Breaking through the constraints of traditional agricultural resources and expanding food supply channels have become essential for safeguarding food security. The non-timber forest-based economy (NTFE), which integrates multiple understory production activities including planting, breeding, and foraging, expands the variety of food sources and provides a new pathway for enhancing regional diversified food supply capacity (DFSC). Based on this perspective, this study constructs evaluation indicator systems for both DFSC and NTFE development. The entropy-weighted TOPSIS method is employed to measure the levels of DFSC and NTFE development across 31 Chinese provinces from 2011 to 2022. A two-way fixed effects model and a spatial Durbin model are applied to empirically investigate the mechanisms through which the NTFE enhances DFSC. The results show the following: (1) Between 2011 and 2022, both the DFSC and the level of NTFE development in China exhibited a sustained upward trend. Specifically, the level of NTFE development grew rapidly before 2019, with a slowdown in growth in the later years, while DFSC maintained a steady increase throughout the study period. (2) NTFE development significantly promotes DFSC. (3) The NTFE enhances DFSC by facilitating the upgrading of the forestry industrial structure and improving forestland productivity. (4) The NTFE generates positive spatial spillover effects on DFSC, and these spillover effects are stronger than direct local effects.

During rapid urbanization, the total area of green space in Guangzhou remained relatively stable; however, its spatial structure changed substantially. Green space became increasingly fragmented, patch shapes grew more complex, and overall connectivity declined, indicating a systematic degradation of green space structure rather than a simple reduction in area. Land-use transition analysis shows that the continuous conversion of farmland and grassland into construction land was the dominant process driving green space fragmentation during the study period. This suggests that urban expansion primarily reshaped the internal configuration of green space instead of directly reducing its total extent. Spatial econometric results reveal significant spatial dependence in green space dynamics, as indicated by a positive and significant spatial lag coefficient in the spatial Durbin model, highlighting strong interregional interactions. Further decomposition of spatial effects indicates heterogeneous driving mechanisms: urbanization intensity, measured by nighttime light intensity, exerts a negative indirect effect, whereas population density and per capita GDP exhibit positive direct and indirect effects. Overall, the results support a "development pressure-ecological response" mechanism, in which urban expansion generates structural degradation and negative spatial spillovers, while socioeconomic agglomeration may, under certain conditions, produce compensatory or synergistic effects on regional green space systems.

Against the backdrop of global economic volatility, environmental pressures, and intensifying industry competition, tourism resilience has become a critical indicator for assessing the capacity of tourism systems to withstand external shocks and achieve sustainable development. As an important engine of high-quality economic growth, the digital economy provides new momentum for strengthening tourism economic resilience. Existing literature predominantly focuses on the direct impacts of the digital economy, with insufficient exploration of its mediating pathways and spatial effects. Based on panel data from 11 provinces in China’s Yangtze River Basin from 2011 to 2023, this study constructs comprehensive evaluation index systems for the digital economy and tourism economic resilience. A mediating effect model and a Spatial Durbin Model are employed to systematically examines the impact mechanisms and spatial spillover effects of the digital economy on tourism resilience. The results show that the digital economy significantly enhances tourism economic resilience, primarily by fostering openness and technological innovation. Heterogeneity analysis indicates that this effect is more pronounced in provinces located in the upper and lower reaches of the Yangtze River Basin. Spatial analysis further reveals a significant positive local effect, accompanied by a negative spillover—or ‘siphon’—effect on neighboring provinces. Building upon the verification of the fundamental relationship, this study further extends the theoretical analytical framework of tourism resilience from the dimensions of mechanism decomposition and spatial effects. It thereby offers new empirical evidence and policy insights for fostering regional tourism resilience in the era of the digital economy.

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.

