{"title":"Can Digital Inclusive Finance Promote Urban Ecological Efficiency?—Impact Mechanism and Spatial Effects","authors":"Baisheng Cui, Songyang Ma, Chunyan Hu","doi":"10.1007/s12061-023-09552-9","DOIUrl":"10.1007/s12061-023-09552-9","url":null,"abstract":"<div><p>The paper utilizes panel data from 278 cities in China spanning the years 2010 to 2020 to comprehensively assess the impact of digital inclusive finance on urban ecological efficiency. The study shows that digital inclusive finance significantly contributes to the enhancement of urban ecological efficiency, primarily attributed to the deepening of digital inclusive finance's usage depth and degree of digitization. Mechanism analysis further indicates that digital inclusive finance can expedite the concentration of human capital, foster technological innovation, and boost foreign direct investment, ultimately promoting the advancement of urban ecological efficiency. Moreover, the spatial spillover effect analysis demonstrates that digital inclusive finance not only enhances the ecological efficiency within a region but also notably elevates the ecological efficiency levels of neighboring cities. Additionally, our findings indicate that the development of digital inclusive finance has a more pronounced positive effect on improving ecological efficiency in the central and western regions, larger cities, and cities with higher levels of digital inclusive finance compared to the eastern region, small and medium-sized cities, and cities with lower digital inclusive finance development.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 2","pages":"471 - 494"},"PeriodicalIF":2.0,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138600243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Density, Division and Distance: Understanding China’s Urban Land-Use Change from an Economic Geography Perspective","authors":"Xing Gao, Jin Zhu, Jiayao Liu","doi":"10.1007/s12061-023-09550-x","DOIUrl":"10.1007/s12061-023-09550-x","url":null,"abstract":"<div><p>Although land-use change driven by general economic factors has been discussed substantially, rarely has any work been done within the perspective of economic geography – considering the impact of economic spatial differences. This study applies the 3Ds (Density, Division and Distance) framework published by the World Bank to explore their impacts on urban land-use change – focusing on urban land and stand-alone industrial land. Employing the dynamic system-GMM (Generalized Method of Moments) model and a mediating effect model, we examine the direct and indirect effects of 3Ds on land-use change in cities with different income levels and in different regions. Our results find that deepening spatial differences facilitate the expansion of urban land and stand-alone industrial land use. Furthermore, the 3Ds has indirect effects on land use through the interactions between density and distance, as well as between division and distance. These impacts are divergent in cities with different income levels and region-specific. The main contribution of this paper is twofold. Theoretically, the study develops a new systematic framework to explain land-use change within the field of economic geography. Empirically, we examine the theoretical framework of spatial inequality by considering both direct and indirect effects. This study also has important policy implications for improving the economic value of land use.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 2","pages":"439 - 469"},"PeriodicalIF":2.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139211828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"School-Housing Nexus in Urban China: A Comparative Study of the Effect of School Districts on Commercial and Danwei Housing Prices","authors":"Siqin Wang, Yuxiao Li, Zhe Gao","doi":"10.1007/s12061-023-09544-9","DOIUrl":"10.1007/s12061-023-09544-9","url":null,"abstract":"<div><p>It has been commonly recognised that school quality has significant impacts on housing prices in Western cities, however, how such school-housing relationships vary across different types of housing and urban space in transition economies is less explored. Our study aims to investigate the relationship between schools and housing in transitional China, where both commercial and Danwei housing coexist within the housing sector. This study makes three contributions to the literature. First, this study distinguishes the school-housing relationship across two types of housing—commercial versus <i>Danwei</i> housing as the unique housing characteristics in transition economies. Second, this study fully considers the neighbourhood effect on housing prices and unveils the spatial heterogeneity of school-housing relationships by spatiotemporal analyses and spatial modelling techniques. Third, this study establishes an analytical framework that can be applied to different contexts, and augmented in an assessing manner for the long-term evaluation of future education and housing policies.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 2","pages":"417 - 438"},"PeriodicalIF":2.