JACIII Vol.10 No.2 pp. 219-224
doi: 10.20965/jaciii.2006.p0219


Fuzzy Ratings and Crisp Feedback in Fuzzy AHP for Supporting Human Decision Making

Toshiyuki Yamashita

Graduate School of Engineering, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan

January 26, 2005
October 26, 2005
March 20, 2006
AHP, fuzzy AHP, fuzzy ratings, decision making, defuzzification

Analytic Hierarchy Process (AHP) is one of the most popular tools for supporting human decision making, and several fuzzy extensions of AHP have been proposed. The present study investigated psychological effects of both fuzzy ratings in fuzzy AHP and crisp feedback of the results from fuzzy AHP. The results suggest that fuzzy ratings could incorporate the fuzziness of a person’s feelings in his/her decision making. The results also suggest that crisp feedback, which exaggerates the superiority of only one alternative or the differences among the alternatives, could help a person to make his/her decision, especially when being deeply puzzled about his/her choice.

Cite this article as:
Toshiyuki Yamashita, “Fuzzy Ratings and Crisp Feedback in Fuzzy AHP for Supporting Human Decision Making,” J. Adv. Comput. Intell. Intell. Inform., Vol.10, No.2, pp. 219-224, 2006.
Data files:
  1. [1] T. Yamashita, “On the support system giving a feeling of satisfaction to a decision maker,” Journal of Japan Society for Fuzzy Theory and Systems, 7, pp. 44-51, 1995 (in Japanese).
  2. [2] T. Yamashita, “On a support system for human decision making by the combination of fuzzy reasoning and fuzzy structural modeling,” Fuzzy Sets and Systems, 87, pp. 257-263, 1997.
  3. [3] T. L. Saaty, “A scaling method for priorities in hierarchical structures,” Journal of Mathematical Psychology, 15, pp. 234-281, 1977.
  4. [4] T. L. Saaty, “The Analytic Hierarchy Process,” McGraw-Hill, New York, 1980.
  5. [5] J. J. Buckley, “Fuzzy hierarchical analysis,” Fuzzy Sets and Systems, 17, pp. 233-247, 1985.
  6. [6] P. J. M. van Laarhoven, and W. Pedrycz, “A fuzzy extension of Saaty’s priority theory,” Fuzzy Sets and Systems, 11, pp. 229-241, 1983.
  7. [7] L. A. Zadeh, “Fuzzy sets,” Information and Control, 8, pp. 338-353, 1965.
  8. [8] B. Hesketh, R. Pryor, and M. Gleitzman, “Fuzzy logic: Toward measuring Gottfredson’s concept of occupational social space,” Journal of Counseling Psychology, 36, pp. 103-109, 1989.
  9. [9] B. Hesketh, R. Pryor, M. Gleitzman, and T. Hesketh, “Practical applications and psychometric evaluation of a computerised fuzzy graphic rating scale,” in T. Zetenyi (Ed.), Fuzzy Sets in Psychology, Elsevier Science Publishers B.V., pp. 425-454, 1988.
  10. [10] T. Hesketh, R. Pryor, and B. Hesketh, “An application of a computerised fuzzy graphic rating scale to the psychological measurement of individual differences,” International Journal of Man-Machine Studies, 29, pp. 21-35, 1988.
  11. [11] N. Matsuda, T. Yamashita, and S. Tamura, “Judgment support by genetic algorithms and the wave model,” Proceedings of Third Workshop on Evaluation of Heart and Mind, pp. 31-34, 1998 (in Japanese).
  12. [12] L. L. Thurstone, “A law of comparative judgment,” Psychological Review, 34, pp. 273-286, 1927.
  13. [13] R. Mosteller, “Remarks on the method of paired comparisons: I. The least squares solution assuming equal standard deviations and equal correlations,” Psychometrika, 16(1), pp. 3-9, 1951.
  14. [14] C. E. Osgood, “The nature and measurement of meaning,” Psychological Bulletin, 49, pp. 197-237, 1952.

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