Skip to main content
SpringerLink
Log in

Industrial environmental efficiency assessment for China’s western regions by using a SBM-based DEA

  • Short Research and Discussion Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

This study employed a data envelopment analysis (DEA) by using slacks-based measure (SBM) with undesirable outputs to assess the industrial environmental efficiency of western China during the period of 2001–2015. The Malmquist index was further used to examine the changes in the industrial environmental efficiency of the analyzed region. The result showed that western China presented a low industrial environmental efficiency throughout the period of 2001–2015. Chongqing City was the only province that exhibited strong economic and environmental coordination. The level of technical development was identified as a key determinant of industrial environmental efficiency. This study provided policy implications on emissions reduction and the improvement of industrial efficiency. Limitations of the approach were provided to lay foundation for future studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Apergis N, Aye GC, Barros CP, Gupta R, Wanke P (2015) Energy efficiency of selected OECD countries: a slacks based model with undesirable outputs. Energy Econ 51:45–53

    Article  Google Scholar 

  • Cecchini L, Venanzi S, Pierri A, Chiorri M (2018) Environmental efficiency analysis and estimation of CO2 abatement costs in dairy cattle farms in Umbria (Italy): A SBM-DEA model with undesirable output. J Clean Prod 197:895–907

    Article  Google Scholar 

  • Chang YT, Zhang N, Danao D, Zhang N (2013) Environmental efficiency analysis of transportation system in China: a non-radial DEA approach. Energ Policy 58:277–283

    Article  Google Scholar 

  • Charnes A, Cooper WW (1978) Rhodes E. Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444

    Article  Google Scholar 

  • Chen L, Jia G (2017) Environmental efficiency analysis of China’s regional industry: a data envelopment analysis (DEA) based approach. J Clean Prod 142:846–853

    Article  Google Scholar 

  • Chen J, Song M, Xu L (2015) Evaluation of environmental efficiency in China using data envelopment analysis. Ecol Indic 52:577–583

    Article  Google Scholar 

  • Cook WD, Seiford LM (2009) Data envelopment analysis (DEA)–Thirty years on. Eur J Oper Res 192(1):1–17

    Article  Google Scholar 

  • Färe R, Grosskopf S, Norris M et al (1994) Productivity growth, technical progress, and efficiency change in industrialized countries. Am Econ Rev 84(3):66–83

    Google Scholar 

  • He F, Zhang Q, Lei J, Fu W, Xu X (2013) Energy efficiency and productivity change of China’s iron and steel industry: accounting for undesirable outputs. Energ Policy 54:204–213

    Article  Google Scholar 

  • He Q, Han J, Guan D, Mi Z, Zhao H, Zhang Q (2018) The comprehensive environmental efficiency of socioeconomic sectors in China: an analysis based on a non-separable bad output SBM. J Clean Prod 176:1091–1110

    Article  Google Scholar 

  • Hong L, Shi JF (2014) Energy efficiency analysis on Chinese industrial sectors: an improved Super-SBM model with undesirable outputs. J Clean Prod 65(4):97–107

  • Iftikhar Y, Wang Z, Zhang B, Wang B (2018) Energy and CO2 emissions efficiency of major economies: a network DEA approach. Energy 147:197–207

    Article  Google Scholar 

  • Kang YQ, Xie BC, Wang J, Wang YN (2018) Environmental assessment and investment strategy for China’s manufacturing industry: a non-radial DEA based analysis. J Clean Prod 175:501–511

    Article  Google Scholar 

  • Laner D, Feketitsch J, Rechberger H, Fellner J (2016) A novel approach to characterize data uncertainty in material flow analysis and its application to plastics flows in Austria. J Ind Ecol 20(5):1050–1063

    Article  Google Scholar 

  • Li H, Shi J (2014) Energy efficiency analysis on Chinese industrial sectors: an improved Super-SBM model with undesirable outputs. J Clean Prod 65:97–107

    Article  Google Scholar 

  • Li H, Fang K, Yang W, Wang D, Hong X (2013) Regional environmental efficiency evaluation in China: analysis based on the Super-SBM model with undesirable outputs. Math Comput Model 58(5-6):1018–1031

    Article  Google Scholar 

  • Li H, Zhang J, Wang C, Wang Y, Coffey V (2018) An evaluation of the impact of environmental regulation on the efficiency of technology innovation using the combined DEA model: a case study of Xi’an, China. Sustain Cities Soc 42:355–369

