Measuring Eco-Inefficiency: A New Frontier Approach

被引:139
作者
Chen, Chien-Ming [1 ]
Delmas, Magali A. [2 ,3 ]
机构
[1] Nanyang Technol Univ, Nanyang Business Sch, Singapore 639798, Singapore
[2] Univ Calif Los Angeles, Inst Environm & Sustainabil, Los Angeles, CA 90095 USA
[3] Univ Calif Los Angeles, Anderson Sch Management, Los Angeles, CA 90095 USA
关键词
DATA ENVELOPMENT ANALYSIS; UNDESIRABLE OUTPUTS; NONPARAMETRIC EFFICIENCY; ENVIRONMENTAL-MANAGEMENT; SUPPLY CHAIN; TRADE-OFFS; DEA; PRODUCTIVITY; PERFORMANCE; TECHNOLOGY;
D O I
10.1287/opre.1120.1094
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Growing social concerns over the environmental externalities associated with business activities are pushing firms to identify activities that create economic value with less environmental impact and to become more eco-efficient. Over the past two decades, researchers have increasingly used frontier efficiency models to evaluate productive efficiency in the presence of undesirable outputs, such as greenhouse gas emissions or toxic emissions. In this paper, we identify critical flaws in existing frontier models and show that these models can identify eco-inefficient firms as eco-efficient. We develop a new eco-inefficiency frontier model that rectifies these problems. Our model calculates an eco-inefficiency score for each firm and improvements in outputs necessary to attain eco-efficiency. We demonstrate through a Monte Carlo experiment that our eco-inefficiency model provides a more reliable measurement of corporate eco-inefficiency than the existing frontier models. We also extend the single-output Cobb-Douglas production function to multiple desirable and undesirable outputs. This extension allows for greater flexibility in the simulation analysis of frontier models.
引用
收藏
页码:1064 / 1079
页数:16
相关论文
共 52 条
[1]   Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction [J].
Adler, Nicole ;
Yazhemsky, Ekaterina .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2010, 202 (01) :273-284
[2]   Does It Pay to Be Green? A Systematic Overview [J].
Ambec, Stefan ;
Lanoie, Paul .
ACADEMY OF MANAGEMENT PERSPECTIVES, 2008, 23 (04) :45-62
[3]  
[Anonymous], 2007, MODELING DATA IRREGU, DOI DOI 10.1007/978-0-387-71607-7_6
[4]   Evaluating contextual variables affecting productivity using data envelopment analysis [J].
Banker, Rajiv D. ;
Natarajan, Ram .
OPERATIONS RESEARCH, 2008, 56 (01) :48-58
[5]   A MONTE-CARLO COMPARISON OF 2 PRODUCTION FRONTIER ESTIMATION METHODS - CORRECTED ORDINARY LEAST-SQUARES AND DATA ENVELOPMENT ANALYSIS [J].
BANKER, RD ;
GADH, VM ;
GORR, WL .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1993, 67 (03) :332-343
[6]   SOME MODELS FOR ESTIMATING TECHNICAL AND SCALE INEFFICIENCIES IN DATA ENVELOPMENT ANALYSIS [J].
BANKER, RD ;
CHARNES, A ;
COOPER, WW .
MANAGEMENT SCIENCE, 1984, 30 (09) :1078-1092
[7]   MAXIMUM-LIKELIHOOD, CONSISTENCY AND DATA ENVELOPMENT ANALYSIS - A STATISTICAL FOUNDATION [J].
BANKER, RD .
MANAGEMENT SCIENCE, 1993, 39 (10) :1265-1273
[8]   A simulation study of joint uses of data envelopment analysis and statistical regressions for production function estimation and efficiency evaluation [J].
Bardhan, IR ;
Cooper, WW ;
Kumbhakar, SC .
JOURNAL OF PRODUCTIVITY ANALYSIS, 1998, 9 (03) :249-278
[9]   MEASURING EFFICIENCY OF DECISION-MAKING UNITS [J].
CHARNES, A ;
COOPER, WW ;
RHODES, E .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1978, 2 (06) :429-444
[10]  
Chen C.-M., 2012, MEASURING ENV EFFICI