Contextualising demography: the significance of local clusters of fertility in Scotland

This study links empirical analysis of geographical variations in fertility to ideas of contextualising demography. We examine whether there are statistically significant clusters of fertility in Scotland between 1981 and 2001, controlling for more general factors expected to influence fertility. Our hypothesis, that fertility patterns at a local scale cannot be explained entirely by ecological socio-economic variables, is supported. In fact, there are ‘unexplained’ local clusters of high and low fertility, which would be masked in analyses at a different scale. We discuss the demographic significance of local fertility clusters as contexts for fertility behaviour, including the role of the housing market and social interaction processes, and the residential sorting of those displaying or anticipating different fertility behaviour. We conclude that greater understanding of local geographical contexts is needed if we are to develop mid-level demographic theories and shift the focus of fertility research from events to processes.Scotland, fertility, geography

Paradoxical Interpretations of Urban Scaling Laws

Scaling laws are powerful summaries of the variations of urban attributes with city size. However, the validity of their universal meaning for cities is hampered by the observation that different scaling regimes can be encountered for the same territory, time and attribute, depending on the criteria used to delineate cities. The aim of this paper is to present new insights concerning this variation, coupled with a sensitivity analysis of urban scaling in France, for several socio-economic and infrastructural attributes from data collected exhaustively at the local level. The sensitivity analysis considers different aggregations of local units for which data are given by the Population Census. We produce a large variety of definitions of cities (approximatively 5000) by aggregating local Census units corresponding to the systematic combination of three definitional criteria: density, commuting flows and population cutoffs. We then measure the magnitude of scaling estimations and their sensitivity to city definitions for several urban indicators, showing for example that simple population cutoffs impact dramatically on the results obtained for a given system and attribute. Variations are interpreted with respect to the meaning of the attributes (socio-economic descriptors as well as infrastructure) and the urban definitions used (understood as the combination of the three criteria). Because of the Modifiable Areal Unit Problem and of the heterogeneous morphologies and social landscapes in the cities internal space, scaling estimations are subject to large variations, distorting many of the conclusions on which generative models are based. We conclude that examining scaling variations might be an opportunity to understand better the inner composition of cities with regard to their size, i.e. to link the scales of the city-system with the system of cities

Mapping the Evolution of "Clusters": A Meta-analysis

This paper presents a meta-analysis of the “cluster literature” contained in scientific journals from 1969 to 2007. Thanks to an original database we study the evolution of a stream of literature which focuses on a research object which is both a theoretical puzzle and an empirical widespread evidence. We identify different growth stages, from take-off to development and maturity. We test the existence of a life-cycle within the authorships and we discover the existence of a substitutability relation between different collaborative behaviours. We study the relationships between a “spatial” and an “industrial” approach within the textual corpus of cluster literature and we show the existence of a “predatory” interaction. We detect the relevance of clustering behaviours in the location of authors working on clusters and in measuring the influence of geographical distance in co-authorship. We measure the extent of a convergence process of the vocabulary of scientists working on clusters.Cluster, Life-Cycle, Cluster Literature, Textual Analysis, Agglomeration, Co-Authorship

Knowledge Flows through Informal Contacts in Industrial Clusters Myths or Realities?

The role of informal networks in the development of regional clusters has received a lot of attention in the literature recently. Informal contact between employees in different firms is argued to be one of the main carriers of knowledge between firms in a cluster. This paper empirically examines the role of informal contacts in a specific cluster. In a recent questionnaire, we ask a sample of engineers in a regional cluster of wireless communication firms in Northern Denmark, a series of questions on informal networks. We analyze whether the engineers actually acquire valuable knowledge through these networks. We find that the engineers do share even valuable knowledge with informal contacts. This shows that informal contacts are important channels of knowledge diffusion.Informal contacts, regional clusters, communication technology

Consumer Data Research

Big Data collected by customer-facing organisations – such as smartphone logs, store loyalty card transactions, smart travel tickets, social media posts, or smart energy meter readings – account for most of the data collected about citizens today. As a result, they are transforming the practice of social science. Consumer Big Data are distinct from conventional social science data not only in their volume, variety and velocity, but also in terms of their provenance and fitness for ever more research purposes. The contributors to this book, all from the Consumer Data Research Centre, provide a first consolidated statement of the enormous potential of consumer data research in the academic, commercial and government sectors – and a timely appraisal of the ways in which consumer data challenge scientific orthodoxies

Clusters and Knowledge Local Buzz, Global Pipelines and the Process of Knowledge Creation

The paper is concerned with spatial clustering of economic activity and its relation to the spatiality of knowledge creation in various sorts of interactive learning processes. It questions the merit of the prevailing explanatory model where the realm of tacit knowledge transfer is confined to local milieus whereas codified knowledge may roam the globe almost frictionless. When doing so the paper highlights the conditions under which both tacit and codified knowledge can be exchanged locally and globally. A distinction is made between, on the one hand, the learning processes taking place among actors embedded in a community by just being there - dubbed buzz - and, on the other, the knowledge attained by investing in building channels of communication - called pipelines - to selected providers located outside the local milieu. It is argued, that the co-existence of high levels of buzz and many pipelines may provide firms located in outward looking and lively clusters with a string of particular advantages not available to outsiders. Finally, some prescriptive elements, stemming from the argument, are identified.knowledge creation, clusters, buzz, pipelines, absorptive capacity

Mobility insights through consumer data: a case study of concessionary bus travel in the West Midlands

