4.6 Article

A Novel Fuzzy-Based VIKOR-CRITIC Soft Computing Method for Evaluation of Sustainable Supply Chain Risk Management

期刊

SUSTAINABILITY
卷 14, 期 5, 页码 -

出版社

MDPI
DOI: 10.3390/su14052827

关键词

fuzzy sets; soft computing; VIKOR; CRITIC; sustainable supply chain; risk management

资金

  1. POZNAN UNIVERSITY OF TECHNOLOGY [0812-SBAD-4170]

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This article evaluates sustainable supply chain risks using a new fuzzy VIKOR-CRITIC technique and focuses on the logistics industry in Pakistan. The study integrates the fuzzy VIKOR approach with the CRITIC method and establishes thirty criteria divided into four categories. The findings highlight the importance of organizational risks and the minimal influence of environmental hazards.
This article aims to evaluate sustainable supply chain risks using a novel fuzzy VIKOR-CRITIC technique. The research contributions of this study are twofold. First and foremost, this is the first attempt to integrate the fuzzy VIKOR approach with the CRITIC method in order to eradicate the inadequacies of the VIKOR method. Second, this is the first study to look at the sustainable supply chain risk management in Pakistan's logistics industry. Four logistics companies were chosen for the study, and thirty criteria were established and divided into four categories using acquired data and literature studies. According to the findings, organizational risks are the most important to consider, whereas environmental hazards have the least influence. Supply delays, freight rate/oil price fluctuations, bankruptcy, and natural catastrophe are the four most important criteria in these categories. Limited suppliers, cargo tracking, IT system failure, and international politics are the four least significant criteria in the four risk categories. The findings are useful for the logistics industry operating in CPEC for risk mitigation and sustainable operation. The research may be used as a guideline for risk identification and management by practitioners and decision-makers in Pakistani logistics organizations.

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