摘要
规范引导场外交易、培育壮大场内交易,对数据合规交易的规范化、规模化发展具有重要意义.构建政府、平台和提供方的演化博弈系统动力学模型,剖析相关变量与主体策略的因果关系和反馈回路,寻找促进合规交易的关键变量,并对比同类变量的作用效果,明确政府监管与平台发展策略的侧重点.研究发现:政府监管策略应以增加处罚力度为主,严厉打击场外黑市交易,平台发展策略应以降低服务费为主,引导促进场内合规交易.政府监管下提供者自律意识的提升,以及平台发展下收益回报的增加均能推进合规交易.最后,基于合规交易的长远发展,提出以提供方自律行为为“基”、政府监管和平台发展为“翼”的“基—翼”相济式策略.
It is significant to standardize and guide OTC transactions and cultivate and expand OTC transactions for the standardization and large-scale development of data compliance transactions.Build an evolutionary game system dynamics model of government,platform and provider,analyze the causal relationship and feedback loop between relevant variables and the main body strategy,find the key variables that promote compliance trading,and compare the effects of similar variables,to clarify the focus of government regulation and platform development strategy.Research findings:Government supervision strategies should focus on increasing penalties and severely cracking down on off-market black market transactions.In contrast,platform development strategies should focus on reducing service fees to guide and promote on-market compliance transactions.The improvement of the self-regulation consciousness of providers under government supervision and increasing revenue return under platform development can promote compliance transactions.Finally,based on the long-term development of compliant transactions,the“base-wing”strategy is proposed,which takes the provider's self-regulatory behavior as the“foundation”,and government supervision and platform development as the“wing”.
作者
沈俊鑫
孙昕晴
张彤昕
SHEN Junxin;SUN Xinqing;ZHANG Tongxin(Faculty of Management and Economics,Kunming University of Science and Technology,Kunming 650500,China)
出处
《昆明理工大学学报（自然科学版）》
北大核心
2024年第4期285-296,共12页
Journal of Kunming University of Science and Technology(Natural Science)
基金
国家自然科学基金项目(71964018)
云南省应用基础研究重点项目(202401AS070112).
关键词
数据合规交易
监管与发展
演化博弈
系统动力学
data compliance transactions
regulation and development
evolutionary game
system dynamics
作者简介
沈俊鑫(1978-),男,博士,教授,博士生导师.主要研究方向:大数据驱动决策管理.E-mail:331065695@qq.com。
