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Fuzzy Preference Based Organizational Performance Measurement

  • Conference paper
Intelligent Decision Technologies

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 10))

Abstract

This paper introduces a methodology for constructing a multidimesional indicator designed for organizational performance measurement. The methodology involves the application of fuzzy models and methods of their analysis. Its use requires the construction of fuzzy preference relations by means of the comparison of performance measures with respect to a reference standard defined as a predetermined scale consisting of linguistic terms. The exploitation of the fuzzy preference relations is carried out by means of the Orlovsky choice procedure. An application example related to the organizational performance evaluation with the use of the proposed methodology is considered, in order to demonstrate its applicability.

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References

  1. Abdel-Maksoud, A., Dugdale, D., Luther, R.: Non-financial performance measurement in manufacturing companies. The Br. Account Rev. 37, 261–297 (2005), doi:10.1016/j.bar.2005.03.003

    Article  Google Scholar 

  2. Berrah, L., Mauris, G., Foulloy, L., Haurat, A.: Global vision and performance indicators for an industrial improvement approach. Comput. Ind. 43, 211–225 (2000), doi:10.1016/S0166-3615(00)00070-1

    Article  Google Scholar 

  3. Bititci, U.S., Suwignjo, P., Carrie, A.S.: Strategy management through quantitative modelling of performance measurement systems. Int. J. Prod. Econ. 69, 15–22 (2001), doi:10.1016/S0925-5273(99)00113-9

    Article  Google Scholar 

  4. Bosilj-Vuksice, V., Milanovic, L., Skrinjar, R., Indihar-Stemberger, M.: Organizational performance measures for business process management: a performance measurement guideline. In: Proc. Tenth Conf. Comput. Model. Simul. (2008), doi:10.1109/UKSIM.2008.114

    Google Scholar 

  5. Brouwer, R.K.: Fuzzy set covering of a set of ordinal attributes without parameter sharing. Fuzzy Sets Syst. 157, 1775–1786 (2006), doi:10.1016/j.fss.2006.01.004

    Article  MathSciNet  MATH  Google Scholar 

  6. Chapman, C.S., Hopwood, A.G., Shields, M.D.: Handbook of management accounting research, vol. 1. Elsevier, Amsterdam (2007)

    Google Scholar 

  7. Clivillé, V., Berrah, L., Mauris, G.: Quantitative expression and aggregation of performance measurements based on the MACBETH multi-criteria method. Int. J. Prod. Econ. 105, 171–189 (2007), doi:10.1016/j.ijpe.2006.03.002

    Article  Google Scholar 

  8. Ekel, P., Pedrycz, W., Schinzinger, R.: A general approach to solving a wide class of fuzzy optimization problems. Fuzzy Sets Syst. 97, 49–66 (1998), doi:10.1016/S0165-0114(96)00334-X

    Article  MathSciNet  MATH  Google Scholar 

  9. Ekel, P.Y., Silva, M.R., Schuffner Neto, F., Palhares, R.M.: Fuzzy preference modeling and its application to multiobjective decision making. Comput. Math Appl. 52, 179–196 (2006), doi:10.1016/j.camwa.2006.08.012

    Article  MathSciNet  MATH  Google Scholar 

  10. Herrera-Viedma, E., Herrera, F., Chiclana, F.: A consensus model for multiperson decision making with different preference structures. IEEE Trans. Syst. Man Cybern – Part A: Syst. Hum. 32, 394–402 (2002), doi:10.1109/TSMCA.2002.802821

    Article  Google Scholar 

  11. Kaplan, R.S., Norton, D.: The Balanced Scorecard: Translating Strategy into Action. Harvard Business School, Boston (1996)

    Google Scholar 

  12. Lu, C., Lan, J., Wang, Z.: Aggregation of fuzzy opinions under group decision-making based on similarity and distance. J. Syst. Sci. Complex 19, 63–71 (2006), doi:10.1007/s11424-006-0063-y

