基于交叉效率DEA和熵IAHP对物流企业绩效评价
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摘要
本文在研究了现有文献对物流企业绩效评价的基础上,基于超效率DEA用以计算效率值的权值只在对被评价单元最有利的特定范围内取值、忽视绩效评价的公平性和IAHP方法主观判断性较大的缺陷,提出了交叉效率DEA和熵IAHP方法。交叉效率DEA的中心思想是采用互评体系,弥补了超效率DEA方法只是选择对被评价决策单元最有效的权重忽视公平性的缺陷。熵IAHP方法是客观确定权重的熵权法和体现决策者偏好的IAHP方法的结合,这有效地解决了IAHP方法确定指标权重时主观性过大的缺陷。笔者给出了交叉效率DEA和熵IAHP模型评价物流企业绩效的基本步骤,最后通过一个实例验证了此方法的有效性和优越性。
Based on the study of the existing literatures on the performance evaluation of logistics enterprises,we present the cross-efficiency DEA and entropy IAHP method. Super-efficiency DEA is used to choose the weights of the efficiency value only when the weighs are in the most advantageous position to a decision making unit,which neglects the fairness. IAHP method has the drawback of larger subjective judgments while evaluating performance. The central idea of the cross-efficiency DEA theory is adopted from the peer assessment system. Ignoring the fairness,the super-efficiency DEA method just chooses weights which are favorable for a decision making unit. This drawback can be compensated by cross-efficiency DEA method. Entropy IAHP method is the combination of the entropy method determining weights justly and the IAHP method reflecting the decision makers' preference. We present the basic steps of the cross-efficiency DEA and IAHP model when evaluating performance of logistics enterprises. In the end,the applicability and superiority of the method is illustrated by using a real case study.
Based on the study of the existing literatures on the performance evaluation of logistics enterprises,we present the cross-efficiency DEA and entropy IAHP method. Super-efficiency DEA is used to choose the weights of the efficiency value only when the weighs are in the most advantageous position to a decision making unit,which neglects the fairness. IAHP method has the drawback of larger subjective judgments while evaluating performance. The central idea of the cross-efficiency DEA theory is adopted from the peer assessment system. Ignoring the fairness,the super-efficiency DEA method just chooses weights which are favorable for a decision making unit. This drawback can be compensated by cross-efficiency DEA method. Entropy IAHP method is the combination of the entropy method determining weights justly and the IAHP method reflecting the decision makers' preference. We present the basic steps of the cross-efficiency DEA and IAHP model when evaluating performance of logistics enterprises. In the end,the applicability and superiority of the method is illustrated by using a real case study.
引文
[1]Andersen B,Fagerhaug T.Performance measurement of logistics processes[J].Journal of Operations Management,2003,20:19-32.
[2]Lambert D M,Stock J R.Strategic logistics management[J].Journal of Business Logistics,2001,20(1):70-82.
[3]林敏,刘勇彪.基于层次分析法的林产品物流绩效评价[J].物流工程与管理,2010,32(2):42-44.
[4]孙晓东,田澎,焦爵,胡劲松.类加权主成分分析在企业物流绩效评价中的应用[J].工业工程与管理,2007(1):57-63.
[5]赵丽君.基于模糊综合评判法的绿色物流评价研究[J].武汉理工大学学报,2008,30(6):174-177.
[6]Mehrabian S,Alirezaee M R,Jahanshaloo G R.A complete efficiency ranking of decision making units in data envelopment analysis[J].Computational Optimization and Applications,1999,14(2):261-266.
[7]陈芝,单泪源,顾恒平.基于DEA的企业供应物流系统效率评价的实例分析[J].湖南大学学报(社会科学版),2005,19(6):68-71.
[8]杨克磊,高博,卢赫.企业物流绩效评价的DEA分析[J].哈尔滨商业大学学报(社会科学版),2006(3):67-69.
[9]杨德权,裴金英.基于DEA-AHP的物流系统绩效评价研究[J].运筹与管理,2009,18(5):81-86.
[10]杨德权,裴金英.基于超效率DEA-IAHP的物流企业绩效评价[J].运筹与管理,2012,21(1):189-195.