    Article  Google Scholar 

  • Lin B, Wang X (2014) Exploring energy efficiency in China’s iron and steel industry: a stochastic frontier approach. Energ Policy 72:87–96

    Article  Google Scholar 

  • Lu C, Zhang X, He J (2010) A CGE analysis to study the impacts of energy investment on economic growth and carbon dioxide emission: a case of Shaanxi Province in western China. Energy 35(11):4319–4327

    Article  Google Scholar 

  • Lu CC, Chiu YH, Shyu MK, Lee JH (2013) Measuring CO2 emission efficiency in OECD countries: application of the hybrid efficiency model. Econ Model 32:130–135

    Article  Google Scholar 

  • Lyu K, Bian Y, Yu A (2018) Environmental efficiency evaluation of industrial sector in China by incorporating learning effects. J Clean Prod 172:2464–2474

    Article  Google Scholar 

  • Mardani A, Zavadskas EK, Streimikiene D, Jusoh A, Khoshnoudi M (2017) A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency. Renew Sust Energ Rev 70:1298–1322

    Article  Google Scholar 

  • Oh D (2010) A global Malmquist-Luenberger productivity index. J Prod Anal 34(3):183–197

    Article  Google Scholar 

  • Park YS, Lim SH, Egilmez G, Szmerekovsky J (2018) Environmental efficiency assessment of US transport sector: a slack-based data envelopment analysis approach. Transp Res Part D-Transp Environ 61:152–164

    Article  Google Scholar 

  • Piao SR, Li J, Ting CJ (2019) Assessing regional environmental efficiency in China with distinguishing weak and strong disposability of undesirable outputs. J Clean Prod 227:748–759

    Article  Google Scholar 

  • Rödder W, Reucher E (2012) Advanced X-efficiencies for CCR-and BCC-models–towards peer-based DEA controlling. Eur J Oper Res 219(2):467–476

    Article  Google Scholar 

  • Shermeh HE, Najafi SE, Alavidoost MH (2016) A novel fuzzy network SBM model for data envelopment analysis: a case study in Iran regional power companies. Energy 112:686–697

    Article  Google Scholar 

  • Shui H, Jin X, Ni J (2015) Manufacturing productivity and energy efficiency: a stochastic efficiency frontier analysis. Int J Energy Res 39(12):1649–1663

    Google Scholar 

  • Song M, Wang J (2018) Environmental efficiency evaluation of thermal power generation in China based on a slack-based endogenous directional distance function model. Energy 161:325–336

    Article  Google Scholar 

  • Song M, Zhang L, An Q, Wang Z, Li Z (2013) Statistical analysis and combination forecasting of environmental efficiency and its influential factors since China entered the WTO: 2002–2010–2012. J Clean Prod 42:42–51

    Article  Google Scholar 

  • Tone K (2001) A slacks-based measure of efficiency in data envelopment analysis. Eur J Oper Res 130(3):498–509

    Article  Google Scholar 

  • Vaninsky A (2018) Energy-environmental efficiency and optimal restructuring of the global economy. Energy 153:338–348

    Article  Google Scholar 

  • Wang Z, Feng C (2015) A performance evaluation of the energy, environmental, and economic efficiency and productivity in China: an application of global data envelopment analysis. Appl Energy 147:617–626

    Article  Google Scholar 

  • Wang F, Zhang B (2016) Distributional incidence of green electricity price subsidies in China. Energ Policy 88:27–38

    Article  Google Scholar 

  • Wang W, Jiang D, Chen D, Chen Z, Zhou W, Zhu B (2016) A material flow analysis (MFA)-based potential analysis of eco-efficiency indicators of China’s cement and cement-based materials industry. J Clean Prod 112:787–796

    Article  CAS  Google Scholar 

  • Wang X, Zhang M, Nathwani J, Yang F (2019) Measuring environmental efficiency through the lens of technology heterogeneity: a comparative study between China and the G20. Sustainability 11(2):461

    Article  Google Scholar 

  • Woo C, Chung Y, Chun D, Seo H, Hong S (2015) The static and dynamic environmental efficiency of renewable energy: a Malmquist index analysis of OECD countries. Renew Sust Energ Rev 47:367–376

    Article  Google Scholar 

  • Wu J, An Q, Yao X, Wang B (2014) Environmental efficiency evaluation of industry in China based on a new fixed sum undesirable output data envelopment analysis. J Clean Prod 74:96–104

    Article  Google Scholar 

  • Yang L, Yang Y (2019) Evaluation of eco-efficiency in China from 1978 to 2016: based on a modified ecological footprint model. Sci Total Environ 662:581–590

