Search

A key feature of the modern space-economy is the transition to a networked society, where interconnectivity and interoperability between the different economic systems play a significant role (Reggiani and Schintler 2005). Consequently, there is a consensus among scientists on the idea that many spatial economic phenomena can be described by a network of interactions among agents (Friesz 2007; Reggiani and Nijkamp 2006). Surprisingly, even though the application fields are quite different and the networks are space–time complex, these networks often show common behaviour, based on their topological characteristics. In other words, the topological properties of a network can give useful insights on how the network is structured, which are the most “important” nodes/agents, and how network topology can influence the conventional spatial economic laws (such as, equilibrium theory, spatial interaction theory, etc.). In sum: “the topology (or architecture) of the interaction is an essential part of many processes and it cannot be ignored without missing a crucial ingredient of the phenomena at hand” (Vega Redondo 2006). Such network embedding is important, for example, to understand how transportation networks are resilient, or how commuting flows and employment are related in modern labour markets, or how hierarchical land use patterns develop over time. Interestingly, the analytical tools developed in this context seem to be quite ‘simple’, mostly devoted to searching for and extrapolating some ‘order’ principles in the complex networks under analysis. In addition, they seem to revisit—in a network framework—the main laws of spatial economics developed in the 1960s– 1970s (e.g. the spatial interaction-entropy models conceived of by Wilson 1967). For example, if we find—in certain complex network typologies—the well-known Netw Spat Econ (2007) 7:297–300 DOI 10.1007/s11067-007-9033-8

The value of travel time savings (VTTS), is one of the key variables which are taken into account when several alternatives leading to different travel times are considered. In the case of households, VTTS is related to the monetary value that is attached to the possibility to save a determined amount of travel time that can be reallocated to other activities. In the case of public administrations, VTTS is one of the most important benefit categories aimed at justifying the investments in transport infrastructures that can allow people to save travel time. The relevance of VTTS has availed various economic studies displaying an analytical as well as an empirical framework both in the European Union and in North-American countries. The present paper aims at providing a meta-analysis of a selection of the studies related to the VTTS in passengers’ transport. It will introduce a brief history of meta-analysis (from its first applications in medical science and psychology to its recent use in spatial economics) and of the microeconomic models used in VTTS estimations. It will also identify the factors that are statistically relevant with respect to the VTTS and it will provide a meta-analytical estimation of the selected studies, with a particular emphasis on the similarities and on the differences among European and North-American studies.

The spatial activity patterns of firms in a multi-regional system are closely connected with the structure and evolution of regional labour markets. Based on an extensive data set (cross-section) on commuting flows in Germany, this paper aims to identify the relationship between entrepreneurial activity and spatial labour markets, by employing in particular the concept of 'entrepreneurial city'. A network connectivity model is adopted to assess connectivity patterns, using the power-law and exponential law as a statistical test framework, in order to detect the presence of economic activity hubs that may resemble the concept of entrepreneurial cities. Various results are presented and interpreted in the final part of the paper. © Springer-Verlag 2007.

This special issue explores the dynamic relationships between transport network design and agents' preferences by outlining the relevance of the spatial components. The seven papers in this volume focus on both changes in the spatial network connectivity structure and changes in consumer preferences/choices due to policies at different spatial levels. The goal is to provide a prospective review on new methodological directions in analyzing transport networks, spatial choices and their related policy implications within the framework of recent European policy interventions and transportation research developments.

The value of travel time savings (VTTS) has been investigated by transport economists since the mid‐1960s. Although the first two decades of research were mainly devoted to VTTS in passenger transport, since the mid‐1980s several studies have analysed the VTTS in freight transport from both a theoretical and an empirical viewpoint. The first part of the paper is devoted to a review of the proposed theoretical models for the value of freight travel time savings (VFTTS), and it discusses the issues arising from the use of different methods to collect empirical VFTTS estimates. The second part is based on a meta‐analysis of a sample of empirical VFTTS observations related to several European and North American countries. It is shown that both the per‐capita gross domestic product and the transport mode are statistically significant variables that can partially explain the variability in VFTTS estimates.

The paper aims to analyse and compare synthetic indices of accessibility in order to measure the impact of high‐speed trains on European cities. In particular, it considers the data and results concerning two previous articles by Gutierrez et al. and Martin et al. that analyse the accessibility gains produced by the construction of Trans‐European Transport Networks (TEN‐Ts). In these two papers, accessibility is studied using, first, a partial approach with three different indicators: location, potential market, and daily accessibility; and, second, data envelopment analysis (DEA) to calculate a synthetic index of global accessibility. The present paper extends these studies by applying principal component analysis (PCA) to obtain a new synthetic accessibility index. DEA and PCA are two good candidates to synthesize the partial information provided by different methods that have been employed in the previous literature that studies accessibility. It is shown that DEA and PCA methodologies yield a...

