The spatial component of R&D networks

We study the role of geography in R&D networks by means of a quantitative, micro-geographic approach. Using a large database that covers international R&D collaborations from 1984 to 2009, we localize each actor precisely in space through its latitude and longitude. This allows us to analyze the R&D network at all geographic scales simultaneously. Our empirical results show that despite the high importance of the city level, transnational R&D collaborations at large distances are much more frequent than expected from similar networks. This provides evidence for the ambiguity of distance in economic cooperation which is also suggested by the existing literature. In addition we test whether the hypothesis of local buzz and global pipelines applies to the observed R&D network by calculating well-defined metrics from network theory.Comment: Working paper, 22 pages, 7 figure

The role of space in urban housing market

This presentation emphasizes the quantitative analysis of space in relation to hedonic housing price models. Three aspects of space will be highlighted: i) spatial heterogeneity (spatial patterns): hedonic housing amenities may be valued differently in different locations which are related to specific housing sub-markets; ii) spatial dependence (spillovers): the degree by which price increases (or decreases) in a given sub-market is influenced by other sub-markets, or by another property within the same sub-market. iii) spatial scale: the study of heterogeneity and spillovers crucially depends on the level of geographical scale at which submarkets are defined. In the literature the difficulty of defining sub-markets and understanding the relationship between them is broadly identified, and appropriate methods for defining housing markets are also presented. However, there is not a consensus on which methodologies should be used. As a contribution to understand spatial structure (heterogeneity and spillovers) in urban spaces some empirical results will be presented. A new methodology to analyse spatial spillovers [rather than an ex ante definition of a spatial weight matrix (W)] will be developed. This procedure based on non-parametric approach will be applied to a rich database. An interesting outcome of this methodology is possibility of finding meaningful values of negative interaction.

The use of Rough Set and Spatial Statistic in evaluating the Periurban Fringe

The distinction among urban, peri-urban and rural areas inside a territory represents a classical example of uncertainty in land classification. The transition among the three classes is not much clear and can be described with Sorites Paradox, considering the residential buildings and the settlements. Peri-urban fringe can be considered as a transition zone between urban and rural areas, as an area with its own intrinsic organic rules, as a built area without formal organisation or as an abandoned rural area contiguous to urban centres. In any case, concepts as density of buildings, services and infrastructures or the degree of rural, residential and industrial activities, will lead to uncertainty in defining classes, due to the uncertainty in combining some properties. One of the methods which can be utilized is the rough sets theory, which represents a different mathematical approach to uncertainty capturing the indiscernibility. The definition of a set is connected to information knowledge and perception about phenomena. Some phenomena can be classified only in the context of the information available about them. Two different phenomena can be indiscernible in some contexts and classified in the same way (Pawlak 83). The rough sets approach to data analysis hinges on two basic concepts, the lower approximation which considers all the elements that doubtlessly belong to the class, and the upper approximation which includes all the elements that possibly belong to the class. The rough sets theory furthermore takes into account only properties which are independent. This approach has been tested in the case of study of Potenza Province. This area, located in Southern Italy, is particularly suitable to the application of this theory, because it includes 100 municipalities with different number of inhabitants, quantity of services and distance from the main road infrastructures.

Exploring countrywide spatial systems: Spatio-structural correlates at the regional and national scales

In this paper we take a step towards extending space syntax analysis into the countrywide scale, through the study of three very-large spatial systems in the UK, namely the top-tier road network of the entire country (170,007 nodes), the complete road network (1,208,674 nodes) of three contiguous NUTS1 regions (the East of England, South East of England and Greater London) and the complete road network of UK's mainland (2,031,971 nodes). We compare the results of our analysis with several types of functional and socio-economic data, finding clear statistical associations at the scale of the entire country between network structure, vehicular movement flows and the spatial distribution of several socio-economic variables. We conclude by arguing that space syntax models and analysis hold their value at very-large territorial scales, being highly robust and producing coherent results between datasets of different sources, themes and dimensionalities

How do Clusters/Pipelines and Core/Periphery Structures Work Together in Knowledge Processes?

This paper contributes to the empirical identification of geographical and structural properties of innovative networks, focusing on the particular case of Global Navigation Satellite Systems (GNSS) at the European level. We show that knowledge bases of organizations and knowledge phases of the innovation process are the critical factors in determining the nature of the interplay between structural and geographical features of knowledge networks. Developing a database of R&D collaborative projects of the 5th and 6th European Framework Programs, we propose a methodology based on social network analysis. Its originality consists in starting from a bimodal network, in order to deduce two affiliation matrixes that allow us to study both the properties of the organization network and the properties of the project network. The results are discussed in the light of the mutual influence of the cognitive, structural and geographical dimensions on knowledge production and diffusion, and in the light of the knowledge drivers that give rise to the coexistence of a relational core-periphery structure with a geographical cluster and pipeline structure.Economic Geography, Knowledge networks, Social network analysis, EU Framework Programs, GNSS

