The impact of measuring internal travel distances on self-potentials and accessibility

Internal travel distances are fundamental in accessibility measurement, as they affect the weight of the intra-regional interactions, especially when using a gravity formulation. The contribution of the internal accessibility of each zone to its overall accessibility is known as self-potential. Several studies demonstrate its importance in accessibility analyses, especially in the most urbanized regions. It is precisely in urban regions where internal travel distances (measured as travel length, time or cost) are more difficult to estimate due to congestion, which in turn may be influenced by factors such as urban density, urban morphology, network infrastructure, etc. Accessibility analyses usually use coarse estimates of internal distances, generally based on the regions' area and in some cases considering its level of urbanization. In this study we explore different forms of estimating internal travel distances in accessibility analysis and reflect on their advantages and drawbacks. One of the main difficulties that arise when measuring internal travel distances is the lack of data. However, the growing potential of ICTs (Information and communication technologies) in providing new sources of data can be used to improve representativeness of data. In this study we used speed profiles data from TeleAtlas/TomTom to calculate internal travel distances for European NUTS-3 regions and we compare this measure with three other metrics traditionally used in the literature. Following this exercise, we discuss the conditions under which it is advantageous to use more complex measures of internal travel distance. Finally we test the sensitivity of potential accessibility indicators to the combined effect of different internal distance metrics and distance decay factors.JRC.J.1-Economics of Climate Change, Energy and Transpor

Transport demand evolution in Europe – factors of change, scenarios and challenges

In the transport sector, where change comes with inertia and investments are made with a long term perspective, decision makers need to consider how the future may look like in the very long term. The work presented in this paper is a scenario analysis focusing on the evolution of transport demand towards 2050, aiming to identify related challenges for European industrial and policy players. It follows up on the work of other recent attempts to study the future of transport from a European perspective, integrating findings from these studies, updating new trends and applying a specific scenario analysis methodology relying also on expert consultation. The diversity of the scenarios created unfolds aspects of the future transport system with rather different outcomes on issues like the volume of transport, travel motives, the prevalent spatial scales of transport and logistics, people’s preferences towards different transport attributes, the relevancy of the State versus the private initiative in transport production, the level of competition, or the relative importance of environment and resource scarcity in setting an agenda for innovation and regulations. Beyond the subsequent challenges and opportunities identified in this work, the scenarios developed may be a useful basis for individual actors of distinct backgrounds to build their own specific futures, supporting them in defining strategies for the future.JRC.J.1-Economics of Climate Change, Energy and Transpor

Replication Data for: Travel speed changes along the European core road network for the period 1960–2030: an application of octilinear cartograms

Historical road networks in Europe: Shapefiles including the correct geometry and speed of the European road networks from 1960. Methodological description and application in: Condeço-Melhorado, A. M., Christidis, P., & Dijkstra, L. (2015). Travel speed changes along the European core road network for the period 1960–2030: An application of octilinear cartograms. Journal of Maps, (November), 1–4. doi:10.1080/17445647.2015.1088482 doi: 10.1080/17445647.2015.1088482 Three classes of roads (1,2,3), class 1 being highways. Six time periods: 2012, 2000, 1990, 1980, 1970 and 1955 Field NCLASS_xxx is the class of the road in each year (last xxx digits) Travel time is the time (in minutes) to travel the distance (shape_length, in meters) at the speed of the class the road has in 2012.JRC.C.6-Economics of Climate Change, Energy and Transpor

Smart guide on regional transport innovation strategy: Transport innovation roadmaps

This guide provides regions with information and guidelines useful for the development of smart specialisation strategies (RIS3) in transport. The guide follows the six steps for Smart Specialization with a special focus in transport. The six steps include the analysis of the regional context and potential for innovation, the discussion of governance structure, the development of a shared vision about the future of the region, approaches for the selection of transport related priorities for regional development, policy mixes and options for the integration of monitoring and evaluation mechanisms. The recommended process consists of a bottom-up analysis of regional capabilities of the industry and scientific community that needs to be aligned with national and European objectives. At the European level, the Strategic Transport Technological Plan (STTP) identifies ten innovation areas that will be extremely important for the future competitiveness of the transport sector. The guide also analyses different innovation area in the context of RIS3 methodology, showing specific examples and roadmaps on how these could be implemented in the regional innovation strategies. Finally tools are offered to analyse the innovation potential, performance and priorities in the transport sector, such as data and indicators regarding regional transport innovation, as well as methodologies to analyse innovation capabilities of European regions.JRC.J.1-Economics of Climate Change, Energy and Transpor

