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This study explores the future of Urban Digital Twin (UDT) in urban planning systems of developing countries, with a focus on Iran. Despite UDT's growing popularity, its implementation in developing countries is limited. The research identifies critical factors influencing UDT development, including organisational acceptance, urban infrastructure, policy and legislation, and technology and innovation. Using a futures studies approach, the study employs the Delphi method, MICMAC (Matrix Impact Cross-Reference Multiplication Applied to a Classification) technique, and SISMW (Strategic Uncertainties and Strengths Weaknesses Opportunities and Threats Matrix) methodologies to analyse these factors. The study reveals that international sanctions, organisational factors, technological factors, and infrastructure limitations hinder UDT development in Iran. However, UDT technology has the potential to transform urban planning in developing countries. The study provides a roadmap for collaboration between public and private sectors and research institutes to facilitate UDT implementation, highlighting the importance of legislative frameworks, digital infrastructure, innovation, and stakeholder engagement. Policy implications suggest that governments should prioritise supportive policies, investments in digital infrastructure, and collaborative efforts to address data privacy, security, and ownership issues. By addressing these challenges, developing countries can leverage UDT technology to improve urban planning, resource management, and quality of life. [ABSTRACT FROM AUTHOR]

We propose a microeconomic foundation for transportation and land use choice model integration based on the theory of home production. A utility function is developed that considers both household monetary expenditure and individual time use. We introduce a parallel constrained multiple discrete-continuous extreme value (MDCEV) structure that allows for the inclusion of multi-person households in the model. An empirical application is provided for the Greater Toronto Area using a validated synthetic dataset. Empirical results demonstrate an economy of scale in time devoted to home production, analogous to scaling exhibit in market production. It was found that the mix of dwelling types (detached, apartment, etc.) has a significant influence on both time use and consumption. Finally, we provide several directions for future research to advance the practice of urban modelling and better capture the complex dynamics of household decision-making. [ABSTRACT FROM AUTHOR]

A key strategy for reducing regional pollution transfer and hastening the transition to carbon neutrality is to encourage the urban green development (UGD). However, UGD in urban agglomerations is hampered by policy inconsistencies and economic inequalities between cities. Urban Agglomeration innovation communities (UAIC), which are supposed to improve GDA by reducing policy and economic disparities between cities through collaborative innovation, are emerging as a new policy strategy for countries to speed up the integration of urban agglomerations and to promote regional cooperation and sharing of science and technology. However, empirical studies of UAIC effects on the environment are still lacking. Based on measured the UAIC index and the UGD level of the urban agglomeration in the middle reaches of the Yangtze River (TUAMRYR) from 2011 to 2019, this paper used spatial regression model to test the direct effect, spillover effect, and attenuation boundaries of UAIC on UGD, as well as to analyze the various impacts of the four sub-systems of UAIC on UGD, respectively, from the system perspective. The following are the key findings: First, the UAIC and UGD of TUAMRYR have been rising gradually and exhibit a spatial distribution pattern of "center-periphery". Second, for every unit increase in the UAIC index, local UGD can be improved by 0.432 units, and UGD in nearby areas can be encouraged by 0.312 units. Third, 325 km serve as the attenuation barrier for the spatial spillover effect of UAIC on UGD. Finally, UGD can be impacted by independent innovation subsystem, collaborative innovation subsystem, innovation ecological environment subsystem, and innovation performance subsystem, however the impacts they have on UGD vary. [ABSTRACT FROM AUTHOR]

This study examines the interplay between urban policy interventions, infrastructure investments, and economic and labor market outcomes in large metropolitan areas from 2017 to 2022. We have employed empirical research to unravel the phenomena among these domains by employing a comprehensive dataset comprising gross value added (GVA), compensation of employees, gross fixed capital formation, environmental taxes, trade, employment, and time series data for demographic cohort transitions. Through a linear regression analysis, we uncovered strong positive associations between gross fixed capital formation and GVA and employment per capita, highlighting the critical role of infrastructure in driving urban economic growth. We also scrutinize how population dynamics—natural population changes and net migration—affect economic performance, offering valuable insights for evidence-driven urban policy. This research informs sustainable urban economic development policies and contributes significantly to the urban economics discourse. [ABSTRACT FROM AUTHOR]

