Addressing the imbalance between on-exchange data trading and off-exchange circulation, this study investigates the synergistic effects of platform guidance strategies and governmental incentive-penalty mechanisms. A quadripartite evolutionary game model-comprising data suppliers, data users, trading platforms, and governmental entities-is constructed to analyze strategic response mechanisms and equilibrium formation, complemented by behavioral evolution simulations using data exchange and policy records. Key findings include: 1) Government policy orientation and regulatory intensity encourage platforms to adopt proactive guidance strategies, strengthening their influence on trading parties and increasing on-exchange transactions. Rising incentive costs and fiscal pressure drive government intervention toward a coordinated regime combining penalties with lower-intensity incentives. 2) Optimal strategy portfolios (platform proactivity, on-exchange participation, sustained high-regulation) emerge only when fiscal subsidies, platform incentives, and penalty thresholds collectively surpass behavioral response thresholds. 3) Differential incentives enhance platform guidance, penalties support compliance, and fiscal compensation helps suppliers internalize compliance costs.
HAO Jun
,
MU Mengdi
,
LI Jianping
. Selection strategy for data trading models based on dynamic evolutionary game[J]. Journal of University of Chinese Academy of Sciences, 0
: 1
-1
.
DOI: 10.7523/j.ucas.2026.002
[1] 李兆睿,许志伟.数据、生产与宏观经济:一个具有企业数字化的一般均衡理论[J]. 管理世界, 2024, 40(9): 80-101. DOI: 10.19744/j.cnki.11-1235/f.2024.0105.
[2] 程聪,严璐璐, 曹烈冰.大数据决策中数据结构转变:基于杭州城市大脑“交通治堵”应用场景的案例分析[J]. 管理世界, 2023, 39(12): 165-185. DOI: 10.19744/j.cnki.11-1235/f.2023.0139.
[3] 中共中央国务院关于构建更加完善的要素市场化配置体制机制的意见[J]. 中华人民共和国国务院公报, 2020, (11): 5-8.
[4] Hao J, Yuan J X, Li J P.HCEG: A heterogeneous clustering ensemble learning approach with gravity-based strategy for data assets intelligent pricing[J]. Information Sciences, 2024, 678: 121082. DOI: 10.1016/j.ins.2024.121082.
[5] Mehta S, Dawande M, Janakiraman G, et al.How to sell a data set? pricing policies for data monetization[J]. Information Systems Research, 2021, 32(4): 1281-1297. DO1: 10.1287/isre.2021.1027.
[6] Zhang X, Yue W T, Yu Y G, et al.How to monetize data: An economic analysis of data monetization strategies under competition[J]. Decision Support Systems, 2023, 173: 114012. DOI: 10.1016/j.dss.2023.114012.
[7] 蔡跃洲, 刘悦欣. 数据流动交易模式分类与规模估算初探[J]. 中国经济学人(英文版), 2022, 17(6): 78-112. DOI: 10.19602/j.chinaeconomist.2022.11.04.
[8] 方锦程,刘颖,高昊宇,等.公共数据开放能否促进区域协调发展?来自政府数据平台上线的准自然实验[J]. 管理世界, 2023, 39(9): 124-142. DOI: 10.19744/j.cnki.11-1235/f.2023.0112.
[9] 中共中央国务院关于构建数据基础制度更好发挥数据要素作用的意见[N]. 人民日报, 2022-12-20(001). DOI: 10.28655/n.cnki.nrmrb.2022.013348.
[10] 端利涛. 引发数据场内交易不足的几个矛盾[J]. 互联网周刊, 2024, (5): 19-21.
[11] 江小涓. 数据交易与数据交互:理解数据要素市场特征的关键[J].中国网信, 2024, (1): 32-36.
[12] 任洪润,朱扬勇.数据管道模型:场外流式数据市场形态探索[J].大数据, 2023, 9(3): 15-8. DOl:10.11959/i.issn.2096-0271.2023031.
[13] 陈宏民,熊红林,胥莉,等.基于平台视角下的数据交易模式及特点分析[J].大数据,20239(2):56-66.DO1:10.11959/jissn.2096-0271.2023020.
