Letters in Spatial and Resource Sciences最新文献

The creative industries are a strategically important sector for the Cardiff Capital Region (CCR) which houses large public sector broadcasters and an ecosystem of IT and software businesses. The CCR is an administrative boundary in Wales which captures just under half of the Welsh population but over half of the Welsh economy. The pandemic and resultant lockdown restrictions have had profound impacts on the creative industries, a sector which depends heavily on in-person interaction. The creative industries are not one homogenous sector, but a collection of different activities some of which faced different supply and demand conditions due to the COVID-19 shock. To understand the impact of the shock in fine inter-industry detail and at a sub-regional scale an input-output table for the Cardiff Capital Region (the CCRC-IO) is utilized. The CCRC-IO estimates that the direct, indirect, and induced impacts of the shock see output fall by £457 m (0.53% of CCR output), GVA by £147 m (0.58% of CCR GVA) and FTE employment by 2416 (0.58% of CCR FTE). The paper finds that the economic impact of the COVID-19 shock varies considerably by both geography and sub-sector.

COVID-19 revealed some major weaknesses and threats that are related to the level of territorial development. In Romania, the manifestation and the impact of the pandemic were not homogenous, which was influenced, to a large extent, by a diversity of sociodemographic, economic, and environmental/geographic factors. The paper is an exploratory analysis focused on selecting and integrating multiple indicators that could explain the spatial differentiation of COVID-19-related excess mortality (EXCMORT) in 2020 and 2021. These indicators include, among others, health infrastructure, population density and mobility, health services, education, the ageing population and distance to the closest urban center. We analyzed the data from local (LAU2) and county level (NUTS3) by applying multiple linear regression and geographically weighted regression models. The results show that mobility and lower social distancing were far more critical factors for higher mortality than the intrinsic vulnerability of the population, at least in the first two years of COVID-19. However, the highly differentiated patterns and specificities of different areas of Romania resulting from the modelling of EXCMORT factors drive to the conclusion that the decision-making approaches should be place-specific in order to have more efficiency in case of pandemics.

As the COVID-19 pandemic hit the European continent at the beginning of 2020, one of the most significant socio-economic effects that immediately become the central focus of media and governing bodies was the unemployment and the sudden transformations suffered by the job market. This effect created major concerns for citizens and governing structures, as the pandemic generated a new and unparalleled economic context, where the short and medium-term future of several sectors seemed unpredictable. The concern acted upon the job insecurity of individuals, a perceived threat to the continuity and stability of their employment. Based on a self-reported survey covering the first pandemic wave, our study classifies the regions (NUTS2 level) from six EU countries according to their performance in terms of job insecurity, but also the shock intensity (death rates and case fatality ratio), and identifies the overall over and under performers. The results show that the regional evolution of the job insecurity could be linked to the pandemic evolution, especially in the stronger economies. However, the model does not follow a classic economic core-periphery pattern. The model is challenged especially by a stronger performance of several less performant regions from Italy, Romania, or France.

Supplementary information: The online version contains supplementary material available at 10.1007/s12076-023-00337-9.

The effectiveness and political feasibility of COVID-19 containment measures such as lockdowns, are contentious. This stems in part from an absence of tools for their rigorous evaluation. Common epidemiological models such as the SEIR model generally lack the spatial resolution required for micro-level containment actions, the visualization capabilities for communicating measures such as localized lockdowns and the scenario-testing capabilities for assessing different alternatives. We present an individual-level ABM that generates geo-social networks animated by agent-agent and agent-building interactions. The model simulates real-world contexts and is demonstrated for the city of Jerusalem. Simulation outputs yield much useful information for evaluating the effectiveness of lockdowns. These include network-generated socio-spatial contagion chains for individual agents, dynamic building level contagion processes and neighborhood-level patterns of COVID-19 imports and exports useful in identifying super-spreader neighborhoods. The policy implications afforded by these various outputs are discussed.

