Skip to main content
SpringerLink
Log in

Total-Factor Energy Efficiency and Its Extensions: Introduction, Computation and Application

  • Chapter
  • First Online:
Data Envelopment Analysis

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 238))

Abstract

This chapter demonstrates how to use different types of DEA models to compute the total-factor energy efficiency (TFEE) scores, including CCR, Russell, QFI, SBM, DF, and DDF models. The TFEE is a disaggregate input efficiency index. Moreover, the TFEE framework which uses cross-section data can be extended to the total-factor energy productivity (TFEP) growth index by following Malmquist, Leunberger, and Malmquist-Leunberger models which use panel data. Finally, the regional data of Chinese regions during 2010–2011 with inputs and desirable as well as undesirable outputs are used for illustrating the computation of TFEE and TFEP scores.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Zhou et al. (2010) construct a total-factor carbon emission performance measurement of which the concept is similar to our total-factor undesirable output efficiency.

  2. 2.

    Zhou et al. (2008) present a clear structure of DEA models. According to their survey, a DEA model can be characterized by its reference technology and efficiency measure.

  3. 3.

    Most of energy efficiency studies using country-level data only take total energy consumption as energy input. However, several literatures use disaggregated energy inputs to analyze region- or sector-level data. For example, Honma and Hu (2008) investigate total-factor energy efficiency of 11 energy inputs of regions in Japan. For simplicity, we choose total energy consumption as only one energy input to illustrate energy-related DEA models. One can straightforward extend these models with multiple energy inputs indeed.

  4. 4.

    CCR and BCC models can be represented in multiplier form or envelopment form. Coelli et al. (2005) suggest that the envelopment form involves fewer constraints than the multiplier form. Therefore, envelopment form is generally preferred to solve the linear programming problem and used in our study instead of multiplier form.

  5. 5.

    Other well-known extended DEA models with similar characteristics are the Zieschang measure and the asymmetric Färe measure (see De Borger and Kerstens 1996).

  6. 6.

    Due to the flexibility of directional distance function, Boussemart et al. (2003) suggest that the Luenberger productivity index is more appropriate than the Malmquist productivity index.

  7. 7.

    The Chinese provincial data in 2011 is available on request to author.

References

  • Ali AI, Seiford LM (1993) The mathematical programming approach to efficiency analysis. In: Fried HO, Lovell CAK, Schmidt SS (eds) The measurement of productive efficiency: techniques and applications. Oxford University Press, New York, pp 120–159

    Google Scholar 

  • Banaeian N, Zangeneh M (2011) Study on energy efficiency in corn production of Iran. Energy 36:5394–5402

    Article  Google Scholar 

  • Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage Sci 30:1078–1092

    Article  Google Scholar 

  • Bian Y, Yang F (2010) Resource and environment efficiency analysis of provinces in China: a DEA approach based on Shannon’s entropy. Energ Policy 38:1909–1917

    Article  Google Scholar 

  • Blomberg J, Henriksson E, Lundmark R (2012) Energy efficiency and policy in Swedish pulp and paper mills: a data envelopment analysis approach. Energ Policy 42:569–579

    Article  Google Scholar 

  • Boussemart JP, Briec W, Kerstens K, Poutineau JC (2003) Luenberger and Malmquist productivity indices: theoretical comparisons and empirical illustration. Bull Econ Res 55:391–405

    Article  Google Scholar 

  • Chang TP, Hu JL (2010) Total-factor energy productivity growth, technical progress, and efficiency change: an empirical study of China. Appl Energy 87:3262–3270

    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 

  • Chambers RG, Färe R, Grosskopf S (1996) Productivity growth in APEC countries. Pac Econ Rev 1:181–190

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Charnes A, Cooper WW, Golany B, Seiford LM, Stutz J (1985) Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. J Econometrics 30:91–107

    Article  Google Scholar 

  • Choi Y, Zhang N, Zhou P (2012) Efficiency and abatement costs of energy-related CO2 emissions in China: a slacks-based efficiency measure. Appl Energy 98:198–208

    Article  Google Scholar 

  • Chung YH, Färe R, Grosskopf S (1997) Productivity and undesirable outputs: a directional distance function approach. J Environ Manage 51:229–240

    Article  Google Scholar 

  • Coelli TJ (1998) A multi-stage methodology for the solution of oriented DEA models. Oper Res Lett 23:143–149

    Article  Google Scholar 

  • Coelli TJ, Rao DSP, O’Donnell CJ, Battese GE (2005) An introduction to efficiency and productivity analysis, 2nd edn. Springer, New York

    Google Scholar 

  • Cooper WW, Seiford LM, Zhu J (2011) Data envelopment analysis: history, models, and interpretations. In: Cooper WW, Seiford LM, Zhu J (eds) Handbook on data envelopment analysis, 2nd edn. Springer, New York, pp 1–39

