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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.
Highlights
Institutions observing the global trade and logistics industry expect the global logistics market to rapidly grow after 2020 by USD 29.66 billion (ReportLinker, n.d.)
Logistics village selection is crucial for logistics companies and operators because it can affect a logistics company’s productivity, effectiveness, and performance
This paper proposes a hybrid fuzzy multiple criteria decision making (MCDM) model because solving this problem is impossible without considering uncertainties existing in an evaluation process
Summary
Institutions observing the global trade and logistics industry expect the global logistics market to rapidly grow after 2020 by USD 29.66 billion (ReportLinker, n.d.). Regarding developing new strategies and improving logistics operations, the paper aims to present an integrated fuzzy decision-making model to identify the most appropriate logistics village alternative and evaluate the selection criteria affecting the assessment process. For this purpose, the Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA) technique, a modified version of the Fuzzy Step-Wise Weight Assessment Ratio Analysis (F SWARA), was implemented to determine the weights of the criteria. – The current paper approves the proposed model’s validity, robustness, and applicability by implementing a comprehensive sensitivity analysis Within this scope, the proposed integrated fuzzy decision-making approach can help decision-makers responsible for making strategic decisions for making rational and reliable decisions. A comprehensive sensitivity analysis was performed in the fourth section to validate the proposed model, and the obtained results are discussed in Section 5, and it has been concluded
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