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中国数据要素市场产权配置改革评价机制构建与实证研究

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明确数据产权配置的改革目标、判定数据产权配置的改革水平,从而指导产权政策优化与落实,是我国开展数据产权配置改革工作的先决条件.围绕权利分置、市场建设、治理保障和开拓创新4 个维度,构建数据要素市场产权配置改革评价指标体系,并提出一种基于网络分析法和优化经典拓扑结构的一维卷积神经网络智能评价机制,对我国数据要素市场产权配置改革水平准确研判.研究发现:数据产权配置改革需重点关注权益分配公平性、效益产出持续性、税制改革创新性和软环境建设保障性;各地区数据产权配置改革水平存在显著差异,大体呈现出"东高西低、沿海高于内陆"的分布态势;改革水平并不简单等同于这个地区的行政级别、经济地位或资源禀赋.
Construction and empirical study on the evaluation mechanism of property right allocation reform in data element market of China
Clarifying the reform objectives of data property right allocation,assessing the level of data property right reform,to provide guidance for the optimization and implementation of property right policies,which are essential prerequisites for China to carry out data property right allocation reform.From the four dimensions of rights allocation,market development,governance assurance and innovation expansion,an evaluation index system for the property right allocation reform in the data element market was constructed.And then the study proposed an intelligent evaluation mechanism of one-dimensional convolutional neural network based on network analysis and the optimization of classic topological structures to accurately evaluate property right allocation reform level of data element market.It is found that the reform of data property right allocation should focus on the fairness of rights distribution,the sustainability of benefit generation,the innovation of tax reform,and the assurance of soft environment construction.There are significant differences in the level of property right allocation reform among different regions,showing a distribution pattern of"higher in the east,lower in the west,and higher along the coast than in inland areas."The reform level is not simply equivalent to the administrative level,economic position or resource endowment of the region.

data elementsdata propertyconvolutional neural networkanalytic network process

李珊、张文德、郑伟鑫

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福州大学经济与管理学院,福建 福州 350108

福州大学计算机与大数据学院,福建 福州 350108

数据要素 数据产权 卷积神经网络 网络分析法

国家社会科学基金后期资助项目福建省社会科学基金重大项目

20FTQB017FJ2021Z020

2024

中国软科学
中国软科学研究会

中国软科学

CSTPCDCSSCICHSSCD北大核心
影响因子:2.793
ISSN:1002-9753
年,卷(期):2024.(1)
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