An Analysis of the Potential for Modal Shift in Freight Transport Using the Logistical Characteristics of Goods
L Tavasszy, TNO and Radboud University Nijmegen, NL; B Lammers, M Jordans, TNO, NL; K Ruijgrok, TNO & Tilburg University, NL
We propose a method to identify the potential for modal shift combining aggregate statistics on transport and regions with disaggregate information on the logistic characteristics of the goods.
For decades, modal shift has been a major objective of freight transport policy, in the interest of reducing the load on the environment, freeing up road capacity and increasing competitiveness. Despite this, apart from very specific niches (e.g. container flows through Rotterdam, Alps crossings), there has been less change in the market shares of rail, inland waterways or short sea, than was expected.
A key reason for this lack of success is that the need for change has been limited from the perspective of the logistics processes that govern the choice of mode. Logistics processes are complex arrangements that also involve production, inventory and handling considerations; they are tuned in on the needs of clients and eventually locked in on certain modes. Until now, companies have shown to be reluctant to consider major changes in the way they run their transport processes. This is slowly changing, however.
Although policy targets for modal shift have softened somewhat, the pressure to consider possibilities for modal shift is more urgent than ever, given the growing demand for responsive and lean logistics, accompanied by the expectation of cost increases in transport due to growing congestion, road charging, emission trading and oil price increases.
The next generation of public policies and private strategies for modal shift has turned much more towards the logistics process, supported by new concepts like ?co-modality? and ?hybrid networks?. This opens up new possibilities, and also requires a new look into the potential for modal shift. We need to look closer into the relevant logistics processes than we have before, whether we study modal shift at the company level or at the level of regions, states and continents.
The question we treat in this paper is what the potential is for modal shift if we take into account the logistics characteristics of goods. Most approaches for assessment of the potential for modal shift have neglected logistics processes in their analysis and instead have relied on probabilistic methods to indicate that certain aspects in the choice process were not included in the model. Other have used more complex micro-level optimization methods, but these have not yet been applied in practice using aggregate data. In our analysis we turn this around, and assume a very simple choice process that does consider logistics variables.
We describe a method to identify the potential for modal shift using statistics of transport flows and additional information on the logistic characteristics of the goods and the regions of origin and destination. The analysis allows us to identify the share of the flows that fits to each individual mode of transport, given the following goods characteristics: transport distance, availability of terminals, packaging and value density, delivery time and shipment size. For all these characteristics we develop simple decision rules to associate goods with possible modes of transport.
In the paper we describe the aggregate and the disaggregate databases, the filtering method developed using the mentioned flow characteristics and the potential for modal shift that results from the filtering process. The results also indicate to which degree the different modes have been able to capture the potential assigned to them. We discuss two logical questions that follow 1) what can be done to capture the existing potential and 2) what is the full potential, once the possibility of logistics re-organisation is taken into account. We discuss how concepts like ?co-modality? and ?hybrid networks? would affect the analysis and identify ways in which this future potential can be forecast. We finalize the paper with a summary of our findings and challenges for future research.
Association for European Transport