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This paper highlights the relevance of connectivity and its architecture as a general conceptual framework which underlies and integrates the concepts of network vulnerability, complexity, and resilience. In particular, it will be pointed out that connectivity architecture can be considered an explicit key element for network vulnerability and shock propagation. While the relevance of the various connectivity configurations is not clearly emphasised in the dynamic complexity models of the space-economy, it appears to play a primary role in network analysis. In this regard, the emerging recognition of connectivity architecture in relation to hubs ‒ and hierarchies of hubs ‒ in a complex network will help the enhancement of network resilience. The paper develops as follows. First, the notion of network vulnerability, which refers not only to the phenomenon of shocks, but also to the propagation of shocks in a network, will be examined. Here it appears that modelling vulnerability and shock propagation, also jointly with cascading disaster models, is strongly based on connectivity issues. The question is: How can conventional (complex) system dynamic modelling, as well as network modelling, take into account these shocks and connectivity dynamics from the methodological viewpoint? A review in this respect shows how connectivity is a ‘hidden’ element in these complexity models, for example, in chaos or (dynamic) competition models, where interaction parameter values might lead to vulnerable domains and chaotic behaviour. On the contrary, connectivity and its various topologies have a distinct, primary role in network analysis. The issue of network resilience appears therefore to be the ‘response’ to vulnerability and chaos, calling for robustness and stability of the network in the presence of shocks and disruptions. Resilience analysis refers to the speed at which a network returns to its equilibrium after a shock, as well as to the perturbations/shocks that can be absorbed before the network is induced into some other equilibrium (adaptivity). Connectivity is relevant here, but not often considered in spatial economics. In order to reach a unified methodological framework, attention will finally be paid to a complementary analysis of the (dynamic) concepts of vulnerability and resilience. In this light, chaos models/properties might be seen in a positive perspective, since small changes can lead to uncertain and unstable effects, but also, thanks to connectivity, to new equilibria which are not necessarily negative. Thus, the architecture of connectivity, in its interdisciplinary insights, can be considered as a fundamental (and analytical) approach for identifying vulnerability and resilience patterns in complex networks.

Spatial systems appear to exhibit often a complex pattern of socio-economic development, in terms of (un)employment, income, mobility, ethnic composition, and urbanisation rates. Their evolution is co-determined by such factors as: market proximity, labour and housing market developments, public amenities, use of and access to transport systems, socio-economic composition of the population, etc. In addition, a sine qua non for sustaining urban economic growth is the local or regional presence of individual and collective cognitive assets that favour knowledge acquisition and transfer, education, innovation, and creativity. In this context, social capital and spatial accessibility are critical factors. The present paper aims to provide an operational framework for mapping out and understanding the mechanisms which drive spatial systems from the perspective of the resilience of urban areas, in the light of their social capital in combination with accessibility. Particular attention is therefore given to the essential role of social capital and transport accessibility in shaping both the economic development of cities and the spatial pattern in the evolution of cities, in terms of, inter alia, education, age, ethnic composition, (un)employment, and socio-economic poverty. For our quantitative analysis of the Swedish urban system, a quantile regression model is introduced and applied in order to study which urban-economic factors in Sweden determine the different levels of social capital, which are seen here as the fundamental component of the resilience capacity of urban areas.

This Handbook explores new and old theoretical, methodological, and empirical insights and perspectives on entropy, complexity, and spatial dynamics. A central and cross-cutting theme of the Handbook is the role of entropy in complex, dynamic spatial socio-economic systems as both a measure of spatial complexity and a process involved in the dynamics and emergent behavior of spatial systems. In this regard, one of the bold aims of the Handbook is to examine how and to what extent entropy is (or might be) a universal principle dictating and describing the structure and dynamics of complex spatial systems across different domains and applications. To this end, the Handbook draws upon perspectives from various disciplines ‒ from economics to geography to physics to biology to information science. Starting from these considerations, this introductory chapter summarizes classic and state-of-the-art cross-disciplinary methods and approaches for modeling and characterizing complex, dynamic, integrated networked spatial systems, including entropy-based and information-theoretic frameworks and derivations, considering relevant theoretical underpinnings. First, this introduction presents a concise history of the foundational concepts, theories, and models behind spatial economic science, from entropy to complexity to spatial dynamics. It then provides a high-level and more detailed overview of the Handbook. Finally, the chapter reflects on the extent to which the emerging insights originate from conventional, old developments and how new models and methods can help inform policymaking and planning, particularly for addressing contemporary issues and challenges tied to our increasingly integrated, uncertain, and dynamic world.

