Research on the operational strategies of data products under China's data element policy: Subsidizing service providers or manufacturers?

The divergence in perceived value of data products leads to discrepancies in value assessment by both parties in transactions, limiting the circulation of data as an economic factor. The government attempts to alleviate this issue through transaction subsidies. While existing studies focus on data market design and the incentive effects of subsidies on corporate R&D, there is a lack of systematic exploration on how governments should design effective subsidy policies for data products. To improve subsidy efficiency and optimize data product operations, this study integrates the demand preferences of data product end users (DPEU) into the utility function. It constructs a game model under three scenarios: no subsidy, subsidy to data product manufacturers (DPM), and subsidy to data product service providers (DPSP), analyzing optimal decisions under various subsidy strategies. Results show that without subsidies, DPM and DPSP, constrained by costs, reduce investments in quality and promotion, significantly suppressing market transactions. With subsidies, DPM increases demand by enhancing quality and optimizing prices, while DPSP promotes transactions through intensified marketing, jointly facilitating data product exchanges. Regardless of subsidies, DPEU's quality and promotion preferences consistently drive profits for all parties, with quality preference having a greater impact. Conversely, investments in quality and promotion costs suppress profits, with quality costs having a stronger inhibitory effect. This study provides a theoretical foundation for governments to design targeted subsidy policies for data products and for companies to optimize their data product operational strategies, thereby contributing to the healthy development of the data product market.