Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends

Measurement of environmental and energy economics presents an analytical foundation for environmental decision making and policy analysis. Applications of data envelopment analysis (DEA) models in the assessment of environmental and energy economics are increasing notably. The main objective of this review paper is to provide the comprehensive overview of the application of DEA models in the fields of environmental and energy economics. In this regard, a total 145 articles published in the high-quality international journals extracted from two important databases (Web of Science and Scopus) were selected for review. The 145 selected articles are reviewed and classified based on different criteria including author(s), application scheme, different DEA models, application fields, the name of journals and year of publication. This review article provided insights into the methodological and conceptualization study in the application of DEA models in the environmental and energy economics fields. This study should enable scholars and practitioners to understand the state of art of input and output indicators of DEA in the fields of environmental and energy economics.

[1]  Peter Nijkamp,et al.  Tracing high-sustainability performers among world cities - design and application of a multi-temporal data envelopment analysis , 2017 .

[2]  Ya Zhou,et al.  Analysis on provincial industrial energy efficiency and its influencing factors in China based on DEA-RS-FANN , 2018 .

[3]  Edmundas Kazimieras Zavadskas,et al.  VIKOR Technique: A Systematic Review of the State of the Art Literature on Methodologies and Applications , 2016 .

[4]  Jaeho Shin,et al.  The Effect of Sustainability as Innovation Objectives on Innovation Efficiency , 2018, Sustainability.

[5]  Gento Mogi,et al.  A fuzzy analytic hierarchy process (AHP)/data envelopment analysis (DEA) hybrid model for efficiently allocating energy R&D resources: In the case of energy technologies against high oil prices , 2013 .

[6]  Mir Saman Pishvaee,et al.  An integrated data envelopment analysis–mathematical programming approach to strategic biodiesel supply chain network design problem , 2017 .

[7]  Jie Wu,et al.  Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspective , 2016, Eur. J. Oper. Res..

[8]  Peng Zhou,et al.  Industrial energy conservation and emission reduction performance in China: A city-level nonparametric analysis , 2016 .

[9]  Ning Zhang,et al.  Chinese Airline Efficiency under CO2 Emissions and Flight Delays: A Stochastic Network DEA Model , 2017 .

[10]  Wen-Shing Lee,et al.  Benchmarking the performance of building energy management using data envelopment analysis , 2009 .

[11]  Yue-Jun Zhang,et al.  Evaluating the dynamic performance of energy portfolios: Empirical evidence from the DEA directional distance function , 2017, Eur. J. Oper. Res..

[12]  Edmundas Kazimieras Zavadskas,et al.  Using fuzzy multiple criteria decision making approaches for evaluating energy saving technologies and solutions in five star hotels: a new hierarchical framework , 2016 .

[13]  Semida Silveira,et al.  Analysis of energy use and CO2 emission in service industries: Evidence from Sweden , 2012 .

[14]  Y. Hao,et al.  The driving forces of the change in China's energy intensity: An empirical research using DEA-Malmquist and spatial panel estimations , 2017 .

[15]  Joanicjusz Nazarko,et al.  Measuring Productivity of Construction Industry in Europe with Data Envelopment Analysis , 2015 .

[16]  MardaniAbbas,et al.  Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014 , 2015 .

[17]  Chunlu Liu,et al.  Slacks-based data envelopment analysis for eco-efficiency assessment in the Australian construction industry , 2017 .

[18]  Wen-Hsien Tsai,et al.  Input-Output Analysis for Sustainability by Using DEA Method: A Comparison Study between European and Asian Countries , 2016 .

[19]  Jin-Li Hu,et al.  Total-factor Energy Efficiency for Regions in Taiwan , 2012 .

[20]  Siqin Xiong,et al.  Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model , 2017 .

[21]  Dong-Shang Chang,et al.  Incorporating the carbon footprint to measure industry context and energy consumption effect on environmental performance of business operations , 2015, Clean Technologies and Environmental Policy.

[22]  Xu Wang,et al.  Environmental Efficiency and Its Determinants for Manufacturing in China , 2016 .