Latin American nations are highly urbanised around a small number of megacities that account for the majority of these nations' productivity and population. Scholars of urban planning and economics argue these cities may be overly large, leading to environmental, transportation and housing issues that depress growth and increase economic inequality. We use fine-grained satellite data from 1992–2018 to document urban concentration in Latin America. We argue political decentralisation creates incentives to distribute urban populations more evenly throughout the territory. Our results demonstrate a strong empirical relationship between political decentralisation and lower urban concentration. We link our findings to literature on economic geography, political institutions and urbanisation, with broader implications for the politics of economic growth. [ABSTRACT FROM AUTHOR]

This paper addresses the gaps in understanding green regional path development and the role of firm-level agency in driving regional green transitions. By analysing a large patent dataset covering 30 years, we provide a systematic account of green regional path development in 70 regions across four Nordic countries. We identify six types of green path development – extension, stagnation, extinction, diversification, renewal and creation – and explore how different types of organisations – incumbents and new entrants – contribute to these paths. We show that regions often have multiple green paths, and the dominant types are mostly driven by incumbents. [ABSTRACT FROM AUTHOR]

This article explores the role that foundational economy (FE) actors can play in innovation in peripheral regions. We argue that research which casts peripheral regions as backwaters of innovation may inadvertently underplay the potential for innovation in such places. Drawing on the peripheral innovation literature, and emerging research on the FE, we develop the concept of mundane innovation and explore its potential for peripheral regions. We address this question through a short case-study of Carmarthenshire (Wales) and find that it may offer potential for such regions to become leaders rather than the laggards they appear in the conventional innovation literature. [ABSTRACT FROM AUTHOR]

We study the impact of agglomeration effects on firms' total factor productivity (TFP) for industry groups defined by technology intensity. This allows for non-uniform effects on firms depending on their technological level. We find that urban economies have the largest impact on firm productivity in high-technology industries, while they have no effect in low-technology industries. For firms in the latter industries, the diversity of the local economic structure is relevant. Localisation effects have a consistently positive and significant impact on TFP, with the effect increasing with the technology intensity of the industries. [ABSTRACT FROM AUTHOR]

This article conceptualises the circular economy as a space of immaterial, as well as material, metabolic flows mediated by capitalism and planetary urbanisation. World-ecology provides us with the critical lens to view the circular economy as part of an emergent regime of accumulation that may supersede neoliberalism. However, if each regime entails new frontier zones for appropriating cheap natures and dumping wastes, then the circular economy—as a strategy for revalorising waste—presents a possible structural limit to capitalism's further expansion. Moreover, when combined with notions of degrowth and doughnut economics, the circular economy may provide an imaginary and set of prefigurative practices that point towards a postcapitalist economy. Through a case study of Amsterdam—a city aiming to be fully circular by 2050—we examine this contradictory crossroads, problematising the idea of circularity within capitalism and exploring the potential of postcapitalist alternatives within the circular economy. [ABSTRACT FROM AUTHOR]

Copyright of Revue d'Économie Régionale & urbaine is the property of Librairie Armand Colin and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article presents the one‐sided intellectual influence of Economics on Urban Studies & Planning, the case of two social science disciplines with different epistemologies and approaches to policy advice. Subsequently, it presents the emergence of the so‐called evidence based policy (EBP) approach in Economics, comprising experimental (randomized control trial) and quasi‐experimental (difference‐in‐differences and propensity score matching) methods. The article shows that even though EBP claims to be exempt from normative/political, and even theoretical, considerations, it builds upon two features of neoclassical economics: sufficiency and separability. These conditions comprise its normative neoclassical theory background. We discuss the neoliberal turn in development narratives and their influence on urban planning, which coincides with the emergence of EBP. We analyze some EBP examples in the urban planning scholarship. [ABSTRACT FROM AUTHOR]

