Green Mining Efficiency and Improvement Countermeasures for China's Coal Mining Industry

This study defines a green mining system as a synergetic operation system composed of a mining subsystem and an environmental governance subsystem. Through conducting a case study of China's coal enterprises, this study identifies the mining subsystem as the first production stage and the environmental governance subsystem as the second production stage. To evaluate green mining efficiency, an entire green mining efficiency indicator system was constructed by analyzing the main inputs and outputs of the two subsystems. Using the 2019 data collected from Chinese coal mining enterprises based on the constructed indicator system, this study presents a two-stage combination Data Envelopment Analysis model to assess green mining efficiency in terms of mining efficiency and environmental governance efficiency. According to this empirical study's results, there were four main findings. First, coal enterprises can be divided into three categories in accordance with the efficiency value ranking generated by the two-stage model and the corresponding synergetic development levels. Second, the percentage distribution of coal enterprises based on their green mining efficiency level embodies the attributes of a spindle structure. Third, the exported parameters information from the two-stage model supports green mining efficiency improvement as quantitative evidence. Fourth, the model results form the basis for policy proposals and improvement countermeasures.

[1]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[2]  Y. Shao,et al.  The Synergy in the Economic Production System: An Empirical Study with Chinese Industry , 2019, Sustainability.

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

[4]  Xunpeng Shi,et al.  Unintended consequences of China’s coal capacity cut policy , 2018 .

[5]  Junyan Yang,et al.  Spatial Correlation of Formats in the Central Districts of a Megacity: The Case of Shanghai , 2019, Sustainability.

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

[7]  Zhongshan Yang,et al.  The measurement and influences of China's urban total factor energy efficiency under environmental pollution: Based on the game cross-efficiency DEA , 2019, Journal of Cleaner Production.

[8]  Toshiyuki Sueyoshi,et al.  China's regional sustainability and diversified resource allocation: DEA environmental assessment on economic development and air pollution , 2015 .

[9]  Toshiyuki Sueyoshi,et al.  Social Sustainability of Provinces in China: A Data Envelopment Analysis (DEA) Window Analysis under the Concepts of Natural and Managerial Disposability , 2017 .

[10]  Lawrence M. Seiford,et al.  Recent developments in dea : the mathematical programming approach to frontier analysis , 1990 .

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

[12]  Qunwei Wang,et al.  Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach , 2013 .

[13]  Renato De Leone,et al.  Data Envelopment Analysis , 2009, Encyclopedia of Optimization.

[14]  Yung‐ho Chiu,et al.  Dynamic Environmental Efficiency Assessment of Industrial Water Pollution , 2019, Sustainability.

[15]  B. W. Ang,et al.  Linear programming models for measuring economy-wide energy efficiency performance , 2008 .

[16]  Liang Liang,et al.  Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs , 2019, Energy Economics.

[17]  L. Liang,et al.  Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model , 2014 .

[18]  P. Bajec,et al.  An Integrated Analytic Hierarchy Process—Slack Based Measure-Data Envelopment Analysis Model for Evaluating the Efficiency of Logistics Service Providers Considering Undesirable Performance Criteria , 2019, Sustainability.

[19]  P. Nurmi.  Green Mining – A Holistic Concept for Sustainable and Acceptable Mineral Production , 2017 .

[20]  Deniz Mamurekli.  Environmental impacts of coal mining and coal utilization in the UK , 2010 .

[21]  Li Xie,et al.  Dynamic Assessment of Environmental Efficiency in Chinese Industry: A Multiple DEA Model with a Gini Criterion Approach , 2019, Sustainability.

[22]  Hongliang Yang,et al.  Incorporating Both Undesirable Outputs and Uncontrollable Variables into Dea: the Performance of Chinese Coal-fired Power Plants Incorporating Both Undesirable Outputs and Uncontrollable Variables into Dea: the Performance of Chinese Coal-fired Power Plants , 2007 .

[23]  Fan Ying,et al.  Does generation form influence environmental efficiency performance? An analysis of China’s power system , 2012 .

[24]  Lei Tong,et al.  Efficiency assessment of coal mine safety input by data envelopment analysis , 2008 .

[25]  Yi-Ming Wei,et al.  Carbon emissions intensity reduction target for China's power industry: An efficiency and productivity perspective , 2018, Journal of Cleaner Production.

[26]  David Brereton,et al.  Managing the cumulative impacts of coal mining on regional communities and environments in Australia , 2010 .

[27]  T. Sueyoshi,et al.  DEA radial measurement for environmental assessment and planning: Desirable procedures to evaluate fossil fuel power plants , 2012 .

[28]  Toshiyuki Sueyoshi,et al.  Should the US clean air act include CO2 emission control?: Examination by data envelopment analysis , 2010 .

[29]  Ye Tao,et al.  Environmental efficiency of electric power industry in the Yangtze River Delta , 2013, Math. Comput. Model..

[30]  Tien-Hui Chen,et al.  Performance measurement of an enterprise and business units with an application to a Taiwanese hotel chain , 2009 .

[31]  Qunwei Wang,et al.  Measurement and decomposition of energy-saving and emissions reduction performance in Chinese cities , 2015 .

[32]  Kuangnan Fang,et al.  Environmental efficiency analysis of power industry in China based on an entropy SBM model , 2013 .

[33]  Yi-Ming Wei,et al.  Spatial heterogeneity and driving forces of environmental productivity growth in China: Would it help to switch pollutant discharge fees to environmental taxes? , 2019, Journal of Cleaner Production.

[34]  T. Sueyoshi,et al.  Measuring energy usage and sustainability development in Asian nations by DEA intermediate approach , 2018, Journal of Economic Structures.

[35]  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..

[36]  Toshiyuki Sueyoshi,et al.  Efficiency-based rank assessment for electric power industry: A combined use of Data Envelopment Analysis (DEA) and DEA-Discriminant Analysis (DA) , 2012 .

[37]  N. Zhu,et al.  Green financial behavior and green development strategy of Chinese power companies in the context of carbon tax , 2020 .

[38]  Toshiyuki Sueyoshi,et al.  Environmental assessment by DEA radial measurement: U.S. coal-fired power plants in ISO (Independent System Operator) and RTO (Regional Transmission Organization) , 2012 .

[39]  Hui-qi Shi,et al.  Mine Green Mining , 2012 .

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