Exploitable results Projection tools and trend estimations for transport options In general, the outcome or impact variables estimated with the use of transport models are quite limited. On the other hand, only a minimum set of policy variables, selected according to the policy objectives, can be considered along with the 'external forces driving structural changes' (the EDSCs). In this context the definition of a 'common scenario' is essential and often a prerequisite for a common understanding of the potential impact of a certain policy. In the 'Thematic network for understanding mobility prediction' (Think-up), a distinction was made between 'external' scenario variables related to the socio-economic environment and 'transport policy' scenario variables. In the definition of each scenario, it was not enough to concentrate on macro-economic variables. Other variables such as urbanisation, household income distribution and sectoral changes mediate the effects of those factors that drive structural changes and help to understand the dynamics of the interaction. This detailed analysis has been useful in defining the input data for the prediction model developed during the 'Expert system-based predictions of demand for internal transport in Europe' (Expedite) project. With regard to the choice of the prediction model, there are four European models which can cover the impact of different policies. It is possible to use all four of these as they stand and eventually combine them in order to identify differences in the outcome of each model as well as the reactions between them. During the consultations that took place within the Think-up network, state-of-the-art modelling tools were presented by their designer and users. Subsequently, a specific 'task force' was charged with the comparison between the input and output of national and European models. Differences were pointed out between traffic reference data and the hypothesis for socio-economic and transport variables. These deviations partly explained the differences observed between mobility predictions and modal shift estimations. In addition, it was shown that certain types of models are better suited than others for the assessment of traffic generation and geographic distribution, modal split or network assignment. This allowed in turn exploration of the possibility of integrating specific policy variables in the prediction process. All the above-mentioned analyses were conducted for passenger and freight transport, national and European models. However, in the case of passenger transport, the focus was set on national models. This allowed for the integration of detailed information about the competition between air transportation and human service transportation (HST) into the meta-model developed by the Expedite project. The latter is suitable for short- and medium-distance travel. For freight transport the European transport forecasting model and appended module 'Scenes' was used instead. In conclusion, important results were derived from the use of different tools which can improve the current understanding of modal shifts in transportation. The Think-up workshops highlighted the need for a common set of data and a set of workable scenarios which would reflect transportation in the current European context. The results of different models with the same set of input data could then be compared with the aim of evaluating alternative scenarios for the development of the transport system. Moreover, experts would share a common understanding and come to a consensus on the segmentation of the transport market. Analysis of passenger transport markets Concrete conclusions as regards the development of rail services can be derived from discussions on the evolution of the air market. The emerging market for low-cost airlines and the enormous growth rate of this new market segment may aggravate the problem of unequal fiscal treatment for the two modes of transport. While the level of value added tax (VAT) for international rail trips differs from country to country, international airline tickets are not subject to VAT. Furthermore, rail companies have to pay fuel taxes, while airlines have access to untaxed fuels. In the future, the tariff plans for long-distance rail services in Europe will be driven more and more by a yield management system, which allows quick reactions to changes in the price policy of competitors. However, the presently prevailing inequality in the financial treatment for these two modes of transport will most probably result in a market distortion. An additional conclusion that was derived during the 'Thematic network for understanding mobility prediction' (Think-up) workshops was that there is a close relationship between land-use patterns and the opportunities of public transport operators to provide efficient and user-friendly services. In several cases land-use and the settlement structure have prevented public transport operators from establishing an efficient public transport network. It is therefore necessary to develop an integrated transport policy, which will combine the transport infrastructure planning with land-use planning. If mobility was considered to be more than just a means of reaching a certain destination - a utility of its own - it could not be explained entirely by means of objectively measurable utilities. For example, the demand for mobility cannot be completely defined by the attractiveness of a certain destination. This view on mobility was suggested during the Think-up workshops and led to the conclusion that there is a substantial share of mobility, which is related to patterns totally different from those usually presumed and thus eludes the classical measures. Furthermore, it has been stressed vigorously that individuals' decisions are not only based on a 'minimising the generalised cost' or 'maximising utility' concept. They are also - and in some cases to a considerable extent - driven by subjective perceptions, constraints, attitudes and values, life-style, the prevailing image of a transport mode, and the level of information on the available services. Rail and public transport are likely to be less preferred, mainly because the level of information on public transport services is at a remarkable low level. Moreover, the complex tariff structures of public transport systems often discourage potential users. As a consequence, 'hard measures' (i.e. changes