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Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China

Author

Listed:
  • Ya Chen

    (University of Science and Technology of China)

  • Wade D. Cook

    (York University)

  • Juan Du

    (Tongji University)

  • Hanhui Hu

    (Southeast University)

  • Joe Zhu

    (Nanjing Audit University
    Worcester Polytechnic Institute)

Abstract

In data envelopment analysis (DEA), it is usually assumed that all data are continuous and not restricted by upper and/or lower bounds. However, there are situations where data are discrete and/or bounded, and where projections arising from DEA models are required to fall within those bounds. Such situations can be found, for example, in cases where percentage data are present and where projected percentages must not exceed the requisite 100 % limit. Other examples include Likert scale data. Using existing integer DEA approaches as a backdrop, the current paper presents models for dealing with bounded and discrete data. Our proposed models address the issue of constraining DEA projections to fall within imposed bounds. It is shown that Likert scale data can be modeled using the proposed approach. The proposed DEA models are used to evaluate the energy efficiency of 29 provinces in China.

Suggested Citation

  • Ya Chen & Wade D. Cook & Juan Du & Hanhui Hu & Joe Zhu, 2017. "Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China," Annals of Operations Research, Springer, vol. 255(1), pages 347-366, August.
    • Handle: RePEc:spr:annopr:v:255:y:2017:i:1:d:10.1007_s10479-015-1827-3
    DOI: 10.1007/s10479-015-1827-3
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    as
    1. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    2. Chang, Tzu-Pu & Hu, Jin-Li, 2010. "Total-factor energy productivity growth, technical progress, and efficiency change: An empirical study of China," Applied Energy, Elsevier, vol. 87(10), pages 3262-3270, October.
    3. Wang, Ke & Lu, Bin & Wei, Yi-Ming, 2013. "China’s regional energy and environmental efficiency: A Range-Adjusted Measure based analysis," Applied Energy, Elsevier, vol. 112(C), pages 1403-1415.
    4. Joe Zhu, 2014. "Quantitative Models for Performance Evaluation and Benchmarking," International Series in Operations Research and Management Science, Springer, edition 3, number 978-3-319-06647-9, December.
    5. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    6. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    7. Kuosmanen, Timo & Matin, Reza Kazemi, 2009. "Theory of integer-valued data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 192(2), pages 658-667, January.
    8. Timo Kuosmanen & Abolfazl Keshvari & Reza Kazemi Matin, 2015. "Discrete and Integer Valued Inputs and Outputs in Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 4, pages 67-103, Springer.
    9. Bi, Gong-Bing & Song, Wen & Zhou, P. & Liang, Liang, 2014. "Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model," Energy Policy, Elsevier, vol. 66(C), pages 537-546.
    10. Cook, Wade D. & Zhu, Joe, 2006. "Rank order data in DEA: A general framework," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1021-1038, October.
    11. Jin-Li Hu & Tzu-Pu Chang, 2016. "Total-Factor Energy Efficiency and Its Extensions: Introduction, Computation and Application," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 45-69, Springer.
    12. Zhang, Ning & Kong, Fanbin & Choi, Yongrok & Zhou, P., 2014. "The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants," Energy Policy, Elsevier, vol. 70(C), pages 193-200.
    13. Wu, F. & Fan, L.W. & Zhou, P. & Zhou, D.Q., 2012. "Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis," Energy Policy, Elsevier, vol. 49(C), pages 164-172.
    14. Honma, Satoshi & Hu, Jin-Li, 2008. "Total-factor energy efficiency of regions in Japan," Energy Policy, Elsevier, vol. 36(2), pages 821-833, February.
    15. Kao, Chiang & Lin, Pei-Huang, 2011. "Qualitative factors in data envelopment analysis: A fuzzy number approach," European Journal of Operational Research, Elsevier, vol. 211(3), pages 586-593, June.
    16. William Cooper & Jesús Pastor & Fernando Borras & Juan Aparicio & Diego Pastor, 2011. "BAM: a bounded adjusted measure of efficiency for use with bounded additive models," Journal of Productivity Analysis, Springer, vol. 35(2), pages 85-94, April.
    17. Bian, Yiwen & Yang, Feng, 2010. "Resource and environment efficiency analysis of provinces in China: A DEA approach based on Shannon's entropy," Energy Policy, Elsevier, vol. 38(4), pages 1909-1917, April.
    18. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    19. Zhou, Yan & Xing, Xinpeng & Fang, Kuangnan & Liang, Dapeng & Xu, Chunlin, 2013. "Environmental efficiency analysis of power industry in China based on an entropy SBM model," Energy Policy, Elsevier, vol. 57(C), pages 68-75.
    20. Zhu, Joe, 2003. "Imprecise data envelopment analysis (IDEA): A review and improvement with an application," European Journal of Operational Research, Elsevier, vol. 144(3), pages 513-529, February.