[23]  Mohammad Alauddin,et al.  Input-Orientated Data Envelopment Analysis Framework for Measuring and Decomposing Economic, Environmental and Ecological Efficiency: An Application to OECD Agriculture , 2012 .

[24]  Jie Wu,et al.  Environmental efficiency evaluation based on data envelopment analysis: A review , 2012 .

[25]  Yi-Ming Wei,et al.  Evaluating energy efficiency for airlines: An application of Virtual Frontier Dynamic Slacks Based Measure , 2016 .

[26]  Peter Grösche,et al.  Measuring residential energy efficiency improvements with DEA , 2007 .

[27]  Adnan Sözen,et al.  Assessment of operational and environmental performance of the thermal power plants in Turkey by using data envelopment analysis , 2010 .

[28]  Jiang Wu,et al.  Identification of key energy efficiency drivers through global city benchmarking: A data driven approach , 2017 .

[29]  Lu Gan,et al.  Economic Feasibility Analysis for Renewable Energy Project Using an Integrated TFN–AHP–DEA Approach on the Basis of Consumer Utility , 2017 .

[30]  Zhenshan Yang,et al.  Efficiency evaluation of material and energy flows, a case study of Chinese cities , 2016 .

[31]  Panos M. Pardalos,et al.  Testing for Environmental Kuznets Curve in the EU Agricultural Sector through an Eco-(in)Efficiency Index , 2017 .

[32]  Markus Lips,et al.  On the link between economic and environmental performance of Swiss dairy farms of the alpine area , 2012, The International Journal of Life Cycle Assessment.

[33]  Jie Wu,et al.  An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: a transportation system application , 2016, Annals of Operations Research.

[34]  Dora Marinova,et al.  Evaluation of the green technology innovation efficiency of China's manufacturing industries: DEA window analysis with ideal window width , 2018, Technol. Anal. Strateg. Manag..

[35]  Zilla Sinuany-Stern,et al.  Review of ranking methods in the data envelopment analysis context , 2002, Eur. J. Oper. Res..

[36]  Malin Song,et al.  Computational analysis of thermoelectric enterprises’ environmental efficiency and Bayesian estimation of influence factors , 2016 .

[37]  Qunxiong Zhu,et al.  Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes , 2017 .

[38]  Yongming Han,et al.  Carbon emission analysis and evaluation of industrial departments in China: An improved environmental DEA cross model based on information entropy. , 2018, Journal of environmental management.

[39]  Jie Wu,et al.  Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output , 2015, Ann. Oper. Res..

[40]  Jie Wu,et al.  Energy and environmental efficiency analysis of China’s regional transportation sectors: a slack-based DEA approach , 2017 .

[41]  Ching-Cheng Lu,et al.  Applying the dynamic DEA model to evaluate the energy efficiency of OECD countries and China , 2017 .

[42]  D. Štreimikienė,et al.  The role of process innovation between firm-specific capabilities and sustainable innovation in SMEs: empirical evidence from Indonesia , 2018 .

[43]  Rolf Färe,et al.  Environmental Investment and Firm Performance: A Network Approach , 2015 .

[44]  G. Pérez-López,et al.  Temporal scale efficiency in DEA panel data estimations. An application to the solid waste disposal service in Spain , 2018 .

[45]  Yong Zha,et al.  Measuring regional efficiency of energy and carbon dioxide emissions in China: A chance constrained DEA approach , 2016, Comput. Oper. Res..

[46]  Yi-Ming Wei,et al.  China’s regional industrial energy efficiency and carbon emissions abatement costs , 2014 .

[47]  Guijun Li,et al.  China’s Input-Output Efficiency of Water-Energy-Food Nexus Based on the Data Envelopment Analysis (DEA) Model , 2016 .

[48]  Edmundas Kazimieras Zavadskas,et al.  Application of multiple criteria decision making techniques in tourism and hospitality industry: a systematic review , 2016 .

[49]  Xueqing Wang,et al.  The energy efficiency of China’s regional construction industry based on the three-stage DEA model and the DEA-DA model , 2016 .

