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Does AHP help us make a choice? An experimental evaluation

Author

Listed:
  • A Ishizaka

    (University of Portsmouth, Portsmouth, United Kingdom)

  • D Balkenborg

    (University of Exeter, Exeter, United Kingdom)

  • T Kaplan

    (1] University of Exeter, Exeter, United Kingdom[2] University of Haifa, Haifa, Israel)

Abstract

In this paper, we use experimental economics methods to test how well Analytic Hierarchy Process (AHP) fares as a choice support system in a real decision problem. AHP provides a ranking that we statistically compare with three additional rankings given by the subjects in the experiment: one at the beginning, one after providing AHP with the necessary pair-wise comparisons and one after learning the ranking provided by AHP. While the rankings vary widely across subjects, we observe that for each individual all four rankings are similar. Hence, subjects are consistent and AHP is, for the most part, able to replicate their rankings. Furthermore, while the rankings are similar, we do find that the AHP ranking helps the decision makers reformulate their choices by taking into account suggestions made by AHP.

Suggested Citation

  • A Ishizaka & D Balkenborg & T Kaplan, 2011. "Does AHP help us make a choice? An experimental evaluation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(10), pages 1801-1812, October.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:10:p:1801-1812
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    Citations

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    Cited by:

    1. Corrente, Salvatore & Greco, Salvatore & Ishizaka, Alessio, 2016. "Combining analytical hierarchy process and Choquet integral within non-additive robust ordinal regression," Omega, Elsevier, vol. 61(C), pages 2-18.
    2. Itzel Inti Maria Donati & Davide Viaggi & Zorica Srdjevic & Bojan Srdjevic & Antonella Di Fonzo & Teresa Del Giudice & Orlando Cimino & Andrea Martelli & Anna Dalla Marta & Roberto Henke & Filiberto A, 2023. "An Analysis of Preference Weights and Setting Priorities by Irrigation Advisory Services Users Based on the Analytic Hierarchy Process," Agriculture, MDPI, vol. 13(8), pages 1-15, August.
    3. Ishizaka, Alessio & Siraj, Sajid, 2018. "Are multi-criteria decision-making tools useful? An experimental comparative study of three methods," European Journal of Operational Research, Elsevier, vol. 264(2), pages 462-471.
    4. Ormerod, Richard J. & Ulrich, Werner, 2013. "Operational research and ethics: A literature review," European Journal of Operational Research, Elsevier, vol. 228(2), pages 291-307.
    5. Binkai Xu & Lei Liu & Yanming Sun, 2023. "The Spatio-Temporal Pattern of Regional Coordinated Development in the Common Prosperity Demonstration Zone—Evidence from Zhejiang Province," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    6. Bottomley, Paul A. & Doyle, John R., 2013. "Comparing the validity of numerical judgements elicited by direct rating and point allocation: Insights from objectively verifiable perceptual tasks," European Journal of Operational Research, Elsevier, vol. 228(1), pages 148-157.
    7. Franco, L. Alberto & Hämäläinen, Raimo P. & Rouwette, Etiënne A.J.A. & Leppänen, Ilkka, 2021. "Taking stock of behavioural OR: A review of behavioural studies with an intervention focus," European Journal of Operational Research, Elsevier, vol. 293(2), pages 401-418.
    8. Dong, Yucheng & Hong, Wei-Chiang & Xu, Yinfeng & Yu, Shui, 2013. "Numerical scales generated individually for analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 229(3), pages 654-662.
    9. Gabriela D. Oliveira & Luis C. Dias, 2020. "The potential learning effect of a MCDA approach on consumer preferences for alternative fuel vehicles," Annals of Operations Research, Springer, vol. 293(2), pages 767-787, October.

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