Natural Hazards

, Volume 84, Supplement 1, pp 243–265 | Cite as

Regional operational and environmental performance evaluation in China: non-radial DEA methodology under natural and managerial disposability

  • Malin Song
  • Guijun Zhang
  • Kuangnan Fang
  • Jing Zhang
Original Paper


In this article, we used a non-radial DEA under natural and managerial disposability to measure the unified efficiency of 30 administrative regions in China and then evaluated their operational and environmental performances. We proposed the performance progress unified index (PPUI) based on the non-radial DEA methodology in a time horizon under natural and managerial disposability with a crossover to measure the performance variety of DMUs. The results of the unified efficiency measured under natural and managerial disposability showed that both operational and environmental performance in eastern China were the highest among the three regions during 2000–2011. The PPUIs under natural and managerial disposability indicated that the operational and environmental performance of the three regions improved during 2000–2011, and the rate of operational and environmental performance of eastern China was higher than the other two regions.


Natural disposability Managerial disposability Non-radial DEA Unified efficiency PPUI 



We thank the editor and reviewers for careful review and insightful comments. This study has partly been supported by National Natural Science Foundation of China (71201139, 71303200), National Bureau of Statistics Funds (2011LD002) of China, and MOE (Ministry of Education in China) Project of Humanities and Social Sciences (12YJC790263).


  1. Bian Y, Yang F (2010) Resource and environmental efficiency analysis of provinces in China: a DEA approach based on Shannon’s entropy. J Energy Policy 38:1909–1917CrossRefGoogle Scholar
  2. Caves DW, Christensen LR, Diewert WE (1982) The economic theory of index numbers and the measurement of input, output, and productivity. J Econom 50:1393–1414Google Scholar
  3. Färe R, Grosskopf S (2000) Slacks and congestion: a comment. J Soc Econ Plann Sci 34:27–33CrossRefGoogle Scholar
  4. Gregory MN (2003) Principles of Macroeconomics, 5th edn. New YorkGoogle Scholar
  5. Hu JL, Wang SC (2006) Total-factor energy efficiency of regions in China. J Energy Policy 34:3206–3217CrossRefGoogle Scholar
  6. Li H, Fang KN, Yang W, Wang D, Hong XX (2013) Regional environmental efficiency evaluation in China: analysis based on the Super-SBM model with undesirable outputs. J Math Comput Model 58:1018–1031CrossRefGoogle Scholar
  7. Mandal SK (2010) Do undesirable output and environmental regulation matter in energy efficiency analysis? Evidence from Indian cement industry. J Energy Policy 38:6076–6083CrossRefGoogle Scholar
  8. Porter ME, Linde C (1995) Toward a new conception of the environment competitiveness relationship. J Econ Perspect 9:97–118CrossRefGoogle Scholar
  9. Rasche RH, Tatom JA (1977) Energy resources and potential GNP. J Rev Fed Reserve Bank St Louis 6:10–24Google Scholar
  10. Shi GM, Bi J, Wang JN (2010) Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs. J Energy Policy 38:6172–6179CrossRefGoogle Scholar
  11. Sueyoshi T, Goto M (2010) Measurement of a linkage among environmental, operational, and financial performance in Japanese manufacturing firms: a use of Data Envelopment Analysis with strong complementary slackness condition. Eur J Oper Res 207:1742–1753CrossRefGoogle Scholar
  12. Sueyoshi T, Goto M (2011) Measurement of Returns to Scale and Damages to Scale for operational and environmental assessment: how to manage desirable (good) DEA-based and undesirable (bad) outputs. Eur J Oper Res 211:76–89CrossRefGoogle Scholar
  13. Sueyoshi T, Goto M (2012a) Weak and strong disposability vs. natural and managerial disposability in DEA environmental assessment: comparison between Japanese electric power industry and manufacturing industries. J Energy Econ 34:686–699CrossRefGoogle Scholar
  14. Sueyoshi T, Goto M (2012b) DEA environmental assessment of coal fired power plants: methodological comparison between radial and non-radial models. J Energy Econ 34:1854–1863CrossRefGoogle Scholar
  15. Sueyoshi T, Goto M (2012c) Returns to scale, damages to scale, marginal rate of transformation and rate of substitution in DEA environmental assessment. J Energy Econ 34:905–917CrossRefGoogle Scholar
  16. Sueyoshi T, Goto M (2012d) DEA radial and non-radial models for unified efficiency under natural and managerial disposability: theoretical extension by strong complementary slackness conditions. J Energy Econ 34:700–713CrossRefGoogle Scholar
  17. Sueyoshi T, Goto M (2012e) Returns to scale and damages to scale on US fossil fuel power plants: radial and non-radial approaches for DEA environmental assessment. J Energy Econ 34:2240–2259CrossRefGoogle Scholar
  18. Sueyoshi T, Goto M (2012f) Returns to scale and damages to scale under natural and managerial disposability: strategy, efficiency, and competitiveness of petroleum firms. J Energy Econ 34:645–662CrossRefGoogle Scholar
  19. Sueyoshi T, Goto M (2013a) A comparative study among fossil fuel power plants in PJM and California ISO by DEA environmental assessment. J Energy Econ 40:130–145CrossRefGoogle Scholar
  20. Sueyoshi T, Goto M (2013b) DEA environmental assessment in a time horizon: Mamquist index on fuel mix, electricity and CO2 of industrial nations. J Energy Econ 40:370–382CrossRefGoogle Scholar
  21. Sueyoshi T, Goto M (2013c) Returns to scale vs. damages to scale in data envelopment analysis: an impact of US clean air act on coal-fired power plants. J Omega 2(41):164–175CrossRefGoogle Scholar
  22. Wang K, Yu SW, Zhang W (2013a) China’s regional energy and environmental efficiency: a DEA window analysis based dynamic evaluation. Math Comput Model 58:1117–1127CrossRefGoogle Scholar
  23. Wang K, Wei YM, Zhang X (2013b) Energy and emissions efficiency patterns of Chinese regions: a multi-directional efficiency analysis. J Appl Energy 104:105–116CrossRefGoogle Scholar
  24. Zhang J, Wu GY, Zhang JP (2004) The estimation of China’s provincial capital stock: 1952–2000. J Econ Res 10:35–44Google Scholar
  25. Zhou P, Ang BW (2008) Linear programming models for measuring economy- wide energy efficiency performance. J Energy Policy 38:2911–2916CrossRefGoogle Scholar
  26. Zhou P, Ang BW, Poh KL (2008) A survey of data envelopment analysis in energy and environmental studies. Eur J Oper Res 189:1–18CrossRefGoogle Scholar
  27. Zou GF, Chen LM, Liu W, Hong XX, Zhang GJ, Zhang ZY (2013) Measurement and evaluation of Chinese regional energy efficiency based on provincial panel data. Math Comput Model 58:1000–1009CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Malin Song
    • 1
  • Guijun Zhang
    • 2
  • Kuangnan Fang
    • 3
    • 4
  • Jing Zhang
    • 3
  1. 1.School of Statistics and Applied MathematicsAnhui University of Finance and EconomicsBengbuChina
  2. 2.School of Statistics, Research Center of Applied StatisticsJiangxi University of Finance and EconomicsNanchangChina
  3. 3.School of EconomicsXiamen UniversityXiamenChina
  4. 4.Collaborative Innovation Center for Peaceful Development of Cross-Strait RelationsXiamen UniversityXiamenChina

Personalised recommendations