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基于DEA-Malmquist指数的物联网企业生产效率变动及影响因素研究
引用本文:宋佳,于娱.基于DEA-Malmquist指数的物联网企业生产效率变动及影响因素研究[J].南京邮电学院学报(社会科学版),2014(1):61-70.
作者姓名:宋佳  于娱
作者单位:[1]南京邮电大学管理学院,江苏南京210023 [2]河海大学商学院,江苏南京211100
基金项目:国家自然科学基金项目“不确定信息环境下的网络DEA模型分析方法及应用研究”(71301080);国家自然科学基金项目“政产学研金’协同创新下知识流动力学模型及制度设计”(71271119);江苏省哲学社会科学基金项目“长三角地区协同发展物联网产业的路径与模式研究”(10CSJ002)
摘    要:针对物联网技术和产业发展的热潮,以我国28家物联网概念上市公司为研究对象,首先从静态角度,运用CCR和BCC模型分析2008-2012年我国物联网企业的运营效率与规模效应。其次运用DEA-Malmquist生产效率指数方法对物联网企业的全要素生产率变化以及各企业生产效率变动来源进行分析。研究发现,28家上市公司中多数企业运营效率不足。整体而言,2008-2012年间,技术效率年均增长1。25%,技术进步年均负增长44。23%。目前我国日益推进的物联网产业的发展仍是粗放型的,高增长的代价是高投入;部分上市公司逐渐进入规模效益递减阶段,出现产能过剩的现象;总体技术效率呈缓慢增长,技术进步逐渐降低,物联网产业发展的“追赶效应”大于“增长效应”。

关 键 词:物联网  DEA-Malmquist指数  技术效率  技术进步

Production efficiency and influencing factors of the Internet of Things corporations based on DEA-Malmquist index
SONG Jia,YU Yu.Production efficiency and influencing factors of the Internet of Things corporations based on DEA-Malmquist index[J].Journal of Nanjing University of Posts and Telecommunications(Social Science),2014(1):61-70.
Authors:SONG Jia  YU Yu
Institution:1. School of Management, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;2. Business School, Hohai University, Nanjing 211100, China)
Abstract:Based on the boom of developing the Internet of Things technology and industry surging at home and abroad in 2009, we first used the CCR and BCC model from DEA to analyze the operation efficiency and scale effect of 28 listed Internet of Things conceptual companies from 2008 to 2012 as research subjeot. Then we applied DEA-Malmquist Index to analyze the total factor efficiency changes and the sources of production efficiency changes of those lnternet of Things companies. We found that most of the 28 companies showed DEA-inefficient. As a whole, the technical efficiency grew annually at an average of 1.25% , while the technology shift reduced annually at an average of 44.23%, from 2008 to 2012. As a result, the increasingly promoted development of Internet of Things industry in China is still extensive with high input to achieve high growth. Additionally, part of the 28 com- panics excess shift; were sliding into the stage of decreasing return to scale, which indicates the emergence of the phenomena of capacity. Generally, there is a slowing growth in technical efficiency and a gradual reduction in technology the "catch-up" effect of Internet of Things industry is greater than growth effect.
Keywords:Internet of Things  DEA-Malmquist Index  technical efficiency  technology shift
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