<p>Personal data, recognized as a fundamental production element in the digital economy, plays a crucial role in data transactions and significantly influences the advancement of the digital economy. To address the challenges of privacy protection and value realization of personal data, this paper considers data authorization and constructs game-theoretic models under two scenarios: the direct transaction model and the value-added transaction model. The research shows: (1) Regarding the demand for personal data when the data owner’s privacy sensitivity is low, the demand for data is higher under the value-added transaction model. Conversely, when privacy sensitivity is high, the demand is higher under the direct transaction model. (2) In terms of the benefits to the data owner and platform, when privacy sensitivity is low, the optimal profit of the data owner under the direct transaction model is lower than that under the value-added transaction model, while the platform’s profit is higher. When privacy sensitivity is high, the optimal profit of the data owner under the direct transaction model is higher, but the platform profit is lower than that under the value-added transaction model. (3) The optimal authorization degree of the data owner under the direct transaction model is higher than that under the value-added transaction model. However, the overall supply chain revenue and consumer surplus are higher under the value-added transaction model. The research findings offer a theoretical foundation for decision-making by a data owner and the optimization of platform operations, thereby fostering the healthy development of the data market.</p>