摘要
基于2013—2018年中国省级面板数据,本文从产品、企业和产业三个层面系统分析大数据与制造业融合的内在机制,从融合基础、融合应用、融合动力和融合效益4个维度构建大数据与制造业融合水平评价指标体系,并利用熵值法对中国29个省市大数据与制造业融合水平进行测度与比较分析。研究发现:中国及各省市大数据与制造业融合水平均在不断提升;大数据与制造业的融合水平呈现出区域差异和两极分化的现象,东部地区大数据与制造业融合水平明显高于中西部地区。在此基础上,提出了推动大数据与制造业深度融合的对策性建议。
Based on China’s provincial panel data from 2013 to 2018,the internal mechanism of the integration of big data and manufacturing industry was systematically analyzed from the three levels of product,enterprise and industry. The evaluation index system of the integration level of big data and manufacturing industry was constructed from the four dimensions of integration foundation,integration application,integration power and integration benefit,and the entropy evaluation method was used to measure and compare the integration level of big data and manufacturing industry in 29 provinces and cities in China. The research shows that the integration degree of big data and manufacturing industry in China and all provinces and cities is constantly improving;the integrated level of big data and manufacturing industry shows regional differences and polarization. The integration level of big data and manufacturing industry in eastern China is obviously higher than that in central and western China. Based on the analysis,it puts forward some countermeasures to promote the integration of big data and manufacturing industry.
作者
吕明元
麻林宵
LüMingyuan;Ma Linxiao(School of Economics,Tianjin University of Commerce,Tianjin 300134,China)
出处
《技术经济》
CSSCI
北大核心
2022年第1期88-100,共13页
Journal of Technology Economics
基金
国家社会科学基金重点项目“大数据与制造业融合机制创新下我国制造业绿色转型的路径与对策研究”(20AJY007)。
关键词
大数据
制造业
融合机制
评价指标体系
熵值法
big data
manufacturing
integration mechanism
evaluation index system
entropy evaluation method
