【摘要】 大数据企业通过组建联盟共享整合数据提升竞争力，关键在于实现合理公平的利益分配。基于联盟成员在数据共享中的不同角色定位，将联盟内的数据共享合作模式划分为单向和双向两种类型。通过对比分析发现，双向数据共享模式在效益上更为优越。进而，基于合作博弈理论，构建了针对大数据联盟双向数据共享的利益分配模型，旨在探讨不同参数对联盟内部成员间的利益分配机制的影响。研究结果表明：（1）数据资源共享成本及风险对联盟及其成员的最终利益分配产生负向影响，而在数据共享风险较低的环境下，联盟及其成员的利益与数据共享量呈正相关关系。但当企业身份与共享数据的联盟成员身份一致时，其利益分配不受成员间数据共享量的直接影响；（2）联盟及其成员的利益与共享合作中数据的有效性正相关，而数据的有效性则直接受到数据资源互补性和成员数据转化能力的双重影响；（3）数据共享合作的协同效应和跨组织效应显著受到参与合作成员身份的差异性和各自投入的数据共享量的影响。研究为优化我国大数据联盟数据共享合作的利益分配机制、激发数据资源的最大效能提供了理论支撑和实践指导。更多还原

【Abstract】 The key to building alliances and sharing and integrating data to enhance competitiveness for big data enterprises lies in the reasonable and fair distribution of benefits. Based on the different roles of alliance members in data sharing, the cooperation modes of data sharing within the alliance can be divided into one-way and two-way modes. Through comparative analysis, it is found that the two-way data sharing model has more advantages in efficiency. Based on cooperative game theory, a benefit distribution model for two-way data sharing in big data alliances is constructed, and the influence of different parameter factors on the benefit distribution mechanism among alliance members is discussed. The results are as follows: 1. The cost and risk of data resource sharing have a negative impact on the final benefit distribution of the alliance and its members, while in an environment with low risk of data sharing, the interests of the alliance and its members are positively related to the amount of shared data. However, when the identity of the enterprise is the same as that of the members of the alliance sharing data, its benefit distribution is not directly affected by the amount of data shared among members; 2. The interests of the alliance and its members are positively related to the effectiveness of data sharing and cooperation, and the effectiveness of data is directly affected by the complementarity of data resources and the ability of members to convert data; 3. The synergistic and crossorganizational effects of data sharing and collaboration are significantly influenced by the membership and the amount of data shared by all party. This study provides solid theoretical support and practical guidance for optimizing the benefit distribution mechanism of data sharing cooperation in China’s Big Data Alliance and stimulating the maximum efficiency of data resources.更多还原