Search Results (744)

In the spirit of the recent debate on the 15-minute city, two concepts are central: urban proximity and resilience. They became cornerstones of new urban planning perspectives on sustainability, livability, and inclusiveness in cities and metropolitan areas. Very recently, the notion of ‘proxilience’ has been introduced as an integration of urban planning views on the drivers of citizens’ wellbeing. The present study seeks to conceptualize and operationalize the proxilience concept for the case of metropolitan agglomerations, in which the core is termed here ‘Superbowl Economy’. Consequently, the paper presents a data-driven analytical approach that uses detailed empirical data on spatial density patterns, demographic factors, socioeconomic indicators, environmental quality attributes, infrastructure accessibility, and access to services and amenities. The empirical part of the study is based on a blend of geostatistical and econometric models (correlation and regression analysis, AHP modelling, and Random Forest model). The analysis framework and the underlying propositions on the proxilience impacts on spatial patterns of disparities in wellbeing are applied and tested for the greater Iași Metropolitan Area, which is one of the largest urban poles in Romania. The findings confirm proxilience as a novel, multidimensional tool that advances spatial (urban–regional) livability in a polarized yet fragmented urban system. Full article

Against the backdrop of coordinated advancement in new urbanization and rural revitalization strategies, the integration of urban and rural areas serves as a core approach to dismantling the urban–rural dichotomy and driving high-quality regional development. The enabling effects of its policy implementation on regional sustainable development have garnered significant attention. As pivotal conduits where urban and rural elements converge, peri-urban fringe zones have emerged as the primary arena for policy implementation and impact realization. Using panel data from 268 prefecture-level and above cities in China from 2015 to 2024 as the sample, this study treats the establishment of urban–rural integration pilot zones as a quasi-natural experiment. Employing a multi-period Difference-in-Differences model, instrumental variables method, and spatial econometric model, it systematically investigates the impact effects, operational mechanisms, heterogeneous characteristics, and spatial spillover effects of urban–rural integration policies on regional sustainable development. Findings reveal that urban–rural integration policies significantly promote regional sustainable development. This conclusion remains robust after endogeneity treatment and stability tests, with policies demonstrating stronger enabling effects on ecological sustainability than on economic and social sustainability, forming a development pattern characterized by “ecological priority and multidimensional coordination”. Policies achieve synergistic enhancement of regional economic, ecological, and social sustainability through three pathways: optimizing urban–rural factor allocation, establishing ecological co-governance systems, and advancing equitable public services. Policy effects exhibit significant heterogeneity: the stronger the urban baseline conditions, the more pronounced the policy’s enabling effect, while excessive population concentration exerts a marginal negative impact on ecological sustainability. Urban–rural integration policies generate a significant positive spatial spillover effect, accounting for 38.9% of the total effect. This spillover gradually diminishes with increasing distance within a 120 km radius, with geographic distance and administrative barriers serving as core constraints. This study provides empirical insights and practical pathways for optimizing urban–rural integration policy design and advancing regional sustainable development. Full article

Understanding the spatial mismatch between population distribution and economic activities is central to regional development, particularly in large river basins experiencing rapid demographic change. Existing studies often rely on slow-moving structural variables and give limited attention to dynamic population processes. This study examines the spatiotemporal patterns, demographic mechanisms, and regional heterogeneity of population–economy mismatch in the Yellow River Basin from 2000 to 2020. We hypothesize that population–economy mismatch exhibits pronounced spatial heterogeneity across the upper, middle, and lower reaches of the basin, and that demographic structure and migration dynamics play a decisive role in shaping these patterns. Using county-level data, we construct a Population–Economy Distribution Disparity Ratio R, apply decomposable Theil indices, and estimate two-way fixed-effects panel models incorporating demographic and migration indicators. Spatial econometric models are further employed as robustness checks. The results show that intra-regional disparities account for more than 97% of total population–economy mismatch, while inter-regional differences remain limited. Population migration intensity and age structure significantly influence mismatch dynamics, with effects varying systematically along the basin gradient. These findings underscore the importance of integrating dynamic demographic processes into spatial mismatch analysis and support regionally differentiated and systemically coordinated policy interventions for high-quality development in the Yellow River Basin. Full article

