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Technological and Economic Development of Economy
Article . 2021 . Peer-reviewed
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EVALUATING LOGISTICS VILLAGES IN TURKEY USING HYBRID IMPROVED FUZZY SWARA (IMF SWARA) AND FUZZY MABAC TECHNIQUES

Authors: Hashemkhani Zolfani, Sarfaraz; Gorcun, Omer Faruk; Küçükönder, Hande; Küçükönder, Hande;

EVALUATING LOGISTICS VILLAGES IN TURKEY USING HYBRID IMPROVED FUZZY SWARA (IMF SWARA) AND FUZZY MABAC TECHNIQUES

Abstract

Positioning in the right location for organizing logistics activities is a determinative factor in the aspect of costs, effectivity, productivity, and performance of these operations carried out by logistics firms. The proper logistics village selection is a crucial, complicated, and time-consuming process for decision-makers who have to make the right and optimal decision on this issue. Decision-makers need a methodological frame with a practical algorithm that can be implemented quickly to solve these decision-making problems. Within this scope, the current paper aims to present an evaluation tool, which provides more reasonable and reliable results for decision-makers to solve the logistics village selection problem that is very complicated and has uncertain conditions based on fuzzy approaches. In this study, we propose the Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA), a modified and extended version of the traditional fuzzy Step-Wise Weight Assessment Ratio Analysis (F-SWARA) to identify the criteria weights. Also, we suggest applying the fuzzy Multi-Attributive Border Approximation area Comparison (F-MABAC) technique to determine the preference ratings of the alternatives. This combination has many valuable contributions. For example, it proposes to use a more reliable and consistent evaluation scale based on fuzzy sets. Hence, decision-makers can perform more reliable and reasonable pairwise comparisons by considering this evaluation scale. Besides, it presents a multi-attribute evaluation system based on the identified criteria weights. From this perspective, the proposed model is implemented to evaluate eight different logistics village alternatives with respect to nine selection criteria. According to the analysis results, while A8 is the most appropriate option, C1 Gross National Product (GNP) is the most significant criterion. A comprehensive sensitivity analysis was performed to test the robustness and validation of the proposed model, and the results of the analysis approve the validity and applicability of the proposed model. As a result, the suggested integrated MCDM framework can be applied as a valuable and practical decision-making tool to develop new strategies and improve the logistics operations by decision-makers.

Country
Turkey
Keywords

multiple criteria decision making (mcdm), Decision-Making, multi-attributive border approximation area comparison (mabac), HF5001-6182, Ahp, Logistics Villages, logistics villages, Transport, Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA), Economic growth, development, planning, Multi-Attributive Border Approximation Area Comparison (Mabac), Moora, Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (Imf Swara), Location Selection, Site Selection, Multiple Criteria Decision Making (Mcdm), multiple criteria decision making (MCDM), HD72-88, Business, Finance, Multi-Attributive Border Approximation Area Comparison (MABAC), improved fuzzy step-wise weight assessment ratio analysis (imf swara), Model

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    popularity
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    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
42
Top 10%
Top 10%
Top 1%
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gold