The aim of the current research is to investigate the position of NGOs in improving the economic, political and social conditions of citizens in Tehran Municipality between 2010 and 2018. The statistical population of this research is the managers and senior experts of the 22 districts of Tehran and their related 121 districts, of which 220 people including the mayors of each district and its districts and senior managers will be selected as a statistical sample in the order of position priority. The required information was also collected through a researcher-made questionnaire whose validity and reliability were confirmed, and the results were obtained based on Friedman’s test, quadratic factor analysis method, and using SPSS and Lisrel software. The obtained results indicate a significant difference in the components of urban management and confirm NGOs’ role in improving urban management (urban social sciences, urban economics and urban politics) in Tehran Municipality from 2018 to 2019. Based on the Friedman test, the significant difference in the components has been investigated. The result of the ranking shows that the urban economy component has the highest rank and is the component in which NGOs play a more effective role. Finally, after performing the exploratory factor analysis, the fitting of the model and second-degree confirmatory analysis were done, the findings of which show that NGOs played an influential role in the component of social sciences, urban economy and urban policy improvement in Tehran Municipality between 2010 and 2018. has it. The main role of NGOs is related to the urban economy component. Considering that providing citizens’ needs, and providing welfare services, are basically infrastructures that are established by municipalities. All of them ultimately lead to the dynamism of the city’s economy and the improvement of the citizens’ well-being. [ABSTRACT FROM AUTHOR]

Introduction Crime is a multifaceted phenomenon that has always attracted the attention of economists, sociologists, lawyers and psychologists. Many experts and economic pioneers consider it necessary to achieve economic development to improve the level of security and reduce crime in the society. Since the occurrence of any phenomenon is affected by various factors, the occurrence of crime as an undesirable phenomenon is not excluded from this rule. Various economic, social and political factors affect crime in society. Identifying these factors can help a lot in the correct understanding and appropriate policy making in order to control and reduce the crime rate in the society. Meanwhile, one of the most important economic factors affecting crime is unemployment. Unemployment is one of the most important macroeconomic variables, which clearly affects many social phenomena, including crime. In this regard, the main goal of the present study is to investigate the relationship between unemployment and crime and to identify factors affecting crime in the Iranian cities. The statistical population of the current research is the cities of Iran and the time range under investigation is 2016. Methodology In this study, the spatial causality test was used to investigate the relationship between unemployment and crime. The first step in investigating the spatial causality relationship between the studied variables is to perform the spatial independence test of the variables. In the second step, the existence of spatial dependence between variables is examined. If both the investigated variables have a spatial structure and there is a spatial dependence between the two variables, then the spatial causality test is performed in the third step. In this study, the spatial econometric approach has also been used to estimate the crime model in the cities of Iran. In this regard, the presence of spatial effects in the model has been tested using Moran's I test, and then the most appropriate spatial regression model has been selected and estimated based on the Lagrange coefficient (LM) test and the LR diagnostic tests. The software packages used in this study are Matlab 2023, GeoDa 1.16 and Stata 15. Findings The results of the spatial tests show that both crime index and unemployment rate have a spatial structure and the spatial dependence between these two variables was also confirmed, so in the third step, the spatial causality has been tested. The results of spatial causality test indicate the existence of a two-way causality relationship between the crime index and the unemployment rate. In other words, unemployment was the cause of crime during the period under investigation, and unemployment also led to the occurrence and increase of crime. According to the results of the spatial causality test, the crime model of the Iranian cities was developed in terms of the unemployment variable and several control variables. In order to estimate the model, the presence of spatial effects was first investigated using Moran's I test. The results of this test indicate the presence of spatial effects in the model. Also, based on the results of the Lagrange coefficient and likelihood ratio tests, the Spatial Durbin Model (SDM) was chosen as the most appropriate method for estimating the model. The results of the estimation of the crime model indicate that the spatial lag coefficient is positive and significant at a high level, which indicates the existence of spatial dependence in the model. The positiveness of this coefficient shows that an increase in crime in one city causes an increase in crime in neighboring cities. Also, according to the results of the research, the variables of unemployment, industrialization, urbanization and divorce rate are the most important variables affecting crime rate. The results show positive and significant relationships between unemployment, urbanization, divorce rate, and crime. The industrialization variable also has a negative and significant effect on crime. Also, the spillover effect of the unemployment variable is negative and significant. Based on the results, the higher the unemployment rate and the urbanization rate in the cities, the crime rate will also increase in those cities. On the other hand, as cities move toward industrialization and the number of industrial enterprises in them increases, the rate of crime will decrease more. Discussion and conclusion The findings reveal that, unemployment is one of the most important variables affecting crime in the Iranian cities. So, it is recommended that authorities pay special attention to sustainable policies regarding employment and its proportional distribution in cities. Considering excessive growth of urbanization and its detrimental impact on rampant crime rates, it is suggested that statesmen and policy makers create more facilities and pay special attention to rural areas to provide reverse migration in order to prevent occurrence of various crimes, which are happenning due to population increase especially in informal settlements of larger cities.