    Chapter  Google Scholar 

  • De Borger B, Kerstens K (1996) Radial and nonradial measures of technical efficiency: an empirical illustration for Belgian local government. J Product Anal 7:41–62

    Article  Google Scholar 

  • Fallahi A, Ebrahimi R, Ghaderi SF (2011) Measuring efficiency and productivity change in power electric generation management companies by using data envelopment analysis: a case study. Energy 36:6398–6405

    Article  Google Scholar 

  • Färe R, Grosskopf S (2004) Modeling undesirable factors in efficiency evaluation: comment. Eur J Oper Res 157:242–245

    Article  Google Scholar 

  • Färe R, Grosskopf S (2010) Directional distance functions and slacks-based measures of efficiency. Eur J Oper Res 200:320–322

    Article  Google Scholar 

  • Färe R, Grosskopf S, Hernandez-Sancho F (2004) Environmental performance: an index number approach. Resour Energy Econ 26:343–352

    Article  Google Scholar 

  • Färe R, Grosskopf S, Lindgren B, Roos P (1994a) Productivity developments in Swedish hospitals: a malmquist output index approach. In: Charnes A, Cooper WW, Lewin A, Seiford LM (eds) Data envelopment analysis: theory, methodology and applications. Kluwer Academic, Boston, pp 253–272

    Google Scholar 

  • Färe R, Grosskopf S, Lovell CAK (1994b) Production frontier. Cambridge University Press, Cambridge

    Google Scholar 

  • Färe R, Grosskopf S, Lovell CAK, Pasurka C (1989) Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. Rev Econ Statist 71:90–98

    Article  Google Scholar 

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

    Google Scholar 

  • Färe R, Grosskopf S, Tyteca D (1996) An activity analysis model of the environmental performance of firms—application to fossil-fuel-fired electric utilities. Ecol Econ 18:161–175

    Article  Google Scholar 

  • Färe R, Lovell CAK (1978) Measuring the technical efficiency of production. J Econ Theory 19:150–162

    Article  Google Scholar 

  • Farrell MJ (1957) The measurement of productive efficiency. J R Statist Soc Ser A 120:253–290

    Article  Google Scholar 

  • Guo XD, Zhu L, Fan Y, Xie BC (2011) Evaluation of potential reductions in carbon emissions in Chinese provinces based on environmental DEA. Energ Policy 39:2352–2360

    Article  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 

  • Hernández-Sancho F, Molinos-Senante M, Sala-Garrido R (2011) Energy efficiency in Spanish wastewater treatment plants: a non-radial DEA approach. Sci Total Environ 409:2693–2699

    Article  Google Scholar 

  • Honma S, Hu JL (2008) Total-factor energy efficiency of regions in Japan. Energ Policy 36:821–833

    Article  Google Scholar 

  • Honma S, Hu JL (2009) Total-factor energy productivity growth of regions in Japan. Energ Policy 37:3941–3950

    Article  Google Scholar 

  • Hu JL, Kao CH (2007) Efficient energy-saving targets for APEC economies. Energ Policy 35:373–382

    Article  Google Scholar 

  • Hu JL, Wang SC (2006) Total-factor energy efficiency of regions in China. Energ Policy 34:3206–3217

    Article  Google Scholar 

  • Hu JL, Wang SC, Yeh FY (2006) Total-factor water efficiency of regions in China. Res Policy 31:217–230

    Article  Google Scholar 

  • Iribarren D, Martín-Gamboa M, Dufour J (2013) Environmental benchmarking of wind farms according to their operational performance. Energy 61:589–597

    Article  Google Scholar 

  • Khoshroo A, Mulwa R, Emrouznejad A, Arabi B (2013) A non-parametric data envelopment analysis approach for improving energy efficiency of grape production. Energy 63:189–194

    Article  Google Scholar 

  • Li LB, Hu JL (2012) Ecological total-factor energy efficiency of regions in China. Energ Policy 46:216–224

    Article  Google Scholar 

  • Liu CH, Lin SJ, Lewis C (2010) Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis. Energ Policy 38:1049–1058

    Article  Google Scholar 

  • Mandal SK, Madheswaran S (2010) Environmental efficiency of the Indian cement industry: an interstate analysis. Energ Policy 38:1108–1118

    Article  Google Scholar 

  • Mousavi-Avval SH, Rafiee S, Mohammadi A (2011) Optimization of energy consumption and input costs for apple production in Iran using data envelopment analysis. Energy 36:909–916

    Article  Google Scholar 

  • Mukherjee K (2008a) Energy use efficiency in the Indian manufacturing sector: an interstate analysis. Energ Policy 36:662–672

