A dynamic evaluation model of data price based on game theory

With the development of big data and artificial intelligence, the value of data has become increasingly prominent. In traditional data trading platforms, pricing is completely controlled by the platform, data owners Then not understand the potential value of data, and online buyers and sellers lack credit, making it difficult to evaluate data prices in data transactions. This paper proposes a dynamic evaluation model of data price based on credit game, which consists of two parts: credit game model and data product pricing strategy. This paper respectively proves the existence of mixed-strategy Bayesian equilibrium and mixed-strategy perfect Bayesian equilibrium in the basic game process and repeated game process of price dynamic game. Compared with traditional trading platforms, this model initializes the pricing mechanism to prevent the deviation of data value, and introduces credit game for evaluation. Finally, through the simulation experiment to simulate the transaction between buyers and sellers, it is concluded that the credit function plays an important role in the data transaction, this model can complete the data price evaluation, the price difference percentage can be controlled around 10%, and the transaction success rate reaches 96%.