Survey of Data Pricing

Abstract

Data pricing is the behavior of taking data as assets and pricing the assets. In the current data markets, there is little transparency and information asymmetry between buyers and sellers, resulting in confusion in data pricing. If there is a standard process and evaluation method for data pricing, buyers can obtain datasets they need with a reasonable price, moreover, it would also improve the efficiency of data trading markets. This paper retrieves the relevant literatures about data pricing in recent years, and then summarizes the definition, characteristics, development and application scenarios of data pricing. It describes the data transaction process and data transaction costs, and focuses on describing two important research hotspots that affect data pricing, data pricing strategy and data pricing model. It comprehensively evaluates the mechanisms, advantages, disadvantages, and application scenarios of the existing six data pricing strategies and five pricing models. Finally, it analyzes the challenges of data pricing from three aspects: data value evaluation, data transaction rule and data privacy protection. And it prospects the future development trends of data pricing. The research results of this paper will provide valuable reference and foundation for future relevant work.

Keywords

• data pricing
• pricing strategy
• pricing model
• data trading