[50]  Kuan Yew Wong,et al.  A Review on Data Envelopment Analysis (DEA) , 2010, 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation.

[51]  Lawrence M. Seiford,et al.  Data envelopment analysis (DEA) - Thirty years on , 2009, Eur. J. Oper. Res..

[52]  So Young Sohn,et al.  Comparison of technology efficiency for CO2 emissions reduction among European countries based on DEA with decomposed factors , 2017 .

[53]  A. Vaninsky Energy-environmental efficiency and optimal restructuring of the global economy , 2018, Energy.

[54]  Giulia Romano,et al.  Energy Efficiency Drivers in Wastewater Treatment Plants: A Double Bootstrap DEA Analysis , 2017 .

[55]  Junjie Wu,et al.  Comparative study on efficiency performance of listed coal mining companies in China and the US , 2009 .

[56]  Chiang Kao,et al.  Network data envelopment analysis: A review , 2014, Eur. J. Oper. Res..

[57]  Qunxiong Zhu,et al.  Energy and environmental efficiency evaluation based on a novel data envelopment analysis: An application in petrochemical industries , 2017 .

[58]  Yun Long,et al.  A Study on the Conduction Mechanism and Evaluation of the Comprehensive Efficiency of Photovoltaic Power Generation in China , 2017 .

[59]  Dequn Zhou,et al.  Energy efficiency and congestion assessment with energy mix effect: The case of APEC countries , 2017 .

[60]  D. Zha,et al.  Performance evaluation of Chinese photovoltaic companies with the input-oriented dynamic SBM model , 2016 .

[61]  S. Mandal,et al.  Energy use efficiency of Indian cement companies: a data envelopment analysis , 2011 .

[62]  Jin-Li Hu,et al.  Clean energy use and total-factor efficiencies: An international comparison , 2015 .

[63]  Luis C. Dias,et al.  Assessing the performance of biogas plants with multi-criteria and data envelopment analysis , 2009, Eur. J. Oper. Res..

[64]  Adel Hatami-Marbini,et al.  A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making , 2011, Eur. J. Oper. Res..

[65]  Boqiang Lin,et al.  Impact of energy conservation policies on the green productivity in China's manufacturing sector: Evidence from a three-stage DEA model , 2016 .

[66]  John S. Liu,et al.  Data envelopment analysis 1978-2010: A citation-based literature survey , 2013 .

[67]  Tao Zhao,et al.  Environmental assessment and investment strategies of provincial industrial sector in China — Analysis based on DEA model , 2016 .

[68]  M. Omid,et al.  Greenhouse strawberry production in Iran, efficient or inefficient in energy , 2012 .

[69]  Boqiang Lin,et al.  Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter? , 2015 .

[70]  Wade D. Cook,et al.  Measuring efficiency with products, by-products and parent-offspring relations: A conditional two-stage DEA model , 2017 .

[71]  Lidia Angulo Meza,et al.  A multiobjective DEA model to assess the eco-efficiency of agricultural practices within the CF + DEA method , 2019, Comput. Electron. Agric..

[72]  Giovanni Zurlini,et al.  A non-parametric bootstrap-data envelopment analysis approach for environmental policy planning and management of agricultural efficiency in EU countries , 2017 .

[73]  Edmundas Kazimieras Zavadskas,et al.  A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015 , 2017 .

[74]  M. H. Alavidoost,et al.  A novel fuzzy network SBM model for data envelopment analysis: A case study in Iran regional power companies , 2016 .

[75]  Prasanta Kumar Dey,et al.  Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis , 2016, Comput. Oper. Res..

[76]  Khalil Md Nor,et al.  Development of TOPSIS Method to Solve Complicated Decision-Making Problems - An Overview on Developments from 2000 to 2015 , 2016, Int. J. Inf. Technol. Decis. Mak..

[77]  R. J. Kuo,et al.  Integration of artificial neural network and MADA methods for green supplier selection , 2010 .