The analysis of complex networks has recently received considerable attention. The work by Albert and Barabási presented a research challenge to network analysis, that is, growth of the network. The present paper offers a network analysis of the spatial commuting network in Germany. First, we study the spatial evolution of the commuting network over time. Secondly, we compare two spatial interaction model (SIM) specifications, in order to replicate the actual network structure. Our findings suggest that the commuting network appeared to become more dense and clustered, while the SIMs seem to require more sophisticated specifications, in order to replicate such a connectivity structure. © Springer Science+Business Media, LLC 2007.

The modern spatial economy has a global “networked” character that is generating important socio-economic and political changes. In this respect, new forms of connectivity play a significant role through their dynamic and complex interplay with the economic and political driving forces behind globalization. In analyzing such impacts, it is useful to consider the tools and models that have been adopted in regional economics as well as in other disciplines. In this context, it is also necessary to reflect on complexity theory and on the models able to map out the complex interconnected spatial networks. This chapter begins with a concise review of the most important definitions of complexity, in the light of their relations with spatial networks. There follows an exploration of the main findings from two “close” disciplines, that is, spatial economics and network science, with reference to their associated approaches and modeling tools which are able to grasp complexity from, respectively, the behavioral and the network structure viewpoint. The emerging discussion – with reference to both static and dynamic frameworks through the lens of complexity issues – indicates that (i) a formal correspondence between the fundamental spatial economic models and network models exists and (ii) this correspondence highlights the “simplicity” of the laws underlying complex spatial networks.

In this paper, a set of neural network (NN) models is developed to compute short-term forecasts of regional employment patterns in Germany. Neural networks are modern statistical tools based on learning algorithms that are able to process large amounts of data. Neural networks are enjoying increasing interest in several fields because of their effectiveness in handling complex data sets when the functional relationship between dependent and independent variables is not specified explicitly. The present paper compares two NN methodologies. First, it uses NNs to forecast regional employment in both the former West and East Germany. Each model implemented computes single estimates of employment growth rates for each German district, with a 2-year forecasting range. Next, additional forecasts are computed, by combining the NN methodology with shift-share analysis (SSA). Since SSA aims to identify variations observed among the labour districts, its results are used as further explanatory variables in the NN models. The data set used in our experiments consists of a panel of 439 German (NUTS 3) districts. Because of differences in the size and time horizons of the data, the forecasts for West and East Germany are computed separately. The out-of-sample forecasting ability of the models is evaluated by means of several appropriate statistical indicators.

Accessibility has been the focus of many studies in recent decades. The widespread adoption of the accessibility concept demonstrates the originality of Hansen’s (1959) and Weibull’s (1976) vision. They were the first to define accessibility systematically. In essence, these two authors interpreted and modeled accessibility as the potential opportunities which can be reached from a given place by paying a certain generalized and space/time based cost. It is worth saying that the vast number of authors that have so far adopted – and still adopt potential accessibility is the best proof of the efficacy and elegance of this approach. Many review studies emphasize the relevance of this definition of accessibility from both the theoretical and empirical viewpoint (see inter alia Baradaran & Ramjerdi, 2001; De Montis & Reggiani, in press; Geurs, Krizek, & Reggiani, 2012; Geurs & Wee, 2004; Handy & Niemeier, 1997; Jones, 1981; Reggiani & Martin, 2011; and Wu & Hine, 2003). Thus accessibility appears to be a useful tool for best practice and planning (Geurs et al ., 2012). In this context, a line of research is clearly devoted to the accessibility of urban systems. There is interesting specialization in the scientific literature on accessibility in an urban setting. Lau and Chiu (2004) study the influences of land-use policy and public transport system development on their accessibility to workers. Many investigations relate accessibility to the following urban public goods: public spaces (Lotfi & Koohsari, 2009; Pasaogullari & Doratli, 2004), opportunities of access to space and time for one or multiple persons (Neutens, Versichele, & Schwanen, 2010), metro systems (Prasertsubpakij & Nitivattananon, in press), labor markets (Reggiani, Bucci, Russo, Haas, & Nijkamp, 2011), streets (Travencolo & Costa, 2008), services (Vasconcelos & Farias, 2012), and green spaces (Wright Wendel, Zarger, & Mihelcic, 2012). Starting from the above considerations, reflections on the role of accessibility in the analysis and planning of urban settlements certainly remain valid arguments that are worth exploring. This is the rationale which characterizes the articles included in this Special Section. To be more precise, Caschili and De Montis (2013) analyze accessibility in the US commuter system; Monzon, Ortega, and Lopez (2013) analyse accessibility in terms of the impact of the Spanish high speed rail system on urban areas; Ratner and Goetz (2013) study the accessibility of transit-oriented development, as well as its impact on urban morphology and land use; Bentlage, Luthi, and Thierstein (2013) consider the accessibility of German agglomerations with respect to physical and non-physical connectivity; and, finally, Tranos, Reggiani, and Nijkamp (2013) construct an index of digital accessibility to European cities. These contributions have been originally selected from among the papers presented in a ERSA-NECTAR1 Special Session on Accessibility and Spatial Patterns organized by Andrea De Montis and Aura Reggiani under the aegis of the ERSA 50th Conference held in Jonkoping (Sweden) on 19–23 August, 2010. Table 1 can be used to link the five articles collected in this Special Section. In detail, in Table 1, the papers collected in this Special Section are classified according to the following main features: 1. Transportation system indicates to which transportation context the authors are referring. 2. Country elucidates the national context under analysis. 3. Socio-economic variable refers to the categories of people that are analyzed in their mobility/accessibility choices. 4. Spatial context explains the level of spatial organization of the data. 5. Time period reports the time span when the data were collected. 6. Methodology indicates the analytical tool(s) adopted for constructing the accessibility measures. 7. Accessibility measurements/proxy reports on the measurements used to calculate the level of accessibility.