in costs of different modes of transportation) which have been introduced in the past did not necessarily result in the expected results. This was not only due to the lack of flexibility of human behaviour, but it is also because transport policy measures lack the essential influence on the general public. Finally, a holistic approach will need to be adopted in order to achieve a modal shift. It should combine classical transport policy measures with 'soft measures'. For example, awareness-arising campaigns which will aim to improve the image of public transport modes. Particularly in the competitive field of passenger transport in urban areas, it is crucial that public transport operators provide sufficient information about the transport services available. Furthermore, a user-friendly and easy-to-understand tariff system should be applied. The marketing and public relations departments of transport operators can play an important role in changing the public image of transport modes, as well as providing enough and reliable information on services and tariffs. Segmentation of demand and supply of freight transport markets Distribution includes all the operations taking place from the production site until delivery of products to the final customer. The 'Thematic network for understanding mobility prediction' (Think-up) project partners identified a distinct trend in the decision-making process that affects transportation organisation. The generalisation of 'just-in-time practices' leads to smaller and more frequent shipments. Furthermore, 'just-in-time' implies stringent requirements which may apply to intermediate products, because these can be subject to tight industrial supply chain constraints (i.e. a delay can disrupt a production process). Since the development of information systems which speed up the flow of information, this trend has been more pronounced. On the other hand, strategic decisions are influenced by the number and the geographical situation of the distribution centres, which can be warehouses, depots or platforms. They lead to more or less centralised distribution structures. These centralised structures allow for a reduction in warehousing costs as well as inventory-carrying costs. As a consequence, pan-European warehouses are preferred to national warehouses. Local depots near consumer markets are also being replaced by platforms for the storage of high turnover rate products. This general trend, which also depends on the characteristics of the product, leads to longer distances and more international transport flows. The Think-up project partners have verified that there is flexibility in the organisation of the logistics system which should be considered independently of the industrial production context. In the production organisation, the following general trends were identified: - sub-contracting intermediate stages of the production process develops links within the industrial production system, and therefore increases product transportation. However, it seems that large firms tend to reduce the number of their suppliers. Still, an increase in the concentration of production together with a reduction in the number of plants can lead to longer average distances of transport; - specialised production units replace consistently multi-product plants dedicated to national/local markets; - production units are being relocated when a highly specialised workforce is no longer needed. A more detailed logistics analysis revealed that - Changes in industrial logistics require a sectoral approach and a segmentation per product type. In particular, the segmentation per product type seems more suited. - Changes in distribution logistics necessitate a reorganisation of distribution centres at European and regional level, and sometimes 'proximity' distribution centres for urban freight transport. This last measure takes into account the spatial dimension of the freight transport segmentation. Nonetheless, transport logistics requirements will need to be introduced with different conditioning constraints in order to give a more precise understanding of competition between modes of general cargo transportation. But this is possible only when the type of product is of comparatively little importance. - For a policy impact analysis, all alternatives modes have to be taken into account and not only rail transport. Inland waterways and short sea shipping should not be forgotten. For this purpose, a policy impact matrix has been proposed. Comments from the participants of the Think-up project workshops are expected on this first attempt to assess policy impacts on specific segments. - The policy implementation (or policy context) cannot be assessed without considering the principal actors, the transport operators and industrialists who can exert a powerful influence on policy through lobbying. Policy variables for mobility prediction Mobility prediction at a European level has made considerable progress in the past few years, in particular thanks to the support for research and technological development (RTD) provided by the Fourth and Fifth Framework Programmes of the European Commission. A major challenge in mobility prediction is the integration of (transport and non-transport) policy concerns in strategic models. These could entail a description of the driving forces of structural change and a comparative testing of policy options, packages or modules and their impact on transport. The consultations on this topic, which have taken place in the framework of the 'Thematic network for understanding mobility prediction' (Think-up) project, have shown that there will always be a certain gap between the policy assessment and mobility prediction with the use of models. This gap is mainly due to differences between these two exercises as well as constraints of the technical tools used or the non-availability of comparative data. It can however be reduced through the development of strategic models with a stronger conceptual and theoretical basis and more importantly, a better understanding of the policy formulation process. A better understanding of the policy formulation process can, in turn, be achieved through setting up of multi-disciplinary teams that will promote knowledge transfer across disciplines as well as national borders. Searching for OpenAIRE data... There was an error trying to search data from OpenAIRE No results available
