Transport Management

Almost half of logistics costs in Europe are transport costs. Consequently, an efficient and effective planning and execution of transportation activities is of high importance for logistics service providers and industrial and commercial companies. Megatrends such as urbanization lead to new demands for distribution activities in cities and the increasing volatility of markets complicates capacity planning. On the other hand, digitalization and the resulting availability of data offer new possibilities for transport planning and dispatching support. Besides an improvement of existing services in transportation, also new services can be developed based on Big Data.

The focal point of the research focus “Transport Management” are intermodal transport chains which are characterized by a high division of labor. The seemingly simple division in pre-, main- and on-carriage unifies different actors and therefore includes a diversity of specialized companies. In these systems which are characterized by a high division of labor an efficient and effective data exchange between actors is of high significance. However, also unimodal road freight transport requires special attention regarding the organization and execution of transports considering the high competition and low profit margins in the sector.

The research in the research focus aims to methodically support cross-company planning of transport chains. By simulating the flow of goods and information, planning alternatives are analysed regarding economic as well as other performance criteria. Thereby, the focus is placed in particular on the behavior of actors concerning the choice of different transport alternatives and the transfer and use of information along the transport chain.

Selected Research Questions

  • How can uncertainties existing in transportation be considered in planning and evaluation of transport chains?
  • Which influence do time slot management systems in road freight transport have on the costs of relevant actors?
  • Which drivers and barriers are crucial for potential users of new technologies (transport equipment and IT systems) for their investment decision?
  • How can dispatchers be supported by data driven transport planning and execution (Big Data)?
  • What is the influence of cross-company information systems and connected information exchange on the efficiency increase in order processing?
  • Which factors influence the decision behavior of different actors in mode choice decisions? Which of these factors are crucial concerning the choice of intermodal transport chains?

Research Topics

Whereas the planning of transport networks without delays and with constant volumes is comparably easy to realize, the consideration of uncertainties in transportation represents a challenge. In this context, the methodology of simulation is an adequate tool to consider deviations and stochastic influences in the design of transport networks. Subject of this research topic is therefore a suitable consideration of uncertainties in the planning of transport networks. Besides an improved planning of existing services in transport networks, new services that account for the increased requirements regarding delivery performance are developed.

For the execution of transports, new technologies are constantly being developed which are supposed to improve the efficiency (e. g. fuel consumption) of transport vehicles or the interoperability between transport modes. Similarly, driven by digitalization, new information systems (e. g. community systems) are being developed to improve information exchange between actors along the transport chain. Even if the technical systems appear to be ready for use from the supplier’s view, it does not automatically mean that these systems are implemented by actors in the transport chain and establish themselves in the market. Therefore, the focal point of this research topic is the economic evaluation of these systems and the investigation of drivers and barriers for an effective and efficient human-machine interaction.

With regard to the often highly utilized infrastructure, an efficient use of transport capacitates especially on roads and railways gains increasing significance. In this context, a target-oriented evaluation and processing of increasingly available data (Big Data) allows an improved planning and use of transport capacities. Subject of this research topic is the question how historical information (e. g. about seasonal variations in transportation demand) and status information can be used to support dispatchers.

With the advances in digitalization and possibilities of cross-company information sharing, order processing in transport chains is increasingly improved by new technologies. Nevertheless, especially in intermodal transport chains, there are big challenges (complex interface management, different business models and individual design of business processes, amongst others) for the reduction of information asymmetries among companies. In addition, technical solutions require a homogenous understanding of processes. Cross-company process analyses and simulation studies are used to analyse order processing in transport chains in terms of potentials for an increase in efficiency.

A rational evaluation of transportation costs and transit times plays an important role for mode choice decisions. However, the pure evaluation of costs often does not reflect the actual actors’ decision making (esp. shippers and forwarders). To comprehend the concrete choice of uni- or multimodal transport chains an analysis of the complex decision behavior is indispensable. On the one hand, the behavior is determined by the decision logic of the used software systems which consider objectively measurable criteria. On the other, also human behavioral patterns and preferences should be considered. Subject of this research topic is the systematic uncovering of rational and human factors that affect the mode choice decisions.