An Incentive Mechanism for Cross-Organization Data Sharing Based on Data Competitiveness
Bingyi Guo, Xiaofang Deng, Quansheng Guan, Jie Tian, Xiangwei Zheng · IEEE Access · 2018
In the era of big data and artificial intelligence, data sharing is desirable for vigorous development of data-driven services, which improves our daily life. Although data sharing is supported to a certain extent by current mechanisms and technologies, organizations especially with potential competitive relationships might refuse to share their data due to the worry that data sharing improves competitors’ competitiveness. To address this problem, this paper focuses on the competitiveness-driven target of win-win, and provides incentives to encourage potentially competing organizations to share their data. By introducing the concept of data competitiveness as a data transaction driving force, an incentive mechanism based on data competitiveness is established, which is formulated as a Stackelberg game. A gradient-based iteration algorithm is proposed to obtain the Stackelberg equilibrium solution to the data sharing incentive problem. Simulation results substantiate that performance of data sharing can be improved significantly by the proposed scheme.