Self-Organised Criticality (SOC) is a concept developed over the last decade from dynamic systems analysis that aims to investigate the transition trajectories of evolutionary systems. The main emphasis in SOC is on the analysis of the impact of slow exogenous forces in combination with strong localised interactions between single elements or components of the systems concerned, with particular regard to the attainment of a critical state at the macro-level. Against this background, SOC serves to identify the critical conditions from the internal dynamics of the systems that lead to major and significant transformations of their behaviour. The present paper aims to offer insights and reflections originating from the SOC concept, as well as to explore its potential contribution to understanding the evolution of regional economic patterns, in particular the functioning of regional labour markets. In our study, the evolutionary dynamics of employment at a district level in West Germany as well as in the combined West and East German setting will be investigated, in order to detect the possible existence of a power law distribution of growth rates, which may be seen as an indication for SOC at the macro-economic level. In this context, SOC may help to explain the presence of large socio-economic regional fluctuations in a country, and, in general, the dynamics inherent to regional development.

This paper develops a flexible multi-dimensional assessment method for the comparison of different statistical-econometric techniques based on learning mechanisms, with a view to analysing and forecasting regional labour markets. The aim of this paper is twofold. A first major objective is to explore the use of a standard choice tool, namely Multicriteria Analysis (MCA), in order to cope with the intrinsic methodological uncertainty on the choice of a suitable statistical- econometric learning technique for regional labour market analysis. MCA is applied here to support choices on the performance of various models – based on classes of Neural Network (NN) techniques – that serve to generate employment forecasts in West Germany at a regional/district level. A second objective of the paper is to analyse the methodological potential of a blend of approaches (NN-MCA) in order to extend the analysis framework to other economic research domains, where formal models are not available, but where a variety of statistical data is present. The paper offers a basis for a more balanced judgement of the performance of rival statistical tests.

The concept of resilience has been receiving both theoretical and empirical attention in recent years, from different disciplinary fields, including spatial economics where resilience is becoming a ‘popular’ term. In particular, the concept of spatial economic resilience seems to assume slightly different interpretations. Starting from the basic definitions of resilience, which stem from ecology, this paper aims to highlight the similarities and the differences in the various analyses of resilience, in order to offer some insights into its use in the spatial economics literature.

Accessibility is a concept that has become central to physical planning and spatial modelling for more than fifty years. As measure of the relative nearness or proximity of one place and persons to all other places or persons, conceptually linked to Newton's law of gravity, its origins can be traced back to the 1920s when it was used in location theory and regional economic planning (Batty, 2009) and retail planning (Stewart, 1948). In his classic paper, Hansen (1959) was the first to define accessibility as a potential of opportunities for interaction and applied the concept to forecast employment developments in Washington D.C. Hansen's gravity-based measure of accessibility was a generalization of the concept of population potential, which was based on the notion of potential in physics systems by Stewart (1948). Since then, accessibility analyses have addressed the issue of spatial interaction. Spatial Interaction Models (SIMs) provide an explicit link between accessibility modelling, and economic, demographic and transport flows. SIMs have a long history and have been used in a wide variety of contexts. Wilson (1970) gave SIMs theoretical strength by deriving them using the entropy maximization approach, and the doubly-constrained form formed the bases for transport flow modelling. The formal equivalence between SIMs and logit models/micro-economic theory was shown by Anas (1983). The accessibility function can be directly derived from SIMs and it therefore contains SIM behavioural cost components ( Reggiani, 2014). Moreover, the relevance of topological/connectivity structures in the accessibility analyses has, in some way, been anticipated by Weibull (1980), who considered accessibility as a property of configuration of opportunities for spatial interaction. Accessibility models have in the past decades been applied in several academic fields such as urban geography, rural geography, health geography, time geography, spatial economics and transport engineering. Many different applications have been developed in these fields and can be categorized in several ways. Here, we use the categorization of accessibility measures from the well-cited review paper from Geurs and Van Wee (2004). They provide an overview of components of accessibility and perspectives on accessibility, which we will use as a categorization of accessibility measures. Geurs and Van Wee distinguish four basic perspectives on accessibility: (i) infrastructure-based measures, analyzing the performance or service level of transport infrastructure, (ii) location-based measures, analyzing accessibility of spatially distributed activities, typically on an aggregate level, (iii) person-based measures, founded in the space-time geography, analyzing accessibility at the level of the individual level, and (iv) utility-based measures, analyzing the welfare benefits that people derive from levels of access to the spatially distributed activities. These perspectives focus on one or several of the four components of accessibility distinguished by Geurs and Van Wee: (i) the land-use component reflecting the amount, quality and spatial distribution of opportunities, (ii) the transportation component describing the disutility of travel in terms of time, cost and effort, (iii) the temporal component reflecting the temporal constraints and variability, and (iv) the individual component reflecting the needs, and abilities of individuals. Here, we describe the directions which academic literature in the recent years took to improve the treatment of the four components in accessibility modelling.... Language: en

