Sustainability performance assessment of freight transportation modes using an integrated decision-making framework based on m-generalized q-neutrosophic sets

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Date

2024

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Springer

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Abstract

The freight transport industry is one of the primary sectors responsible for excessive energy consumption and greenhouse gas emissions. Restructuring international and domestic freight transport chains based on sustainability and green transportation is critical for practitioners and policymakers to reduce pressure on the logistics and transportation industries. This study aims to develop a mathematical model for selecting the most appropriate transportation type, and accordingly, the optimal route in transportation operations to improve the sustainability performance of the freight transportation industry. Therefore, the main goal is to choose the most suitable route and transportation type which contributes to create a more eco-friendly and sustainable transportation system. For this purpose, Neutrosophic Number-based Delphi (NN-Delphi), m-Generalized q-Neutrosophic Sets (mGqNSs)-based Stepwise Weight Assessment Ratio Analysis (MGqNS-SWARA) and mGqNSs-based Additive Ratio Assessment (mGqNS-ARAS) are developed and implemented to set the influential criteria, compute the weights of these criteria, and identify the sustainability performance of the freight mode variants, respectively. According to the final results, "Cargo security" and "Accident rates" are the most important criteria with a relative importance score of 0.0237, contributing to the sustainability of load transport modes. Moreover, "Maritime Transport Mode" is identified as the most sustainable transportation type with a relative importance score of 0.7895. Finally, it is revealed that there is a positive relationship between maritime transport and sustainability.

Description

Tirkolaee, Erfan Babaee/0000-0003-1664-9210; Aytekin, Ahmet/0000-0002-1536-7097

Keywords

Sustainability performance, Freight transportation, Decision-making framework, NN-Delphi, MGqNS-SWARA method, MGqNS-ARAS method

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0

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Q1

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Volume

57

Issue

5

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