Supplementary information: The online version contains supplementary material available at 10.1007/s12076-023-00336-w.

The physical structure of cities is the result of self-organization processes in which profit-maximizing developers are key players. The recent Covid-19 pandemic was a natural experiment by means of which it is possible to gain insights into shifts in the spatial structure of cities by studying developers' behavior. Behavioral changes of urbanites triggered by the quarantine and lockdown periods, such as home-based work and online shopping on scales that were unthinkable heretofore, are expected to persist. These are likely to induce changes in the demand for housing, for work, and for retail space, impacting developers' decisions. Associated changes in the land values at different locations are occurring faster than changes of the physical shape of urban landscapes. It is possible that current changes in dwelling preferences will result in significant future shifts in the locational incidence of the urban intensities. We test this hypothesis by examining changes in land values during the last two years by means of a land value model calibrated with vast Geo-referenced data of the major metropolitan area in Israel. Data concerning all real estate transactions include information about the assets and the price of the exchanges. In parallel, built densities are calculated using detailed building data. Based on these data, we estimate the changes of land values for different types of dwellings before and during the pandemic. The result allows us to highlight possible initial signs of post-Covid-19 urban structures, driven by shifting behavior of developers.

Supplementary information: The online version contains supplementary material available at 10.1007/s12076-023-00346-8.

We study the effects of the COVID-19 pandemic on U.S. entrepreneurial activities, as measured by the overall number of new business applications, high-propensity business applications, business applications from corporations, and business applications with paid wages. However, the number of business applications increased significantly after the lockdown. Also, the portion of high-propensity business applications as a share of total business applications declined considerably during and after the lockdown. Our findings could partially explain the tight labor market in the U.S. during the pandemic.

The daily announcement of positive COVID-19 cases had a major socioeconomic impact. In Japan, it is well known that the characteristic of this number as time series data is the weekly periodicity. We assume that this periodicity is generated by changes in the timing of reporting on the weekend. We analyze a lag structure that shows how congestion that occurs over the weekend affects the number of new confirmed cases at the beginning of the following week. We refer to this reporting delay as the weekend effect. Our study aims to describe the geographical heterogeneity found in the time series of reported positive cases. We use data on the number of new positives reported by the prefectures. Our results suggest that delays generally occur in prefectures with a population of more than 2 million, including Japan's three largest metropolitan areas, Tokyo, Osaka, and Nagoya. The number of new positives was higher in the more populated prefectures. This will explain the weekend effect.

It is well established that a variety of physical distancing measures are invaluable as part of the overall response to pandemics. COVID-19 is the most recent such pandemic, a respiratory disease transmitted through interaction, necessitating steps to minimize or eliminate the potential for exposure. Of course, this is driven by a desire to keep the economy moving, allow for social activity, continue education, support the livelihoods of individuals, etc. Regional science and supporting analytics have an important role in managing activity through the development and application of methods that enable spatial interaction that mitigates transmission. This paper details methods to plan for physical distancing at micro-scales, enabling the return of social, economic, entertainment, etc. activities. Geographic information systems combined with spatial optimization offers important spatial coronametrics for the mitigation of risk in disease transmission. Applications detailing office space occupancy and travel along with room seating are highlighted.

Environmental degradation has been one of the hot topics discussed since the 1980s. In the literature, CO₂ emissions are generally used to represent environmental degradation. However, in this study, environmental degradation is examined in the context of ecological footprint. The study aims to investigate the effect of economic growth, energy consumption, and mineral saving on the ecological footprint in Turkey for the period of 1975-2017. For this purpose, the bootstrap autoregressive distributed lag model with a Fourier function (FARDL) method is utilized to test the long-term relationship between the variables. The findings indicate a long-term relationship between the variables. In addition, long-run estimation results based on the FARDL model show that economic growth and mineral saving increase the ecological footprint in Turkey. The conclusion discusses these findings and presents long-term policy recommendations for Turkey.