Over the past decade the concept of social capital has attracted a vast research interest at the interface of economics and the social sciences, giving rise to a large amount of literature from both a methodological and empirical viewpoint (see, for a review, Östh et al., 2018). Broadly defined, social capital is the benefit individuals gain from mutual relations, interactions, social networks and the associated norms of reciprocity and trustworthiness (Putnam, 2000; Helliwell and Putnam, 2004). However, the topographic, demographic and socio-economic differences between rural and urban areas might lead to different social capital experiences for their residents. Additionally, given recent dramatic changes characterized by urbanization; in particular, a rise in the number of densely populated cities, and a corresponding decline in population and accessibility of amenities in rural areas, it becomes of great importance to review the rural/urban differences of social capital. The present chapter discusses the social capital concept in the light of the current socio-economic evolution of rural areas. The aim of the chapter is to identify the role and importance of accessibility, migration and occupation in interaction with social capital, given the emerging urbanization trend and the related isolation of rural areas.

Over the past years, we have observed a growing interest among social scientists and policy makers in deepening their understanding of the importance of the social capital concept, against the background of a broad set of socio-economic experiences in various countries. The concept is popularly defined as a set of individual and societal gains embedded in social ties and networks. The extent to which societies produce and benefit from social capital depends, inter alia, on locational characteristics such as human capital accumulation, segregation, employment rates, the wellbeing of individuals, as well as daily and periodic mobility patterns in relation to the job/housing balance, commuting distances, and in a general sense, rural-urban differences. The aim of this chapter is to examine the impact of job accessibility on social capital at a regional scale, with special attention to rural areas. Job accessibility is considered as an indicator of spatial connectivity, and thus it can strongly relate to social capital. The associated analyses will be done by empirically studying Turkish and Italian provinces (on the basis of the European Union-NUTS3 level regions). A quantile regression model is employed to examine job accessibility and rurality in relation to social capital in 81 Turkish and 110 Italian provinces. In the analysis, social capital is measured by a community resilience index based on a set of relevant data on civic infrastructure, metropolitan stability, home ownership, and political participation. The empirical analysis is carried out for Italy and Turkey. In the last few decades, both countries have experienced a decline in rural livelihood and now have a similar percentage of rural population. Meanwhile, mainly due to the geographical and socio-economic structure, the two countries show different patterns and development characteristics of accessibility. The findings of this paper highlight these differences and similarities, and show social capital variations in response to accessibility and rurality in both Turkey and Italy.

The concept of resilience has recently been investigated from the perspective of several disciplines. This extensive research has produced many approaches to determine the key definitions, linked to both the notion of stability in dynamics (return to the previous equilibrium after a shock) and the idea of adaptivity (absorption of the shock leading to new equilibria). Among the various definitions and measurements which can be found in the literature, the Resilience Capacity Index (RCI) defines a kind of ‘potential resilience’, i.e. the potential ability of a region to recover, or bounce back in the presence of external shocks. However, the RCI should also be tested empirically versus other resilience/vulnerability indicators. Vulnerability denotes a different view on the state of the system in the presence of shocks, i.e. the degree to which a system is susceptible to harm. In the present paper, this concept will be adopted by analysing the dynamics of the unemployment growth rate, and then comparing it to the RCI. The country of interest in this paper is Slovakia. Slovakia is a small country in Central-Eastern Europe and can serve as a good example of an open and export-based economy, subjected to the global crisis. Thus, in the context of the 2007–2008 economic crisis, the RCI in the 79 Slovak districts is examined with respect to their vulnerability in the first period of rising unemployment (2008–2012), as well as in the second period following vulnerability to the economic shock (2012–2014). A clear West-East divide in the resilience capacity can be seen. The more urban and export-oriented districts with high RCI values are shown to be exposed to high vulnerability compared with the rural districts. On the other hand, the small, peripheral districts respond to a lesser extent, or with a delay, to the shock.