This paper uses the question posed in its title—what drives urban redevelopment activity?—to frame a comparison of machine learning and econometric approaches for modeling parcel change. It starts by arguing that geographical science has an obligation to weigh the tradeoffs of methods as they emerge into the mainstream—especially when they spread like wildfire as, machine learning has. The empirical analysis, which makes up the middle sections of the paper, examines parcel changes in Boston, Chicago, and Seattle between 2010 and 2020. Two machine learning approaches, k nearest neighbors and random forest, are benchmarked against an econometric approach, probit. The models are explained in a way that is intended to be accessible to a broad audience and evaluated using intuitive metrics; throughout, an effort is made to draw a clear link between machine learning and econometric methods. The modes of analysis rest on different knowledge bases, so analysts should take care to ensure to distinguish between the two. The paper closes with a summary and some concluding thoughts. Overall, it suggests that machine learning and econometric approaches extend the reach of other's capabilities and, therefore, should be viewed as complements, not substitutes. [ABSTRACT FROM AUTHOR]

This article explores the territorial stigmatisation–gentrification nexus and how it is advanced by an intellectual pipeline between academics and policymakers in the USA. Despite much research revealing the pathologising narratives latent within displacement-inducing urban policies, little work has explicitly sought to underscore the influence of academic discourses in promoting these policies. Centring a triad of discourses surrounding concentrated disadvantage, social mix and neighbourhood effects – emergent namely from the academic fields of urban sociology, criminology, urban planning and urban economics – I provide an evidential linkage between academic discourse and displacement-causing US policymaking by conducting a document analysis of official reports related to two major US government programmes: the Moving to Opportunity for Fair Housing (MTO) Demonstration programme and the Housing Opportunities for People Everywhere (HOPE) VI programme. I suggest that these academic discourses operate to legitimise displacement via neighbourhood-centric framings which advance territorial stigmatisation and related gentrification. These discourses, I argue, reinforce the real estate state and the destructive capitalist force of uneven geographical development while working to facilitate the disregard of propositions that would effect structural change. I conclude with an explanation for the present configuration of the academy-to-policy pipeline and why it has failed to onboard critical, macro-structurally orientated scholarship, and issue a call for a direction forward. [ABSTRACT FROM AUTHOR]

In celebration of the centennial of the birth of Charles M. Tiebout, the current essay establishes the Tiebout hypothesis regarding jurisdictional composition as an origin of club theory and the study of local public goods. The Tiebout hypothesis and club theory constitute two of many foundational contributions to public choice. Tiebout's voting-with-the-feet analysis exerts a lasting influence on empirical investigations in urban and regional economics regarding city size, regional composition, housing price capitalization, and migration patterns. The current paper displays three fundamental club models to establish an unmistakable linkage between the Tiebout hypothesis and club theory. Given that linkage, the paper also identifies essential differences between the two analyses. Myriad applications of club theory to virtually all fields of economics highlight Tiebout's far-reaching legacy. [ABSTRACT FROM AUTHOR]