This study investigates the resilience of the agricultural sector in Türkiye to climate shocks at the provincial level during 2005–2024 by examining the spatial structure and the determinants of resilience within a spatial econometric framework. In the study, a new index, namely the Provincial Agricultural Resilience Index (PARI), comprising the productivity, stability, and diversity sub-indices, was constructed; the trends, spatial patterns, and relationships between the index and climatic as well as structural factors were examined. The results indicate that although the average agricultural resilience of Türkiye has recorded a marginal increase, the improvement is not spatially uniform and is accompanied by a pronounced regional divergence pattern. During 2005–2024, PARI levels displayed significant and increasingly stronger spatial clustering; higher resilience levels were concentrated in the Western and Mediterranean basins, whereas lower resilience levels were concentrated in Eastern and Northeastern Anatolia, pointing to an inter-provincial sigma-divergence. The results of the Spatial Durbin Model (SDM) reveal that agricultural resilience has a strong spatial dependence; the impacts of climate shocks transcend provincial boundaries and have spillover effects on neighboring provinces. The negative and statistically significant direct and total effects of the drought indicator indicate that climate shocks are likely to undermine agricultural resilience. However, the negative direct and indirect effects of agricultural credit and mechanization variables imply that financial access and capital use can serve mainly as short-term coping mechanisms rather than investment channels enhancing agricultural resilience against climate shocks. The results of marginal-effects analysis imply that the use of credit may even exacerbate rather than compensate for the loss of resilience, particularly in the case of drought, implying that the existing financial instruments may be insufficient to support long-term structural adaptation capacity. Overall, the results suggest that financial policies for a climate-resilient agricultural system should be redesigned by incorporating productive technology investments and regional adaptation differentials.

ABSTRACT Industrial robot adoption’s environmental impact is time-dependent and spatially heterogeneous. Using data from 281 Chinese cities between 2008 and 2023 with STIRPAT models, we find robots significantly reduce total carbon emissions short-to-medium term but become insignificant long-term, while carbon intensity consistently decreases across all horizons. This divergence stems from a rebound effect: efficiency gains are offset by enterprise scale expansion. Mechanism analysis reveals robots promote green innovation and energy structure upgrading. Spatial Durbin models uncover asymmetries: robots reduce total emissions more in neighboring regions than locally due to a siphoning effect whereby advanced automation areas attract high-carbon production from surroundings. In contrast, carbon intensity reductions are stronger locally. Cities in China’s new energy demonstration program maintain long-term emission reductions, suggesting clean energy infrastructure mitigates rebound effects. Findings inform policies accounting for temporal dynamics and spatial spillovers.

ABSTRACT New quality productivity not only helps to optimize the allocation of resources among regions, but also promotes economic development. Therefore, studying the influence of new quality productivity on the spatial spillover effect of resource mismatch is of great significance for formulating scientific and reasonable regional economic policies and promoting high-quality economic development. This paper analyses regional differences between new quality productive forces and resource misallocation using the Moran Index and Trend Surface Analysis. A spatial Durbin model is constructed to further explore the spatial effects of new quality productive forces on resource allocation. The conclusions are as follows: (1) From 2012 to 2022, the new quality productive forces show an obvious growth trend, while the resource misallocation exhibits an overall decreasing trend. (2) Spatially, new quality productive forces are highest in the Central region, followed by the South. Resource misallocation is highest in the West, followed by the East, and higher in the Central and North than the South, with a pronounced gap between the East and West. (3) There is a significant negative correlation between new quality productive forces and resource misallocation. Additionally, there is a significant spatial spillover effect where new quality unproductive forces inhibit resource misallocation.

ABSTRACT Evidence on how China’s outward foreign direct investment (OFDI) affects trade flows and generatesspatial spillovers among Belt and Road Initiative (BRI) countries remains scarce. Using panel data for 47 BRI countries over 2010–2021, this study estimates a spatial Durbin model (SDM) to decompose the direct and indirect (spillover) effects of China’s OFDI stock on host-country imports and exports, employing an economic-distance-based spatial weights matrix. The results show that a 1% increase in China’s OFDI stock is associated with a 0.005% rise in host-country imports (p < 0.05) and a 0.034% increase in exports (p < 0.10). Moreover, spatial spillovers are asymmetric: neighbouring countries experience a 0.044% increase in imports (p < 0.01) but a 0.304% decline in exports (p < 0.05). These findings suggest that assessments of trade gains from Chinese capital inflows in BRI countries must account for cross-border linkages and the potential for regional redistribution of export opportunities.

