Data Pricing for Data Exchange: Technology and AI
Minnu Malieckal, Anjula Gurtoo, Rupsa Majumdar · 2024
The data economy has grown significantly in the last several years, and governments are now marketing data as a commodity that can be traded, opening up the arena for "data pricing." Despite the rise of data markets, there is lack of research to establish pricing models and specifications for maximising profits when pricing datasets. Furthermore, the magnitude of data providers and massive volume of data impedes data pricing specifications as well. The paper fills both the gaps, by first, systematically examining the major data pricing approaches using content analysis methodology, and secondly, applying technological interventions using the thematic analysis methodology. The analysis categorizes the pricing strategies into five main themes: general pricing, quality-based pricing, query-based pricing, privacy-based pricing, and special cases. The technology models applied indicate the forecasting techniques and technology application assessment that are key to pricing frameworks and strategies. The paper lists out different technologies used in various types of data pricing. In doing so, the article establishes an outline for developing technically sound data pricing strategies.