The impact of sporting events on local economies and their spatial distribution is a topic of active policy debate. This study adds to the discussion by examining granular cellphone location data to assess the spillover effects of Major League Baseball (MLB) games in a major US city. Focusing on the 2019 season, we explore granular geospatial patterns in mobility and consumer spending on game days versus non-game days in the Saint Louis region. Through density-based clustering and hotspot analysis, we uncover distinct spatiotemporal signatures and variations in visitor affluence across different teams. This study uses features like game day characteristics, location data (latitude and longitude), business types, and spending data. A significant finding is that specific spatial clusters of economic activity are formed around the stadium, particularly on game days, with multiple clusters identified. These clusters reveal a marked increase in spending at businesses such as restaurants, bars, and liquor stores, with revenue surges of up to 38% in certain areas. We identified a significant change in spending patterns in the local economy during games, with results varying greatly across teams. Notably, the XGBoost model performs best, achieving a test R2 of 0.80. The framework presented enhances the literature at the intersection of urban economics, sports analytics, and spatial modeling while providing data-driven actionable insights for businesses and policymakers. [ABSTRACT FROM AUTHOR]

In urban economics, transportation costs are a key determinant of land value. However, in virtual worlds, these costs are generally limited by the users' ability to teleport. Drawing from urban and attention economic literature, we propose a theoretical model microfounded on user behavior. The model suggests that the relative value of land parcels hinges on their potential to attract visitors. Our empirical analysis supports this by demonstrating that location remains crucial in virtual worlds and highlighting the role of the teleportation threshold. We discuss the model's general applicability, reaffirming the significance of location within most virtual worlds. [ABSTRACT FROM AUTHOR]

The article delves into the Framework Conditions for Net-Zero Industry Clusters in Europe, emphasizing the significance of innovation and industrial perspectives in achieving decarbonization goals. It underscores the need to enhance competitiveness in key net-zero technologies to avoid external dependencies and highlights the role of industry clusters in sustainable growth. The document also explores potential characteristics and locations of future net-zero industry clusters in Europe, addressing spatial competitiveness issues and relevant location factors. Insights from experts like Michael Porter are included, covering topics such as clusters, regional development, and renewable energy sources. [Extracted from the article]

Identifying land use mix (LUM) in urban areas is challenging, often requiring extensive human intervention and fieldwork. Accurate classification of LUM is crucial for various disciplines, including urban planning, urban economics, and public health. This study addresses this need by employing Voronoi triangulation and an entropy-based LUM formula using point-based geospatial data collected from publicly available sources. The methodology was tested in two distinct urban settings: Ankara and Kadıköy. Ankara, the capital city, provides a large and diverse urban environment, while Kadıköy, a district in Istanbul known for its dynamic urban life, offers a contrasting scenario. Results were analyzed concerning local spatial autocorrelation and point of interest (POI) intensity. The comparative analysis demonstrated that the approach performs well across different urban contexts, with improved results observed in Kadıköy due to its higher density of mixed-use development. Specifically, we managed to identify mixed land use areas with an accuracy of up to 78% and an F1-score of 83% in urban regions. These findings highlight the robustness and applicability of our approach in diverse urban environments, providing valuable insights for city planners and policymakers in optimizing the allocation of urban resources and enhancing land use efficiency. [ABSTRACT FROM AUTHOR]

Summary Prompted by modern technologies in data acquisition, the statistical analysis of spatially distributed function‐valued quantities has attracted a lot of attention in recent years. In particular, combinations of functional variables and spatial point processes yield a highly challenging instance of such modern spatial data applications. Indeed, the analysis of spatial random point configurations, where the point attributes themselves are functions rather than scalar‐valued quantities, is just in its infancy, and extensions to function‐valued quantities still remain limited. In this view, we extend current existing first‐ and second‐order summary characteristics for real‐valued point attributes to the case where, in addition to every spatial point location, a set of distinct function‐valued quantities are available. Providing a flexible treatment of more complex point process scenarios, we build a framework to consider points with multivariate function‐valued marks, and develop sets of different cross‐function (cross‐type and also multi‐function cross‐type) versions of summary characteristics that allow for the analysis of highly demanding modern spatial point process scenarios. We consider estimators of the theoretical tools and analyse their behaviour through a simulation study and two real data applications. [ABSTRACT FROM AUTHOR]

