This research is part of the Swiss National Research Programme “Digital Transformation” (NRP 77) which investigates the interrelationships and effects of digital transformation.
With the rise of digitalization, the ground rules of where and how we work are undergoing changes: more flexible structures emerge, knowledge formation becomes the primary driver of economic success, and, most importantly, the relevance of spatial proximity may change as digitalization facilitates social contacts without geographical proximity. This seismic shift extends beyond how we earn our income into how we spend it. The rise of ecommerce companies proves the increasing relevance of online-based, time and location independent consumption outlets. These dramatic changes in the way we earn and spend our money will likely drive the spatial distribution of economic activities. On the macro level, digitalization will affect the balance between agglomeration and dispersion forces, and consequently whether cities will gain at the expense of peripheral regions or vice versa. On the micro level, the organization of economic activities within cities may change.
The recent COVID-19 pandemic could change the future of work and cities forever. The comprehensive removal of underlying technical barriers combined with a changing work culture could lead to an increasing proportion of work being carried out remotely or regularly from home. This could also have a significant influence on the decision in which locations the public sector should invest in local infrastructure projects or construction projects in the future, as well as fundamentally changing the general direction of regional policy. Despite the obvious importance of this development, very little is known about the associated effects on the spatial structure of economies.
In this project, we aim to change this by analyzing how the underlying forces that influence the spatial distribution of economic activity change in a world of increasing remote working. To do this, we calculate an index which shows the possibility of working from home for individual occupations and labor market regions (working from home, WfH). The possibility of working from home is mainly influenced by the digitization of work processes, a suitable IT infrastructure within the company, the availability of digital communication tools and further training measures for employees. Figure 1 shows that in April and May 2020 (after the first lockdown in Germany) in precisely those labor market regions in which employees had a higher ability to work from home, there was a greater decrease in commuting between German cities and districts. A possible explanation for this pattern might be a higher number of workers who worked from home in the first phase of the COVID-19 pandemic. While this is informative in and of itself, it does not tell us much about how the spatial distribution of skills, people and ideas changes as more and more people work from home. How is the productivity of employees and companies changing? To what extent do the average commuting costs decrease when it becomes less necessary to commute to the original place of work 5 days a week? What effects does this have on the choice of place of residence? How does this relate to the general welfare level of the economy when households can choose to live in places for which they have stronger preferences rather than where commuting costs are low enough? Who works where and do people have to live near these places?
Cities are platforms for social interactions, composed of complex, vibrant networks of individuals with different histories and backgrounds. These social networks are of particular importance as they foster learning and innovation spillovers, contributing to information diffusion and agglomeration economies. Mobility changes due to new digital possibilities (home office and e-commerce), shuffle these networks' structure that shapes urban areas as we know them.
This project intends to understand how individuals' exposure to different demographic groups is affected by such treatments. Using anonymized collocation cell phone data for more than 1.2 million individuals in Singapore (21% of the 2020 population) between September 2019 and May 2020, we assess how social mixing is affected by several mobility shocks, including the Covid-19 social distancing measures, heavy air pollution, and weather anomalies. In particular, we measure social mixing across age groups and ethnic groups.
With these results in hand, we focus on the ties holding these different demographic clusters together. We then compute a betweenness centrality index for each node and identify the agents and places pivotal for the network cohesion. We complete this with a percolation analysis exercise to estimate who and how many agents need to be removed from the city's network for the latter to collapse in a multitude of demographically homogenous clusters. Overall, this project provides new insights into the key agents and places that hold urban networks together. At the dawn of a digital age, it sheds light on the process through which lessened mobility unravels cities' social bonds and may affect agglomeration economies.
We develop a novel framework for the detection of consumption areas for different types of socio-demographic population groups. This structural framework provides with information about the value of consumption access. We identify potential case studies across Switzerland where digitalization in form of online shopping contributed to the replacement of traditional inner-city retail and department stores. The aim is to quantify how these replacements affect not only the location and importance of consumption areas, but also the flows and spatial interactions among individuals and population groups.