    Article  CAS  Google Scholar 

  • Yang L, Zhang X (2018) Assessing regional eco-efficiency from the perspective of resource, environmental and economic performance in China: a bootstrapping approach in global data envelopment analysis. J Clean Prod 173:100–111

    Article  Google Scholar 

  • Yang T, Chen W, Zhou K, Ren M (2018) Regional energy efficiency evaluation in China: a super efficiency slack-based measure model with undesirable outputs. J Clean Prod 198:859–866

    Article  Google Scholar 

  • Yao X, Feng W, Zhang X, Wang W, Zhang C, You S (2018) Measurement and decomposition of industrial green total factor water efficiency in China. J Clean Prod 198:1144–1156

    Article  Google Scholar 

  • Zhang T (2009) Frame work of data envelopment analysis—a model to evaluate the environmental efficiency of China's industrial sectors. Biomed Environ Sci 22(1):8–13

    Article  Google Scholar 

  • Zhang B, Bi J, Fan Z, Yuan Z, Ge J (2008) Eco-efficiency analysis of industrial system in China: a data envelopment analysis approach. Ecol Econ 68(1-2):306–316

    Article  Google Scholar 

  • Zhang XP, Cheng XM, Yuan JH, Gao XJ (2011) Total-factor energy efficiency in developing countries. Energ Policy 39(2):644–650

    Article  Google Scholar 

  • Zhang J, Zeng W, Shi H (2016) Regional environmental efficiency in China: analysis based on a regional slack-based measure with environmental undesirable outputs. Ecol Indic 71:218–228

    Article  Google Scholar 

  • Zhang J, Zeng W, Wang J, Yang F, Jiang H (2017) Regional low-carbon economy efficiency in China: analysis based on the Super-SBM model with CO2 emissions. J Clean Prod 163:202–211

    Article  CAS  Google Scholar 

  • Zhang C, Zhou B, Wang Q (2019) Effect of China’s western development strategy on carbon intensity. J Clean Prod 215:1170–1179

    Article  Google Scholar 

  • Zhao X, Zhang S, Fan C (2014) Environmental externality and inequality in China: current status and future choices. Environ Pollut 190:176–179

    Article  CAS  Google Scholar 

  • Zhao R, Zhou X, Han J, Liu C (2016) For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation. Technol Forecast Soc Change 112:262–274

    Article  Google Scholar 

  • Zhao R, Min N, Geng Y, He Y (2017) Allocation of carbon emissions among industries/sectors: an emissions intensity reduction constrained approach. J Clean Prod 142:3083–3094

    Article  CAS  Google Scholar 

  • Zhao R, Geng Y, Liu Y, Tao X, Xue B (2018) Consumers’ perception, purchase intention, and willingness to pay for carbon-labeled products: a case study of Chengdu in China. J Clean Prod 171:1664–1671

    Article  Google Scholar 

  • Zhou P, Ang BW, Poh KL (2008) Measuring environmental performance under different environmental DEA technologies. Energy Econ 30(1):1–14

    Article  CAS  Google Scholar 

  • Zhou Y, Liang D, Xing X (2013) Environmental efficiency of industrial sectors in China: an improved weighted SBM model. Math Comput Model 58(5-6):990–999

    Article  Google Scholar 

  • Zhu J (2004) Imprecise DEA via standard linear DEA models with a revisit to a Korean mobile telecommunication company. Oper Res 52(2):323–329

    Article  Google Scholar 

Download references

Funding

This study is sponsored by National Natural Science Foundation of China (No.41571520), Sichuan Provincial Key Technology Support (No. 2019JDJQ0020), Sichuan Province Circular Economy Research Center Fund (No. XHJJ-1802), and Guangxi Key Laboratory of Spatial Information and Geomatics (No. 17-259-16-11).

Author information

Authors and Affiliations

  1. Sichuan Province Cyclic Economy Research Centre, Southwest University of Science and Technology, Mianyang, 621010, China

    Si-Dai Guo & Hang Li

  2. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China

    Rui Zhao

  3. School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China

    Xiao Zhou

Authors
  1. Si-Dai Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rui Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiao Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rui Zhao.

Additional information

Responsible editor: Marcus Schulz

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guo, SD., Li, H., Zhao, R. et al. Industrial environmental efficiency assessment for China’s western regions by using a SBM-based DEA. Environ Sci Pollut Res 26, 27542–27550 (2019). https://doi.org/10.1007/s11356-019-06062-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-019-06062-5

Keywords

Search

Navigation