摘要
对所有平行级别上的同等类型的决策单元(DMUs)在绩效表现上的排序一直是管理决策领域研究的重要课题之一。基于数据包络分析的超效率理论和SBM模型,探讨考虑非期望因素的DMUs排序问题。首先构建新的考虑非期望因素的超效率SBM模型,此模型不仅能对有效DMUs排序,而且能够转化成线性规划问题求解,具有有界性、单调性等良好性质。然后将新模型与Tone的SBM模型结合提出了考虑非期望因素的SBM综合排序法,同时给出了相对应的多项式时间算法。该方法以SBM模型作为第一阶段完成非有效DMUs排序,以新模型作为第二阶段完成有效DMUs排序,两阶段综合即完成所有DMUs排序。研究结果表明,综合排序法能够完成对考虑非期望因素的DMUs的排序,为绩效评价的管理实践提供了重要的理论依据。选取中国2010年的30个省份为实证研究对象,应用所提出的综合效率排序法对其环境效率进行排序。分析结果与中国的现实情况的相吻合,表明该排序方法是合理的,能够完成对这些地区的环境效率进行排序,可以为决策者评价环境的绩效表现提供有效的决策支持。
The rankings of the same type of decision making units with the parallel level on performance is always one of the important issues in the management decisions field.Based on the super-efficiency and slack-based measure model in data envelopment analysis,this paper focuses on the ranking problem of DMUs with undesirable factors.This paper firstly proposes a new super-efficiency SBM model with undesirable factors.This model can not only complete rankings of the efficient DMUs,but be transformed into linear model.It also has some good properties,such as boundedness and monotonic property.This paper then proposes a comprehensive efficiency SBM ranking method with undesirable factors and a polynomial-time algorithm based on new model and Tone’s SBM model.The method takes the SBM model as the first stage to rank the non-efficient DMUs and takes the new model as the second stage to rank efficient DMUs.The two stages are combined to complete the rankings of all DMUs.The results show that the comprehensive ranking method can complete rankings of DMUs with undesirable factors and provides an important theoretical basis for the practice of performance evaluation.We apply the proposed method to rank the environmental efficiencies of China’s 30 provinces in 2010.The results of empirical analyses are consistent with the realities in China.It indicates that the method is reasonable.The method can complete the rankings of all regional environmental efficiencies and provide policy makers with decision support for evaluating environmental performance.
作者
张琳彦
陈鸣
徐倩
张健
ZHANG Lin-yan;CHEN Ming;XU Qian;ZHANG Jian(School of Economics and Management,Beijing Information Science&Technology University,Beijing 100192,China;School of Management&Economics,Beijing Institute of Technology,Beijing 100081,China;Research Center for Knowledge Management,Beijing 100192,China;Beijing Key Lab of Green Development Decision Based on Big Data,Beijing 100192,China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2021年第10期57-63,共7页
Operations Research and Management Science
基金
国家自然科学基金资助项目(71901032)
教育部人文社会科学基金资助项目(19C11232004)
北京市自然科学基金资助项目(9212005)
北京市社会科学基金资助项目(19GLC073,19JDGLB021)
北京市教委科研计划一般项目(SM202011232003,SM202011232004)
北京信息科技大学‘勤信人才’培育计划
北京信息科技大学促进高校内涵发展-科研重点研究培育项目(2020KYNH215)。
关键词
效率排序
非期望因素
SBM模型
超效率
综合效率
efficiency ranking
undesirable factors
slacks-based measure(SBM)
super-efficiency
comprehensive efficiency