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A multi-component enhanced Russell measure of efficiency: With application to water supply plans

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  • Entezam, Hasan Farmani
  • Sobhani, Farzad Movahedi
  • Najafi, Seyed Esmaeil
  • Roshdi, Israfil

Abstract

Public water providers aim at developing a water supply plan (WSP) that not only provides a reliable and satisfactory level of service but also is efficient in terms of performance. This paper deals with evaluating the performance of WSPs within the framework of multi-component data envelopment analysis. Specifically, we consider the overall performance of each WSP as a decision making unit (DMU) so that economic, social, hygienic, technological, managerial and environmental performances of the WSP make up independent components of the defined DMU. To assess the performance of a set of WPSs, we propose a multi-component enhanced Russell measure of efficiency that takes all sources of inefficiency into account. We show that the proposed measure can be decomposed into individual efficiency measures at component level. This decomposition much enhances the efficiency of computing the proposed measure, noting the fact that this measure is obtained by solving a single linear program. It also guarantees the proposed measure to inherit two important—unit invariance and strong monotonicity—properties of the conventional enhanced Russell measure. In our empirical study, we apply our model to evaluate the efficiency of 10 urban WSPs in Qom city of Iran. In line with experts’ practical opinions, our findings reveal that the (relatively) most efficient WSP is to construct a potable water network and separation of non-drinking water network for urban usage.

Suggested Citation

  • Entezam, Hasan Farmani & Sobhani, Farzad Movahedi & Najafi, Seyed Esmaeil & Roshdi, Israfil, 2020. "A multi-component enhanced Russell measure of efficiency: With application to water supply plans," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    • Handle: RePEc:eee:soceps:v:70:y:2020:i:c:s0038012119300667
    DOI: 10.1016/j.seps.2019.06.004
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    1. Chen, Ci & Yan, Hong, 2011. "Network DEA model for supply chain performance evaluation," European Journal of Operational Research, Elsevier, vol. 213(1), pages 147-155, August.
    2. Lovell, C. A. Knox & Pastor, Jesus T., 1999. "Radial DEA models without inputs or without outputs," European Journal of Operational Research, Elsevier, vol. 118(1), pages 46-51, October.
    3. Wade D. Cook & Joe Zhu, 2006. "Incorporating Multiprocess Performance Standards into the DEA Framework," Operations Research, INFORMS, vol. 54(4), pages 656-665, August.
    4. Victor V. Podinovski & Ole Bent Olesen & Cláudia S. Sarrico, 2018. "Nonparametric Production Technologies with Multiple Component Processes," Operations Research, INFORMS, vol. 66(1), pages 282-300, January.
    5. Amor Diez-Ticio & Maria-Jesus Mancebon, 2002. "The efficiency of the Spanish police service: an application of the multiactivity DEA model," Applied Economics, Taylor & Francis Journals, vol. 34(3), pages 351-362.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Imanirad, Raha & Cook, Wade D. & Aviles-Sacoto, Sonia Valeria & Zhu, Joe, 2015. "Partial input to output impacts in DEA: The case of DMU-specific impacts," European Journal of Operational Research, Elsevier, vol. 244(3), pages 837-844.
    8. 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.
    9. Lorenzo Castelli & Raffaele Pesenti & Walter Ukovich, 2010. "A classification of DEA models when the internal structure of the Decision Making Units is considered," Annals of Operations Research, Springer, vol. 173(1), pages 207-235, January.
    10. Jamal Ouenniche & Skarleth Carrales, 2018. "Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback," Annals of Operations Research, Springer, vol. 266(1), pages 551-587, July.
    11. Monica Bonacina & Anna Cretì & Carlotta Mariotto & Federico Pontoni, 2014. "What Determines Efficiency? An Analysis of the Italian Water Sector," IEFE Working Papers 72, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    12. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    13. Tsai, P. F. & Mar Molinero, C., 2002. "A variable returns to scale data envelopment analysis model for the joint determination of efficiencies with an example of the UK health service," European Journal of Operational Research, Elsevier, vol. 141(1), pages 21-38, August.
    14. Wade D. Cook & R. H. Green, 2014. "Multicomponent Efficiency Measurement and Core Business Identification in Multiplant Firms," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 431-449, Springer.
    15. Wade Cook & Moez Hababou & Hans Tuenter, 2000. "Multicomponent Efficiency Measurement and Shared Inputs in Data Envelopment Analysis: An Application to Sales and Service Performance in Bank Branches," Journal of Productivity Analysis, Springer, vol. 14(3), pages 209-224, November.
    16. Roll, Yaakov & Cook, Wade D., 1993. "Partial efficiencies in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 27(3), pages 171-179, September.
    17. Cook, Wade D. & Zhu, Joe, 2007. "Within-group common weights in DEA: An analysis of power plant efficiency," European Journal of Operational Research, Elsevier, vol. 178(1), pages 207-216, April.
    18. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
    19. Wade D. Cook & Julie Harrison & Raha Imanirad & Paul Rouse & Joe Zhu, 2013. "Data Envelopment Analysis with Nonhomogeneous DMUs," Operations Research, INFORMS, vol. 61(3), pages 666-676, June.
    20. Cook, Wade D. & Hababou, Moez, 2001. "Sales performance measurement in bank branches," Omega, Elsevier, vol. 29(4), pages 299-307, August.
    21. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    22. Raha Imanirad & Wade D. Cook & Joe Zhu, 2015. "Partial Input to Output Impacts in DEA: Production Considerations and Resource Sharing Among Business Sub-Units," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 13, pages 355-380, Springer.
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    Cited by:

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