In the context of China’s pursuit of high-quality economic development, enhancing agricultural productivity is crucial for ensuring food security and promoting common prosperity. This paper constructs a systematic IV-LP-ACF-SAR econometric framework to analyze agricultural Total Factor Productivity (TFP) growth using panel data from 31 Chinese provinces spanning 2014 to 2023 (n = 341 observations). The framework employs the instrumental variable (IV)-based Levinsohn–Petrin (LP) proxy variable method under the Ackerberg–Caves–Frazer (ACF) system to estimate a Translog production function while addressing endogeneity using multiple spatial weight matrices. TFP growth is decomposed into technical change (TC), technical efficiency (EC), and scale efficiency (SC). A Spatial Autoregressive (SAR) model with Dynamic Common Correlated Effects (DCCE) explores spatial spillover effects and regional heterogeneity. Results show that China’s agricultural TFP remained largely stagnant from 2014 to 2023 with an average annual growth rate of −0.18%, where technical efficiency decline (−0.33% annually) was the main constraint. Technical change remained neutral, while scale efficiency contributed positively (+0.15% annually). Mechanization showed the highest output elasticity (0.99), while fertilizers, pesticides, and labor exhibited negative marginal returns. Spatial analysis revealed significant negative scale efficiency spillovers with regional patterns of “scale synergy in the Northeast/Northwest” and “efficiency synergy in East/North China.” These findings suggest that productivity policy should shift toward a dual-driver model combining efficiency enhancement and optimal scaling, with differentiated regional policies and inter-provincial coordination mechanisms necessary to mitigate negative spillovers and enhance sustainable agricultural growth quality. Full article

Assessing urban resilience under compound shocks requires observable and comparable process evidence that can inform resilient land governance and cross-jurisdiction planning. Using China’s Pilot Free Trade Zones (PFTZs) as a staged institutional setting, this research examines whether institutional exposure is associated with deviation–recovery trajectories of urban activity during the 2020 COVID-19 shock and whether these associations propagate through spatial spillovers with an identifiable scale profile. Institutional exposure is operationalized by the prefecture-level cities actually covered by PFTZ functional areas. With harmonized administrative boundaries, we construct an annual city-level VIIRS nighttime light (NTL) series for 2013–2024 and treat NTL as an activity-change signal rather than a direct proxy for output. We trace shock deviation in 2020 and subsequent recovery via staged differencing. Spatial interaction frictions are represented by least-cost path distance (LCPD) derived from a multi-source cost surface, which is used to build a gravity-based spatial weight matrix. Estimation relies on the Spatial Durbin Model (SDM), with LeSage–Pace impact decomposition to distinguish direct and spillover effects, complemented by distance-threshold diagnostics to map attenuation patterns. Results indicate persistent clustering within the PFTZ-related urban system. The shock year is characterized by compressed connectivity and fragmented brightening, whereas recovery proceeds in a layered manner with earlier core repair, partial corridor reconnection, and weaker adjustment at the periphery. Spatial dependence in activity change is statistically significant. Associations linked to institutional exposure are realized primarily locally, while structural and scale conditions more readily operate through spatial externalities. Spillovers are most detectable at meso-scales and attenuate gradually across distance thresholds. Overall, the integrated earth-observation and spatial-econometric framework provides replicable geospatial evidence to support resilient land governance and regional coordination under common shocks. Full article

As the global urban economy accelerates its transition from an “industrial economy” to a “service economy”, consumption has replaced investment as the core engine driving economic development. Commercial land serves as the physical foundation for consumer activities and plays a vital role in boosting urban economic vitality, enhancing residents’ quality of life, and promoting regional sustainable development when appropriately allocated. This study constructs a technical framework for analyzing the mismatch between commercial land supply and residential consumption demand, along with its impact mechanism, based on the integrated application of the multidisciplinary quantitative models such as the Boston Consulting Group Matrix (BCGM), Exploratory Spatial Data Analysis (ESDA), Decoupling Model (DM), and Explainable Machine Learning (EML). It conducts empirical research across 87 county-level cities in Gansu Province. The findings reveal that commercial land supply and consumption demand exhibit dynamic diversification, with prominent regional disparities and spatial autocorrelation characteristics. Commercial land in Gansu faces a severe mismatch, with demand exceeding supply and supply exceeding demand occurring simultaneously, and the former holding absolute dominance. The formation of mismatched relationships is influenced by many factors, exhibiting significant path nonlinearity, spatial non-stationarity, and relational interactivity. It is suggested that strategies of planning zoning and regional coordination be developed for mismatch governance, and differentiated management measures be implemented based on local conditions. This will provide a scientific basis for commercial territorial space planning and consumption policy design. Full article