The regional economics and geography literature on urban population size has in recent years shown interesting conceptual and methodological contributions on the validity of Gibrat’s Law and Zipf’s Law. Despite distinct modeling features, they express similar fundamental characteristics in an equilibrium situation. Zipf’s law is formalized in a static form, while its associated dynamic process is articulated by Gibrat’s Law. Thus, it is likely that both Zipf’s Law and Gibrat’s Law share a common root. Unfortunately, empirical investigations on the direct relationship between Gibrat’s Law and Zipf’s Law are rather rare and not conclusive.The present paper aims to answer the question whether (a generalisation of) Gibrat’s Law allows us to infer Zipf’s Law, and vice versa? In our conceptual and applied framework, particular attention will be paid to the role of the mean and the variance of city population as key indicators for assessing the (non-) validity of the generalised Gibrat’s Law.Our empirical experiments are based on a comparative analysis between the dynamics of the urban population of four countries with entirely mutually contrasting spatial-economic and geographic characteristics: Botswana, Germany, Hungary and Luxembourg. We arrive at the following results: if (i) the mean is independent of city size (first necessary condition of Gibrat’s law) and (ii) the coefficient of the rank-size rule/Zipf’s Law is different from one, then the variance is dependent on city size.

In recent years, the complex dynamics of local as well as global transport networks have attracted ever increasing attention due to reports of their multiple failures and deleterious impacts, which have often occurred during disruptive events. Not only have hazards recently increased in complexity and intensity but their impacts are also no longer confined within the local boundaries of specific transport operations, and instead more widely affect global connections and accessibility. The above mentioned merge of characteristics within transport systems has compelled scholars and practitioners to place great emphasis on exploring transport systems from different perspectives of resilience and vulnerability. Research findings from the analyses on the various dimensions of transport resilience and vulnerability now allow us to better understand the similarities and differences in systems, but more importantly, they have opened the way for researchers to relate concepts of resilience and vulnerability with those of interdependency and connectivity/accessibility. From this stand point, it seems necessary to reflect on the relevance of transport network resilience and vulnerability by exploring definitions, interpretations and applications from different methodological/empirical angles and perspectives. This is the platform which has paved the way to this Special Issue (SI).

According to the Annual Disaster Statistical Review of 2012, the average number ofnaturally-triggered disasters occurring within a period of 1 year is about 300 events, inwhich over 100,000 people are killed as a consequence of their impacts. The statisticsofdisastersshedlightonimportanttrendsarising,ofwhichthetwomostsalientarethatdeveloping and emerging economies suffer the most from human losses, and that thecosts of natural disasters are escalating over time. In 2012 the Hurricane Sandy, one ofthe most ever expensive natural disasters in the United States, created damages forapproximately US$ 50.0 billion (Guha-Sapir et al. 2013). Both natural and man-madedisasters may have various spatial effects (from local to global scales) which reverber-ate for hours and even years when the damages affect the backbone of a system. Thusinvestigating these phenomena represent a complex but compelling issue. In the aim topredict and minimise the substantial economic losses generated by disruptive events,the attention of scholars, practitioners and policy makers is nowadays turning squarelytoward such concepts as resilience, vulnerability, robustness, and reliability of econom-ic spatial systems (Rose 2009).In essence, resilience refers to the capacity of a network: a) to retain its organiza-tional structure following the perturbation of some state variable from a given value; b)to adapt itself to new states; thus evolution is formed by the switch of these resilientnetworks from one equilibrium state to another. These definitions stem from ecology(for a review, Reggiani et al. 2002). The main question is then how fast and efficientlythe network returns/shifts to steady states. Vulnerability research stems, by contrast,from hazard studies in geophysical/social sciences and in political economy/ecology.