    Article  Google Scholar 

  • Mukherjee K (2008b) Energy use efficiency in U.S. manufacturing: a nonparametric analysis. Energy Econ 30:76–96

    Article  Google Scholar 

  • Ouellette P, Vierstraete V (2004) Technological change and efficiency in the presence of quasi-fixed inputs: a DEA application to the hospital sector. Eur J Oper Res 154:755–763

    Article  Google Scholar 

  • Pastor JT, Ruiz JL, Sirvent I (1999) An enhanced DEA Russell graph efficiency measure. Eur J Oper Res 115:596–607

    Article  Google Scholar 

  • Seiford LM, Zhu J (2002) Modeling undesirable factors in efficiency evaluation. Eur J Oper Res 142:16–20

    Article  Google Scholar 

  • Shi G-M, Bi J, Wang J-N (2010) Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs. Energ Policy 38:6172–6179

    Article  Google Scholar 

  • Song ML, Zhang LL, Liu W, Fisher R (2013) Bootstrap-DEA analysis of BRICS’ energy efficiency based on small sample data. Appl Energy 112:1049–1055

    Article  Google Scholar 

  • Sueyoshi T, Goto M (2011) DEA approach for unified efficiency measurement: assessment of Japanese fossil fuel power generation. Energy Econ 33:292–303

    Article  Google Scholar 

  • Sueyoshi T, Goto M (2012) Environmental assessment by DEA radial measurement: U.S. coal-fired power plants in ISO (Independent System Operator) and RTO (Regional Transmission Organization). Energy Econ 34:663–676

    Article  Google Scholar 

  • Sueyoshi T, Goto M (2013) DEA environmental assessment in a time horizon: malmquist index on fuel mix, electricity and CO2 of industrial nations. Energy Econ 40:370–382

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Tone K (2011) Slacks-based measure of efficiency. In: Cooper WW, Seiford LM, Zhu J (eds) Handbook on data envelopment analysis, 2nd edn. Springer, New York, pp 195–209

    Chapter  Google Scholar 

  • Wang H, Zhou P, Zhou DQ (2013) Scenario-based energy efficiency and productivity in China: a non-radial directional distance function analysis. Energy Econ 40:795–803

    Article  Google Scholar 

  • Wei C, Ni J, Shen M (2009) Empirical analysis of provincial energy efficiency in China. China World Econ 17:88–103

    Article  Google Scholar 

  • Wu F, Fan LW, Zhou P, Zhou DQ (2012) Industrial energy efficiency with CO2 emissions in China: a nonparametric analysis. Energ Policy 49:164–172

    Article  Google Scholar 

  • Zhang N, Zhou P, Choi Y (2013) Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: a meta-frontier non-radial directional distance function analysis. Energ Policy 56:653–662

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Zhou P, Ang BW (2008) Linear programming models for measuring economy-wide energy efficiency performance. Energ Policy 36:2911–2916

    Article  Google Scholar 

  • Zhou P, Ang BW, Han JY (2010) Total factor carbon emission performance: a Malmquist index analysis. Energy Econ 32:194–201

    Article  Google Scholar 

  • Zhou P, Ang BW, Poh KL (2006) Slacks-based efficiency measures for modeling environmental performance. Ecol Econ 60:111–118

    Article  Google Scholar 

  • Zhou P, Ang BW, Poh KL (2008) A survey of data envelopment analysis in energy and environmental studies. Eur J Oper Res 189:1–18

    Article  Google Scholar 

  • Zhou P, Ang BW, Wang H (2012) Energy and CO2 emission performance in electricity generation: a non-radial directional distance function approach. Eur J Oper Res 221:625–635

    Article  Google Scholar 

  • Zhou Y, Xing X, Fang K, Liang D, Xu C (2013) Environmental efficiency analysis of power industry in China based on an entropy SBM model. Energ Policy 57:68–75

    Article  Google Scholar 

  • Zhu J (1996) Data envelopment analysis with preference structure. J Oper Res Soc 47:136–150

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Business and Management, National Chiao Tung University, Hsinchu, Taiwan

    Jin-Li Hu

  2. Department of Finance, National Yunlin University of Science and Technology, Yunlin, Taiwan

    Tzu-Pu Chang

Authors
  1. Jin-Li Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tzu-Pu Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jin-Li Hu .

Editor information

Editors and Affiliations

  1. School of Business, Worcester Polytechnic Institute, Worcester, Massachusetts, USA

    Joe Zhu

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media New York

About this chapter

Cite this chapter

Hu, JL., Chang, TP. (2016). Total-Factor Energy Efficiency and Its Extensions: Introduction, Computation and Application. In: Zhu, J. (eds) Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 238. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7684-0_3

Download citation

Publish with us

Policies and ethics

Search

Navigation