The spatial distribution of immigrants and associated patterns of residential segregation and integration can manifest not only at the metropolitan scale but also at finer micro-spatial resolutions, reflecting the interaction between path dependence and structural reconfiguration. This article examines the micro-spatial residential patterns of Chinese immigrants in Seoul under institutional and market constraints. Using a Spatial Durbin Model and Multiscale Geographically Weighted Regression, it shows that from 2011 to 2025, immigrant settlements shifted from a monocentric pattern to a polycentric, functionally differentiated, and networked structure. While overall spatial embeddedness is high and segregation remains low, traditional cores such as Guro–Daerim persist. Selective clustering is shaped by path-dependent migrant networks, urban redevelopment policies, and intra-group differentiation, while infrastructure homogenization renders transportation accessibility a background condition. The findings support segmented assimilation theory in high-density East Asian cities and underscore the importance of incorporating immigrant needs into urban policy to promote inclusive integration.

ABSTRACT Africa's sustainable socioeconomic development is increasingly challenged by institutional disparities, where weak governance undermines progress in human capital indicators such as life expectancy and educational attainment. Despite recognition of institutional quality's role in fostering transparency, accountability, and stability, existing research often overlooks its spatial spillover effects across interconnected African nations. This study aims to examine the direct and spillover impacts of institutional quality proxied by transparency (corruption perception), rule of law, and political stability on life expectancy and mean years of schooling in 42 African countries over the period 2012–2022. Employing spatial panel econometric models, including the Spatial Durbin Model (SDM), Spatial Autoregressive Model (SAR), and Spatial Error Model (SEM), the analysis controls for GDP per capita and population growth. The results reveal significant positive spatial autocorrelation in both outcomes (Moran's I: 0.536 for life expectancy; 0.469 for schooling). For life expectancy, institutional quality (particularly the rule of law) exhibits strong positive direct and spillover effects, amplified by regional GDP and population dynamics, indicating that governance improvements in one country enhance health outcomes in neighbors through policy diffusion and cross‐border cooperation. In contrast, educational attainment shows no significant spillovers, driven primarily by domestic GDP, population, and rule of law, highlighting fragmented regional education systems. These findings underscore institutional quality as a regional public good, offering nuanced insights for harnessing spatial interdependence in Africa's development agenda.

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 &lt; 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.

Empowering urban water resilience in the Yellow River Basin: evaluation, influencing mechanisms, and obstacle diagnosis.

IntroductionWith the looming global warming crisis, the question of how to achieve carbon neutrality is becoming an important issue confronting many countries. Although the spatial studies have indicated that education can spatially reduce the carbon intensity, they have ignored the transmission mechanism and dynamic interrelationship between education and carbon intensity.MethodsBased on spatial economics theory, this study uses a spatial Durbin model and spatial vector autoregressive model to examine how education affects carbon intensity and how they relate to each other in China’s 30 provinces from 2000 to 2021.ResultsThe results show that education and the carbon intensity have positive global spatial autocorrelation. Education reduces the carbon intensity mainly through the spillover effect. The negative spillover effects in provinces with low carbon intensity are significantly greater than the direct effects are, whereas the spillover effects in provinces with high carbon intensity are negative but not significant. Education reduces the carbon intensity through green technology innovation and consumption structure upgrading. Furthermore, there is a dynamic interrelationship between education and carbon intensity. This study suggests that local governments should increase investment in education and focus on educational equity. They should also consider the spatial spillover effects of education when implementing tailored emission reduction policies based on local conditions. Additionally, educational institutions are encouraged to invest more in researching and promoting green technologies, as well as integrating low-carbon lifestyles into the education system.DiscussionThe findings can help policymakers achieve sustainable development goals 4 and 13 and a net-zero future.