This paper aims to adopt a critical stance on the relevance and interpretation of the recently emerging concepts of resilience and vulnerability in transportation studies. It makes a clear distinction between engineering and ecological interpretations of these concepts and offers a systematic typology of various studies in this field. A core element in the study is the linkage between the aforementioned concepts and connectivity/accessibility in transport networks. The methodological findings in the study are put in perspective by addressing also such concepts as robustness, reliability and friability of transport systems.

The concept of resilience has received a great deal of attention in the past decades. Starting from the first fundamental definitions offered by Holling, Pimms and Perrings in an economic-ecological modeling context, the present paper explores the ‘evolution’ of the resilience concept—as well as related different measures—in both a continuous and discrete time setting.

Contents: 1. Accessibility and Spatial Interaction: An Introduction Ana Condeco-Melhorado, Aura Reggiani, Javier Gutierrez PART I: ADVANCES IN MODELING ACCESSIBILITY AND SPATIAL INTERACTION 2. Novel Methods for the Estimation of Cost/Distance Decay in Potential Accessibility Models John Osth, Aura Reggiani, Giacomo Galiazzo 3. Transport Networks and Accessibility: Complex Spatial Interactions David Philip Mcarthur, Inge Thorsen, Jan Uboe 4. High Resolution Accessibility Computations Thomas W. Nicolai, Kai Nagel 5. Sensing 'Socio-Spatio' Interaction and Accessibility from Location-Sharing Services Data Laurie A. Schintler, Rajendra Kulkarni, Kingsley Haynes, Roger Stough PART 2: THE SOCIAL AND SPATIAL DIMENSION OF ACCESSIBILITY 6. Spatial Organisation and Accessibility: A Study of US Counties Andrea De Montis, Simone Caschili And Daniele Trogu 7. Border Effect and Market Potential: The Case of the European Union Maria Henar Salas-Olmedo, Ana Condeco-Melhorado, Javier Gutierrez 8. Mapping Transport Disadvantages of Elderly People in Relation to the Health Services: Contribution of Geographic Information Systems Vitor Ribeiro, Paula Remoaldo, Javier Gutierrez PART 3: ACCESSIBILITY AS A DRIVER OF SPATIAL INTERACTION 9. Productivity and Accessibility of Road Transportation Infrastructure in Spain. A Spatial Econometric Approach Pelayo Arbues, Matias Mayor, Jose Banos 10. Location, Accessibility and Firm-Level Productivity in Spain Adelheid Holl 11. Accessibility: An Underused Analytical and Empirical Tool in Spatial Economics. Urban Grasjo, Charlie Karlsson

In much accessibility research, arbitrary estimates of the distance sensitivity parameters have been used to represent the distance decay parameters in potential accessibility models. These estimat ...

This paper provides a different interpretation of resilience on the light of a very well known empirical regularities that is Gibrat's Law. Gibrat's Law is a rule stating that the growth of a given entity (city, firm, income and so on) is independent on its size. Resilience, instead, is a concept firstly adopted in ecology and subsequently 'exported' in different research fields. It refers to the capacity of a given system to respond to shocks by recovering to a state similar to the initial one. Although, at the first glance, the two concepts look quite different, Gibrat's Law can be interpreted in economic terms, as the reproposal, after a certain (long) time, of the deterministic pattern generated by some structural fundamental variables. Indeed Gibrat's Law arises as the steady state equilibria of stochastic processes that describe the underlying economic or demographic forces and characteristically, the steady state is independent of initial conditions. Then, this paper aims at reassessing the idea of resilience in the light of Gibrat's Law. In more detail, we provide a comparison with a previous research on resilience that shows a high degree of homogeneity of the resilience across Italian regions in the period 1890-2009 using data on real per capita income. In particular we adopt different methodologies commonly used in evaluating Gibrat's Law over the same dataset used in the previous research. We first check for departures from the Gibrat Law, using a linear test, that means testing the deviations of logarithms of capita income levels from their means. Secondly, we use a unit root test approach to check whether the data show mean reversion in the stochastic growth process. Finally we compare our results with those of the previous research. Our results show that, although not perfectly, we can define a relationship between Gibrat's law and resilience.

There is an increasing awareness of the potentials of nonlinear modeling in regional science. This can be explained partly by the recognition of the limitations of conventional equilibrium models in complex situations, and also by the easy availability and accessibility of sophisticated computational techniques. Among the class of nonlinear models, dynamic variants based on, for example, chaos theory stand out as an interesting approach. However, the operational significance of such approaches is still rather limited and a rigorous statistical-econometric treatment of nonlinear dynamic modeling experiments is lacking. Against this background this paper is concerned with a methodological and empirical analysis of a general misspecification test for spatial regression models that is expected to have power against nonlinearity, spatial dependence, and heteroskedasticity. The paper seeks to break new research ground by linking the classical diagnostic tools developed in spatial econometrics to a misspecification test derived directly from chaos theory—the BDS test, developed by Brock, Dechert, and Scheinkman (1987). A spatial variant of the BDS test is introduced and applied in the context of two examples of spatial process models, one of which is concerned with the spatial distribution of regional investments in The Netherlands, the other with spatial crime patterns in Columbus, Ohio.

