Uwe Neumann (p)

Boris A. Portnov

In the current debate about the labour market outcomes of technological progress, concerns arise that labour may be replaced by machines in line with decreasing costs of computing power and advances in artificial intelligence and robotics. It is uncertain whether positive employment effects due to creation of new tasks and as an outcome of price reductions made possible by productivity increases might outweigh the risks of automation The study explores to what extent adaptation to digital change has affected regional employment growth and regional disparities in Germany over the past decade. It draws on data from the German Employment Office and further administrative statistics characterising local economies at the level of municipal districts and labour market regions. The empirical framework derives from a model of change in labour demand in the light of technological progress. The analysis finds no evidence for a net decline in employment in connection with technological progress during the study period. On the contrary, labour market regions where many employees perform occupational tasks susceptible to automation have fared comparatively well so far. After all, these regions often comprise strong manufacturing industries, e.g. in rural southern Germany. In regions dominated by less prosperous industries, however, implementation of job creation potentials may turn out to be a much greater challenge.

Alexandra Sandu (p)

Uwe Neumann

The Covid-19 pandemic has brought the issue of digital divides to the forefront, particularly in the context of remote learning. In Wales, the remote learning platform – Hwb, has been an important resource for facilitating online learning during the Covid-19 pandemic. However, disparities in access have created spatial and social inequalities, with pupils from disadvantaged backgrounds facing barriers to remote learning. This research employs statistical analysis of Hwb learning platform access data to identify the socio-economic and geographic factors that contribute to these inequalities before and during the Covid-19 pandemic. The findings reveal inequalities in remote learning access, with pupils from disadvantaged backgrounds facing the most challenges. By highlighting the spatial and social inequalities that exist in access to remote learning (Hwb learning platform), this research aims to promote awareness of these issues and allow for more targeted policies to address them.

Oleg Dashkevych, Boris A. Portnov (p)

Alexandra Sandu

Policymakers are often proud to advertise their cities as smart, emphasizing the wide–spread adoption of internet technologies, innovation activities, and a number of universities the city host as a proof of successful transition towards greater smartness. Question, however, remains whether this push towards greater smartness results in tangible benefits for local residents. We attempt to answer this question by comparing different measures of city smartness – innovation index, the number of wireless access points, the number of universities, etc., – with indicators of intra–urban income disparity and environmental conditions in cities. For the analysis, we use data on 100+ major cities worldwide, of which 40 cities are national capitals. As our analysis shows, the proliferation of internet technologies and the number of universities the city hosts, i.e., popular ways of advancing city “smartness”, are not related to either intra–urban income disparity or environmental performance of cities per se. We attribute this, rather surprising, result to the fact that internet proliferation and more places of higher learning might create opportunities for bettering cities but do not guarantee that these opportunities are realized. The study helps to understand better the smart city phenomenon and its implication for urban development.