Recent years have shown a rising popularity of the concept of resilience—both theoretically and empirically—in complex systems analysis. There is also a rising literature on resilience in the transport and spatial-economic field. The pluriform interpretation of resilience (e.g., engineering vs. ecological resilience) is related to methodological differences (e.g., stability in dynamics vs. evolutionary adaptivity). But in all cases the fundamental question is whether a complex system that is subjected to an external shock is able to recover, and if so, to which extent. The present paper [Based on presentation from cluster 6 (Accessibility) of the Nectar 2015 conference in Ann Arbour, USA.] aims to add a new dimension to resilience analysis in spatial systems, by addressing in particular the relationship between spatial accessibility at a municipality level and the resilience outcomes of the spatial system concerned. It does so by investigating to which extent accessibility of Swedish and Dutch municipalities has mitigated the local shock absorption from the recent economic recession. In our study the shock absorption capacity of municipal accessibility is estimated by analysing the relevant resilience indicators for the period concerned. In this context, conventional resilience indicators based on either multivariate complex data (in particular, the Foster Resilience Capacity Index) or employment data (in particular, the Martin Resilience-Employment Index) are confronted with spatial connectivity data based on local accessibility measures, so that geographical mobility may be regarded as one of the shock-mitigating factors. The empirical analysis is carried out for two countries which have both proven to be rather shock-resistant during the recent economic crisis, viz. Sweden and The Netherlands. Clearly, the geographical structure of these countries forms a sharp mutual contrast, viz. a spatially dispersed economy with a few distinct urban concentrations versus a spatially dense economy with one major metropolitan centre (the Randstad), respectively. Our experiments are carried out for the 290 municipalities in Sweden and 40 COROPs in The Netherlands. Our research findings show relevant and new insights into differences in the local recovery potential in Sweden and The Netherlands.

Accessibility, trade and locational behaviour - an introduction, Aura Reggiani. Part 1 Theoretical frameworks - measurements of accessibility: the concept of accessibility revisited, Dino Martellato measuring accessibility in a general equilibrium framework, Johannes Brocker a new definition of spatial accessibility function in transportation networks - axiomatic approach, Tochihiko Miuagi and Takaji Suzuki accessibility, peripherality and spatial development - the question of choice, Roger Vickerman. Part 2 Methodological frameworks - locational behaviour and trade: education intensity and interregional location dynamics, Ulla M. Forslund-J. economic milieu, specialization and location dynamics, Borje Johansson some simple macroeconomics of increased accessibility and spatial integration - the case of a small open region, Peter McGregor et al a prototype computable general equilibrium model of trade between two countries, Hideo Hashimoto proximity in networks - the role of transport infrastructure, Antje Burmeister and Kristian Colletis-Wahl regional active space - a regional scientist's paradigmatic answer to the local-global debate, Remigio Ratti. Part 3 Empirical frameworks - European freight transport networks: what port for the future? from "mainports" to ports as nodes of logistic networks, Paul Drewe and Ben Janssen transport of goods between the Nordic countries and the European mainland, Simo Pasi and Veli Himanen price effects of regulation -stated offers for trans-Alpine freight transport services, Karin Muller and Rico Maggi on the crossing of the Alpine chain and the Swiss regulation of trucking, Maurent Demilie et al external effects of evaluation and environmental impact reduction in freight transportation, Domenico Campisi et al European freight transport analysis using neural networks and logit models, Aura Reggiani et al.

The economic recession which followed the 2008 financial crisis has raised important issues on differences in the impact, especially from a spatial perspective, of the socio-economic shocks ‒ at both the regional and the community level, especially in the European Union Member States. These differences may be due to the different levels of vulnerability, resilience and exposure, and may arise because of dissimilarities in the intrinsic characteristics of regions or communities (e.g. the pre-crisis economic characteristics of regions, ageing, household income, and so on). While, in the scientific literature, a great deal of attention has been paid to the concept of resilience (e.g. the capacity to bounce back or to resist a given shock) and vulnerability (e.g. the inherent characteristics that create the potential for harm), less attention has been paid to the full set of measures of socio-economic exposure (e.g. the things affected by a shock), as well as both to the relationship between vulnerability, resilience and exposure and to the losses which ensue as a result of different external shocks and exposure. The objective of this chapter is the exploration of the above-mentioned links, since a closer analysis of these interrelations might produce different outcomes. This study aims to review systematically the existing literature on vulnerability, resilience and exposure, in order to understand the connections between these concepts, with reference not only to economic shocks but also to other catastrophic events, such as natural disasters, man-made disasters, and so on.

The present paper aims to offer a specific contribution to the general issue of search of evaluation indicators and assessment methods for complementary and competing trans european networks, by investigating recent studies, analyses and models which have been conducted in the context of the Transalpine freight transport flows.