This paper discusses analytical advances in evolutionary methods with a view towards their possible applications in the space-economy. For this purpose, we present a brief overview and illustration of models actually available in the spatial sciences which attempt to map the complex patterns of spatial/social networks. Particular attention is given to new emerging tools, such as neural networks (NNs) and evolutionary algorithms (EAs), belonging to the field of neurocomputing. The main part of the paper focuses specifically on EAs, in order to better comprehend the potentiality and applicability of this new methodological tool, also in comparison with “conventional” approaches (like logit and spatial interaction models). A historical review of EAs, together with an exposition of their theoretical structure, is offered. Moreover, an empirical application related to the modal split analysis in the European freight transport network shows the potential of EAs in this particular context of analysis. The final section concludes and points to new research directions. It is mainly based on the idea that, since EAs are optimising techniques generating mechanisms of natural selection and genetics, it is methodologically interesting to investigate their compatibility with the rational behavioural paradigm underlying conventional logit and spatial interaction models (and thus also the potential compatibility between natural selection and economic choice).

This paper presents an overview of European policy on the interconnected cross-border transport networks as well as severe problems in estimating empirically the avalanche of goods movements in the European Union (EU). In particular, it deals with the Transalpine freight transport case, which represents one of the most challenging operational and policy issues of the present and future – both international (EU) and national (the Alpine countries) – freight transport development. The paper is organised to briefly describe the main objectives of EU transport policy, to generally introduce the concept of intermodal transport with particular emphasis on intermodal freight transport and to describe past, present and future development of Trans-Alpine intermodal transport. The scenarios of future development of Trans-Alpine intermodal transport have been particularly analysed.

There is no doubt that spatial interaction is related to accessibility, since improved accessibility will increase the spatial interaction between places. However this relation is often asymmetric, since some places take more advantage than others of better accessibility. Accessibility improvements can emerge from transport infrastructure developments or from land use changes, that is, increased number of jobs in a certain location. Accessibility indicators are able to capture changes in both components (transport infrastructure and land use) and for this reason their performance has been recognized in the framework of sustainability policy, in light of best practice planning and decisionmaking processes where evaluation methods, such as cost–benefit analysis, multi- criteria analysis and risk analysis, can embed accessibility results.Accessibility is associated with higher productivity levels, as regions with high accessibility benefit from lower transport costs and agglomeration economies. Accessibility also concerns patent output, regional economic growth, new firm formation, labour and export performance of regions. It should be noted that, given the increasing relevance of accessibility issues, mostly in this globalized space- economy, a great number of review studies have been published that also show the potential and role of this tool for best practice and planning. In this context, we aim to go beyond these accessibility analysis studies and to reflect on the specific issue of the link between spatial interaction and accessibility from the theoretical, methodological, empirical and policy analysis perspectives. On the basis of the above, the rationale of this book is to present a collection of recent studies modelling and discussing spatial interaction by means of accessibility indicators.

In the present paper a modal split problem is analysed by means of two competing statistical models, the traditional logit model and the new technique for information processing, viz. the feedforward neural network model. This study aims to explore the modal split between rail and road transport modes in Italy in relation to the introduction of a new technological innovation, the new High-Speed Train. The paper is sub-divided into two major parts. The first part offers some general considerations on the use of neural networks in the light of the increasing number of empirical applications in the specific area of transport economics. The second part describes the Italian case study by using the two above mentioned statistical models. The results highlights the fact that the two adopted models, although methodologically different, are both able to provide a reasonable spatial forecasting of the phenomenon studied. In particular, the neural network model turns out to have a slightly better performance, even though there are still critical problems inherent in its application.

See also the article in Cities (2013). Volume 30, pages 59-67. This paper introduces a new measure to approach the accessibility of places in the frame of the digital economy. Information and Communication Technologies (ICTs) and the Internet are not equally spread around places and this heterogeneity affects spatial configuration. Despite the wide societal changes due to ICTs and the extensive interest in accessibility studies, these two themes have not yet come together in order to study the digital accessibility (DA) of places. Adopting an infrastructural perspective and a potential accessibility framework, a DA measure – embedding different types of impedance distance functions – is calculated for cities in Europe. Spatial Interaction Model and Complex Network Analysis are employed to calibrate and validate the DA results. The outcome of this approach is a new urban hierarchy which reveals a core-periphery pattern in Europe owing to digital accessibility.