[14] 黄丽华,窦一凡,郭梦珂,等.数据流通市场中数据产品的特性及其交易模式[J].大数据,2022, 8(3): 3-14. DOI: 10.11959/j.issn.2096-0271.2022045
[15] 王煜心,李建平,郝俊.集成效用与数据产品最优定价[J].中国科学:信息科学, 2024, 54(11): 2533-2553. DOI:10.1360/SSI-2023-0277.
[16] 刘东霞, 陈红. 产品服务供应链定价决策:数据资源挖掘与共享策略的影响分析[J]. 中国管理科学, 2024, 32(2): 129-140. DOI: 10.16381/j.cnki.issn1003-207x.2022.0007.
[17] 李金,徐姗,卓子寒,等.数据跨境流转的风险测度与分析——基于数据出境统计信息的实证研究[J]. 管理世界, 2023, 39(7): 180-201. DOI:10.19744/j.cnki.11-1235/f.2023.0087.
[18] 许宪春, 张钟文, 胡亚茹. 数据资产统计与核算问题研究[J]. 管理世界, 2022, 38(2): 16-30+2. DOI: 10.19744/j.cnki.11-1235/f.2022.0030.
[19] 王今朝, 窦一凡, 黄丽华. 单一供方情境下竞争企业的数据购买策略[J]. 管理科学学报, 2025, 28(4): 47-62. DOI:10.19920/j.cnki.jmsc.2025.04.004.
[20] 王衍之,黄静思,王剑晓,等.数据要素流通与收益分配机制研究:以风电场景融合气象数据为例[J]. 管理评论, 2024, 36(6): 30-41. DOI:10.14120/j.cnki.cn11-5057/f.2024.06.021.
[21] 袁健,段巍.数据交易、专业化人工智能与经济增长[J].管理评论, 2024, 36(6): 3-18. DOI:10.14120/j.cnki.cn11-5057/f.2024.06.001.
[22] 包晓丽,杜万里.数据可信交易体系的制度构建:基于场内交易视角[J]. 电子政务,2023(6):38-50. DO1:10.16582/.cnki.dzzw.2023.06.003.
[23] 王珊珊,王海芸,姚怡帆. 数据交易企业策略及政府监管激励——基于三方演化博弈模型分析[J]. 科技和产业, 2024, 24(15): 187-196.
[24] 张丽丽,章政.基于多主体演化博弈均衡模型的数据要素的进场交易与可信流通体系构建研究[J]. 计算机科学, 2025, 52(3): 127-136. DOI: 10.11896/isikx.240200003.
[25] 刘业政,宗兰芳,周芦娟,等.数据要素流通交易的可信指标及测度方法[J]. 管理评论, 2024, 36(12): 26-36. DOI: 10.14120/j.cnki.cn11-5057/f.2024.12.005.
[26] 刘涛雄,李若菲,戎珂.基于生成场景的数据确权理论与分级授权[J].管理世界, 2023, 39(2): 22-39. DOI: 10.19744/j.cnki.11-1235/f.2023.0022.
[27] 胡春华,陈皖,周艳菊,等.基于演化博弈的直播电商监管机制研究[J].管理科学学报,2023,26(6): 126-141. DOI: 10.19920/j.cnki.jmsc.2023.06.008.
[28] 许博,左莉琳,金珈伊,等.基于演化博弈的“双边-集中”电力市场交易机制研究[J].中国管理科学, 2023, 31(8):193-203. DOI: 10.16381/j.cnki.issn1003-207x.2021.2187.
[29] 温越,吕本富,张馨元,等.数据交易基础设施建设中政府规制与企业协同的博弈研究[J].管理评论, 2024, 36(6): 42-53. DOI: 10.14120/j.cnki.cn11-5057/f.2024.06.002.
[30] Friedman D.On economic applications of evolutionary game theory[J]. Journal of Evolutionary Economics, 1998, 8(1): 15-43. DOI: 10.1007/s001910050054.