Evidence on Impact Evaluation of Road Transport Networks using Network Theory

The development of network theory has resulted in a growing understanding of the topological properties of transport networks. This has led to knowledge on how network indicators relate to the performance of a network, their wider socio-economic impacts and insights about how networks can best be extended. It has also provided transport planners with an insight into traffic flow, travel demand, centrality and connectivity of transport networks. This rapid evidence-review summarises literature (1999-2019) that have used network theory to evaluate the impact evaluation of road networks, it also presents the technological advancements in network theory. The identified studies outline the beneficial impacts of road networks on the economy, how connectivity can be improved to improve network resilience, reliability, performance and reduce maintenance costs. A number of studies describe how networks can be designed to reduce the impact on the environment. However, with the exception of only three studies i.e Kumar and Kumar (1999), Vasas and Magura et al. (2009) and Walker et al. (2013), the impacts are not quantified. The magnitude of the impact, for a particular network, is a function of the type of model used. As studies could not be found where different models have been used to assess similar impacts, it was not possible to compare numerically the impacts of different model types. Enhancements to network theory have focused on (i) developing new measures and indicators to assess connectivity, vulnerability and economic impact of transport networks, (ii) applying weightages to nodes and links to evaluate economic and ecological impacts and (iii) developing multiple layers within the network models for better spatial analysis. Recent studies have also expanded network theory and integrated it with risk modelling and probabilistic methodologies to identify vulnerable or critical elements within a given transport network

Simulating infrastructure networks in the Yangtze River Delta (China) using generative urban network models

This paper explores the urban-geographical potential of simulation approaches combining spatial and topological processes. Drawing on Vértes et al.'s (2012) economical clustering model, we propose a generative network model integrating factors captured in traditional spatial models (e.g., gravity models) and more recently developed topological models (e.g., actor-oriented stochastic models) into a single framework. In our urban network-implementation of the generative network model, it is assumed that the emergence of inter-city linkages can be approximated through probabilistic processes that speak to a series of contradictory forces. Our exploratory study focuses on the outline of the infrastructure networks connecting prefecture-level cities in the highly urbanized Yangtze River Delta (China). Possible hampering factors in the emergence of these networks include distance and administrative boundaries, while stimulating factors include a measure of city size (population, gross domestic product) and a topological rule stating that the formation of connections between cities sharing nearest neighbors is more likely (i.e., a transitive effect). Based on our results, two wider implications of our research are discussed: (1) it confirms the potential of the proposed method in urban network simulation in that the inclusion of a topological factor alongside geographical factors generates an urban network that better approximates the observed network; (2) it allows exploring the differential extent to which driving forces influence the structure of different urban networks. For instance, in the Yangtze River Delta, transitivity plays a less important role in the Internet-network formation; GDP and boundaries more strongly affect the rail network; and distance decay effects play a more prominent role in the road network

How to monitor sustainable mobility in cities? Literature review in the frame of creating a set of sustainable mobility indicators

The role of sustainable mobility and its impact on society and the environment is evident and recognized worldwide. Nevertheless, although there is a growing number of measures and projects that deal with sustainable mobility issues, it is not so easy to compare their results and, so far, there is no globally applicable set of tools and indicators that ensure holistic evaluation and facilitate replicability of the best practices. In this paper, based on the extensive literature review, we give a systematic overview of relevant and scientifically sound indicators that cover different aspects of sustainable mobility that are applicable in different social and economic contexts around the world. Overall, 22 sustainable mobility indicators have been selected and an overview of the applied measures described across the literature review has been presented

Measuring urban form : overcoming terminological inconsistencies for a quantitative and comprehensive morphologic analysis of cities

Unprecedented urbanisation processes characterise the Great Acceleration, urging urban researchers to make sense of data analysis in support of evidence-based and large-scale deci- sion-making. Urban morphologists are no exception since the impact of urban form on funda- mental natural and social patterns (equity, prosperity and resource consumption’s efficiency) is now fully acknowledged. However, urban morphology is still far from offering a comprehensive and reliable framework for quantitative analysis. Despite remarkable progress since its emergence in the late 1950s, the discipline still exhibits significant terminological inconsistencies with regards to the definition of the fundamental components of urban form, which prevents the establishment of objective models for measuring it. In this article, we present a study of existing methods for measuring urban form, with a focus on terminological inconsistencies, and propose a systematic and comprehensive framework to classify urban form characters, where ‘urban form character’ stands for a characteristic (or feature) of one kind of urban form that distinguishes it from another kind. In particular, we introduce the Index of Elements that allows for a univocal and non-interpretive description of urban form characters. Based on such Index of Elements, we develop a systematic classification of urban form according to six categories (dimension, shape, spatial distribution, intensity, connectivity and diversity) and three conceptual scales (small, medium, large) based on two definitions of scale (extent and grain). This framework is then applied to identify and organise the urban form characters adopted in available literature to date. The resulting classification of urban form characters reveals clear gaps in existing research, in particular, in relation to the spatial distribution and diversity characters. The proposed framework reduces the current inconsistencies of urban morphology research, paving the way to enhanced methods of urban form systematic and quantitative analysis at a global scale