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Ranking Decision Alternatives By Integrated Dea, Ahp And Gower Plot Techniques

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  • HAN-LIN LI

    (Institute of Information Management, National Chiao Tung University, No. 1001, Ta Hsueh Road, Hsinchu, Taiwan 300, ROC)

  • LI-CHING MA

    (Department of Information Management, National United University, No. 1, Lianda, Gongjing Village, Miaoli City, Taiwan 36003, ROC)

Abstract

Data Envelop Analysis (DEA) and Analytic Hierarchy Process (AHP) are widely used methods in ranking decision alternatives. However, current DEA models are difficult to discriminate decision-making units through articulating the decision makers' preferences. While AHP and Gower plot models have to specify complete pairwise preferences without providing assisting information. This study develops an iterative method of ranking decision alternatives by integrating DEA, AHP and Gower plot techniques. The developed method first utilizes a modified DEA model to narrow the ranges of a decision maker's preferences. Then, the tentative ranks of the decision alternatives, computed by embedding the decision maker's preferences, are depicted via Gower plots to illustrate the cardinal and ordinal inconsistencies of these preferences. The decision maker then adjusts the preferences iteratively until the inconsistencies are within the tolerance.

Suggested Citation

  • Han-Lin Li & Li-Ching Ma, 2008. "Ranking Decision Alternatives By Integrated Dea, Ahp And Gower Plot Techniques," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 241-258.
    • Handle: RePEc:wsi:ijitdm:v:07:y:2008:i:02:n:s0219622008002922
    DOI: 10.1142/S0219622008002922
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    Citations

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    Cited by:

    1. Yash Daultani & Ashish Dwivedi & Saurabh Pratap, 2021. "Benchmarking higher education institutes using data envelopment analysis: capturing perceptions of prospective engineering students," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 773-789, December.
    2. Valdecy Pereira & Helder Costa, 2015. "Nonlinear programming applied to the reduction of inconsistency in the AHP method," Annals of Operations Research, Springer, vol. 229(1), pages 635-655, June.
    3. Li-Ching Ma, 2018. "Discovering Consensus Preferences Visually Based on Gower Plots," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(03), pages 741-761, May.
    4. Cooper, Orrin & Yavuz, Idil, 2016. "Linking validation: A search for coherency within the Supermatrix," European Journal of Operational Research, Elsevier, vol. 252(1), pages 232-245.
    5. Jiamin Wang, 2012. "Robust optimization analysis for multiple attribute decision making problems with imprecise information," Annals of Operations Research, Springer, vol. 197(1), pages 109-122, August.
    6. Yugang Yu & Chengbin Chu & Haoxun Chen & Feng Chu, 2012. "Large scale stochastic inventory routing problems with split delivery and service level constraints," Annals of Operations Research, Springer, vol. 197(1), pages 135-158, August.
    7. Gwo-Hshiung Tzeng & Chi-Yo Huang, 2012. "Combined DEMATEL technique with hybrid MCDM methods for creating the aspired intelligent global manufacturing & logistics systems," Annals of Operations Research, Springer, vol. 197(1), pages 159-190, August.
    8. Ergu, Daji & Kou, Gang & Peng, Yi & Shi, Yong, 2011. "A simple method to improve the consistency ratio of the pair-wise comparison matrix in ANP," European Journal of Operational Research, Elsevier, vol. 213(1), pages 246-259, August.

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