基于复杂网络的数据双方交易监管演化博弈研究

Research on the Evolutionary Game of Bilateral Data Transaction Supervision Based on Complex Networks

摘要: 为了更好地探究数据产权制度中数据拥有方与使用方之间的数据交易合作行为演化机制，以复杂二部图网络模拟现实网络的非对称拓扑特征，结合演化博弈理论，构建带有政府监督的数据拥有方与数据使用方之间的两群体非对称博弈演化模型，并进行数值仿真，得出影响交易双方采取不同策略的主要因素，并提高数据交易双方的合作水平。结果表明：监管力度和反垄断处罚的增加以及垄断收益的降低都能够促进数据交易双方合作行为的产生；侵权处罚、赔偿以及起诉侵权胜诉概率和赔偿的增加，对使用方合作行为有积极影响，但会抑制拥有方的合作行为；而合理收费的增加虽然会增加拥有方合作密度，但是会降低使用方合作密度。

Abstract: In order to better explore the evolution mechanism of data transaction cooperation behavior between data owners and users in the data property rights system, a complex bipartite graph network is used to simulate the asymmetric topological characteristics of real networks. Combined with evolutionary game theory, a two-group asymmetric game evolution model with government supervision between data owners and data users is constructed, and numerical simulation is conducted to identify the main factors affecting the adoption of different strategies by both parties in the transaction, and to improve the cooperation level of both parties in the data transaction. The results indicate that an increase in regulatory efforts and antitrust penalties, as well as a decrease in monopoly profits, can promote the emergence of cooperative behavior between data trading parties; The increase in infringement penalties, compensation, and the probability of winning a lawsuit for infringement and compensation has a positive impact on the cooperative behavior of users, but it will inhibit the cooperative behavior of owners; The increase in reasonable fees may increase the cooperation density among owners, but it will decrease the cooperation density among users.