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Remarks on the impact of the adopted scale on the priority estimation quality

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Języki publikacji
EN
Abstrakty
EN
The Analytic Hierarchy Process (AHP) is the method that supports people’s decisions in the multi-criteria decision making problems. In this method the decision process is based on pairwise comparing of every two possible alternatives. The decision maker (DM) compares alternatives by choosing an appropriate “linguistic phrase” or a number from a proper set. This set of “linguistic phrases” and/or the numbers connected with them are referred to as the priority scale. There are several different scales that are described in literature and used in AHP practice. In dependence of the scale chosen by the DM, the final decisions might differ. In the AHP it is assumed that DMs make mistakes over comparing pairs of alternatives, but it was also observed that the assumed scale increases these errors as well. In our paper, we investigate the impact of the adopted scale to the number and magnitude of errors in the final decision. Our results show that the choice of the scale has a big impact on the final decision, so it is crucial part of AHP. It turns out that scales with bigger resource of options result in better evaluations of priority vectors.
Rocznik
Strony
105--116
Opis fizyczny
Bibliogr. 16. poz., tab.
Twórcy
  • Institute of Mathematics, Czestochowa University of Technology Czestochowa, Poland
Bibliografia
  • [1] Grzybowski A.Z., New results on inconsistency indices and their relationship with the quality of priority vector estimation, Expert Systems with Applications 2016, 43, 197-212
  • [2] Saaty T., Decision making - the analytic hierarchy and network processes (AHP/ANP), Journal of Systems Science And Systems Engineering 2004, 13, 1, 1-35, March.
  • [3] Dong Y., Xu Y., Li H., Dai M., A comparative study of the numerical scales and the prioritization methods in AHP, European Journal of Operational Research 2008, 186, 229-242.
  • [4] Franek J., Kresta A., Judgment scales and consistency measure in AHP, Procedia Economics and Finance 2014, 12, 164-173.
  • [5] Budescu D.V., Zwick R., Rapoport A., A comparison of the eigenvalue method and geometric mean procedure for ratio scaling, Applied Psychological Measurement 1986, 10, 1, 69-78, March.
  • [6] Lootsma F., Conflict resolution via pairwise comparison of concessions, European Journal of Operational Research 1989, 40(1), 109-116.
  • [7] Basak I., Comparison of statistical procedures in analytic hierarchy process using a ranking test. Mathematical and Computer Modelling 1998, 28, 105-118.
  • [8] Dijkstra T.K., On the extraction of weights from pairwise comparison matrices, Central European Journal of Operations Research 2013, January, 21, 1, 103-123.
  • [9] Kazibudzki P.T., Grzybowski A.Z., On some advancements within certain multicriteria decision making support methodology, Business and Management 2013, 2, 2, 143-154.
  • [10] Grzybowski A.Z., Note on a new optimization based approach for estimating priority weights and related consistency index, Expert Systems with Applications 2012, 39, 11699-11708.
  • [11] Crawford G., Williams C.A., A note on the analysis of subjective judgment matrices, Journal of Mathematical Psychology 1985, 29, 387-405.
  • [12] Saaty T.L., The Analytic Hierarchy Process, McGraw Hill, New York 1980.
  • [13] Kazibudzki P.T., On some discoveries in the field of scientific methods for management within the concept of Analytic Hierarchy Process, International Journal of Business and Management 2013, 8(8), 22-30.
  • [14] Choo E.U., Wedley W.C., A common framework for deriving preference values from pairwise comparison matrices, Computers and Operations Research 2004, 31, 893-908.
  • [15] Lin C-C., A revised framework for deriving preference values from pairwise comparison matrices, European Journal of Operational Research 2007, 176, 1145-1150.
  • [16] Starczewski T., Relationship between priority ratios disturbances and priority estimation errors, Journal of Applied Mathematics and Computational Mechanics 2016, 15, 3, 143-154.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fff389fa-12bf-4522-9f86-5c8c6d251cac
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