Research on the Pricing Model of B2B Data Transactions and Its Nature for a Single Industrial Chain - Weiqing Zhuang; Hanyu Yu; Morgan C. Wang (Mathematics)
With the advancement of global digital transformation, data trading has become a pivotal element in value circulation and innovation among enterprises. In particular, pricing strategies in the industrial chain’s data trading process critically influence the cooperation and market competitiveness of upstream and downstream enterprises. To address this issue, this study develops a Business-to-Business data transaction pricing model tailored to a single industry chain. The model incorporates factors such as data scarcity, encryption protection efforts, and market demand dynamics. By employing a Stackelberg dynamic model, the study systematically examines the pricing strategies of upstream and downstream enterprises under various incentive mechanisms and evaluates the impacts of encryption protection efforts and incentive mechanism coefficients on the profitability of the industry chain. The experimental results reveal that introducing incentive mechanisms for downstream enterprises modestly increases the profits of both upstream and downstream entities. Meanwhile, incentivizing upstream enterprises yields a multiplier effect, significantly boosting their profits while causing a slight decline in the profitability of downstream enterprises.