Cassava mosaic disease (CMD) is a major constraint to cassava production in sub-Saharan Africa, particularly in Burkina Faso, where it poses a serious threat to rural food security. This study examined the impact of adopting innovative cassava mosaic disease management practices on cassava yields in the Guiriko and Nando regions of Burkina Faso. To address potential biases arising from differences in characteristics between adopters and non-adopters, an econometric approach based on the instrumental variables (IV) method within a counterfactual framework was employed to estimate the local average treatment effect (LATE). The data were drawn from a survey conducted in September 2023 among 511 cassava producers. The results indicate that the adoption of innovative cassava mosaic disease management practices had a positive and statistically significant effect on agricultural yields. Productivity gains were estimated at 29% in the Guiriko region and 41% in the Nando region, highlighting spatial heterogeneity in impacts. These findings suggest that promoting the diffusion of such practices can substantially improve cassava productivity and reduce the vulnerability of rural households. In addition, the analysis showed that socioeconomic and technical factors, including farmers’ age, membership in cassava producer organizations, household income levels, and the use of chemical fertilizers, also influence productivity outcomes. Overall, the study underscores the importance of strengthening agricultural extension services, supporting producer organizations, and promoting appropriate technologies to maximize the benefits of cassava mosaic disease management practices for food security and rural development. Full article

The conflict between the economy and the ecological environment is prominent in China’s coastal cities, and these cities contend with heightened uncertainty. Therefore, this study uses the econometric model to analyze the spatial–temporal pattern characteristics and affecting factors of the coupling coordination level between urban economic resilience (ER) and urban ecological resilience (EcR) in China’s coastal cities based on improvement of the evaluation index system, thus advancing policy suggestions. The main conclusions are as follows: (1) The coupling coordination degree (CCD) between ER and EcR across different types of coastal cities strongly correlates with their spatial distribution patterns of economic development. From the East China Sea to the South China Sea and Yellow and Bohai Sea Coast cities and from central cities to industrial cities, other types of cities, and resource-based cities, CCD exhibits an overall declining trajectory. (2) The gap in CCD in China’s coastal cities generally shows an expanding trend. (3) The spatial distribution pattern of the centrality of CCD in China’s coastal cities has a relatively high consistency. Urban spillover roles are highly consistent with levels of economic development. (4) The number and diversity of dominant influencing factors have steadily increased. Full article

This paper employs a top-down methodological approach to identify the most relevant contributions in the literature on the impact of European Cohesion Policy and European Structural and Investment Funds (ESIFs) on regional development. After a broad-spectrum bibliometric review, identifying the overall structure of research in this field, we systematically narrow its focus to quantitative studies and, ultimately, to econometric analyses of ESIF effectiveness. The results indicate that empirical research on ESIFs has grown in complexity, with increasing reliance on advanced econometric techniques such as spatial econometrics, difference-in-differences, and regression discontinuity designs. While a large portion of the literature finds positive effects on economic growth, employment, and regional convergence, these effects are frequently conditional on governance quality, institutional frameworks, and regional characteristics. In contrast, some studies report insignificant or even negative impacts, highlighting inefficiencies in fund allocation and policy implementation. The findings emphasize the necessity for context-specific policy adaptations, ensuring that ESIFs continue to support the evolving needs of regional economies in the European Union. Full article

