Research on Pricing and Coordination Strategies in a Data Supply Chain Under Different Cooperation Modes and Privacy Protection Investment

Against the backdrop of the continuous advancement of the market-oriented allocation of data factors, problems such as high data circulation costs, unclear pricing mechanisms, insufficient value conversion, and unreasonable profit allocation have constrained the coordinated development of the data supply chain. To address these issues, this paper develops a model of transactions in data and its derivative products among the data provider, the data service provider, and the data demander. On the basis of considering data integrity, privacy sensitivity, privacy protection investment, and data analytics capability, it compares the optimal strategies and total supply chain profit under four modes: non-cooperation, cooperation between the data provider and the data service provider, cooperation between the data service provider and the data demander, and tripartite cooperation. It further employs an improved Shapley value to allocate and coordinate cooperative profits. The results show that improvements in data integrity and data analytics capability help expand data scale, increase the prices of data and data products, and improve the target performance of the application product, whereas increases in data processing cost, data analytics cost, privacy sensitivity, and privacy protection investment inhibit the optimal strategies and total profit of the data supply chain. Cooperation modes can effectively mitigate the efficiency loss caused by decentralized decision-making, and the more complete the scope of cooperation, the better the overall performance of the supply chain. A higher degree of cooperation can further improve total supply chain profit under cooperation modes. The improved Shapley value can effectively coordinate the data supply chain and enhance the fairness of profit allocation and the stability of cooperation. This study enriches the theory of pricing and revenue coordination in data supply chains and provides decision support for the efficient circulation of data factors and multi-party collaborative governance.