Pricing and sample set strategies of data providers under quality information asymmetry

Current data transactions are usually driven by data providers, and data buyers have little information about the data they will buy. In turn, this information asymmetry impacts the data providers' sales decisions. In this paper, we consider a data provider with private quality information to sell a data set to multiple potential data buyers, and the data provider signals quality information to the potential buyers by setting the price and sample set size. We study how the data provider decides the optimal trading strategy in terms of price and sample set size based on different characteristics of data buyers through a signalling game. It is found that the degree of information asymmetry and the cost of providing a sample set affect the data provider's choice of whether to signal data quality truthfully or to hide quality information. The joint signal of price and sample set is a better signalling option for data providers to achieve higher profits than the price signal alone. Tracing data trading back to the production process of datasets, the increased information asymmetry and inefficient data production make data providers more inclined to generate low-quality datasets, which adversely affects the data trading market.