Border effect and market potential: the case of the European Union

The globalization of population and trade flows yielded an increase of interactions within the international framework. Accessibility indicators are especially suited to represent spatial interaction since they capture two basic factors that determine the amount of flows between a set of places: the opportunities available and the infrastructure used to move those flows. While globalization trends contributed to the weakening of borders, several studies confirm that borders still matter in international trade, and play a significant role in the form of home bias, i.e. a marked preference for domestic products. Still, most studies of international accessibility ignore this fact, thus failing to show realistic results. This paper makes use of gravity equations to calibrate the distance decay parameter as well as a new coefficient to control for the border effect in the market potential indicator. We used official trade data at the country level in the European Union and evaluated different distance metrics in order to obtain a realistic measure of the border effect within the EU. Our results suggest that the border effect in Europe was previously underestimated due to an excessive simplification when measuring distances. While our preliminary results were similar to previous research, once we apply realistic measures of transports cost (either travel time or generalized transport costs) and removed those countries that are highly affected by the Rotterdam effect, we found that European countries trade 15 times more within themselves than with any other European country. Consequently, integrating the effects of borders in accessibility analysis of international scope evidences that the gap between central and peripheral countries is even larger than expected.JRC.J.1-Economics of Climate Change, Energy and Transpor

Distributive effects of new highway infrastructure in the Netherlands: the role of network effects and spatial spillovers

Network effects and spatial spillovers are intrinsic impacts of transport infrastructure. Network effects imply that an improvement in a particular link in a network generates effects in many other elements of that network, while spillover effects can be defined as those impacts occurring beyond the regions where the actual transport investment is made. These two related effects entail a redistribution of impacts among regions, and their omission from road planning is argued to cause the systematic underestimation of the profitability of transport projects and therefore the public financing they require. However, traditional transport appraisal methodologies fail to consider network and spillover effects. In this study we focus on the spillover impacts of two highway sections planned in the city region of Eindhoven, located in the Dutch province of Noord-Brabant, a region with traffic congestion problems. The new road infrastructure will be financed mainly by national government, the province and the urban region of Eindhoven (‘Stadsregio Eindhoven’), which consists of 21 municipalities. We measure the benefits of the additional links in terms of travel time savings and the accompanying monetary gains. The results show that important spillovers occur in those municipalities close to the new links. The province of Noord-Brabant will benefit the most. We also found important spillovers in the province of Limburg. This latter province will benefit from reduced travel times without contributing financially to the establishment of the analysed new road links.JRC.J.1-Economics of Climate Change, Energy and Transpor

Road pricing in the European Union: direct revenue transfer between countries

In 2011 the ‘Eurovignette’ directive on distance-based road pricing in Europe was finally passed by the European Parliament and the European Council. Although this will bring benefits to the environment and contribute towards financing the cost of maintaining road infrastructure, it will also have negative effects on trade because of the increased costs of accessing markets. This study measures the transfer of revenue (spatial spillovers) derived from the introduction of the Eurovignette directive using a Geographic Information System (GIS). A spatial spillover matrix is obtained that reflects the cost of toll fees on exports paid by each country for the use of roads in each of the other countries. From this spillover matrix between countries and calculation of the repercussion of the fees on the final price of exports, it is possible to know which countries are winners and which are losers as a consequence of introducing a common road pricing policy.JRC.J.1-Economics of Climate Change, Energy and Transpor

Generalized transport costs and index numbers: A geographical analysis of economic and infrastructure fundamentals

We rely on the economic theory approach to index numbers to improve the existing definitions and decompositions of variations in generalized transport costs (GTCs). As a value index, we decompose GTCs into price and quantity indices associated to economicmarketcosts and infrastructure variablesdistance and time within a network. The methodology allows the accurate identification of the sources of GTCs decline. We illustrate it for the case of road freight transportation in Spain between 1980 and 2007 and at a highly detailed geographical level. Average GTCs weighted by trade flows have decreased by 16.3%, with infrastructure driving that reduction. We find large territorial disparities in GTCs, but also significant geographical clusters where the market and network indices show spatial association.JRC.J.1-Economics of Climate Change, Energy and Transpor

Integrating Network Analysis with the Production Function Approach to Study the Spillover Effects of Transport Infrastructure

The production function approach is used to analyze the role of transport infrastructure on regional GDP using new definitions and measures of road network capital stock that represent the real benefit obtained by regions when accessing markets. Improving the existing methodologies, we weight the infrastructure stock with trade data so as to estimate the direct effects on production of a region’s own infrastructure (what we term internal stock), as well as the spillover effects that it receives from using that of neighboring regions (imported stock). We illustrate our methodology using Spanish data for the 1980-2007 period and calculate these internal and imported infrastructure stocks using GIS network analysis based on generalized transportations costs. With this new dataset we perform successive regressions controlling for endogeneity and compare the obtained results to those of previous research. We confirm the validity of this methodology and the existence of significant and rather large spillover effects that even outweigh the effect of the internally endowed capital stock on aggregate production. On average the relative magnitude of the spillover effects to that of the internal (own) stock effect increases with the level of territorial disaggregationi.e., it is larger for provincial data than for regional data. Unfortunately, we also find that spillover effects are asymmetric, exhibiting negative values for poorer regions, as they do not profit from the capital stock existing in their neighboring areas as their richer counterparts do, thereby casting doubts on the cohesion effects attributed to transport infrastructure investments.JRC.J.1-Economics of Climate Change, Energy and Transpor