This paper proposes a general conceptual framework which aims to integrate the concept of network resilience within that of transport security. In particular, methodological reflections on the role of resilience vs vulnerability in connectivity network structures, such as scale-free networks, are highlighted. Operational measures of resilience are also outlined, in order to enhance resilience in transport and communication networks. Current policy strategies which focus on resilience show the relevance of this issue and the need for continuing research on the links between complex transport networks and resilience, mostly by exploring this relationship at different scale levels and its impact on the whole network.

The aim of the present chapter is to provide an accurate description of the distribution of people in space, taking into account the demographic differences between people. To provide this analysis, we focus on both population (in terms of place of residence) and employment (in terms of place of work) data: we use annual observations regarding population and employment for all German towns and cities in the period 2001–2011. So, the questions we want to answer are the following: does the growth rate of employment/population depend on the size of the cohort? What is the level of employment and population concentration/deconcentration?Are there any differences between these two variables? Are there any differences if we differentiate for age cohorts?In answering all these questions, we will first show the results of the analysis of Zipf’s law and then those of the analysis of Gibrat’s law. The main idea is to verify whether the size of a city (measured by population and employment) and its growth rate are independent for 5-year age groups. To the best of our knowledge, this is the first study which attempts to introduce demographic characteristics (and, in particular, age structure) into an analysis of Zipf’s and Gibrat’s law.

The EU Community Support Framework (CSF), in the transport sector, aims at implementing a sustainable network characterised by a more balanced modal split – both in passengers and in freight transport – and by an integrated connectivity among the transport nodes along these lines. It follows the main goals of the 2001 White Book on Transport and it also tends to support sustainable dynamics of local development. Such strategy wants to: a) strengthen the links of southern local nodes and terminals with national networks; b) improve the links among local southern networks and the overall quality of service; c) pursue a balanced modal split both in urban and in freight transport. Consequently, the Italian National Operational Programme (PON from Piano Operativo Nazionale) and Regional Operational Programmes (POR from Piano Operativo Regionale), spanning since 2001 to 2006, should have been developed according to the above-mentioned goals. This study provides a concise description of CSF, PON and POR programs and to test – by means of a multicriteria approach – the degree of coherence among them. The evaluation is based on the following macro-criteria: a) degree of accessibility; b) modal shift; c) intermodality; d) urban mobility; e) quality and efficiency; f) reduction of environmental impact. Each of them will be characterised by one or more indicators which will allow to assign a quantitative/qualitative measure to each of the infrastructure investments considered. The results highlight that the strategy pursued during the 2001-2006 period aimed at strengthening some priority nodes located in the TEN-T network. Moreover, it was possible to ascertain a relevant heterogeneity between PON projects, that follow a global perspective, and POR projects, mainly focused on the local networks.

An avalanche of empirical studies has addressed the validity of the rank-size rule (or Zipf's law) in a multicity context in many countries. Under which conditions (eg, sample size, spatial scale) this ‘law’ holds remains as yet largely underinvestigated, while spatial network constellations also deserve more attention. Against this background, we investigate the relationship between network connectivity and the rank-size rule (or Zipf's law) in an urban economic network constellation. In particular, we address 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 (eg, entropy maximization, spatial interaction theory); (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. We test the sensitivity of rank-size rules for changes in scale, functional forms, time periods, and connectivity structures. Our application uses an extensive spatiotemporal panel database on the evolution of the urban population in Germany. We test the relevance of the rank-size rule (Zipf's law), and—in parallel—the related ‘socioeconomic’ connectivity in these urban networks. In particular, we will show that Zipf's law (ie, with the rank-size coefficient equal to 1) is only valid under particular conditions of the sample size.

The ‘network embedding’ implications for complexity theory raise the issue of the search for a ‘hidden’ order/simplicity (Reggiani and Nijkamp, 2009). In this context, a dual analysis (Spatial Economic Science vs. Network Science) seems essential. This will be briefly reviewed in this chapter, by focusing on the role of accessibility. In particular we will show how accessibility can be the ‘simplest’ model which – by embedding connectivity – can link network science and spatial-economic science, and thus capture the homogeneity/heterogeneity of the spatial system concerned from both the methodological and the empirical viewpoint . Starting from these considerations, we will then explore the relationships between accessibility and an interesting concept linked to the robustness of the network: i.e. the resilience. Some reflections and suggestions for future research will be finally provided.