    Article  MathSciNet  MATH  Google Scholar 

  13. Nudurupati, S.S., Bititci, U.S., Kumar, V., Chan, F.T.S.: State of the art literature review on performance measurement. Comput. Ind. Eng. (in press), doi:10.1016/j.cie.2010.11.010

    Google Scholar 

  14. Orlovsky, S.A.: Decision making with a fuzzy preference relation. Fuzzy Sets Syst 1, 155–167 (1978), doi:10.1016/0165-0114(78)90001-5

    Article  MathSciNet  MATH  Google Scholar 

  15. Orlovsky, S.A.: Problems of Decision Making with Fuzzy Information. Nauka, Moscow (1981) (in Russian)

    Google Scholar 

  16. Pedrycz, W.: Fuzzy equalization in the construction of fuzzy sets. Fuzzy Sets Syst. 119, 329–335 (2001), doi:10.1016/S0165-0114(99)00135-9

    Article  MathSciNet  MATH  Google Scholar 

  17. Pedrycz, W., Ekel, P., Parreiras, R.: Fuzzy Multicriteria Decision-Making: Models, Methods, and Applications. Wiley, Chichester (2010)

    Book  Google Scholar 

  18. Popova, V., Sharpanskykh, A.: Modeling organizational performance indicators. Inf. Syst. 35, 505–527 (2010), doi:10.1016/jis.2009.12.001

    Article  Google Scholar 

  19. Shobrys, D.E., White, D.C.: Planning, scheduling and control systems: why cannot they work together. Comput. Chem. Eng. 26, 149–160 (2000), doi:10.1016/S0098-1354(00)00508-1

    Article  Google Scholar 

  20. Yager, R.R.: Multicriteria decision making using fuzzy quantifiers. In: Proc. IEEE Conf. Comput. Intell. Financial Eng. (1995), doi:10.1109/CIFER.1995.495251

    Google Scholar 

  21. Yu, V.F., Hu, K.J.: An integrated fuzzy multi-criteria approach for the performance evaluation of multiple manufacturing plants. Comput. Ind. Eng. 58, 269–277 (2010), doi:10.1016/j.cie.2009.10.005

    Article  Google Scholar 

  22. Zimmermann, H.J.: Fuzzy Set Theory and Its Application. Kluwer Academic Publishers, Boston (1990)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Pontifical Catholic, University of Minas Gerais, Av. Dom José Gaspar, 500, 30535-610, Belo Horizonte, MG, Brazil

    Roberta O. Parreiras & Petr Ya Ekel

Authors
  1. Roberta O. Parreiras
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  2. Petr Ya Ekel
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Editor information

Editors and Affiliations

  1. Graduate School of Information, Production and Systems (IPS), Waseda University, 2-7 Hibikino Wakamatsuku, 808-0135, Fukuoka, Kitakyushu, Japan

    Junzo Watada

  2. Sellinger School of Business and Management, Loyola University Maryland, 4501 N Charles Street, 21210, Baltimore, MD, USA

    Gloria Phillips-Wren

  3. School of Electrical and Information Engineering, University of South Australia, Mawson Lakes Campus Adelaide, 5095, South Australia, SA, Australia

    Lakhmi C. Jain

  4. KES International, Shoreham-by-seaWest Sussex, PO Box 2115, BN43 9AF, United Kingdom

    Robert J. Howlett

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© 2011 Springer-Verlag Berlin Heidelberg

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Parreiras, R.O., Ekel, P.Y. (2011). Fuzzy Preference Based Organizational Performance Measurement. In: Watada, J., Phillips-Wren, G., Jain, L.C., Howlett, R.J. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22194-1_45

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  • DOI: https://doi.org/10.1007/978-3-642-22194-1_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22193-4

  • Online ISBN: 978-3-642-22194-1

  • eBook Packages: EngineeringEngineering (R0)

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