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139215282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Convergence and Catch-Up of the Region Types in the Central and Eastern European Countries","authors":"Zoltán Egri, Imre Lengyel","doi":"10.1007/s12061-023-09551-w","DOIUrl":"10.1007/s12061-023-09551-w","url":null,"abstract":"<div><p>Our study investigates the economic growth and catch-up of the NUTS3 regions of 6 Central and Eastern European (CEE) member states of the European Union (EU), 4 countries acceding in 2004 (Czechia, Poland, Hungary, and Slovakia) and further two admitted in 2007 (Bulgaria and Romania), compared to the average of 14 older members of the EU between 2000 and 2019. We based our analysis on the urban–rural region types of the EU in the case of 185 regions, identifying predominantly urban, intermediate, and predominantly rural types. We apply Theil Index to examine the development of disparities and test the phenomena with unconditional β-convergence hypothesis. The analysis indicates that the growth of all CEE countries and their regions is faster than the EU14 average; the capitals considerably exceed it, the catch-up of other urban regions is also relatively fast, while it is very slow in the case of other regions. The convergence between the 185 regions is weak, based on the EU region typology it was initially strong between the capitals, moderate in the case of intermediate and rural types, while divergence can be observed in the urban types. The catch-up of less developed regions is very slow despite EU cohesion funding, even though 80% of the population live here. The stagnation of regional disparities and slow catch-up of less developed regions indicate the poor efficiency of the EU cohesion policy.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 2","pages":"393 - 415"},"PeriodicalIF":2.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12061-023-09551-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138513611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Spatiotemporal Patterns of Community Vulnerability in the U.S. Mobile Bay from 2000–2020","authors":"Hemal Dey, Wanyun Shao, Shufen Pan, Hanqin Tian","doi":"10.1007/s12061-023-09549-4","DOIUrl":"10.1007/s12061-023-09549-4","url":null,"abstract":"<div><p>The coastal community is confronted with heightened risks posed by climate change. Mobile Bay in the United States is a large estuarine system along the Gulf of Mexico (GOM) coast, providing critical ecosystem services for the nation. This region is however subject to increased urbanization and uncertain impacts of climate change. To ensure sustainability of this important ecosystem, it is imperative to examine the changing spatial patterns of community vulnerability to environmental changes in this region. Using data from the U.S. Census of multiple years, we investigate the changing spatial patterns of social vulnerability at the census block group level in Mobile Bay consisting of Mobile County and Baldwin County over the past 20 years (2000 – 2020). Additionally, we utilize hotspot and cluster analyses to formalize the observations of the spatiotemporal changes. Further, we examine how land use and land cover (LULC) changes co-occur with social vulnerability changes across Mobile Bay. We identify several hotspots where land cover has been converted to urban land and social vulnerability has increased. The investigation of the spatial patterns over a relatively long period helps to deepen the insight into the dynamic spatiotemporal changes of social and environmental vulnerability. This insight can better inform future plans to cope with climate change and ensure sustainability. Specifically, hotspots that have undergone urbanization and increased social vulnerability demand special attention from policy makers for future risk mitigation and disaster planning.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 1","pages":"371 - 392"},"PeriodicalIF":2.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138513634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ian Shuttleworth, Marina Toger, Umut Türk, John Östh
{"title":"Did Liberal Lockdown Policies Change Spatial Behaviour in Sweden? Mapping Daily Mobilities in Stockholm Using Mobile Phone Data During COVID-19","authors":"Ian Shuttleworth, Marina Toger, Umut Türk, John Östh","doi":"10.1007/s12061-023-09543-w","DOIUrl":"10.1007/s12061-023-09543-w","url":null,"abstract":"","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 1","pages":"345 - 369"},"PeriodicalIF":2.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12061-023-09543-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Index for Measuring Spatial Graph Dispersion in Socio-Economic Networks","authors":"Mehmet Gençer","doi":"10.1007/s12061-023-09545-8","DOIUrl":"10.1007/s12061-023-09545-8","url":null,"abstract":"<div><p>Spatial or geographical distance is influential in many socio-economic networks, but its combination with graph theoretical analysis is challenging. In this study, we define a node and network level spatial dispersion index which combines tie strength and spatial distance in a weighted graph to measure average spatial dispersion of socio-economic activities. The index is computed using an average of tie distances weighted with tie strengths. We define weighted vs unweighted, directed vs undirected, and generalized variants of the index. We demonstrate the use of our index to analyse the network of migration flows between provinces of Turkey by (1) comparing the geographic outreach of migration from provinces in different regions, (2) comparing spatial dispersion of migration to different country level spatial networks of flow such as trade, travel, or health services, and (3) testing effects of population and economic development on spatial dispersion of migration. Our results use weighted vs unweighted, and directed vs undirected variants of the index. Since the index is not problem specific, its use not only prove useful in quantifying features of the network in focus but also allows comparison across different networks. Results of this application demonstrate the suitability of the new index in quantifying and comparing the socio-economic activity in geographically dispersed networks and interpreting the differences.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 1","pages":"323 - 343"},"PeriodicalIF":2.