This paper develops heuristic approaches to define the market and measure concentration in the inland transhipment market where different terminal operators compete. These approaches can be used by policymakers to implement more effective policies that could lead to an increase in the market share of intermodal freight transport (IFT). The first approach segments the market using a transport cost analysis. The second approach uses the total trade and the aggregate throughput of the terminals in each IFT demand area. The similarity in results validates the two approaches, suggesting that they can both be used in situations of limited data availability. Applying these approaches to the IFT network of the European Union, we find that inland transhipment markets in the EU are oligopolistic in structure and thus highly concentrated. In general, the north of the EU shows less concentration compared with the central and southern regions of Europe. According to the second approach, transhipment markets have a slightly higher degree of concentration compared with the first approach. Such concentration needs more attention from policymakers so as to develop policies to increase competition and to make economic policies more effective.

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This paper presents a modified Network DEA model (NDEA) to measure the performance of intermodal freight transport (IFT) chains and to find the sources of inefficiencies. The model addresses two challenges in the application of NDEA to the IFT domain: first, the chains may differ in the number of divisions (i.e., transshipment/transportation activities); and second, one needs to define a relevant intermediate service. For purposes of illustration, the model is applied to a particular European IFT network for which the inefficient transport/transshipment segments are identified and discussed.@en

To cope with increasing vulnerability, global business especially chemical manufacturing companies need to actively manage (the risk of) disruptive events in their supply chains. This calls for systematic frameworks to guide their efforts. Further, due to the complexity of today's global supply chains, decision making tools are needed to provide support in different stages of the supply chain disruption management process. This paper presents an agent-oriented simulation framework for disruption management in supply chains. This simulation framework provides a flexible modelling and simulation environment for decision makers to experiment with different types of disruptions and disruption management strategies. The application of the simulation model to support decision-making in different steps of the pre- and post-disruption management processes is illustrated using a lube oil supply chain case study.

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