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The Consistency Adjustment Problem of AHP Pairwise Comparison Matrices

In: Quantitative Marketing and Marketing Management

Author

Listed:
  • Dominic Gastes

    (TRUMPF Werkzeugmaschinen GmbH & Co. KG)

  • Wolfgang Gaul

    (Karlsruhe Institute of Technology (KIT))

Abstract

The Analytic Hierarchy Process (AHP) is an often applied and well researched method in the area of multiattribute decision making. One of the main recurring tasks in AHP situations is the creation of pairwise comparison matrices, the examination of their consistencies, and the derivation of weights for the underlying objective functions. The importance of controlling these consistencies and the consequences of subsequent adjustments of comparison matrices are sometimes unvalued issues in AHP applications. We conduct a simulation study to show that increasing inconsistencies caused by superimposed stochastic error-terms on consistent starting pairwise comparison AHP data result in decreasing correlations between the corresponding weights of the error-perturbed matrices and those of the consistent starting data and demonstrate that the weights derived from adjusted matrices do not show the improvements expected.

Suggested Citation

  • Dominic Gastes & Wolfgang Gaul, 2012. "The Consistency Adjustment Problem of AHP Pairwise Comparison Matrices," Springer Books, in: Adamantios Diamantopoulos & Wolfgang Fritz & Lutz Hildebrandt (ed.), Quantitative Marketing and Marketing Management, edition 127, chapter 2, pages 51-62, Springer.
    • Handle: RePEc:spr:sprchp:978-3-8349-3722-3_2
    DOI: 10.1007/978-3-8349-3722-3_2
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    Citations

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    Cited by:

    1. Garbuzova-Schlifter, Maria & Madlener, Reinhard, 2016. "AHP-based risk analysis of energy performance contracting projects in Russia," Energy Policy, Elsevier, vol. 97(C), pages 559-581.
    2. Höfer, Tim & Sunak, Yasin & Siddique, Hafiz & Madlener, Reinhard, 2016. "Wind farm siting using a spatial Analytic Hierarchy Process approach: A case study of the Städteregion Aachen," Applied Energy, Elsevier, vol. 163(C), pages 222-243.
    3. Feifei Jin & Zhiwei Ni & Reza Langari & Huayou Chen, 2020. "Consistency Improvement-Driven Decision-Making Methods with Probabilistic Multiplicative Preference Relations," Group Decision and Negotiation, Springer, vol. 29(2), pages 371-397, April.
    4. Szybowski, Jacek & Kułakowski, Konrad & Prusak, Anna, 2020. "New inconsistency indicators for incomplete pairwise comparisons matrices," Mathematical Social Sciences, Elsevier, vol. 108(C), pages 138-145.
    5. Giamalaki, Marina & Tsoutsos, Theocharis, 2019. "Sustainable siting of solar power installations in Mediterranean using a GIS/AHP approach," Renewable Energy, Elsevier, vol. 141(C), pages 64-75.
    6. Gkeka-Serpetsidaki, Pandora & Tsoutsos, Theocharis, 2022. "A methodological framework for optimal siting of offshore wind farms: A case study on the island of Crete," Energy, Elsevier, vol. 239(PD).

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