This is the first study to analyse the contribution of context to firms' perception of innovation barriers in a single country. Using the Ecuadorian Innovation Survey and multilevel logit models, we study whether the geographical location of Ecuadorian firms makes them more likely to assess three financial, five knowledge and two market barriers as relevant factors hindering their innovation activities. Our results indicate that location in one of Ecuador's 24 regions has only a subtle effect on perception of barriers. After controlling for internal and sectoral characteristics of firms in each region, we find that only 2–6% of the dispersion observed for whether a barrier is perceived as relevant is due to regional differences. For financial and knowledge barriers, half of that small geographical component disappears when the model includes regional population density. Based on the latter result, we argue that urban economics arguments can explain the spatial distribution of firms' perception of innovation barriers in this small developing country. Our results provide a critical reflection to advance the current research agenda on contextual factors affecting innovation. [ABSTRACT FROM AUTHOR]

We document how a select set of large and growing metropolitan areas have accommodated growth in their housing supply over 40 years. In particular, we examine how housing provision has evolved for the largest four metropolitan statistical areas (MSAs) in California and Texas. Despite differences in their topographies and regulatory environments, we find several common dynamics. As these MSAs grow, we see that fewer new net units are built at the periphery and a smaller share of the new units are built as single‐family detached houses. As a greater share of new net units are built in infill locations, more units are built using higher‐density—and more costly—multifamily housing construction techniques. Interestingly, we see these housing supply patterns in both "pro‐growth" MSAs and "highly regulated" MSAs. Among all of our sample MSAs, we also find a declining share of Census tracts that participate in accommodating growth. Our results are consistent with the existence of a convex housing supply curve. We believe that this secular trend will pose genuine challenges to many urban housing policies aimed at improving affordability. [ABSTRACT FROM AUTHOR]

Space has always been essential within the economy, yet its importance in economics has been downplayed in several ways. This editorial introduces the seven papers comprising this issue of Spatial Economic Analysis (SEA) and shows that while the classics of economics acknowledged the importance of the location of economic activities, for many years the study of space was left to heterodox economics scholars and geographers. This is despite the established tradition of learned societies, such as Regional Science International and the Regional Studies Association, which are placed at the intersection of these fields. Space finally became mainstream in economics again due, on the one hand, to the introduction of the new economic geography some 30 years ago and, on the other, to the fact that several different economic sub-disciplines have come to understand and consider space as essential for the processes they study. This was facilitated by methodological advancements, such as in spatial econometrics. The seven papers in this issue henceforth illustrate some of the situations and approaches which make space relevant to contemporary economic questions. Essential are, in particular, the interactions between different locations and the interactions between individuals and geographical features. [ABSTRACT FROM AUTHOR]

The article is a report from the editor of the American Economic Journal: Applied Economics, a journal that publishes empirical papers on various topics in applied economics. The report discusses the distribution of papers published, the editorial process, and the use of associate editors. The journal aims for quick turnaround times and has increased the number of papers published per year. The given text appears to be a list of names, possibly of authors or contributors to a document or publication, but it is unclear what the specific content of the document is based solely on the list of names. [Extracted from the article]

Over the last 20 years, the stock market indicates that value creation has become heavily concentrated in a few headquarter cities. At the same time, firms in value-creating cities have experienced declines in their profitability, because of large increases in wages and rents. Our findings thus highlight the difference between flow-based (e.g., operating profits) and stock-based (e.g., securities prices) indicators of local productivity. Conventional proxies for a city's appeal to high value-added workers, such as education rates and weather, are positively related to stock market valuations, but negatively related to near-term operating performance. [ABSTRACT FROM AUTHOR]

Abstract Accessibility of transport infrastructure, commercial amenities, recreational facilities, and green spaces is widely recognised as crucial to the well-being of urban residents. However, these features are often unevenly distributed across the geographical boundaries of a city, leading to disparities in the local quality of life. This study focuses on the city of Warsaw, Poland, and uses the aforementioned characteristics and the framework of the '15-min city' concept to construct a grid-level urban Quality of Life Index (QOLI) that facilitates comparisons between the city’s districts and local neighbourhoods. The results of our study reveal a “high-inside, low-outside” pattern of quality of life, characterised by higher standards of living in the central districts and lower standards at the city's periphery.