Current transport facilities are often built around efficiency and meeting the needs of the commuting population. These can therefore struggle to provide services suited to some of the most vulnerable members of society. In order to achieve an inclusive transport system, it is vital that transport authorities have access to detailed insights into the mobility needs and demands of different groups of the population. Increasingly, these transport authorities are making use of smart technologies and the resulting data to gain greater insight into transport users, and in turn inform decision making and policy planning. These smart technologies include automated fare collection (AFC) systems, which produce large volumes of detailed transport and mobility data from smart card transactions. To a lesser extent, retail datasets, such as loyalty card transaction data, have also been utilised. The spatiotemporal components of these data can provide valuable insight into the activity patterns of cardholders that may not be captured in traditional transport data. This thesis presents an exploration of these two forms of consumer data, with a focus on the older population in the West Midlands. Firstly, this thesis demonstrates how smart card data can be processed and analysed to provide detailed insights into the mobility patterns of concessionary bus users and how these relate to long-term changes in bus patronage recorded in the study area. Secondly, the extent to which loyalty card transaction data can be employed to understand retail behaviours and activity patterns is explored, with a focus on how these insights can be used to supplement and enhance the understanding of mobility gained from the smart card data. Finally, these insights are discussed in terms of the capacity of the current transport network to meet the mobility needs of the older population and the potential of consumer data for future transport-related research

Dimensions of urban mobility cultures – a comparison of German cities

In the context of the immense economic and social challenges urban transport faces in the near future, the analysis of city-specific differences in supply and usage of urban transport systems is a promising approach for identifying potential strategies for establishing more sustainable transport systems and mobility patterns. This study aims to address such differences by a comparative approach and is, to our best knowledge, the first one capturing the subjective dimension of urban mobility by integrating satisfaction and perception-related indicators at a city-level. Drawing on the socio-technical concept of urban mobility cultures, which combines socio-economic and urban form characteristics, mode-specific infrastructure supply, as well as the travel behaviour and underlying attitudes of a city’s inhabitants, we collected a set of 23 indicators from several sources, mainly from the early 2000s. These data have been applied to a sample of 44 German cities. As a result of a factor and cluster analysis we identified six groups of cities ranging from relatively mature and homogenous socio-technical settings, referred to as ‘cycling cities’ or ‘transit metropolises’, to rather less well-defined urban mobility cultures such as ‘transit cities with multimodal potential’, whose forthcoming development is not yet directed towards a specific future and, therefore, is open for political debate. The mismatch between objective and subjective indicators of urban mobility culture that has been shown for some city groups is another starting-point for changing urban mobility cultures in terms of taking people’s perceptions and evaluations of the local transport system more seriously

Image-based activity pattern segmentation using longitudinal data of the German Mobility Panel

In this paper, we present an approach to segment people based on a visualization of the longitudinal week activity data from the German Mobility Panel. In order to perform segmentations, different clustering methods are commonly used. Most of the approaches require comprehensive prior knowledge about the input data, e.g., condensing information to cluster-forming variables. As this may influence the method itself, we used images with a high degree of freedom. These images show week activity schedules of people, including all trips and activities with their purposes, modes as well as their duration or their temporal position within the week. Thus, we answer the question whether using only this type of image data as input will produce reasonable clustering results as well. For the clustering, we extracted the images from an existing tool, processed them for the method and finally used them again to select the final cluster solution based on the visual impression of cluster assignments. Our results are meaningful as we identified seven activity patterns (clusters) using this visual validation. The approach is confirmed by the data-based analysis of the cluster solution showing also interpretable key figures for all patterns. Thus, we show an approach taking into account many aspects of travel behavior as an input to clustering, while ensuring the interpretability of solutions. Usually, key figures from the data are used for validation, but this practice may obscure some aspects of the longitudinal data, which are visible when looking on the images as validation

A planetary nervous system for social mining and collective awareness

We present a research roadmap of a Planetary Nervous System (PNS), capable of sensing and mining the digital breadcrumbs of human activities and unveiling the knowledge hidden in the big data for addressing the big questions about social complexity. We envision the PNS as a globally distributed, self-organizing, techno-social system for answering analytical questions about the status of world-wide society, based on three pillars: social sensing, social mining and the idea of trust networks and privacy-aware social mining. We discuss the ingredients of a science and a technology necessary to build the PNS upon the three mentioned pillars, beyond the limitations of their respective state-of-art. Social sensing is aimed at developing better methods for harvesting the big data from the techno-social ecosystem and make them available for mining, learning and analysis at a properly high abstraction level. Social mining is the problem of discovering patterns and models of human behaviour from the sensed data across the various social dimensions by data mining, machine learning and social network analysis. Trusted networks and privacy-aware social mining is aimed at creating a new deal around the questions of privacy and data ownership empowering individual persons with full awareness and control on own personal data, so that users may allow access and use of their data for their own good and the common good. The PNS will provide a goal-oriented knowledge discovery framework, made of technology and people, able to configure itself to the aim of answering questions about the pulse of global society. Given an analytical request, the PNS activates a process composed by a variety of interconnected tasks exploiting the social sensing and mining methods within the transparent ecosystem provided by the trusted network. The PNS we foresee is the key tool for individual and collective awareness for the knowledge society. We need such a tool for everyone to become fully aware of how powerful is the knowledge of our society we can achieve by leveraging our wisdom as a crowd, and how important is that everybody participates both as a consumer and as a producer of the social knowledge, for it to become a trustable, accessible, safe and useful public good.Seventh Framework Programme (European Commission) (grant agreement No. 284709