The purpose of this study is to investigate the impact of new-type urbanization on land use efficiency and its spatial spillover effects, aiming to provide theoretical support and practical references for improving land resource allocation and optimizing regional development strategies. Using panel data from 61 counties in Zhejiang Province between 2010 and 2022, this research applies a two-way fixed effects model, supplemented by mediation effect analysis and spatial econometric models, to empirically examine these relationships. The results indicate that: (1) both the level of new-type urbanization and land use efficiency show an overall upward trend, exhibiting a spatial pattern characterized by “coastal regions outperforming inland areas, and northern Zhejiang surpassing the south”; (2) new-type urbanization exerts a significantly positive impact on land use efficiency, with industrial structure upgrading serving as a partial mediator in this relationship; (3) significant spatial spillover effects are observed—new-type urbanization not only enhances local land use efficiency but also generates positive spillovers to neighboring regions through spatial diffusion mechanisms; (4) the influence of new-type urbanization on land use efficiency displays regional heterogeneity, with stronger promoting effects observed in coastal and low-efficiency areas, whereas marginal effects diminish in non-coastal and high-efficiency regions. In conclusion, strategic priorities should be established to enhance the quality of new-type urbanization, foster green and intensive development, optimize the industrial structure, and strengthen land conservation practices. Furthermore, region-specific policies are essential to improve land use efficiency across diverse areas, which will ultimately contribute to coordinated regional development. Full article

Financial systems are quintessential complex adaptive systems, where stability emerges from the dynamic interactions among multiple subsystems and regulatory components. Grounded in systems theory, this study re-frames the establishment of China’s fintech regulatory sandbox as a systemic intervention within the broader financial governance framework. Utilizing this policy as a quasi-natural experiment, we employ a difference-in-differences (DID) model integrated with spatial econometric modeling to evaluate its impact on regional financial system risk—an emergent property of the system. The benchmark regression results indicate that this systemic policy innovation significantly enhances regional financial resilience, with effects that are both continuous and robust. Mechanism tests, analyzed through the lens of subsystem coordination, demonstrate that the policy curbs systemic risk by improving the synergy within economic inner cycles, outer cycles, and their dual-cycle integration, thereby optimizing the system’s internal structure and feedback loops. Further analysis reveals a significant negative spatial spillover effect, evidencing the policy’s role in reshaping inter-regional systemic linkages: it reduces financial risk in both implementing and neighboring regions, with the effect’s intensity following an inverted U-shaped pattern relative to distance. Heterogeneity analysis shows that the policy’s inhibitory effect varies significantly across different systemic configurations, including risk circulation patterns, macro–micro risk perspectives, financial inclusion coverage, government–market relationships, and the north–south regional divide. These findings provide critical insights for developing synergistic macro-prudential and micro-behavioral regulatory mechanisms, contributing to a more robust and adaptive financial security framework from a systems governance perspective. Full article

Digital technologies such as big data are reshaping resource allocation, raising interest in whether and how heterogeneous science and technology innovation (STI) policies can help unlock urban carbon lock-in. Using panel data for 286 prefecture-level cities in China from 2009 to 2023, this paper examines the relationship between heterogeneous STI policy intensity—classified as supply-side, demand-side, complementary-factor, and institutional-reform policies—and urban carbon unlocking efficiency. We develop a mechanism-based framework and empirically assess (i) the moderating roles of digital infrastructure, science and technology finance, and government green attention, and (ii) spatial spillover effects using spatial econometric models. The results show that all four policy types show a significant positive association with local carbon unlocking efficiency, with institutional-reform policies exhibiting the strongest association. When the four types are included jointly, only supply-side and demand-side policies retain statistically significant direct associations. Heterogeneity analyses indicate that demand-side, complementary-factor, and institutional-reform policies are more strongly associated with efficiency gains in low-pollution cities, whereas supply-side and demand-side policies have a stronger association in high energy-consuming cities. Mechanism analysis reveals that regional digital infrastructure exerts a selective moderating effect on the relationship between heterogeneous sci-tech innovation policies and urban carbon emission reduction efficiency. It positively reinforces the effectiveness of supply-side, demand-side, and institutional reform-oriented policies, while its interaction with complementary policies is statistically insignificant. Technology finance and government green policies function as a “resource catalyst” and an “institutional guarantee” respectively, significantly enhancing the correlation between heterogeneous sci-tech innovation policies and urban carbon emission reduction efficiency. Finally, carbon unlocking efficiency displays significant spatial dependence: the intensity of supply-side and institutional-reform policies is positively associated with carbon unlocking efficiency in neighboring cities, while complementary-factor policies exhibit a negative spatial association. Overall, the findings provide empirical evidence to inform the design and coordination of heterogeneous STI policy portfolios aimed at improving urban carbon unlocking efficiency. Full article