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135870255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unraveling the Impact of Pandemic: Investigating COVID-19 Effects on Seoul’s Alley Market Districts through Sales Variance and Urban Decline Assessment","authors":"Minju Jeong, Yunmi Park, Hyun Woo Kim","doi":"10.1007/s12061-023-09547-6","DOIUrl":"10.1007/s12061-023-09547-6","url":null,"abstract":"<div><p>The global spread of COVID-19 and continuing emergence of mutated viruses have taken a direct economic toll on local alley market districts. However, the measurable economic impact of COVID-19 differs by market, depending on the characteristics of the local market district. Studies are required on market sales that reflect changes in people’s perceptions of the market’s surroundings and green spaces when considering unusual circumstance, such as a large-scale pandemic. This study aims to identify factors that influenced sales of the alley market districts in Seoul, South Korea before and during COVID-19, focusing on the perceived urban decline, index of greenness, and accessibility to parks and green spaces. A spatial regression analysis is conducted based on six factors affecting face-to-face businesses’ sales variance from 2017 to the third quarter of 2021. The findings show that perceived urban decline has a positive association with sales variance, while the index of greenness and park/green space accessibility have no statistically significant relationships with sales variance. The results suggest the need to apply the index of perceived urban decline when evaluating market revitalization according to the Regional Market Act in social disaster situations, and the need to improve market surroundings to implement the revitalization project.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 1","pages":"301 - 322"},"PeriodicalIF":2.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135617624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Urban Night Vitality Measurements and Related Factors Based on Multisource Data: a Case Study of Central Shanghai","authors":"Ziang Liu, Jining Zhang, Xiao Luo, Yuan Liang, Shangwu Zhang","doi":"10.1007/s12061-023-09540-z","DOIUrl":"10.1007/s12061-023-09540-z","url":null,"abstract":"<div><p>Urban night vitality is a manifestation of a city's diverse life and economic prosperity. However, few existing studies pay attention to urban night vitality. Furthermore, large spatial scale research of urban night vitality remains scarce. To fill these gaps, this empirical study on the urban night vitality of central Shanghai is based on fine-grained mobile phone signaling data and other multisource data. The objective of this study is twofold. First, mobile phone signaling data (with refined spatiotemporal resolutions) is applied to measure urban night vitality on a city-level spatial scale. Second, the spatial lag model is utilized to identify factors that influence urban night vitality. The results indicate that urban vitality presents a stronger commercially driven spatial agglomeration pattern during the night, and the urban night vitality of young people has a more concentrated spatial pattern than that of middle-aged and older people. Furthermore, the spatial agglomeration pattern of urban night vitality diminishes as time passes. The results of the spatial lag model reveal that night businesses and mixed land use are significantly and positively related to urban night vitality. Specifically, bars and consumption levels of stores have the highest relative significance, followed by mixed land use. These findings illuminate the understanding of the spatiotemporal characteristics of urban night vitality, which has universal significance.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 1","pages":"269 - 300"},"PeriodicalIF":2.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136152653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spatio-Temporal Investigation of Public Transport Demand Using Smart Card Data","authors":"Robert Klar, Isak Rubensson","doi":"10.1007/s12061-023-09542-x","DOIUrl":"10.1007/s12061-023-09542-x","url":null,"abstract":"<div><p>Policymakers must find efficient public transport solutions to promote sustainability and provide efficient urban mobility in the course of urban growth. A growing number of research papers are applying Geographically weighted regression (GWR) to model the relationship between public transport demand and its influential factors. However, few studies have considered the rapid development of journey inference from ticket transaction data. Similarly, the potential of GWR to analyze spatio-temporal changes that reflect changes in transportation supply and thus provide a measure for evaluating the local success of transport supply changes has yet to be exploited. In this paper, we use inferred journeys from smart card inferences as the dependent variable and analyze how public transport demand responds to a set of explanatory variables, emphasizing transport supply. Consequently, GWR and its successor Multiscale Geographically Weighted Regression (MGWR) are applied to analyze the spatially varying impact of transport supply changes for seven consecutive time frames between autumn 2017 and spring 2020, allowing conclusions about local changes in transport demand, as well as the benchmarking of transport supply changes. The (M)GWR framework’s predictive power is evaluated by training the model with past transport supply data and testing the model with data from the following consecutive years. The conducted analyses reveal that the (M)GWR model, using inferred journeys and transport supply data, can retrospectively predict the impact of transport supply changes on travel behavior and thus provides conclusions about the success of transport policies.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"17 1","pages":"241 - 268"},"PeriodicalIF":2.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12061-023-09542-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135014701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}