乔晗*,李卓伦.数据要素市场化配置效率评价研究[J].中国科学院院刊,2022,37(10):1444-1456.
数据要素市场化配置效率评价研究
Research on Market Allocation Efficiency of Data Elements
数据要素市场化配置效率评价研究
Research on Market Allocation Efficiency of Data Elements
作者
乔晗*
中国科学院大学 经济与管理学院 北京 100190;中国科学院大学 数字经济监测预测预警与政策仿真教育部哲学社会科学实验室(培育) 北京 100190
QIAO Han*
School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;MOE Philosophy and Social Science Laboratory of Digital Economic Monitoring, Forecasting, Early Warning, and Policy Simulation (Cultivation), University of Chinese Academy of Sciences, Beijing 100190, China
李卓伦
中国科学院大学 经济与管理学院 北京 100190;中国科学院大学 数字经济监测预测预警与政策仿真教育部哲学社会科学实验室(培育) 北京 100190
LI Zhuolun
School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;MOE Philosophy and Social Science Laboratory of Digital Economic Monitoring, Forecasting, Early Warning, and Policy Simulation (Cultivation), University of Chinese Academy of Sciences, Beijing 100190, China
中国科学院大学 经济与管理学院 北京 100190;中国科学院大学 数字经济监测预测预警与政策仿真教育部哲学社会科学实验室(培育) 北京 100190
QIAO Han*
School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;MOE Philosophy and Social Science Laboratory of Digital Economic Monitoring, Forecasting, Early Warning, and Policy Simulation (Cultivation), University of Chinese Academy of Sciences, Beijing 100190, China
李卓伦
中国科学院大学 经济与管理学院 北京 100190;中国科学院大学 数字经济监测预测预警与政策仿真教育部哲学社会科学实验室(培育) 北京 100190
LI Zhuolun
School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;MOE Philosophy and Social Science Laboratory of Digital Economic Monitoring, Forecasting, Early Warning, and Policy Simulation (Cultivation), University of Chinese Academy of Sciences, Beijing 100190, China
中文关键词
数据要素;市场化配置效率评价;网络 DEA;Malmquist指数;全要素生产率
英文关键词
data elements;market allocation efficiency;network DEA;Malmquist index;total factor productivity
中文摘要
推进数据要素市场化配置，是实现数据要素价值转化、驱动数字经济高质量发展的关键。文章基于文献研究和实践经验阐释了数据要素市场化配置的理论过程，将数据要素市场化配置过程划分为市场化建设和价值化配置 2 个阶段。文章以理论为基础，应用追加中间投入的网络 DEA模型，测算 2019—2020 年我国 30 个省（区、市）的数据要素市场化配置效率；进一步，通过 Malmquist 指数分析，研究我国数据要素市场化配置效率和全要素生产率的动态变化情况。研究发现：（ 1） 2019— 2020 年我国数据要素市场化配置效率整体呈上升趋势，价值化配置阶段效率较高，市场化建设阶段效率低于价值化配置阶段。因此，未来进一步提高公共数据开放水平、完善数据流通和交易基础设施仍是提高数据要素市场化配置效率的工作重点。（ 2）研究期内，我国全要素生产率提升明显，提高技术进步率和数据要素市场化配置效率均对提升全要素生产率有正向作用，且提高数据要素市场化配置效率对推动全要素生产率提升更为关键。
英文摘要
Promoting the market allocation of data elements is the key to realize the value of data resources,which drives the high-quality development of digital economy.Based on the literature review,this study first analyses the theoretical process of market allocation of data elements,and divides the whole process into two stages:market-based construction and value-based allocation.According to the proposed theoretical model,this study designs the network DEA model with additional intermediate inputs to calculate the market allocation efficiency of data elements of 30 provincial administrative regions in China from 2019 to 2020.Moreover,by Malmquist index analysis,we further investigate the dynamic changes of both market allocation efficiency of data elements and total factor productivity in China.The study finds that during the period of 2019 to 2020,the market allocation efficiency of data elements in China is on an upward trend.The efficiency of value-based allocation stage reached a higher level than that of the market-based allocation stage.This finding suggests that the orderly opening of public data and the construction of data trading platform will still be the focus in improving the market allocation efficiency of data elements in the future.The results of the study further indicates that China's total factor productivity increased significantly-both the technology progress and the improvement of market allocation efficiency of data elements had a positive effect on improving total factor productivity,and the latter driving force is more critical to promoting the improvement of total factor productivity.
DOI10.16418/j.issn.1000-3045.20220629001
作者简介
乔晗 中国科学院大学经济与管理学院副院长、教授、博士生导师。“国家高层次人才特殊支持计划”哲学社会科学领军人才，《管理评论》常务副主编，国家自然科学基金重大项目课题“数字经济中数据要素有效使用与消费者保护”负责人。主要研究领域：数字经济、科技创新与商业模式创新、风险投资与创业等。主持国家自然科学基金重大项目 1项，面上及青年项目 3项，其他各级政府或企业咨询项目 20余项，发表论文 100余篇。
E-mail: qiaohan@ucas.ac.cn
QIAO Han Deputy Dean and Professor of School of Economics and Management, University of Chinese Academy of Sciences; one of the Leading Talent (Philosophy and Social Sciences) in the National Special Support Program for High-level Talents; Executive Associate Editor-in-Chief of Management Review; Principle Investigator of the Major Project Effective Use of Data Elements and Consumer Protection in the Digital Economy of National Natural Science Foundation of China (NSFC). Dr. Qiao’s main research areas cover digital economy, technological innovation and business model innovation, venture capital and entrepreneurship, etc. As the principle investigator, she has hosted 1 major program, 3 general and youth programs of NSFC, and over 20 other governments or business consulting projects, and she has published more than 100 high-quality journal articles.
E-mail: qiaohan@ucas.ac.cn
E-mail: qiaohan@ucas.ac.cn
QIAO Han Deputy Dean and Professor of School of Economics and Management, University of Chinese Academy of Sciences; one of the Leading Talent (Philosophy and Social Sciences) in the National Special Support Program for High-level Talents; Executive Associate Editor-in-Chief of Management Review; Principle Investigator of the Major Project Effective Use of Data Elements and Consumer Protection in the Digital Economy of National Natural Science Foundation of China (NSFC). Dr. Qiao’s main research areas cover digital economy, technological innovation and business model innovation, venture capital and entrepreneurship, etc. As the principle investigator, she has hosted 1 major program, 3 general and youth programs of NSFC, and over 20 other governments or business consulting projects, and she has published more than 100 high-quality journal articles.
E-mail: qiaohan@ucas.ac.cn