Conventional infrastructure appraisal in Africa prioritizes short-term economic performance while insufficiently accounting for the environmental conditions that govern long-term sustainability, spatial equity, and development resilience. To address this gap, this study develops an explicitly SDG-oriented spatial–ecological framework to examine how environmental quality conditions the economic returns of large-scale infrastructure investments under corridor-based development. The primary objective is to quantify infrastructure–environment complementarity and identify ecological thresholds regulating spatial spillovers and investment effectiveness along Tanzania’s Belt and Road Initiative (BRI) corridors. High-resolution remote sensing and spatially explicit socioeconomic data for 2012–2023 are integrated within a spatial econometric design. A Spatial Durbin Model (SDM) incorporating the Normalized Difference Vegetation Index (NDVI) is estimated to capture non-linear interaction effects, with economic activity proxied by Night-Time Light (NTL) intensity across 2680 corridor grid cells. The results identify a statistically robust ecological threshold at NDVI = −0.8σ, beyond which infrastructure investments shift from low to high economic effectiveness. A strong positive infrastructure–environment interaction (β = 6.44, p < 0.001) indicates that environmental quality functions as a productive modulating factor rather than a passive constraint. Spatial classification shows that 63% of corridor areas are investment-ready, while 15% require ecological restoration prior to effective infrastructure deployment. Although institutional quality and long-term post-construction dynamics are not explicitly modeled, the framework provides a replicable and policy-relevant decision-support tool, offering actionable guidance for aligning corridor development with SDGs 9, 11, and 13 and advancing sustainable infrastructure planning in the Global South. Full article

Alumni relationships are essential social capital that are significant in companies’ resource acquisition and information sharing. Using 2018 data from Chinese listed companies, this study examines the impact of the chairperson–alumni network on corporate artificial intelligence (AI) adoption. The results show that chairperson–alumni relations are positively associated with AI adoption. Moreover, the impact of chairperson–alumni networks on AI adoption may span industrial, administrative, and geographical boundaries. This study shows that chairperson–alumni networks can indirectly influence AI adoption by influencing board size. Finally, this study demonstrates the heterogeneity of the impact of the chairperson–alumni network on AI adoption. Full article

Spatial disparities in housing values during the Great Depression reflect not only regional housing market conditions but also deeper inequalities in economic opportunity, social infrastructure, and environmental resilience that are central to place-based sustainability. Despite extensive research on housing inequality during this period, spatial disparities in housing values—particularly in relation to race beyond the neighborhood level—remain underexplored. This study examines county-level spatial disparities in housing values in the United States between 1930 and 1940, framing housing values as an indicator of place-based sustainability. Using spatial visualization, global and local spatial econometric models, and Multi-Scale Geographically Weighted Regression (MGWR), we analyze how economic shocks, environmental stressors, and socioeconomic and demographic factors jointly shaped uneven housing outcomes across space. Our findings reveal distinct regional trends: higher housing values were concentrated in the Northeast, Midwest, and West Coast, while lower values prevailed in the Mountain and Southern regions. Housing values declined from 1930 to 1940, with the Dust Bowl intensifying losses in affected areas. Socioeconomic factors, such as higher illiteracy and unemployment rates, were associated with lower housing values, whereas higher retail sales per capita, a proxy for income, were linked to higher values. Housing values also varied significantly by racial and nativity composition, with persistent disparities disadvantaging Black and other minority populations relative to native White populations within the same regions. By quantifying spatial inequality and identifying uneven regional vulnerability and resilience during a major historical crisis, this study contributes a place-based sustainability perspective on long-term housing inequality and its structural roots. Full article