The Current Association between Machine learning Techniques and Digital Smart Supply Chain 4.0 in Managing Transportation Distribution Risk

Abstract

Monitoring supply chain transportation through distribution transportation network is a challenging issue that must be properly and effectively monitored. Disruption risk has led to a significant growth in freight network requirements in smart supply chain management. Several researches provided enabling models to assess freight and traffic transportation risks in supply chain. Yet, the key challenge within the supply chain management is elaborating advanced technologies in distribution network and disruption risks mitigation. This paper presents a literature review on the explored relation between disruptions risks in smart supply chain transportation, industries and organizations throughout the world to enhance the effectiveness of distribution networks. This study explores the necessity of collaboration between smart supply chain management and transportation distribution network during disruptions. Within this context, different research requirement were thoroughly investigated to highlights all aspects and criteria including advanced management, decision-making tools, enabling technologies, risk management approaches, ISO39001, ISO14001, sustainability, resilience and Covid-19 implications. Foreseeing several significant challenges, this study examines the need of cooperation between academics and manufacturers to provide new approaches to manage distribution network in supply chain during disruption from different aspects. The results of this paper serves as a succinct reference guide for academics and companies seeking to implement viable and innovative future transportation solution and approaches.