Environmental efficiency and abatement potential analysis with a two-stage DEA model incorporating the material balance principle

Abstract Appropriate measurement of environmental efficiency in actual production process is of great significance for promoting sustainable development. However, traditional methods of measurement based on joint production function have deviation when the approach is applied to non-joint production activities or any production activity that violates the material balance principle (MBP). In this paper, we propose a two-stage DEA linear model to evaluate environmental efficiency, which adopts MBP and meanwhile considers both production stage and end-of-pipe abatement stage. Our model fits well to the non-joint production activities where the distribution ratio of shared inputs between these two stages is ambiguous. Further, we decompose the environmental efficiency (EE) into production efficiency (PE) and abatement efficiency (AE). Then, we explore the abatement potentials from cleaning production and end-of-pipe abatement, which is demonstrated by pollutant abatement potential index and emission reduction space. We also establish a global Malmquist production index to analyze the dynamic changes of EE, PE, and AE. The proposed approaches are applied to analyze the environmental efficiency of China’s thermal power industry. The results show that PE is generally high, and the effect of AE on EE is dominant. Especially, the abatement activities of SO2 and Soot have greater impact on EE. By opening the “black box”, our work makes a greater exposure to reduction potential.

[1]  Wenbin Liu,et al.  Carbon emission performance evaluation and allocation in Chinese cities , 2018 .

[2]  Stefan Baumgärtner,et al.  The concept of joint production and ecological economics , 2001 .

[3]  Sebastián Lozano Technical and environmental efficiency of a two-stage production and abatement system , 2017, Ann. Oper. Res..

[4]  Biresh K. Sahoo,et al.  Alternative measures of environmental technology structure in DEA: An application , 2011, Eur. J. Oper. Res..

[5]  Qian Zhang,et al.  Fixed costs and shared resources allocation in two-stage network DEA , 2019, Ann. Oper. Res..

[6]  Joe Zhu,et al.  Additive efficiency decomposition in two-stage DEA , 2009, Eur. J. Oper. Res..

[7]  Zhongbao Zhou,et al.  Two-stage DEA models with undesirable input-intermediate-outputs $ , 2015 .

[8]  R. Ayres,et al.  Production, Consumption, and Externalities , 1969 .

[9]  Kenneth Løvold Rødseth Environmental efficiency measurement and the materials balance condition reconsidered , 2016, Eur. J. Oper. Res..

[10]  A. Hailu,et al.  Non‐Parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry , 2001 .

[11]  Lei Chen,et al.  A two-stage network data envelopment analysis approach for measuring and decomposing environmental efficiency , 2018, Comput. Ind. Eng..

[12]  Benjamin Hampf,et al.  Separating environmental efficiency into production and abatement efficiency: a nonparametric model with application to US power plants , 2014 .

[13]  Rolf Färe,et al.  Modeling undesirable factors in efficiency evaluation: Comment , 2004, Eur. J. Oper. Res..

[14]  Jianlin Wang,et al.  Environmental efficiency evaluation of thermal power generation in China based on a slack-based endogenous directional distance function model , 2018, Energy.

[15]  T. Sueyoshi,et al.  A literature study for DEA applied to energy and environment , 2017 .

[16]  M. Cropper,et al.  Environmental Economics: A Survey , 1992 .

[17]  Madjid Tavana,et al.  Efficiency decomposition and measurement in two-stage fuzzy DEA models using a bargaining game approach , 2018, Comput. Ind. Eng..

[18]  Chiang Kao,et al.  Production , Manufacturing and Logistics Multi-period efficiency and Malmquist productivity index in two-stage production systems , 2013 .

[19]  Rolf Färe,et al.  Malmquist Productivity Indexes and Fisher Ideal Indexes , 1992 .

[20]  J. Pastor,et al.  A global Malmquist productivity index , 2005 .

[21]  Kenneth Løvold Rødseth,et al.  Capturing the least costly way of reducing pollution: A shadow price approach , 2013 .

[22]  Zhaohua Wang,et al.  Energy and CO2 emissions efficiency of major economies: A non-parametric analysis , 2016 .

[23]  Huangxin Chen,et al.  Research on the Regional Differences and Influencing Factors of the Innovation Efficiency of China’s High-Tech Industries: Based on a Shared Inputs Two-Stage Network DEA , 2020, Sustainability.

[24]  Zhibin Wu,et al.  Decomposition weights and overall efficiency in a two-stage DEA model with shared resources , 2019, Comput. Ind. Eng..

[25]  Malin Song,et al.  Review of environmental efficiency and its influencing factors in China: 1998–2009 , 2013 .

[26]  Xiao Shi,et al.  Environmental efficiency analysis based on relational two-stage DEA model , 2016, RAIRO Oper. Res..