[11]王瑛,孙林岩,陈宏.基于两阶段的物流系统综合评价DEA/AHP法[J].长安大学学报,2003,23(3):79-84.
[12]Sexton T R,Silkman R H,Hogan A J.Data envelopment analysis:critique and extensions[A].Silkinan R H.Measuring efficiency:an assessment of data envelopment analysis[C].San Francisco:Jossey-Bass,1986,32:73-105.
[13]吴杰.数据包络分析(DEA)的交叉效率研究—基于博弈理论的效率评估方法[D].合肥:中国科技大学,2008.
[14]Chames A,Cooper W W,Rhods E.Measuring the efficiency of decision making units[J].European Journal of Operational Research,1978,2(6):429-444.
[15]栾金昶,翁继林,迟国泰.基于熵AHP的经济发展评价[J].统计与决策,2008,(19):70-72.
[16]张瑞龙.基于熵权与AHP的上市公司经营绩效评价[J].南京:南京理工大学,2007.
[17]邱菀华.管理决策与应用熵学[M].北京:机械工业出版社,2002.
[18]姚平.IAHP-Entropy集成确权的煤炭企业可持续发展综合评[J].科技进步与对策,2009,18(5):153-157.
[19]Toloo Mehdi,Nalchigar Soroosh.A new integrated DEA model for finding most BCC-efficient DMU[J].Applied Mathematical Modelling,2009,33(1):597-604.
[2]Lambert D M,Stock J R.Strategic logistics management[J].Journal of Business Logistics,2001,20(1):70-82.
[3]林敏,刘勇彪.基于层次分析法的林产品物流绩效评价[J].物流工程与管理,2010,32(2):42-44.
[4]孙晓东,田澎,焦爵,胡劲松.类加权主成分分析在企业物流绩效评价中的应用[J].工业工程与管理,2007(1):57-63.
[5]赵丽君.基于模糊综合评判法的绿色物流评价研究[J].武汉理工大学学报,2008,30(6):174-177.
[6]Mehrabian S,Alirezaee M R,Jahanshaloo G R.A complete efficiency ranking of decision making units in data envelopment analysis[J].Computational Optimization and Applications,1999,14(2):261-266.
[7]陈芝,单泪源,顾恒平.基于DEA的企业供应物流系统效率评价的实例分析[J].湖南大学学报(社会科学版),2005,19(6):68-71.
[8]杨克磊,高博,卢赫.企业物流绩效评价的DEA分析[J].哈尔滨商业大学学报(社会科学版),2006(3):67-69.
[9]杨德权,裴金英.基于DEA-AHP的物流系统绩效评价研究[J].运筹与管理,2009,18(5):81-86.
[10]杨德权,裴金英.基于超效率DEA-IAHP的物流企业绩效评价[J].运筹与管理,2012,21(1):189-195.
[11]王瑛,孙林岩,陈宏.基于两阶段的物流系统综合评价DEA/AHP法[J].长安大学学报,2003,23(3):79-84.
[12]Sexton T R,Silkman R H,Hogan A J.Data envelopment analysis:critique and extensions[A].Silkinan R H.Measuring efficiency:an assessment of data envelopment analysis[C].San Francisco:Jossey-Bass,1986,32:73-105.
[13]吴杰.数据包络分析(DEA)的交叉效率研究—基于博弈理论的效率评估方法[D].合肥:中国科技大学,2008.
[14]Chames A,Cooper W W,Rhods E.Measuring the efficiency of decision making units[J].European Journal of Operational Research,1978,2(6):429-444.
[15]栾金昶,翁继林,迟国泰.基于熵AHP的经济发展评价[J].统计与决策,2008,(19):70-72.
[16]张瑞龙.基于熵权与AHP的上市公司经营绩效评价[J].南京:南京理工大学,2007.
[17]邱菀华.管理决策与应用熵学[M].北京:机械工业出版社,2002.
[18]姚平.IAHP-Entropy集成确权的煤炭企业可持续发展综合评[J].科技进步与对策,2009,18(5):153-157.
[19]Toloo Mehdi,Nalchigar Soroosh.A new integrated DEA model for finding most BCC-efficient DMU[J].Applied Mathematical Modelling,2009,33(1):597-604.