Classification of disruptive events

The transport network in Europe is facing severe and frequent disruptions due to the dynamic geo-political situation in the region, as well as the effects of climate change. The EU Horizon project Resilient Multimodal Transport Networks (ReMuNet) is focused on improving the resilience of the transport network, considering alternate routing options, and identifying disruptions and ways to mitigate their effects.
One of the four core objectives of the ReMuNet project is to develop a standardized methodology to describe multimodal transport networks. The proposed standard is derived from existing approaches and developed together with critical stakeholders to ensure Europe-wide practicability and acceptance. This allows for the standard to be easily transferred into appropriate regulatory frameworks ensuring more efficient communication and operational stakeholder interconnectivity. The first task towards this core objective is Task 1.3: Creating a typology of disruptive events, which is addressed in this report. Building on existing typologies, for example classifications of disasters, this report analyzes disruptive events in European transport networks for a better understanding of the disruptions, the potential reactions to them and the actions to prevent them from occurring and to mitigate their effects.
As a first step in this research, the team at HUMLOG Institute (Hanken School of Economics) conducted an interview study to 1) define disruptive events from the perspective of logistics operators and key stakeholders, 2) to identify frequently occurring and severe disruptive events and 3) to understand standard practices of managing these disruptive events. One of the key findings from this study was that although stakeholders have different definitions for disruptions, their thoughts on disruptions converge to thematic groups such as viewing disruptions as blockages, delays, or change in business-as-usual. The other important result included the viewpoints of participants on what they considered to be the vulnerable link in the EU transport network, and a majority highlighted the railways. The analysis revealed that railways were considered critical for achieving the goals of sustainability and yet, they were sensitive to infrastructural damage and irregularities in energy pricing. Another insight offered was that the managers often prioritized impact and response of disruptions over an analysis of root-causes. This is because of the financial pressures that govern the operational practices.
The viewpoints of various stakeholders including terminal operators, freight forwarders, software system developers, rail, road, and shipping operators, government agencies, and consultants are considered in defining the key terminology related to disruptions in the EU multimodal freight network. The typology developed here highlights ten different categories of causes, as well as dimensions of disruptive events, and their impacts on individual actors, nodes, links, the entire transport network, and cascading effects on supply chains and society. This study is an important exercise to achieve the ultimate goal of the project: the building of a collaborative platform and taking the first steps towards an Artificial Intelligence (AI) based self-learning transport network to promote synchro-modal relay transport across European rail, road, and inland waterways to improve network resilience, reduce emissions, and boost corridor efficiency during disruptive events. The terminology and classifications developed in this qualitative study will be a critical input to the mathematical models that follow in subsequent work packages.