Amid the growing challenges of energy security and carbon neutrality, green finance has become an important policy instrument for promoting sustainable energy transitions. Using city-level data from China between 2009 and 2019 and a spatial Durbin model, this study not only examines local effects but also focuses on identifying the geographic and administrative boundaries of their spatial spillovers. The analysis reveals that green finance advances energy transition via fostering green innovation and optimizing industrial structures, with stronger effects in regions where public environmental awareness is higher. Pronounced regional heterogeneity is identified, as resource-abundant and economically developed cities respond more strongly to green finance. Furthermore, green finance generates positive spatial spillovers, improving the energy transition of neighboring cities within a 400 km radius, although these effects are weakened by interprovincial competition. Overall, the findings highlight the importance of regionally differentiated and coordinated green finance policies in supporting effective energy transitions.

The coordinated development of the rural economy and the ecological environment remains a central challenge in China’s rural revitalization agenda. Against this backdrop, the rapid expansion of the digital economy (DE) has the potential to reshape traditional development pathways and ease the longstanding tension between economic growth and environmental sustainability. However, existing studies have predominantly examined the economic or environmental effects of digitalization in isolation, leaving its role in fostering their coordinated development largely unexplored. Using balanced panel data for 30 Chinese provinces from 2011 to 2021, this paper constructs an index of the coupling coordinated development of the rural economy–environment (CREE) and employs a two-way fixed-effects framework, complemented by mediation analysis, panel threshold regression, and a spatial Durbin model, to examine the impact of the DE on CREE and its transmission mechanisms. The results show that the DE significantly enhances CREE on average. This positive effect, however, is non-linear and conditional: it emerges only after rural educational attainment exceeds a critical threshold, and its marginal contribution diminishes as the level of digital development increases. Mechanism analyses indicate that the DE promotes CREE primarily by stimulating technological innovation and advancing urbanization, while improvements in the structure of human capital further strengthen this relationship. Spatial econometric evidence reveals pronounced spillover effects of the DE on CREE across regions, with spillovers based on economic distance outweighing those associated with geographic proximity. By adopting a coupling perspective that integrates economic and environmental dimensions, this paper clarifies the non-linear dynamics, transmission channels, and spatial diffusion processes through which the DE contributes to rural green development. The findings underscore the importance of strengthening rural education foundations, deepening the application of digital technologies, and enhancing regional coordination to fully harness the DE’s role in promoting coordinated economy–environment development.

National parks are a key institutional tool for coordinating ecological conservation and sustainable development. This paper takes the pilot national park program in Yunnan Province, China, as a case study. Using panel data from 127 counties between 2001 and 2023, we empirically examine the economic impact of the national park pilot program using a Time-varying difference-in-differences (DID) approach and a Spatial Durbin Model (SDM). The study finds that (1) the pilot policy significantly increased per capita GDP in the counties by approximately 5057 RMB, with a 4- to 5-year lag effect and a long-term marginally increasing trend; (2) the policy drives economic growth through three main channels: increased fiscal transfers from higher levels of government, induced industrial upgrading, and the stimulation of fixed-asset investment; (3) the policy’s impact is more significant in areas with low economic levels, high altitudes, and high ecological quality; (4) national parks not only stimulate local economic growth but also promote coordinated development in surrounding regions through significant spatial spillover effects. This paper confirms the feasibility of transforming ecological advantages into economic advantages and provides empirical evidence for optimizing spatial governance in “Global South” countries.

To investigate whether tourism can act as a catalyst for regional economic convergence during the period 2000–2023, this study fills a critical gap in previous research by simultaneously examining the impact of tourism on economic disparities from both static stock and dynamic incremental perspectives, while accounting for spatial dependence. This study analyzes the economic convergence effects of tourism at the Chinese provincial and regional levels using σ convergence and the spatial Durbin model in a conditional β convergence framework. The results confirm the benefits that tourism brings to economic growth and convergence. Spatially, northeastern China exhibits stronger effects, followed by western and eastern China, in contrast to the relatively weaker impacts in central China. Structurally, its direct effect is more pronounced: the convergence effect is stronger for local areas than for neighboring areas. Temporally, the effect is most pronounced in the early (2000–2012) and late (2020–2023) phases, but becomes statistically insignificant in the intermediate period (2013–2019). By moving beyond the question of whether tourism drives growth to reveal for which regions it is most beneficial, this study offers a refined analytical perspective and actionable insights for achieving balanced regional development in China and other countries and regions at a comparable stage of development. The findings also highlight the potential of cultural heritage as a lever for sustainable and equitable regional growth, channeled through tourism.