[78]  Edmundas Kazimieras Zavadskas,et al.  Sustainable and Renewable Energy: An Overview of the Application of Multiple Criteria Decision Making Techniques and Approaches , 2015 .

[79]  S. Rafiee,et al.  Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach , 2011 .

[80]  Wen-Shing Lee,et al.  Benchmarking the energy efficiency of government buildings with data envelopment analysis , 2008 .

[81]  Rahim Ebrahimi,et al.  Investigation of CO2 emission reduction and improving energy use efficiency of button mushroom production using Data Envelopment Analysis , 2015 .

[82]  Toshiyuki Sueyoshi,et al.  Measuring scale efficiency and returns to scale on large commercial rooftop photovoltaic systems in California , 2017 .

[83]  Wei Zhou,et al.  A synthesized data envelopment analysis model and its application in resource efficiency evaluation and dynamic trend analysis , 2017 .

[84]  Jingzheng Ren,et al.  Determining the life cycle energy efficiency of six biofuel systems in China: a Data Envelopment Analysis. , 2014, Bioresource technology.

[85]  Cheng Shao,et al.  Ethylene cracking furnace TOPSIS energy efficiency evaluation method based on dynamic energy efficiency baselines , 2018 .

[86]  Reza Farzipoor Saen,et al.  A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context , 2015, Comput. Oper. Res..

[87]  P. He,et al.  Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach , 2013 .

[88]  Q. Cui,et al.  Airline energy efficiency measures considering carbon abatement: A new strategic framework , 2016 .

[89]  X. Xue,et al.  A Dynamic Analysis to Evaluate the Environmental Performance of Cities in China , 2018 .

[90]  Boqiang Lin,et al.  An application of a double bootstrap to investigate the effects of technological progress on total-factor energy consumption performance in China , 2017 .

[91]  Endong Wang,et al.  Benchmarking energy performance of residential buildings using two-stage multifactor data envelopment analysis with degree-day based simple-normalization approach , 2015 .

[92]  Hana Moon,et al.  Assessing energy efficiency and the related policy implications for energy-intensive firms in Korea: DEA approach , 2017 .

[93]  Mehdi Toloo,et al.  A non-radial directional distance method on classifying inputs and outputs in DEA: Application to banking industry , 2018, Expert Syst. Appl..

[94]  Alireza Keyhani,et al.  Joint Life Cycle Assessment and Data Envelopment Analysis for the benchmarking of environmental impacts in rice paddy production , 2015 .

[95]  Duk Hee Lee,et al.  Energy and environment efficiency of industry and its productivity effect , 2016 .

[96]  Yi-Ming Wei,et al.  Exploring the impacts of the EU ETS emission limits on airline performance via the Dynamic Environmental DEA approach , 2016 .

[97]  William W. Cooper,et al.  Data Envelopment Analysis: History, Models, and Interpretations , 2011 .

[98]  Dr. Sam C. M. Hui,et al.  Study of hotel energy performance using data envelopment analysis , 2013 .

[99]  A. Makui,et al.  Operational and non-operational performance evaluation of thermal power plants in Iran: A game theory approach , 2012 .

[100]  Ke Wang,et al.  A comparative analysis of China’s regional energy and emission performance: Which is the better way to deal with undesirable outputs? , 2012 .

[101]  Jin-peng Liu,et al.  Analysis, Evaluation and Optimization Strategy of China Thermal Power Enterprises’ Business Performance Considering Environmental Costs under the Background of Carbon Trading , 2018, Sustainability.

[102]  Clara Inés Pardo Martínez,et al.  Regional analysis across Colombian departments: a non-parametric study of energy use , 2016 .

[103]  Edmundas Kazimieras Zavadskas,et al.  Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014 , 2015, Expert Syst. Appl..

[104]  Qunxiong Zhu,et al.  Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry , 2015 .

[105]  Kiyotaka Masuda Energy Efficiency of Intensive Rice Production in Japan: An Application of Data Envelopment Analysis , 2018 .

