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Improving performance evaluation based on balanced scorecard with grey relational analysis and data envelopment analysis approaches: Case study in water and wastewater companies

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  • Sarraf, Fatemeh
  • Nejad, Shabnam Hashemi

Abstract

Various approaches are used to measure the firms’ performance. Grey relational analysis is one of the multiple attribute decision-making methods and data envelopment analysis is used to calculate the efficiency. Regarding the importance of water and wastewater companies’ services, the present study, evaluates the performance and rank these companies by using grey relational analysis and data envelopment analysis approaches based on balanced scorecard criteria. Besides, balanced scorecard considers all levels of organization. In this research, statistical population includes thirty-five municipal water and wastewater companies in Iran for the year 2017. In order to ascertain grey relational grade, fuzzy normalization method was used then by subtracting normalized numbers from one, reference sequences obtained and in the next step, grey relational coefficient was calculated and finally, grey relational grade was determined by multiplying relative weight from Shannon entropy to relational coefficients. In order to assess companies’ efficiency in data envelopment analysis, after ascertaining input and output indices, with the assumption of constant returns to scale and output-oriented viewpoint, the efficiency scores were calculated. Also, to rank efficient units Anderson-Petersen model implemented. Results demonstrated that, grey relational analysis is a more accurate method to measure the performance of water and wastewater companies.

Suggested Citation

  • Sarraf, Fatemeh & Nejad, Shabnam Hashemi, 2020. "Improving performance evaluation based on balanced scorecard with grey relational analysis and data envelopment analysis approaches: Case study in water and wastewater companies," Evaluation and Program Planning, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:epplan:v:79:y:2020:i:c:s0149718918303963
    DOI: 10.1016/j.evalprogplan.2019.101762
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    References listed on IDEAS

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    1. María Molinos-Senante & Simon Porcher & Alexandros Maziotis, 2018. "Productivity change and its drivers for the Chilean water companies: A comparison of full private and concessionary companies," Post-Print hal-02145824, HAL.
    2. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    3. Vilanova, Mateus Ricardo Nogueira & Magalhães Filho, Paulo & Balestieri, José Antônio Perrella, 2015. "Performance measurement and indicators for water supply management: Review and international cases," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 1-12.
    4. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    5. Lin, Sue J. & Lu, I.J. & Lewis, Charles, 2007. "Grey relation performance correlations among economics, energy use and carbon dioxide emission in Taiwan," Energy Policy, Elsevier, vol. 35(3), pages 1948-1955, March.
    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. Basso, Antonella & Casarin, Francesco & Funari, Stefania, 2018. "How well is the museum performing? A joint use of DEA and BSC to measure the performance of museums," Omega, Elsevier, vol. 81(C), pages 67-84.
    8. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    9. Varmazyar, Mohsen & Dehghanbaghi, Maryam & Afkhami, Mehdi, 2016. "A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach," Evaluation and Program Planning, Elsevier, vol. 58(C), pages 125-140.
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