Title: The most common type of disruption in the supply chain - evaluation based on the method using artificial neural networks

Authors: Augustyn Lorenc; Małgorzata Kuźnar

Addresses: Logistics Systems Division, Department of Rail Vehicles and Transport, Cracow University of Technology, Cracow, Poland ' Reliability and Technical Exploitation Division, Department of Rail Vehicles and Transport, Cracow University of Technology, Cracow, Poland

Abstract: The article focuses on intermodal transport. Developed method was used in article to estimate the most common type of disruptions in supply chain, which turned out to be a cargo theft during road transport, and hence the probability of theft risk appearance, but presented in the article method can be useful to estimate the probability of appearance other types of disruptions in the supply chain. The article presents an outline of a complex method uses ANN for identifying and forecasting disruptions in the supply chain. This method is based on the latest data of disruptions in the supply chain, which allow for appropriate response to supply chain disruptions in order to minimise losses and costs associated with losses. Developed model can be used to support decisions about additional cargo insurance for high risk of theft transport cases or the usage of monitoring systems for the location or parameters of the cargo.

Keywords: intermodal transport; supply chain disruption; supply chain resilience; cargo parameters monitoring; risk appearance in transport chain; intermodal transport risk; cargo theft; numerical modelling; performance analysis.

DOI: 10.1504/IJSTL.2021.112910

International Journal of Shipping and Transport Logistics, 2021 Vol.13 No.1/2, pp.1 - 24

Accepted: 08 Jul 2019
Published online: 09 Feb 2021 *

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