The article "Notes on Contributors" from Social Research provides brief biographical information about various experts in fields such as economics, history, and politics. The contributors come from diverse backgrounds and have expertise in areas like fascism, sovereign debt, and economic policy. They hold positions at prestigious institutions and have authored numerous books on their respective subjects. [Extracted from the article]

The article focuses on advancing methods for evaluating, managing, and implementing technologies aimed at creating sustainable cities. Topics include the use of econometric models to assess sustainability, strategies for integrating global costs and benefits into urban governance decisions, and the effects of land use changes on urban resilience and health.

With the increasing demand for accurate multimodal data analysis in complex scenarios, existing models often struggle to effectively capture and fuse information across diverse modalities, especially when data include varying scales and levels of detail. To address these challenges, this study presents an enhanced Swin Transformer V2-based model designed for robust multimodal data processing. The method analyzes urban economic activities and spatial layout using satellite and street view images, with applications in traffic flow and business activity intensity, highlighting its practical significance. The model incorporates a multi-scale feature extraction module into the window attention mechanism, combining local and global window attention with adaptive pooling to achieve comprehensive multi-scale feature fusion and representation. This approach enables the model to effectively capture information at different scales, enhancing its expressiveness in complex scenes. Additionally, a cross-attention-based multimodal feature fusion mechanism integrates spatial structure information from scene graphs with Swin Transformer’s image classification outputs. By calculating similarities and correlations between scene graph embeddings and image classifications, this mechanism dynamically adjusts each modality’s contribution to the fused representation, leveraging complementary information for a more coherent multimodal understanding. Compared with the baseline method, the proposed bimodal model performs superiorly and the accuracy is improved by 3%, reaching 91.5%, which proves its effectiveness in processing and fusing multimodal information. These results highlight the advantages of combining multi-scale feature extraction and cross-modal alignment to improve performance on complex multimodal tasks.

This study examines the effects of South Korea’s Innovative City (IC) policy, which aims to redistribute public institutions to local cities to alleviate urban congestion and mitigate regional disparities. Utilizing the synthetic control method, this study evaluates the policy’s influence on local productivity and investigates its spillover effects. The findings reveal a marked increase in productivity within rural cities, highlighting the policy’s efficacy in less urbanized areas. However, the outcomes vary across different locales, with some urban ICs experiencing productivity enhancements, while rural ICs near expanding urban areas do not. Additionally, the study observes limited spillover effects in cities near ICs, indicating that indirect benefits are not uniformly distributed. [ABSTRACT FROM AUTHOR]

There is a growing awareness that the condition of the built environment has a substantial impact on health. Systematic housing conditions surveys are a method for developing information about the physical condition of housing. This paper introduces the Center for Economic Information's (CEI) Neighborhood Housing Conditions Survey (NHCS). We discuss the history and implementation of the NHCS in light of other academic and civic housing conditions surveys. The paper also reviews the history and method of the NHCS. We find that housing conditions surveys are generally designed from scratch for each new research program, translating survey results into policy remains underdeveloped in the scholarly literature, and heterogeneity between surveys reduces the ability to compare observations across space and time. The NHCS may address some of these issues, suitable as an "off the shelf" template, adjustable to suit programmatic needs, and providing a baseline consistency across space and time. [ABSTRACT FROM AUTHOR]