    21. Du, Kerui & Lu, Huang & Yu, Kun, 2014. "Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach," Applied Energy, Elsevier, vol. 115(C), pages 491-501.
    22. William W. Cooper & Kyung Sam Park & Gang Yu, 2001. "An Illustrative Application of Idea (Imprecise Data Envelopment Analysis) to a Korean Mobile Telecommunication Company," Operations Research, INFORMS, vol. 49(6), pages 807-820, December.
    23. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    24. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    25. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    26. Liu, C.H. & Lin, Sue J. & Lewis, Charles, 2010. "Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis," Energy Policy, Elsevier, vol. 38(2), pages 1049-1058, February.
    27. William W. Cooper & Kyung Sam Park & Gang Yu, 1999. "IDEA and AR-IDEA: Models for Dealing with Imprecise Data in DEA," Management Science, INFORMS, vol. 45(4), pages 597-607, April.
    28. Hu, Jin-Li & Kao, Chih-Hung, 2007. "Efficient energy-saving targets for APEC economies," Energy Policy, Elsevier, vol. 35(1), pages 373-382, January.
    29. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    30. Lim, Sungmook & Zhu, Joe, 2013. "Incorporating performance measures with target levels in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 230(3), pages 634-642.
    31. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    32. Guo, Xiao-Dan & Zhu, Lei & Fan, Ying & Xie, Bai-Chen, 2011. "Evaluation of potential reductions in carbon emissions in Chinese provinces based on environmental DEA," Energy Policy, Elsevier, vol. 39(5), pages 2352-2360, May.
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    3. De Witte, Kristof & Schiltz, Fritz, 2018. "Measuring and explaining organizational effectiveness of school districts: Evidence from a robust and conditional Benefit-of-the-Doubt approach," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1172-1181.
    4. Kang, Jijun & Yu, Chenyang & Xue, Rui & Yang, Dong & Shan, Yuli, 2022. "Can regional integration narrow city-level energy efficiency gap in China?," Energy Policy, Elsevier, vol. 163(C).
    5. Sidhoum, Amer Ait & Serra, Teresa, 2018. "Measuring Sustainability Efficiency At Farm Level: A Data Envelopment Analysis Approach," 166th Seminar, August 30-31, 2018, Galway, West of Ireland 276184, European Association of Agricultural Economists.
    6. Sun Meng & Wei Zhou & Jin Chen & Cheng Zhang, 2018. "A synthesized data envelopment analysis model and its application in resource efficiency evaluation and dynamic trend analysis," Energy & Environment, , vol. 29(2), pages 260-280, March.
    7. Monireh Jahani Sayyad Noveiri & Sohrab Kordrostami & Alireza Amirteimoori, 2022. "Performance analysis of sustainable supply networks with bounded, discrete, and joint factors," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 238-270, January.
    8. Shih-Heng Yu & Yu Gao & Yih-Chearng Shiue, 2017. "A Comprehensive Evaluation of Sustainable Development Ability and Pathway for Major Cities in China," Sustainability, MDPI, vol. 9(8), pages 1-15, August.
    9. Kalinichenko, Olena & Amado, Carla A.F. & Santos, Sérgio P., 2022. "Exploring the potential of Data Envelopment Analysis for enhancing pay-for-performance programme design in primary health care," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1084-1100.
    10. Fritz Schiltz & Kristof Witte & Deni Mazrekaj, 2020. "Managerial efficiency and efficiency differentials in adult education: a conditional and bias-corrected efficiency analysis," Annals of Operations Research, Springer, vol. 288(2), pages 529-546, May.
    11. Shuanglian Chen & Gaoke Liao & Benjamin M. Drakeford & Pierre Failler, 2019. "The Non-Linear Effect of Financial Support on Energy Efficiency: Evidence from China," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    12. Ghimire, Sarad & Amin, Saman Hassanzadeh & Wardley, Leslie J., 2021. "Developing new data envelopment analysis models to evaluate the efficiency in Ontario Universities," Journal of Informetrics, Elsevier, vol. 15(3).
    13. Milad Kolagar & Seyed Mohammad Hassan Hosseini & Ramin Felegari & Parviz Fattahi, 2020. "Policy-making for renewable energy sources in search of sustainable development: a hybrid DEA-FBWM approach," Environment Systems and Decisions, Springer, vol. 40(4), pages 485-509, December.
    14. Utsav Pandey & Sanjeet Singh, 2022. "Data envelopment analysis in hierarchical category structure with fuzzy boundaries," Annals of Operations Research, Springer, vol. 315(2), pages 1517-1549, August.
    15. Zhao, Linlin & Zha, Yong & Zhuang, Yuliang & Liang, Liang, 2019. "Data envelopment analysis for sustainability evaluation in China: Tackling the economic, environmental, and social dimensions," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1083-1095.
    16. Guo, Wen & Liu, Xiaorui, 2022. "Market fragmentation of energy resource prices and green total factor energy efficiency in China," Resources Policy, Elsevier, vol. 76(C).

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