[106]  J. Nazarko,et al.  Labour efficiency in construction industry in Europe based on frontier methods: data envelopment analysis and stochastic frontier analysis , 2017 .

[107]  Peng Zhou,et al.  A survey of data envelopment analysis in energy and environmental studies , 2008, Eur. J. Oper. Res..

[108]  Jie Wu,et al.  A comprehensive analysis of China's regional energy saving and emission reduction efficiency: From production and treatment perspectives , 2015 .

[109]  Ali Emrouznejad,et al.  A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016 , 2018 .

[110]  Panos M. Pardalos,et al.  Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks , 2017 .

[111]  Zaiwu Gong,et al.  DEA Efficiency of Energy Consumption in China’s Manufacturing Sectors with Environmental Regulation Policy Constraints , 2017 .

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

[113]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[114]  M. Farrell The Measurement of Productive Efficiency , 1957 .

[115]  Reza Farzipoor Saen,et al.  Forecasting efficiency of green suppliers by dynamic data envelopment analysis and artificial neural networks , 2017 .

[116]  Hui Li,et al.  Sustainability Assessment of Refining Enterprises Using a DEA-Based Model , 2017 .

[117]  E. Jeon,et al.  The Promotion of Environmental Management in the South Korean Health Sector—Case Study , 2018, Sustainability.

[118]  Li Yang,et al.  Energy saving in China: Analysis on the energy efficiency via bootstrap-DEA approach , 2013 .

[119]  O. A. Olanrewaju,et al.  Integrated IDA–ANN–DEA for assessment and optimization of energy consumption in industrial sectors , 2012 .

[120]  Abbas Mardani,et al.  Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014 , 2015 .

[121]  Tser-yieth Chen,et al.  A comparative study of energy utilization efficiency between Taiwan and China , 2010 .

[122]  Qingyuan Zhu,et al.  Efficiency evaluation of regional energy saving and emission reduction in China: A modified slacks-based measure approach , 2017 .

[123]  J. Johnes Data Envelopment Analysis and Its Application to the Measurement of Efficiency in Higher Education. , 2006 .

[124]  Bai-Chen Xie,et al.  Is there a difference between the energy and CO2 emission performance for China’s thermal power industry? A bootstrapped directional distance function approach , 2016 .

[125]  S. Rafiee,et al.  Optimization of energy required and greenhouse gas emissions analysis for orange producers using data envelopment analysis approach , 2014 .

[126]  Zongyun Song,et al.  Analysis of wind turbine micrositing efficiency: An application of two-subprocess data envelopment analysis method , 2018 .

[127]  Qunxiong Zhu,et al.  Energy efficiency analysis based on DEA integrated ISM: A case study for Chinese ethylene industries , 2015, Eng. Appl. Artif. Intell..

[128]  Yih-Chearng Shiue,et al.  A Comprehensive Evaluation of Sustainable Development Ability and Pathway for Major Cities in China , 2017 .

[129]  Jie Wu,et al.  Using a hybrid heterogeneous DEA method to benchmark China’s sustainable urbanization: an empirical study , 2018, Annals of Operations Research.

[130]  Muhamad Zameri Mat Saman,et al.  A systematic review and meta-Analysis of SWARA and WASPAS methods: Theory and applications with recent fuzzy developments , 2017, Appl. Soft Comput..

[131]  Edmundas Kazimieras Zavadskas,et al.  Application of Structural Equation Modeling (SEM) to Solve Environmental Sustainability Problems: A Comprehensive Review and Meta-Analysis , 2017 .

[132]  Ali Emrouznejad,et al.  Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years , 2008 .

[133]  Feng Yang,et al.  Resource and environment efficiency analysis of provinces in China: A DEA approach based on Shannon’s entropy , 2010 .

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

[135]  Mara Madaleno,et al.  The economic and environmental efficiency assessment in EU cross-country: Evidence from DEA and quantile regression approach , 2017 .

[136]  Qingyou Yan,et al.  Economic and Technical Efficiency of the Biomass Industry in China: A Network Data Envelopment Analysis Model Involving Externalities , 2017 .