This paper serves two purposes. First, it aims to offer a comprehensive and critical overview of recent developments in the field of non-linear dynamic models, with particular relevance for spatial systems. Starting from a methodological review of central concepts of chaos theory and related modelling attempts, the paper reviews possible evolutions of dynamic spatial systems known from the literature (such as self-organizing systems and Lotka-Volterra models), by investigating in particular the relevance of chaos theory for (spatial) economics. Next, the paper shows that recent developments in dynamic ecological modelling provide an elegant integrative framework for various popular (spatial) economic models (e.g. logistic growth models, spatial competition models). Therefore, ecological approaches based on niche theory and competition models are dealt with from the viewpoint of the possibility of chaotic behaviour. Some simulation results are added as well in order to illustrate the arguments. The paper concludes with further reflections on new research directions which need to be developed in regional science.

In recent years there has been a growing awareness that advanced transport telematics (ATT) may offer a significant contribution to the solution of problems in European transport corridors. Such problems include congestion, lack of safety and environmental decay. However, the use of road transport informatics is not justified under all conditions and on all European roads. Therefore, it is necessary to develop a priority scheme of roads (links and corridors) that lend themselves in particular to the application of ATT. The present paper develops a practical typology of European inter-urban road corridors aimed at tracing the effects of ATT applications on constituent road links. In this study the identification of typologies is based on relevant attributes of a set of European transport corridors by gathering all appropriate information on region-specific and site-specific links of these corridors in order to determine in a systematic way the potential of these connections for ATT introduction and application. Furthermore, ranking(s) of corridors according to the needs of ATT are developed by means of multi-criteria analysis. Various results on European transport axes are shown as well.

Much attention has recently been paid to the potential of using analytical tools derived from ecology and biology for analyzing competitive (or synergetic) interactions in a complex spatial network. Defining a network as a complex space-time system, this article investigates the implications of spatial interconnections when oscillating or chaotic behavior in a certain node of a network is spread in both space and time. The main focus is on stability/ complexity in a network with a view to varying complexity in terms of the number of functional elements (e.g., nodes, competing/growing centers). Some simulation experiments involving simple-dimensional spatial systems are described.

An avalanche of empirical studies has addressed the validity of the rank-size rule (or Zipf’s law) in a multi-city context in many countries. City size in most countries seems to obey Zipf’s law, but the question under which conditions (e.g. sample size, spatial scale) this ‘law’ holds remained largely underinvestigated. Another complementary question is whether socio-economic networks in space also show a similar hierarchical pattern. Against this background, the present paper investigates – from a methodological viewpoint – the relationship between network connectivity and the rank-size rule (or Zipf’s law) in an urban-economic network constellation. After a review of the literature, we address in particular the following methodological issues: (i) the (aggregate) behavioural foundation underlying the rank-size rule/Zipf’s law in the light of spatial-economic network theories (e.g. entropy maximization, spatial interaction theory, etc.); (ii) the nature of the analytical relationship between social-spatial network analysis and the rank-size rule/Zipf’s law. We argue that the rank size rule is compatible with conventional economic foundations of spatial network models. Consequently, a spatial-economic interpretation – as well as a network connectivity interpretation – of the rank-size rule coefficient is provided. Our methodological contribution forms the foundation for the subsequent empirical analysis applied to spatial networks in a socio-economic context. The aim here is to test the sensitivity of empirical findings for changes in scale, functional forms, time periods, and network structures. Our application is concerned with an extensive spatio-temporal panel database related to the evolution of urban population in Germany. We test the relevance of the rank-size rule/Zipf’s law, and its evolution over the years, and – in parallel – the related ‘socio-economic’ connectivity in these urban networks. In particular, we will show that Zipf’s law (i.e., with the rank-size coefficient equal to 1) is only valid under particular conditions of the sample size. The paper concludes with some retrospective and prospective remarks.

Spatial labour markets are subjected to the forces of regional economic activity and competing network effects. Commuting is, therefore, an important equilibrating vehicle in a City Network constellation. Cities act as attractors of commuters, as most economic activity occurs in cities, thus providing a high share of attractive workplaces. Cities that are centrally connected in a network may act as both centripetal and centrifugal forces in the whole system. The present paper focuses on what is named the City Network (CN) approach. A central idea is the accessibility concept, which is interpreted here as the potential of opportunity for interaction, which has a positive impact on economic growth. In our paper, the accessibility concept and the CN concept are linked together by positioning accessibility in the CN system. Since accessibility measures give geographical insights into the distribution of economic activities and the related (dis)equilibrium of regional development patterns, the connection with the labour market is evident, and, therefore, a second focus of our analysis. In an applied setting, our paper aims to investigate spatial accessibility patterns in the main CN in Germany. The 17 districts which belong to the country's CN were chosen from the 439 German labour market districts on the basis of three criteria: (a) their connection to the high speed railway network; (b) the most accessible districts according to previous results (2002); (c) relevant districts for the German economy. Our applied modelling research concerns home-to-work commuters travelling between the selected districts belonging to the German CN, for both 2003 and 2007. Here, a comparative analysis of the ranking of the most accessible districts - also for different intra-zonal travel times - is carried out in order to map out the changes in accessibility between 2003 and 2007, especially in the light of new high speed connections and commuting flow dynamics. © 2010 Elsevier Ltd.

