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A hybrid multi‐attribute decision‐making procedure for ranking project proposals: A historical data perspective

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  • Amar Oukil
  • Srikrishna Madhumohan Govindaluri

Abstract

This paper develops a hybrid multiattribute decision‐making methodology for ranking project proposals (PPs) through a judicious usage of historical data of completed projects to determine attribute weights, enabling elimination of problems associated with projected data such as cost and schedule overruns of real‐world projects. The weights generated from data envelopment analysis are explicitly utilized for ranking PPs while allowing subjectivity to be ingeniously incorporated into the decision process. The new approach is implemented for ranking 25 PPs, and the rankings it yields are found indifferent to the decision maker's attitude, which ascertains the robustness of the ranking methodology.

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  • Amar Oukil & Srikrishna Madhumohan Govindaluri, 2020. "A hybrid multi‐attribute decision‐making procedure for ranking project proposals: A historical data perspective," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(3), pages 461-472, April.
    • Handle: RePEc:wly:mgtdec:v:41:y:2020:i:3:p:461-472
    DOI: 10.1002/mde.3113
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    References listed on IDEAS

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    Cited by:

    1. Yuzhong Lu & Zengrui Tian & Guillermo A. Buitrago, 2021. "Evaluation and selection of Chinese government venture capital investment projects: A research based on analytic hierarchy process and intuitionistic fuzzy set–technique for order of preference by sim," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(4), pages 821-835, June.
    2. Amar Oukil & Slim Zekri, 2021. "Investigating farming efficiency through a two stage analytical approach: Application to the agricultural sector in Northern Oman," Papers 2104.10943, arXiv.org.

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