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Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

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Author Info

  • Alessio Ishizaka

    (University of Portsmouth, Portsmouth Business School)

  • Dieter Balkenborg

    (Department of Economics, University of Exeter)

  • Todd Kaplan

    (Department of Economics, University of Exeter)

Abstract

Analytic Hierarchy Process (AHP) is one of the most popular multi-attribute decision aid methods. However, results depend on the preference measurement sacle and the aggregation technique used. In this paper, we describe a decision problem with an inherent trade-off between two criteria. A decision-maker has to choose among three alternatives: two extremes and one "compromise". Six different measurement scales described previously in the literature and the new proposed logarithmic scale are considered for applying the additive and the multiplicative AHP. The results are compared with the standard consumer choice theory. The geometric and power scales offer no chance (for the additive AHP) and very few chances (for the multiplicative AHP) for a compromise to be selected. The logarithmic scale used with the multiplicative AHP is the most in agreement with the consumer choice theory.

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File URL: http://people.exeter.ac.uk/cc371/RePEc/dpapers/DP0506.pdf
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Bibliographic Info

Paper provided by Exeter University, Department of Economics in its series Discussion Papers with number 0506.

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Date of creation: Nov 2005
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Handle: RePEc:exe:wpaper:0506

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Related research

Keywords: : Decision Analysis; Multiple criteria analysis; Utility theory; Additive AHP; Multiplicative AHP; Logarithmic scale;

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  1. Stam, Antonie & Duarte Silva, A. Pedro, 2003. "On multiplicative priority rating methods for the AHP," European Journal of Operational Research, Elsevier, vol. 145(1), pages 92-108, February.
  2. Lootsma, F. A. & Mensch, T. C. A. & Vos, F. A., 1990. "Multi-criteria analysis and budget reallocation in long-term research planning," European Journal of Operational Research, Elsevier, vol. 47(3), pages 293-305, August.
  3. Alessio Ishizaka & Markus Lusti, 2006. "How to derive priorities in AHP: a comparative study," Central European Journal of Operations Research, Springer, vol. 14(4), pages 387-400, December.
  4. Lootsma, F. A., 1989. "Conflict resolution via pairwise comparison of concessions," European Journal of Operational Research, Elsevier, vol. 40(1), pages 109-116, May.
  5. Robert L. Winkler, 1990. "Decision Modeling and Rational Choice: AHP and Utility Theory," Management Science, INFORMS, vol. 36(3), pages 247-248, March.
  6. Thomas L. Saaty, 1990. "An Exposition of the AHP in Reply to the Paper "Remarks on the Analytic Hierarchy Process"," Management Science, INFORMS, vol. 36(3), pages 259-268, March.
  7. James S. Dyer, 1990. "Remarks on the Analytic Hierarchy Process," Management Science, INFORMS, vol. 36(3), pages 249-258, March.
  8. Vargas, Luis G., 1990. "An overview of the analytic hierarchy process and its applications," European Journal of Operational Research, Elsevier, vol. 48(1), pages 2-8, September.
  9. Vaidya, Omkarprasad S. & Kumar, Sushil, 2006. "Analytic hierarchy process: An overview of applications," European Journal of Operational Research, Elsevier, vol. 169(1), pages 1-29, February.
  10. Patrick T. Harker & Luis G. Vargas, 1987. "The Theory of Ratio Scale Estimation: Saaty's Analytic Hierarchy Process," Management Science, INFORMS, vol. 33(11), pages 1383-1403, November.
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Cited by:
  1. Ishizaka, Alessio & Balkenborg, Dieter & Kaplan, Todd R, 2010. "Does AHP help us make a choice? - An experimental evaluation," MPRA Paper 24213, University Library of Munich, Germany.
  2. Siraj, S. & Mikhailov, L. & Keane, J.A., 2012. "Preference elicitation from inconsistent judgments using multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 220(2), pages 461-471.

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