Spatial dynamics of logistic allocation in large urban centers has gained relevance in urban economics, public policy formulation and transport engineering. A crucial aspect of these spatial, agglomerative, and dispersive phenomena are the causal links that such processes generate or by which they are generated. This study investigates the causal relationships linked to the allocation of logistics warehouses in the context of the sub-regions of the São Paulo Metropolitan Region (SPMR) based on the theory of agglomeration economies. Two variables related to the urban distribution of goods were selected: (a) Gross Domestic Product (GDP) and (b) Cargo Theft (CT) and contrasted with the number of logistics warehouses (NW). Five regions of the SPMR were considered both for spatial descriptive analysis and for the study of causality based on the Granger methodology, adapted by Hurlin, and on the cointegration methodology and Panel Vector Error Correction Model. For SPMR, the relationships obtained demonstrate, in the short term, unidirectional causalities between GDP/NW. In the short term, the causal relationship between CT/NW for the metropolitan region was unidirectional from the amount of cargo theft to the number of warehouses. The subregions showed strong heterogeneity in causal relationships, both in the short and long term, demonstrating the complexity of the logistical allocation phenomena in the SPMR. • Cargo theft is a crucial decision factor when installing a logistic warehouse. • The demand in high-GDP regions increases the need for nearby logistics services. • The number of warehouses affects long-term economic growth. [ABSTRACT FROM AUTHOR]

An "urban" subfield exists in virtually every social science discipline, but these subfields seldom engage one another. We asked scholars from five urban subfields to respond to questions about the state of urban research within their discipline. This article consists of their consequent essays and reflections on their responses. The questions posed included the discipline's conception of "urban," the main concerns motivating the subfield, the primary methodologies pursued, the extent to which their subfield interacted with or was informed by research in other urban subfields, and the main concepts or approaches it had to offer to other subfields or might take away from them. In our reflections, we particularly note the intellectual and institutional difficulties in creating a broader field of urban research or of engaging in truly inter-disciplinary research. We also highlight the desirability of greater engagement across these subfields through encouraging a "republic of conversation" among them. [ABSTRACT FROM AUTHOR]

New models of agglomeration cast the urban productivity premium as the outcome of agglomeration economies, a spatial sorting of skilled entrepreneurs and greater selection effects leading to less, but more productive businesses. We provide descriptive evidence of the spatial distribution of growing early‐stage businesses in Chile that concurs with the theory. We show, first, that while business entry rates increase systematically with the size of a region, the rates of growing early‐stage businesses are not related to the levels of agglomeration. Second, we show that, on the contrary, average early‐stage business productivity, the levels of human capital and business exit rates all relate positively with agglomeration. Third, we estimate regression models that verify the expected relationships between agglomeration factors and regional growing early‐stage‐business activity. The results for Chile suggest that the disadvantages of agglomeration largely offset the benefits, and therefore there is no obvious location penalty to venturing in peripheral areas. Entrepreneurship policies in less‐developed countries should not target excessively to specific industries and regions, as they might curtail an entrepreneurial potential that is ubiquitous. [ABSTRACT FROM AUTHOR]

Copyright of Urban History Review / Revue d'Histoire Urbaine is the property of University of Toronto Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Industrial Organization, the Resource-Based View, and the Relational View are some classical, well-established, and widely accepted theories in the strategic management domain regarding the understanding, explanation, and prediction of competitive advantage of firms and above-average firm performance. Recent evidence of economic geography and regional economics added to this stream of research new perspectives like cluster theory and microeconomic competitiveness. Despite the high enthusiasm with which companies and policymakers embraced the new advancements, there is some contradictory evidence regarding the positive effect of local conditions on firm performance. Thus, in this paper, we aim to empirically test some aspects of a modern regional development theory, proposed mainly by Michael Porter and collaborators, and the impact of these aspects on firm performance. External determinants considered at three levels of analysis (local economy, local clusters, and industry) will be investigated in relation to firm performance. We will analyze empirical data through detailed correlational analyses and by building multilinear regression models. After the statistical analysis of the answers provided directly by 67 medium and large manufacturing companies operating in Romania, we will provide empirical support for some external determinants, while for other determinants, we will show that the data rejected the proposed associations. The main conclusion derived from this study is that different combinations of external determinants, considered at all three levels of analysis, have a positive and significant effect on different measures of firm performance. The findings in our paper are important for both regional economics and the strategic management literature, suggesting the importance of creating local or urban conditions depending on the type of performance that the firms in the local economy are underperforming. [ABSTRACT FROM AUTHOR]