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Measuring national energy performance via Energy Trilemma Index: A Stochastic Multicriteria Acceptability Analysis

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  • Song, Lianlian
  • Fu, Yelin
  • Zhou, Peng
  • Lai, Kin Keung

Abstract

The World Energy Council annually releases the Energy Trilemma Index to measure the country-level energy performance. However, the preferences among the trilemma can change from country to country, which always is an undetermined issue and full of controversy. This paper comprehensively considers all possible preferences, and formulates interval evaluation results under certain preference. Such formulations are motivated by the observations that it is difficult to reach a consensus about the weights associated with the trilemma, since different weight elicitation methods inevitably produce different weighting schemes. Therefore, we propose an interval decision making problem and apply a Stochastic Multicriteria Acceptability Analysis to present a holistic measurements of the country-specific energy performance. This differs from the conventional wisdom that assigns exact values to corresponding weights, but explores the weight space to make each country the most preferred one. Our analysis is demonstrated by measuring the energy performance of top 10 countries based on 2015 Energy Trilemma Index.

Suggested Citation

  • Song, Lianlian & Fu, Yelin & Zhou, Peng & Lai, Kin Keung, 2017. "Measuring national energy performance via Energy Trilemma Index: A Stochastic Multicriteria Acceptability Analysis," Energy Economics, Elsevier, vol. 66(C), pages 313-319.
    • Handle: RePEc:eee:eneeco:v:66:y:2017:i:c:p:313-319
    DOI: 10.1016/j.eneco.2017.07.004
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    1. Lahdelma, Risto & Salminen, Pekka, 2006. "Classifying efficient alternatives in SMAA using cross confidence factors," European Journal of Operational Research, Elsevier, vol. 170(1), pages 228-240, April.
    2. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    3. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, vol. 60(1), pages 111-118, November.
    4. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    5. Nielsen, Lene & Jeppesen, Tim, 2003. "Tradable Green Certificates in selected European countries--overview and assessment," Energy Policy, Elsevier, vol. 31(1), pages 3-14, January.
    6. F. Hutton Barron & Bruce E. Barrett, 1996. "Decision Quality Using Ranked Attribute Weights," Management Science, INFORMS, vol. 42(11), pages 1515-1523, November.
    7. Wade D. Cook & Boaz Golany & Moshe Kress & Michal Penn & Tal Raviv, 2005. "Optimal Allocation of Proposals to Reviewers to Facilitate Effective Ranking," Management Science, INFORMS, vol. 51(4), pages 655-661, April.
    8. Angilella, Silvia & Corrente, Salvatore & Greco, Salvatore, 2015. "Stochastic multiobjective acceptability analysis for the Choquet integral preference model and the scale construction problem," European Journal of Operational Research, Elsevier, vol. 240(1), pages 172-182.
    9. Lahdelma, Risto & Salminen, Pekka, 2006. "Stochastic multicriteria acceptability analysis using the data envelopment model," European Journal of Operational Research, Elsevier, vol. 170(1), pages 241-252, April.
    10. Tommi Tervonen, 2014. "JSMAA: open source software for SMAA computations," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(1), pages 69-81.
    11. Corrente, Salvatore & Figueira, José Rui & Greco, Salvatore, 2014. "The SMAA-PROMETHEE method," European Journal of Operational Research, Elsevier, vol. 239(2), pages 514-522.
    12. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.
    13. Yang, Feng & Ang, Sheng & Xia, Qiong & Yang, Chenchen, 2012. "Ranking DMUs by using interval DEA cross efficiency matrix with acceptability analysis," European Journal of Operational Research, Elsevier, vol. 223(2), pages 483-488.
    14. Lahdelma, Risto & Salminen, Pekka, 2009. "Prospect theory and stochastic multicriteria acceptability analysis (SMAA)," Omega, Elsevier, vol. 37(5), pages 961-971, October.
    15. Tervonen, Tommi & Lahdelma, Risto, 2007. "Implementing stochastic multicriteria acceptability analysis," European Journal of Operational Research, Elsevier, vol. 178(2), pages 500-513, April.
    16. Durbach, Ian N. & Calder, Jon M., 2016. "Modelling uncertainty in stochastic multicriteria acceptability analysis," Omega, Elsevier, vol. 64(C), pages 13-23.
    17. Tanaka, Kanako, 2008. "Assessment of energy efficiency performance measures in industry and their application for policy," Energy Policy, Elsevier, vol. 36(8), pages 2877-2892, August.
    18. Lahdelma, Risto & Hokkanen, Joonas & Salminen, Pekka, 1998. "SMAA - Stochastic multiobjective acceptability analysis," European Journal of Operational Research, Elsevier, vol. 106(1), pages 137-143, April.
    19. Durbach, Ian, 2006. "A simulation-based test of stochastic multicriteria acceptability analysis using achievement functions," European Journal of Operational Research, Elsevier, vol. 170(3), pages 923-934, May.
    20. Persson, Tobias A. & Azar, Christian & Lindgren, Kristian, 2006. "Allocation of CO2 emission permits--Economic incentives for emission reductions in developing countries," Energy Policy, Elsevier, vol. 34(14), pages 1889-1899, September.
    21. Angilella, Silvia & Corrente, Salvatore & Greco, Salvatore & Słowiński, Roman, 2016. "Robust Ordinal Regression and Stochastic Multiobjective Acceptability Analysis in multiple criteria hierarchy process for the Choquet integral preference model," Omega, Elsevier, vol. 63(C), pages 154-169.
    22. Lahdelma, Risto & Makkonen, Simo & Salminen, Pekka, 2009. "Two ways to handle dependent uncertainties in multi-criteria decision problems," Omega, Elsevier, vol. 37(1), pages 79-92, February.
    23. Tigran Melkonyan & Zvi Safra, 2016. "Intrinsic Variability in Group and Individual Decision Making," Management Science, INFORMS, vol. 62(9), pages 2651-2667, September.
    24. Lahdelma, Risto & Miettinen, Kaisa & Salminen, Pekka, 2003. "Ordinal criteria in stochastic multicriteria acceptability analysis (SMAA)," European Journal of Operational Research, Elsevier, vol. 147(1), pages 117-127, May.
    25. Luzzati, T. & Gucciardi, G., 2015. "A non-simplistic approach to composite indicators and rankings: an illustration by comparing the sustainability of the EU Countries," Ecological Economics, Elsevier, vol. 113(C), pages 25-38.
    26. Zhou, Peng & Poh, Kim Leng & Ang, Beng Wah, 2007. "A non-radial DEA approach to measuring environmental performance," European Journal of Operational Research, Elsevier, vol. 178(1), pages 1-9, April.
    27. Wang, Huilong & Xu, Peng & Lu, Xing & Yuan, Dengkuo, 2016. "Methodology of comprehensive building energy performance diagnosis for large commercial buildings at multiple levels," Applied Energy, Elsevier, vol. 169(C), pages 14-27.
    28. Risto Lahdelma & Pekka Salminen, 2001. "SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making," Operations Research, INFORMS, vol. 49(3), pages 444-454, June.
    29. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    30. Lahdelma, Risto & Makkonen, Simo & Salminen, Pekka, 2006. "Multivariate Gaussian criteria in SMAA," European Journal of Operational Research, Elsevier, vol. 170(3), pages 957-970, May.
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    More about this item

    Keywords

    Energy performance; Stochastic Multicriteria Acceptability Analysis; Rank;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • F5 - International Economics - - International Relations, National Security, and International Political Economy
    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics
    • O5 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies
    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • P4 - Political Economy and Comparative Economic Systems - - Other Economic Systems

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