In this paper, we present a review of various computational experiments concerning neural network (NN) models developed for regional employment forecasting. NNs are nowadays widely used in several fields because of their flexible specification structure. A series of NN experiments is presented in the paper, using two data sets on German NUTS-3 districts. Individual forecasts are computed by our models for each district in order to answer the following question: How relevant are NN parameters in comparison to NN structure? Comprehensive testing of these parameters is limited in the literature. Building on different specifications of NN models-in terms of explanatory variables and NN structures-we propose a systematic choice of NN learning parameters and internal functions by means of a sensitivity analysis. Our results show that different combinations of NN parameters provide significantly varying statistical performance and forecasting power. Finally, we note that the sets of parameters chosen for a given model specification cannot be light-heartedly applied to different or more complex models. © 2010 Springer-Verlag.

A great deal of attention has recently been paid to the analysis of the structure and evolution of (complex) networks, starting from pioneering contributions in the physical and social sciences – and more recently in the regional and transportation sciences – mainly concerning the relevance of highly connected nodes (hubs). The presence of hubs identifies a network as Scale-Free (SF), because of its intrinsic characteristic of exhibiting power-law distributions in its connectivity structure, and thus highly heterogeneous patterns. The focus of this paper is to explore the homogeneous vs. heterogeneous characteristics of the German commuting network, by focussing on the role of accessibility. The concept of accessibility has a long tradition in the transport economics literature, starting with the fundamental works by Hansen in the 1950’s and later on by Weibull in the 1980’s. These authors defined accessibility as the potential of opportunities for spatial interaction. Accessibility conceived in this manner should also capture spatial structure effects and thus the network configuration properties, such as connectivity. This conventional accessibility function – in the light of the related economic activities – is be used as a suitable instrument to identify the major German hub/attraction nodes. As the functional form in this potential accessibility, the power-decay function will be considered – in addition to the negative exponential function – in order to explore the spatial configuration patterns, i.e. whether people perceive commuting cost in log-like way. The connectivity network analysis will then be developed as a benchmark to testing the results emerging from the spatial-economic analysis. In our application we consider home-to-work commuters travelling between 439 German districts, for the year 2002. The final results seem to highlight the tendency, in Germany, towards a multi-nodality network, where accessibility can play a fundamental role.

This paper describes how a key factor in railway use is the number and location of stations and their catchment areas. Opening new stations to reduce access/egress distance to and from the station, is often seen as one of the main ways to increase rail use. However, this strategy is very costly and might be counterproductive as some existing rail travelers could be adversely affected. There are particular challenges in the decision-making process involved in opening new stations in urban areas that are already being well served. A major consideration in deciding whether to build a new station in this situation is the ability of potential users to access the new facility. The paper shows how there are considerable overlaps in the catchment areas of the stations in Amsterdam. These overlaps may be an indication of an oversupply of railway stations, which, from a network or city perspective, can be inefficient when increasing rail use and improving profitability of rail operations. The authors have seen that while there is a demand across the system in the Amsterdam area, this does not necessarily mean that it is high enough to justify all these stations in operation. There is a case for looking carefully at the different factors affecting the choices of passengers of departure stations and the weight given to each. The factors that seem important are travel time to each station by different modes and the destinations served by each station, or, more generally, the level of service including scheduling. The balance between the access time to stations and travel time by rail between stations should be determined when considering the optimal number of stations. In order to reduce any adverse environmental- or congestion-related impacts of passengers switching modes if a station is closed, polices to improve access to the remaining stations may be needed.

Commuting is, therefore, an important equilibrating vehicle in a city network constellation. Cities act as attractors of commuters, as most economic activity occurs in cities, thus providing a high share of attractive workplaces. Cities that are centrally connected in a network may act as both centripetal and centrifugal forces in the whole system. The present paper focuses on what is named the City Network (CN) approach. A central idea is the accessibility concept, which is interpreted here as the potential of opportunity for interaction, which has a positive impact on economic growth. In our paper, the accessibility concept and the CN concept are linked together by positioning accessibility in the CN system. Since accessibility measures give geographical insights into the distribution of economic activities and the related (dis)equilibrium of regional development patterns, the connection with the labour market is evident, and, therefore, a second focus of our analysis. In an applied setting, our paper aims to investigate spatial accessibility patterns in the main CN in Germany. The 17 districts which belong to the country's CN were chosen from the 439 German labour market districts on the basis of three criteria: (a) their connection to the high speed railway network; (b) the most accessible districts according to previous results (2002); (c) relevant districts for the German economy. Our applied modelling research concerns home-to-work commuters traveling between the selected districts belonging to the German CN, for both 2003 and 2007. Here, a comparative analysis of the ranking of the most accessible districts - also for different intra-zonal travel times - is carried out in order to map out the changes in accessibility between 2003 and 2007, especially in the light of new high speed connections and commuting flow dynamics.