In recent years there has been an increasing interest in analysis of accessibility and related studies. The concept of accessibility is multifaceted, since it is investigated in a variety of disciplines, such as transportation planning, spatial planning, transport geography, urban and environmental planning, spatial economics and transport economics. Accessibility is an important theme of research, because it concerns the benefits to people of accessing a certain location, by using a particular transportation system. In this respect, the level of accessibility can be considered to be a relevant indicator of the efficiency of the transportation system under analysis. Individuals adapt their movements and activities, often albeit unconsciously, to the possibilities provided by a given transportation system. Broadly speaking, this should enable them to reach as many desired goods or places as possible at the lowest possible cost. While this general definition can be outlined, policy makers must be more specific when they tackle particular case studies. Many varying definitions are found in the literature. However, in methodological terms, most of these boil down to the concept and measurement of potential accessibility (Martin and Reggiani, 2007). In this context, accessibility embeds – in a compound way – simple indicators of the economic activities together with the cost/utility of reaching such activities. Consequently accessibility can be seen as one of the driving forces for producing desired economic activities (Levinson and Xie, 2011). Accessibility is also strictly linked to the network concept (Levinson and Krizek, 2008), as well as to the inherent complex configurations. From a modeling viewpoint, accessibility, in the formulation presented in Hansen’s (1959) and Weibull’s (1976) works, can be considered as a simple – although very powerful – indicator, capable of ‘decoding’ complex systems. On one hand, accessibility can be linked to spatial interaction models, and thus to the related theories on which statistical information principles and entropy maximization are founded. On the other, accessibility can be linked to logit models and thus to micro-economic theory (stochastic utility maximization). To sum up, all the theories to which accessibility can be linked show that – when dealing with a complex network – a ‘hidden’ order/simplicity has governed the scientific arena in spatial economic science in the past few decades. Accessibility is one of the strong theoretical instruments in this complex framework (for a review, see Reggiani, 2012). In this context, an intriguing research issue is the interpretation and measurement of the fundamental (potential) accessibility indicator, given the social and economic variables involved. Thus attention has recently been paid to the associated distance/travel time/travel costs, as well as to the related functional forms and network structures, seen from both a theoretical and an empirical viewpoint (see Reggiani et al ., 2011). In this vein, researchers have experimented with a variety of measurements of or proxies for the accessibility indicator. There have been a long series of methodological and empirical contributions in recent decades: for example, Bruinsma and Rietveld, 1998, Hillman and Pool, 1997, Litman, 2007 and Weber and Kwan, 2003, and Yamaguchi (2007). Reviews of accessibility measurements can be found, among others, in Baradaran and Ramjerdi, 2001, Geurs and van Wee, 2004, Geurs et al ., in press, Handy and Niemeier, 1997, Jones, 1981 and Reggiani and Martin, 2011, and Wu and Hine (2003). All these works bear witness to the popularity of the accessibility approach, which has evolved from the fundamental definition by Weibull (1976), where accessibility refers to the ‘properties of the configuration of opportunities for spatial interaction’ , becoming enriched with economic and social contents that include relevant aspects of the new patterns of transport, economic networks and land use. Recent developments in our globalized era, which is characterized by very-high connectivity in transport and socio-economic fields, mean that an interesting area which is worth exploring are methodological reflections on the feedback relationships between the new patterns of economic activities and the new transport networks, identified by individuals or groups, in different areas of studies, from the point of view of accessibility. This is also the rationale behind the articles included in this Special Section. As a result the authors in this Special Section have been invited to discuss the impact of accessibility on social and economic activities connected to: population growth (Koopmans et al .), the emerging mobility patterns in the presence of a new high speed train (Martinez Sanchez-Mateos and Givoni), employment and commuting (de Graaff et al .), services provision (Neutens et al .), public care facilities (Paez et al .) and land value finance (Medda). These contributions were originally selected from among the papers presented in a NECTAR Cluster 6 Workshop on Accessibility and Spatial Planning held in Cagliari (Italy), on 17–18 October 2009. We would like to thank Andrea de Montis and his collaborators for their excellent organization in this respect.

The regional economics and geography literature has in recent years shown interesting conceptual and methodological contributions on the validity of Gibrat's law and Zipf's law. Despite distinct modelling features, they express similar fundamental characteristics in an equilibrium situation. Zipf's law is formalised in a static form, while its associated dynamic process is articulated by Gibrat's law. Thus, it seems that both Zipf's law and Gibrat's law share a common root. Unfortunately, although several studies analyse both the laws looking at the validity of these regularities, very few empirical investigations assess the implication of one law from the other one (i.e. deviations from Zipf's law result in a deviation from Gibrat's law). Moreover, due to heterogeneity in data sources, comparative analyses between countries are difficult to perform. The present chapter aims at building the basis for further innovative research in this field, while it also aims to provide some caveats in empirical research. Specifically, we pay particular attention to the role of the mean and the variance of city population as key indicators for assessing the (non-)validity of the so-called generalised Gibrat's law. Our empirical experiments are based on illustrative case studies on the dynamics of the urban population of five countries with entirely mutually contrasting spatial-economic characteristics: Botswana, Germany, Hungary, Japan and Luxembourg. We provide evidence on 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 1, then the variance is dependent on city size.

