我国民营能源上市公司技术效率与要素投入优化分析
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  • 英文篇名:Analysis on technical efficiency and factor input optimization of private energy listed companies in China
  • 作者:向冰
  • 英文作者:Xiang Bing;School of Economics and Management,Guangdong University of Technology;
  • 关键词:DEA模型 ; 技术效率 ; 径向调整 ; 松弛调整 ; 民营能源上市公司
  • 英文关键词:DEA model;;technical efficiency;;radial adjustment;;relaxation adjustment;;private energy listed company
  • 中文刊名:MTJN
  • 英文刊名:Coal Economic Research
  • 机构:广东理工学院经济管理学院;
  • 出版日期:2019-05-28
  • 出版单位:煤炭经济研究
  • 年:2019
  • 期:v.39;No.455
  • 基金:广东省青年创新人才类项目(人文社科)(2016WQNCX166);; 广东理工学院校级教改项目(JXGG2018027)
  • 语种:中文;
  • 页:MTJN201905014
  • 页数:7
  • CN:05
  • ISSN:11-1038/F
  • 分类号:81-87
摘要
运用以投入为导向的DEA模型对2012—2018年我国民营能源上市公司技术效率及决定因素进行分析,测算投入要素的径向调整和松弛调整,优化要素投入。研究表明:我国民营能源上市公司总体技术效率较高,除龙宇燃油一直处于最优外,其他公司仍存在改进空间。改进方式应主要通过优化规模水平,其次应加快技术创新、优化制度和管理水平。研究期径向调整均值为10%,个体差异大。准油股份径向调整值最大,其次为宝泰隆。公司应加快技术创新,优化制度、规模、管理水平。投入要素中营业成本无松弛调整、管理费用松弛调整少、员工数松弛调整多。公司应相应适当减少投入要素,优化资源配置。
        Using the input-oriented DEA model to analyze the technical efficiency and determinants of China's private energy listed companies in 2012-2018,measure the radial adjustment and slack adjustment of input factors,and optimize the input of factors. The research showed that the overall technical efficiency of China's private energy listed companies was relatively high. Except Longyu fuel has been in the best position,other companies still had room for improvement. The improvement method should mainly focus on optimizing the scale of the scale,and secondly,accelerate the technological innovation,optimization system and management level. The mean radial adjustment during the study period was 10%,and the individual differences were large. The Zhundong Petrotech Co.,Ltd. had the largest radial adjustment,followed by Baotailong. The company should accelerate technological innovation and optimize the system,scale and management level. There is no slack adjustment in operating costs,less adjustment of management fee slack,and more adjustments in employee slack. Companies should appropriately reduce input factors and optimize resource allocation.
引文
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