东北大学学报（社会科学版）

东北大学学报（社会科学版） ›› 2014, Vol. 16 ›› Issue (1): 45-51.DOI: -

• 经济与管理研究 • 上一篇    下一篇

基于两种包络面的机械制造业技术效率评价

逄红梅1,2，唐晓华1   

  1. (1.辽宁大学经济学院，辽宁沈阳110136;2.沈阳工业大学经济学院，辽宁沈阳110870)
  • 收稿日期:2013-08-10 修回日期:2013-08-10 出版日期:2014-01-25 发布日期:2014-12-30
  • 通讯作者: 逄红梅等
  • 作者简介:逄红梅(1978-)，女(满族)，辽宁岫岩人，辽宁大学博士研究生，沈阳工业大学讲师，主要从事产业经济及组织理论研究;唐晓华(1956-)，男，广西桂林人，辽宁大学教授，博士生导师，主要从事产业经济研究。
  • 基金资助:
    国家社会科学基金重大资助项目(08&ZD040)。

Technical Efficiency Evaluation of Machinery Manufacturing Based on Two Envelopment Frontiers

PANG Hongmei1,2， TANG Xiaohua1   

  1. (1. School of Economics， Liaoning University， Shenyang 110136， China; 2. School of Economics， Shenyang University of Technology， Shenyang 110870， China)
  • Received:2013-08-10 Revised:2013-08-10 Online:2014-01-25 Published:2014-12-30
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摘要： 为更客观评价制造业的技术效率，运用最优和最劣两种包络面的数据包络分析(DEA)模型分别对选取的2012年85家机械制造业上市企业的技术效率进行了测算，并运用几何平均法组合对两种包络面结果进行了合理化排序。研究结果表明:最优效率或最劣效率与组合效率排名存在偏差，利用组合排序结果更具有客观性;投入要素总量越小、波动幅度越大或者投入变量差额比越大，组合效率相对最优效率和最劣效率的排名变化幅度越大。基于以上结论，建议上市企业应该强化要素投入的均衡性和提高要素的利用率。

关键词: 技术效率, 数据包络分析, 最优面, 最劣面, 机械制造业

Abstract: In order to more objectively evaluate the technical efficiency of machinery manufacturing， two data envelopment analysis (DEA) models (both the optimal and the worst) were applied for the first time to estimate the technical efficiency of 85 listed machinery manufacturing companies of 2012， and by means of the geometric method the two envelopment frontiers results were reasonably sorted. The findings indicate that the optimal or the worst efficiency deviates from the combined efficiency in ranking， and the results are more objective when it comes to the combined efficiency; the fewer the input factors， the greater the volatility， or the more different the input variables are， the more differently the combined efficiency ranks as opposed to the optimal and the worst efficiency. Based on the above conclusions， listed companies are recommended to strengthen the balance of input factors and improve the efficiency of these factors.

Key words: technical efficiency, data envelopment analysis (DEA), optimal frontier, worst frontier, machinery manufacturing

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