研究论文

三方博弈视角下数据交易平台监管策略研究——以贵交所为例

  • 马小琪 ,
  • 张峰领
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  • 黑龙江大学信息管理学院 哈尔滨 150080
马小琪,教授,博士;张峰领,硕士研究生,通信作者,E-mail: zhangfeng-ling@Foxmail.com。

收稿日期: 2024-08-26

  修回日期: 2025-02-13

  网络出版日期: 2025-08-20

基金资助

本文系2024年度网络安全和信息化项目“基于‘结构—行为—绩效’范式的数据交易商业模式研究”(项目编号:HCSIAK2410)和黑龙江省哲学社会科学一般项目“基于‘结构—行为—绩效’范式的图书开放获取商业模式研究”(项目编号:23TQB179)研究成果之一。

Research on Regulatory Strategies of Data Trading Platforms from the Perspective of Tripartite Game: A Case Study of the Guiyang Big Data Exchange

  • Ma Xiaoqi ,
  • Zhang Fengling
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  • School of Information Management, Heilongjiang University, Harbin 150080
Ma Xiaoqi, Professor, PhD; Zhang Fengling, Master’s Candidate, Corresponding Author, E-mail: zhangfeng-ling@Foxmail.com.

Received date: 2024-08-26

  Revised date: 2025-02-13

  Online published: 2025-08-20

Supported by

This work is supported by the FY 2024 Cybersecurity and Informatization Program project “A Study of Data Trading Business Models Based on the Structure-Behaviour-Performance Paradigm” (Grant No. HCSIAK2410) and the General Project of Philosophy and Social Science in Heilongjiang Province “One of the Research Results of Research on Open Access Business Model of Books Based on Structure-Behaviour-Performance Paradigm” (Grant No. 23TQB179).

摘要

[目的/意义] 旨在通过三方博弈视角,深入分析数据交易平台在监管方面存在的问题和不足。以贵阳大数据交易所为例,探讨如何优化监管策略,提高数据交易的规范性和安全性。[方法/过程] 结合交易成本理论和演化博弈理论,构建一个包含数据需求方、数据交易平台和数据供应方的三方博弈模型,并利用贵阳大数据交易所的实际交易数据进行仿真模拟。[结果/结论]结果表明:①数据交易平台监管积极性将影响数据要素交易的达成率;②数据交易平台对违规行为的监管能力将影响各方的参与积极性;③数据交易平台的数据要素定价机制将直接决定供需双方的交易策略选择;④数据交易平台对数据质量的监管水平是交易规模化的关键;⑤数据交易平台的奖惩机制能够显著提升数据交易的质量和规模。针对贵交所现状,进一步提出完善数据交易平台监管策略方面的建议,如建议构建全流程监管体系、完善数据要素定价机制、建立多方协同监管机制、开发面向数据交易监管的核心技术等。

本文引用格式

马小琪 , 张峰领 . 三方博弈视角下数据交易平台监管策略研究——以贵交所为例[J]. 图书情报工作, 2025 , 69(18) : 69 -85 . DOI: 10.13266/j.issn.0252-3116.2025.18.006

Abstract

[Purpose/Significance] The purpose is to deeply analyse the problems and deficiencies in the supervision of data trading platforms from the perspective of a tripartite game. It also explores how to optimize the supervision strategy and improve the regularity and security of data trading by taking the Guiyang Big Data Exchange as an example. [Method/Process] Combining the transaction cost theory and evolutionary game theory, a tripartite game model containing the data demand side, the data transaction platform and the data supply side was constructed, and a simulation was carried out using the actual transaction data of the Guiyang Big Data Exchange. [Result/Conclusion] This paper draws the following conclusions. ① The supervision positivity of the data trading platform affects the rate of data element transactions. ② The ability of the data trading platform to supervise violations affects the participation enthusiasm of all parties. ③The data trading platform’s data element pricing mechanism directly determines the choice of trading strategies between supply and demand parties. ④ The level of the data trading platform’s supervision of data quality is the key to transaction scale. ⑤ The reward and punishment mechanism of the data trading platform can significantly improve the quality and scale of data trading. In view of the status quo of the Guiyang Big Data Exchange, it further puts forward suggestions to improve the regulatory strategy of data trading platforms, such as suggesting the construction of a full-process regulatory system, perfecting the pricing mechanism of data elements, establishing a multi-party collaborative regulatory mechanism, and developing core technologies for the regulation of data trading, and other suggestions.

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