This chapter discusses the changes in the patterns of interaction that may point to important changes in the effects of barriers in the different parts of the studied area. On a generalized level, the changing patterns of interaction in the Baltic Sea Area should primarily be viewed as a process of internationalization. Baltic integration is here viewed as a process connecting the major city regions in the Baltic Sea Area, by means of interaction. When discussing interaction between city regions in a transborder environment such as the Baltic Sea Area, two major concepts come naturally in focus: systems of cities, and barriers. The chapter describes the traffic in terms of potential flows: the highest possible number of passengers to fly during a week. This can also be described as number of seats flown per week. These figures are taken from the international aviation timetables, from which it is possible to draw information about flight frequency and types of aircraft used.

This Manifesto provides a joint proposal to create a Regional Science Academy as a think-tank support platform for a strategic development of the spatial sciences. The Regional Science Academy is a strategic spatial knowledge catalyst: it acts as a global intellectual powerhouse for new knowledge network initiatives and scholarly views on regions and cities as vital centrepieces of interconnected spatial systems. This contribution highlights its role and presents various activity plans.

There is a well established body of research that deals with how accessibility affects land use planning and spatial interaction. Hansen (1959) is usually cited as the father of this “scientific term”. In his seminal work, he defines accessibility as “the potential of opportunities for interaction” (p.73). Since then, the interest of how transport systems and spatial interaction are related has grown exponentially and accessibility analysis has played for more than five decades a central role in the agenda of regional and transport research. The concept of accessibility is open to different areas of study regarding the activities that can be carried out, to multiple transport systems and to different individuals or groups, so it is not surprising that in the literature we can find many different definitions (Geurs and van Wee 2004; Bruinsma and Rietveld 1998; Reggiani 1998; Vickerman 1995; and Morris et al. 1979). Handy and Niemeier (1997) showed that different types of accessibility measures exist according to particular criteria, and it is difficult to suggest the best approach to measure accessibility because different situations and purposes demand different approaches. This comment is quite pertinent at the light of the articles included in our special issue. We will see that four of them analyze accessibility in commuting and the authors use different methods, demarcation areas and opportunities are in some cases aggregated at the level of areas or individuals. In the last decade with the continuing development and deployment of geographic information systems (GIS) and other geospatial technologies that have greatly enhanced the ability to collect and analyse data relevant to accessibility analysis, researchers, in some cases, have changed from place-based measures of accessibility Netw Spat Econ (2011) 11:577–580 DOI 10.1007/s11067-011-9155-x

Information, communication and transport networks have always been in a state of flux, while they also influence each other. Extensive research efforts have been made to investigate the dynamics in the structure and use of networks, e.g., by means of network geometries, small-world effects and scale-free phenomena. We will illustrate these new developments on the basis of airline network evolution. The present paper provides a new contribution to the analysis of topological properties of complex airline networks. Using Lufthansa's networks as an example, this paper aims to show the empirical relevance of various network indicators - such as connectivity and concentration - for understanding changing patterns in airline network configurations. After an extensive discussion of various statistical results, a decision-aid method, viz. multi-criteria analysis, is used to investigate the robustness of our findings. The results highlight the actual strategic choices made by Lufthansa for its own network, as well in combination with its partners in Star Alliance.

This paper develops and applies neural network (NN) models to forecast regional employment patterns in Germany. Computer-aided optimization tools that imitate natural biological evolution to find the solution that best fits the given case (namely, genetic algorithms, GAs) are also used to detect the best NN structure. GA techniques are compared with more ‘traditional’ techniques which require the supervision of experienced analysts. We test the performance of these techniques on a panel of 439 districts in West and East Germany. Since the West and East datasets have different time spans, the models are estimated separately for West and East Germany. The results show that the West and East NN models perform with different degrees of precision, mainly because of the different time spans of the two datasets. Automatic techniques for the choice of the NN architecture do not seem to outperform selection procedures based on the supervision of expert analysts.