, companies not only increase their financial strength, but also pose new challenges for the valuation and pricing of data assets. In this paper, we use game theory to explore the impact of different market structures and the competitive characteristics of market participants on the pricing of data assets, with the aim of determining an appropriate price that can maximize the profits of both the supply and demand sides of data assets. It is found that the competitive characteristics of the demand side of data assets, such as the ability to exploit data and the ability to control costs, indirectly influence the pricing of data assets by regulating the level of data services. In addition, the study shows that the introduction of competition into the market structure helps to improve the pricing of data assets and the level of data services, thereby stimulating market dynamics and creating larger profit margins for data asset suppliers. Finally, the supply side of data assets needs to take into account the data needs of different demand sides when pricing, and ignoring vulnerable customers can harm the profits of both the supply and demand sides. Numerical analyses further support these conclusions. This study provides strong theoretical support and practical guidance for value measurement and transaction pricing of data assets.