[137]  Weidong Chen,et al.  Fossil energy saving and CO2 emissions reduction performance, and dynamic change in performance considering renewable energy input , 2017 .

[138]  Qian-Ru Yang,et al.  Total-Factor Energy Efficiency (TFEE) Evaluation on Thermal Power Industry with DEA, Malmquist and Multiple Regression Techniques , 2017 .

[139]  Semih Önüt,et al.  Energy efficiency assessment for the Antalya Region hotels in Turkey , 2006 .

[140]  D. Štreimikienė,et al.  A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency , 2017 .

[141]  Mahmoud Omid,et al.  Reduction of CO2 emission by improving energy use efficiency of greenhouse cucumber production using DEA approach , 2013 .

[142]  Mehrbakhsh Nilashi,et al.  Multi-criteria decision making approach in E-learning: A systematic review and classification , 2016, Appl. Soft Comput..

[143]  A. Bryman,et al.  The SAGE handbook of organizational research methods , 2009 .

[144]  D. Tranfield,et al.  Producing a systematic review. , 2009 .

[145]  Kwok-wing Chau,et al.  Energy consumption enhancement and environmental life cycle assessment in paddy production using optimization techniques , 2017 .

[146]  Jin-Li Hu,et al.  Efficient energy-saving targets for APEC economies , 2007 .

[147]  Ângela Carrancho da Silva,et al.  Performance assessment of Alternative Energy Resources in Brazilian power sector using Data Envelopment Analysis , 2012 .

[148]  Kaoru Tone,et al.  Dynamic DEA with network structure: A slacks-based measure approach , 2013 .

[149]  T. Sueyoshi,et al.  Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention , 2017 .

[150]  Yongmei Bentley,et al.  The debate on flexibility of environmental regulations, innovation capabilities and financial performance : a novel use of DEA , 2018 .

[151]  Edmundas Kazimieras Zavadskas,et al.  Application of data envelopment analysis models in supply chain management: a systematic review and meta-analysis , 2017, Annals of Operations Research.

[152]  Rodney H. Green,et al.  Efficiency and Cross-efficiency in DEA: Derivations, Meanings and Uses , 1994 .

[153]  Maghsoud Amiri,et al.  A dynamic network efficiency measurement of airports performance considering sustainable development concept: A fuzzy dynamic network-DEA approach , 2016 .

[154]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[155]  Jin-Li Hu,et al.  Efficient saving targets of electricity and energy for regions in China , 2011 .

[156]  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..

[157]  Jun Bi,et al.  Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs , 2010 .

[158]  Tao Zhao,et al.  Regional energy-environmental performance and investment strategy for China's non-ferrous metals industry: a non-radial DEA based analysis , 2017 .

[159]  Liang Chen,et al.  Environmental efficiency analysis of China's regional industry: a data envelopment analysis (DEA) based approach , 2017 .

[161]  Yuanxin Liu,et al.  The industrial performance of wind power industry in China , 2015 .

[162]  Chao Feng,et al.  A performance evaluation of the energy, environmental, and economic efficiency and productivity in China: An application of global data envelopment analysis , 2015 .

[163]  Edmundas Kazimieras Zavadskas,et al.  An overview of renewable energy companies in stock exchange: Evidence from minimal spanning tree approach , 2017 .

[164]  Qingxian An,et al.  Energy efficiency measurement of Chinese Yangtze River Delta’s cities transportation: a DEA window analysis approach , 2018 .

[165]  B. Rugani,et al.  On the feasibility of using emergy analysis as a source of benchmarking criteria through data envelopment analysis: A case study for wind energy , 2014 .

[166]  Shixiong Cheng,et al.  Economic Growth Effect and Optimal Carbon Emissions under China’s Carbon Emissions Reduction Policy: A Time Substitution DEA Approach , 2018 .

[167]  Aijun Li,et al.  Social Sustainability Assessment across Provinces in China: An Analysis of Combining Intermediate Approach with Data Envelopment Analysis (DEA) Window Analysis , 2018 .