Evaluating radial efficiency considering environmental factors: A generalization of classical DEA

被引:15
作者
Afzalinejad, Mohammad [1 ]
机构
[1] Tafresh Univ, Dept Math, Tafresh 3951879611, Iran
关键词
Data Envelopment Analysis; Undesirable outputs; Environmental efficiency; Economic performance; Social; Eco-efficiency measure; DATA ENVELOPMENT ANALYSIS; UNDESIRABLE OUTPUTS; TECHNICAL EFFICIENCY; ENERGY; PERFORMANCE; COUNTRIES; INEFFICIENCY; MODEL; OECD; INDEX;
D O I
10.1016/j.measurement.2021.109497
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Environmental issues are becoming a significant and serious worldwide problem. Undesirable outputs like waste and pollution are by-products of desirable outputs in a production system. To motivate environment friendly production, undesirable outputs should be included in the performance assessment of firms, organizations and countries. Data Envelopment Analysis (DEA) is one of the most successful methods of efficiency evaluation. Unfortunately, there is no reliable radial efficiency measure for environmental assessment in DEA. In this paper, the conventional modeling in DEA is extended to develop a new radial model for efficiency assessment in the presence of undesirable outputs. This method enables more accurate modeling of the problem. It opens a new door to the issue, and shows more reliabilities than the existing methods. The new efficiency measure is more rigorous, and provides higher discriminating power. Evaluating divisional efficiency is another advantage of the model. It also provides credible targets with greater practical accessibility for each inefficient decision making unit. The model is studied by an axiomatic approach and employed to evaluate the performance of 28 countries in economic, social and environmental dimensions. The results show that only one country achieves efficiency, and the average environmental efficiency is considerably lower than the operational efficiency among the studied countries.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Measurement of environmental efficiency in the countries of the European Union with the enhanced data envelopment analysis method (DEA) during the period 2005-2012
    Jesus Hermoso-Orzaez, Manuel
    Garcia-Alguacil, Miriam
    Terrados-Cepeda, Julio
    Brito, Paulo
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2020, 27 (13) : 15691 - 15715
  • [32] Evaluating economic and environmental efficiency of global airlines: A SBM-DEA approach
    Chang, Young-Tae
    Park, Hyo-soo
    Jeong, Jae-beom
    Lee, Jin-woo
    TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2014, 27 : 46 - 50
  • [33] Environmental efficiency assessment of Dublin Port using two-stage non-radial DEA model
    Djordjevic, Boban
    Maitra, Raja
    Ghosh, Bidisha
    MARITIME TRANSPORT RESEARCH, 2023, 4
  • [35] Assesing the radial efficiency in the agroindustrial sector through model DEA VRS with undesirable outputs
    Alfonso Lizarazo, Edgar Hernan
    Gutierrez Franco, Edgar
    INGENIERIA, 2007, 12 (02): : 39 - 45
  • [36] A NOVEL DEA APPROACH FOR EVALUATING SUSTAINABLE SUPPLY CHAINS WITH UNDESIRABLE FACTORS
    Moghaddas, Zohreh
    Vaez-Ghasemi, Mohsen
    Hosseinzadeh Lotfi, Farhad
    ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, 2021, 55 (02) : 177 - 192
  • [37] Environmental regulation efficiency analysis by considering regional heterogeneity
    Liu, Xiaohong
    Yang, Jiangjiang
    Xu, Chengzhen
    Li, Xingchen
    Zhu, Qingyuan
    RESOURCES POLICY, 2023, 83
  • [38] Environmental efficiency analysis of China's regional industry: a data envelopment analysis (DEA) based approach
    Chen, Liang
    Jia, Guozhu
    JOURNAL OF CLEANER PRODUCTION, 2017, 142 : 846 - 853
  • [39] An Interval Efficiency Measurement in DEA When considering Undesirable Outputs
    Mo, Renbian
    Huang, Hongyun
    Yang, Liyang
    COMPLEXITY, 2020, 2020
  • [40] Evaluating the environmental efficiency of the U.S. airline industry using a directional distance function DEA approach
    Xu, Yuan
    Park, Yong Shin
    Park, Ju Dong
    Cho, Wonjoo
    JOURNAL OF MANAGEMENT ANALYTICS, 2021, 8 (01) : 1 - 18