Ranking of Institutes Using MCDM SAW Method Under Uncertainty

Hiremani, Vani; Devadas, Raghavendra M; Gujjar, Praveen; Johar, Sayyed; R, Sapna

doi:10.1109/incet61516.2024.10593015

2024 5th International Conference for Emerging Technology (INCET) 2024

DOI: 10.1109/incet61516.2024.10593015

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Ranking of Institutes Using MCDM SAW Method Under Uncertainty

Vani Hiremani,

Raghavendra M Devadas,

Praveen Gujjar

et al.

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2024

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Cited by 1 publication

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Addressing the Global Logistics Performance Index Rankings with Methodological Insights and an Innovative Decision Support Framework

Stević,

Ersoy,

Başar

et al. 2024

Applied Sciences

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This study examines the Logistics Performance Index (LPI) rankings developed by the World Bank from a methodological perspective and proposes an alternative decision support framework. LPI serves as an interactive tool that helps countries identify challenges, innovative solutions, and opportunities in their trade and logistics sectors. In this study, the efficiency of logistics operations in 118 countries was evaluated using an integrated multi-criteria decision-making (MCDM) model objectively weighted by the Entropy method. Countries were ranked using the MCRAT, SAW, TOPSIS, and FUCA methods. According to the findings, large datasets provide more robust insights for sensitivity analyses, and wider weighting coefficient combinations make the data more meaningful. In addition, it is suggested to use low-compensation methods instead of classical additive methods for LPI. Unlike other studies in literature, this research applied an innovative sensitivity analysis to test the robustness of the model and comprehensively examined the effects of weighting techniques based on over 2500 different MCDM results. The findings suggest that the FUCA method should be recommended to decision-makers for calculating LPI rankings due to its simplicity, practicality, low compensatory power, and low sensitivity. This study offers methodological improvements when evaluating logistics performance and provides significant contributions to decision-making processes. The findings are expected to provide a valuable resource for policymakers and businesses in understanding a country’s position in global competition, as well as serving as a reference for researchers evaluating the logistics performance of countries.

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Addressing the Global Logistics Performance Index Rankings with Methodological Insights and an Innovative Decision Support Framework

Stević,

Ersoy,

Başar

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

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Ranking of Institutes Using MCDM SAW Method Under Uncertainty

Cited by 1 publication

References 11 publications

Addressing the Global Logistics Performance Index Rankings with Methodological Insights and an Innovative Decision Support Framework

Addressing the Global Logistics Performance Index Rankings with Methodological Insights and an Innovative Decision Support Framework

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