[27]  Wendi Ouyang,et al.  The network energy and environment efficiency analysis of 27 OECD countries: A multiplicative network DEA model , 2020 .

[28]  Ning Zhang,et al.  Carbon emissions dynamics, efficiency gains, and technological innovation in China's industrial sectors , 2016 .

[29]  Liang Liang,et al.  Two-stage cooperation model with input freely distributed among the stages , 2010, Eur. J. Oper. Res..

[30]  Raimund Bleischwitz,et al.  Rethinking Productivity: Why has Productivity Focussed on Labour Instead of Natural Resources? , 2001 .

[31]  Dong-hyun Oh,et al.  A global Malmquist-Luenberger productivity index , 2010 .

[32]  Lawrence M. Seiford,et al.  Modeling undesirable factors in efficiency evaluation , 2002, Eur. J. Oper. Res..

[33]  Wei Zhao,et al.  A fuzzy non-radial data envelopment analysis (dea) approach to measure regional environmental performance of china , 2015 .

[34]  Jie Wu,et al.  Total-factor energy efficiency evaluation of Chinese industry by using two-stage DEA model with shared inputs , 2017, Ann. Oper. Res..

[35]  Wenyu Yang,et al.  A bargaining game model for efficiency decomposition in the centralized model of two-stage systems , 2013, Comput. Ind. Eng..

[36]  R. Pethig,et al.  Nonlinear Production, Abatement, Pollution and Materials Balance Reconsidered , 2005, SSRN Electronic Journal.

[37]  Yue Huang,et al.  Is metabolism in all regions of China performing well? – Evidence from a new DEA-Malmquist productivity approach , 2019, Ecological Indicators.

[38]  Zhongbao Zhou,et al.  A Unified Approach to Efficiency Decomposition for a Two-Stage Network DEA Model with Application of Performance Evaluation in Banks and Sustainable Product Design , 2019, Sustainability.

[39]  K. Rødseth Axioms of a Polluting Technology: A Materials Balance Approach , 2017 .

[40]  Ludwig Lauwers,et al.  Justifying the incorporation of the materials balance principle into frontier-based eco-efficiency models , 2009 .

[41]  Chiang Kao,et al.  Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan , 2008, Eur. J. Oper. Res..

[42]  Ming-Miin Yu,et al.  Efficiency and effectiveness in railway performance using a multi-activity network DEA model , 2008 .

[43]  Lili Yang,et al.  Combining global Malmquist–Luenberger index and generalized method of moments to investigate industrial total factor CO2 emission performance: A case of Shanghai (China) , 2015 .

[44]  Ludwig Lauwers,et al.  Environmental efficiency measurement and the materials balance condition , 2007 .

[45]  Elkafi Hassini,et al.  Evaluating sustainability performance in fossil-fuel power plants using a two-stage data envelopment analysis , 2018, Energy Economics.

[46]  Ke Wang,et al.  Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach , 2017, Eur. J. Oper. Res..

[47]  Eric W. Welch,et al.  Joint Environmental and Cost Efficiency Analysis of Electricity Generation , 2009 .

[48]  Benjamin Hampf,et al.  Arbeitspapiere Der Volkswirtschaftlichen Fachgebiete Der Tu Darmstadt Carbon Dioxide Emission Standards for U.s. Power Plants: an Efficiency Analysis Perspective , 2022 .

[49]  Mehdi Toloo,et al.  A linear relational DEA model to evaluate two-stage processes with shared inputs , 2017 .

[50]  Joe Zhu,et al.  Measuring efficiency in DEA in the presence of common inputs , 2020, J. Oper. Res. Soc..

[51]  Lawrence M. Seiford,et al.  A response to comments on modeling undesirable factors in efficiency evaluation , 2005, Eur. J. Oper. Res..

[52]  Rolf Färe,et al.  Productivity and Undesirable Outputs: A Directional Distance Function Approach , 1995 .

[53]  L. R. Christensen,et al.  THE ECONOMIC THEORY OF INDEX NUMBERS AND THE MEASUREMENT OF INPUT, OUTPUT, AND PRODUCTIVITY , 1982 .

[54]  Peter F. Wanke,et al.  Two-stage DEA: An application to major Brazilian banks , 2014, Expert Syst. Appl..

[55]  C.A.K. Lovell,et al.  Multilateral Productivity Comparisons When Some Outputs are Undesirable: A Nonparametric Approach , 1989 .

[56]  Ali Emrouznejad,et al.  Eco-efficiency measurement and material balance principle: an application in power plants Malmquist Luenberger Index , 2017, Ann. Oper. Res..

[57]  Surender Kumar,et al.  Measuring environmental efficiency of industry: a case study of thermal power generation in India , 2007 .