Ubiquitous digital technologies and spatial structure; An update

This paper examines the impact of widespread adoption of information and communication technologies (ICT) on urban structure worldwide. Has it offset agglomeration benefits and led to more dispersed spatial structures, or has it strengthened urban externalities and thus resulted in more concentrated spatial structures? Theoretical and empirical studies on this question have produced contradictory findings. The present study recognizes that assumptions made earlier about the evolution of technological capabilities do not necessarily hold today. As cutting-edge digital technologies have matured considerably, a fresh look at this question is called for. The paper addresses this issue by means of several data sets using instrumental variable methods. One is the UN data on Urban Settlements with more than 300, 000 inhabitants. Estimation methods with these data show that increased adoption of ICT has resulted in national urban systems that are less uniform in terms of city sizes and are characterized by higher population concentrations in larger cities, when concentration is proxied the Pareto (Zipf) coefficient for national city size distributions. Two, is disaggregated data for the urban systems of the US, defined as Micropolitan and Metropolitan Areas, and for the UK, defined as Built-up Areas in England and Wales, respectively. These data allow for the impacts to be studied for cities smaller than those included in the cross-country data. Increased internet usage improved a city's ranking in the US urban system. Similarly, increased download speed improves a built-up area's ranking in England and Wales

Whether weather causes contention: assessing the ongoing resilience opportunity of telecommuting

The Covid-19 pandemic resulted in an unprecedented overnight explosion in telecommuting. It has highlighted a new dependence on digital infrastructures and raised new questions regarding the resilience of internet connectivity as an alternative to travel. Pre-pandemic, we considered how telecommuting could offer an opportunity for resilience when travel was disrupted by weather extremes. We analysed five years’ of recorded broadband speed variation across England and Wales in order to quantify the changing demand for internet access during the working day under adverse weather conditions. Slower broadband speeds, also known as contention, are an indication of increased demand. Thus, during the working day, contention is an indication that external factors like weather can influence the choice to telecommute instead of travel. A multilevel regression model is estimated to investigate the relationship between contention during the working day and weather, whilst controlling for background spatial and demographic differences in internet services. Emergent patterns suggest that even before the pandemic, online connectivity was in greater demand when travel was disrupted or at risk of disruption. Our research provides insights into the roles that both the supply of and the demand for transport and digital technologies might play in increasing resilience and maintaining productivity during severe weather and other disruptions as experience of both types of working has become so widespread

The role of space, time and sociability in predicting social encounters

Space, time and the social realm are intrinsically linked. While an array of studies have tried to untangle these factors and their influence on human behaviour, hardly any have taken their effects into account at the same time. To disentangle these factors, we try to predict future encounters between students and assess how important social, spatial and temporal features are for prediction. We phrase our problem of predicting future encounters as a link-prediction problem and utilise set of Random Forest predictors for the prediction task. We use data collected by the Copenhagen network study; a study unique in scope and scale and tracks 847 students via mobile phones over the course of a whole academic year. We find that network and social features hold the highest discriminatory power for predicting future encounters

International migration: a global complex network

Migration has become a prominent research theme in geography and regional science and it has been approached from various methodological angles. Nonetheless, a common missing element in most migration studies is the lack of awareness of the overall network topology, which characterizes migration flows. Although gravity models focus on spatial interaction—in this case migration—between pairs of origins and destinations, they do not provide insights into the topology of a migration network. We employ network analysis to address such systemic research questions, in particular: how centralized or dispersed are migration flows and how does this structure evolve over time? And, how is migration activity clustered between specific countries, and if it is clustered, do such patterns change over time? Going a step further than exploratory network analysis, in this paper we estimate international migration models for OECD countries based on a dual approach: gravity models estimated using conventional econometric approaches such as panel data regressions and network-based regression techniques such as multivariate regression quadratic assignment procedures. The empirical results reveal not only the determinants of international migration among OECD countries, but also the value of blending network analysis with more conventional analytic methods

Better by Bus?:Insights into public transport travel behaviour during Storm Doris in Reading, UK

This case study uses datasets from Reading Buses’ electronic ticketing system to gain insights into the reactions of public transport passengers to the disruption to bus and rail services in Reading, UK during Storm Doris on 23 February 2017. The analysis generally supports previous research findings that there are fewer public transport trips in adverse weather conditions. However, an increase in bus trips on services parallel to the more severely disrupted train services suggests that some travellers respond flexibly by using the bus as an alternative, more resilient mode