ABSTRACT The impact of environmental regulation and green credit on green industries is gaining attention in environmental economics. However, insufficient research has explored their synergistic influence on new energy industry agglomeration (NEIA). Using the Spatial Durbin Model and Threshold Model, we find that this synergy increases local NEIA while having adverse effects on surrounding areas. This results in negative externalities, driven by the green financing’s profit focus, leading capital to shift to less concentrated sectors. The relationship between synergy and NEIA was found to be nonlinear, with environmental regulation as the threshold. The adverse effects of green credit on NEIA vary with regulatory intensity. Geographically, the externalities also vary: they are insignificantly negative in the east, strongly negative in the centre, and positive in the west. This study supports China’s new energy industry, informs environmental policies, and provides insights into global new energy development.

Urban agglomerations are concentrated production areas of new-quality productivity (NQP), and developing NQP is an inevitable requirement and obligation to promote the high-quality development of urban agglomerations. It is of great concern whether green finance (GF) can serve as a catalyst in promoting the formation and development of NQP in urban agglomerations. This study selects panel data from 41 cities in the Yangtze River Delta urban agglomeration spanning 2011–2023 to construct a comprehensive indicator system for NQP based on the composition, quality, and function of productive factors in the urban agglomeration, and explores the impact effects, mechanisms of action, spatial spillover effects, and heterogeneity of GF on the development of NQP using a two-way fixed-effects model, an intermediary effect model, and a spatial Durbin model (SDM). The empirical results indicate the following: (1) GF can significantly promote the development of NQP in the Yangtze River Delta urban agglomeration, and there is a significant positive spatial spillover effect. The above conclusions remain valid after a series of robustness tests and endogeneity treatments. (2) The mechanism tests find that industrial structure upgrading and environmental regulation play positive mediating roles in GF’s promotion of NQP development in urban agglomerations. (3) The impact of GF on NQP exhibits significant heterogeneity. In regions with higher levels of economic and financial development, as well as a higher degree of marketization, the promotional effect of GF on NQP is more pronounced. In terms of city size and geographical location, the empowering effect and spatial spillover effect of GF on NQP are more evident in prefecture-level cities and the northern plain area of the Yangtze River Delta. Therefore, it is recommended to implement differentiated GF policies to promote the development of NQP in the Yangtze River Delta urban agglomeration through regional cooperation, green technology innovation, industrial transformation and upgrading, and environmental regulation.

This study investigates regional heterogeneity and spatial interdependence in digital skills mismatch across Indonesia by constructing a Digital Skills Supply–Demand Ratio (DSSDR) from the Indonesia Digital Society Index (IMDI). In line with SDG 10 (Reduced Inequalities) and SDG 4 (Quality Education), the study aims to provide policy-relevant evidence to support a more inclusive and balanced digital transformation. Using district-level data and spatial econometric models (OLS, SAR, and the SDM), the analysis evaluates both local determinants and cross-regional spillover effects. Model comparison identifies the Spatial Durbin Model as the best specification, revealing strong spatial dependence in digital skills imbalance. The results show that most local socioeconomic and digital readiness indicators do not have significant direct effects on DSSDR, while school internet coverage exhibits a consistently negative association, indicating that digital demand expands faster than local supply. In contrast, spatial spillovers are decisive: a higher share of ICT study programs in neighboring regions improves local DSSDR through knowledge and human-capital diffusion, whereas higher GRDP per capita in adjacent regions exacerbates local mismatch, consistent with a talent-attraction mechanism. These findings demonstrate that digital skills mismatch is a spatially interconnected phenomenon driven more by interregional dynamics than by local conditions alone, implying that policy responses should move beyond isolated district-level interventions toward coordinated regional strategies integrating education systems, labor markets, and digital ecosystem development. The study contributes a spatially explicit, supply–demand-based framework for diagnosing regional digital inequality and supporting more equitable and sustainable digital development in Indonesia.