Based on the provincial panel data from 2010 to 2022, the entropy method was used to measure the new quality productivity score, and its spatio-temporal evolution, influencing factors, and promotion path were explored using ArcGIS, geo-detector, and progress index. The results show that (1) The level of new quality productivity in China's provincial areas is on the rise, and this index is significantly higher in the east than in the central and western parts of the country, and its spatial spillover effect is obvious. (2) Factor detection results show that per capita GDP, marketization index, degree of openness to the outside world and urbanization level are the main influencing factors of the spatial differentiation of the new quality productivity; and it is found that the influence of two factors is significantly greater than that of a single factor. (3) Constructing the progress index of new quality productivity, the average value of the new quality productivity index and its progress index is taken as the origin to construct a four-quadrant map, and it is found that the number of provinces in the “low-low” quadrant is the largest, and there is more room for the improvement of the level of new quality productivity.

Based on census data and manufacturing statistics, this paper explored the spatio-temporal characteristics of population migration and different types of manufacturing transfer during 2000—2020, and analyzed the effects of population migration and different types of manufacturing transfer on regional economic gap from a spatial perspective by using GeoDetector. The findings are as follows: (1) Capital-intensive, labor-intensive, and technology-intensive manufacturing industries all exhibit a trend of initial agglomeration followed by diffusion, while energy-intensive manufacturing industries consistently show a diffusion pattern. (2) The pattern of net population migration shows attractiveness in the central and western provinces to the migrating population .(3) In terms of gravity center shifts, all types of manufacturing industries are trending toward a westward and southward movement, while the population migration center shows a certain lag in its shift. (4) The explanatory power of the four types of manufacturing relocations in reducing regional economic growth disparities follows the order: capital-intensive, technology-intensive, energy-intensive and labor-intensive manufacturing, with population migration having the weakest explanatory power. The interaction between population migration and manufacturing transfer significantly enhances the explanatory power for regional economic growth, particularly in the interaction between population migration and technology-intensive and capital-intensive manufacturing industries. (5) Periodic study results indicate that regional economic growth is more effectively promoted when the directions of population migration and manufacturing relocations are aligned.

The Yangtze River Economic Belt is one of China's major national strategic development regions. Exploring the coupling coordination relationship between digital financial inclusion and agricultural new quality productive forces in this region is of great significance for promoting the agricultural high\|quality development in the Yangtze River Economic Belt. On the basis of identifying the mechanism of the coupling coordination between digital financial inclusion and agricultural new quality productive forces, this paper applies the comprehensive evaluation model, the coupling coordination degree model, the Dagum's Gini coefficient, and the exploratory spatial data analysis method to conduct a systematic study of the coupling coordination degree of digital financial inclusion and agricultural new quality productive forces in the Yangtze River Economic Belt from 2011 to 2021, and its future evolution trend were systematically studied. The study found that: (1) The development level of digital financial inclusion, agricultural new quality productive forces and their coupling coordination degree in the Yangtze River Economic Belt showed a steady upward trend, and the downstream region is better than the middle and upstream region; (2) The overall difference of coupling coordination degree showed a decreasing trend, and the inter-regional difference was the main source; (3) The spatial correlation of coupling coordination degree was obvious and gradually strengthened with the passage of time.

This study takes the nine provinces and regions along the Yellow River Basin as the research object, and constructs a three-stage model of logistics green efficiency measurement and driver decomposition. On the basis of measuring carbon emissions by using the emission factor method, combined with the super-efficient SBM model and the improved LMDI model, the green efficiency of logistics in the Yellow River Basin and the driving factors are measured in both horizontal and vertical dimensions from 2013 to 2021. The results show that: during the period of 2013—2021, carbon emissions show a continuous upward trend, and the overall green efficiency of logistics oscillates repeatedly, but the proportion of clean energy consumption, such as heat and electricity, increases; during this period, the green efficiency of logistics in the nine provinces and regions fluctuates upward, but the development is not balanced among the regions, and spatially presents a pattern of “low in the upper reaches and high in the middle and lower reaches”, and a spatial pattern of “high in the middle and lower reaches”. During this period, the green efficiency of logistics in the nine provinces and regions has increased volatility, but the development is not balanced among regions, showing a spatial pattern of “low in the upstream and high in the middle and lower reaches”, and the spatial difference has gradually expanded. Factor decomposition shows that there is spatial and temporal heterogeneity in the driving factors of carbon emissions in the Yellow River Basin, the regional economic development level and population size are the main driving factors for the rise of carbon emissions in the Yellow River Basin, and the intensity of logistics transportation and energy efficiency are the main constraints, and the inhibition of the intensity of logistics transportation is the most significant.

Based on the panel data of 80 prefecture-level cities in the central region from 2013 to 2022, the SBM-ML index, panel fixed effect model, mediation effect model, and threshold effect model are used to analyze the spatio-temporal evolution trend of industrial structure optimization and green total factor productivity in the central region and to test the impact of the optimization of the industrial structure in the central region on the improvement of green total factor productivity. The results show that (1) There is an uneven development of green total factor productivity in the central region; there is a mismatch between the levels of industrial structure rationalization, advancement and optimization; and the types of aggregation between industrial structure rationalization, advancement and optimization and green total factor productivity are high-low, low-low and low-low, and there is a large space for development. (2) The optimization of industrial structure, such as rationalization of industrial structure and advanced industrial structure, can effectively improve green total factor productivity by influencing technical efficiency. (3) There is regional heterogeneity in the impact of industrial structure rationalization and industrial structure advancement, and the different levels of economic and social development and resource endowment in different provinces lead to different directions and intensity of their effects. (4) Different stages of industrial structure optimization levels can provide different empowering effects, and there exists a suitable optimization level interval to promote the rapid increase of green total factor productivity.

This paper selects projection pursuit method to measure and analyze the temporal characteristics of the digital development level of cultural industries in 41 cities in the Yangtze River Delta from 2013 to 2022. Exploratory spatial data analysis and dynamic QCA method are used to conduct in-depth analysis of their spatial agglomeration characteristics and configuration paths. The results show that:(1) The digital development level of cultural industries in the Yangtze River Delta region is showing an increasing trend year by year, but there are obvious differences and differentiation phenomena between cities.(2) The digital development level of cultural industries in the Yangtze River Delta region shows significant spatial clustering characteristics, mainly in the “HH” and “LL” spatial clustering states, and the local spatial structure is also relatively stable.(3) From the perspective of configuration, there are nine paths for high-level cultural industry digitization, which can be summarized into four driving modes:“linkage-based”“technology-organization-based”“organization-environment-based” and “technology-environment-based”.

From the perspective of collaborative development, this study constructs a comprehensive evaluation index system for smart logistics. Utilizing the cloud PDR-Cosine similarity model and obstacle degree model, it conducts multidimensional measurements of smart logistics development in the Beijing-Tianjin-Hebei Urban Agglomeration. Key findings include: (1) Beijing, Tianjin, and Shijiazhuang form the core growth poles of regional development, while medium-high development level cities in Hebei Province demonstrate temporal fluctuation characteristics in their smart logistics advancement; (2) Spatial analysis reveals a tri-polar pattern centered on Beijing, Tianjin, and Shijiazhuang, with southeastern regions exhibiting higher development levels compared to northwestern areas, accompanied by an emerging concentration of development momentum in southeastern Hebei; (3) Obstacle factor analysis identifies four critical constraints: infrastructure supporting capacity, professional talent reserves, digital technology penetration capabilities, and environmental coordination mechanisms. Based on these findings, targeted countermeasures are proposed to promote regional smart logistics development.

In this paper, the spatial evolution process and characteristics of the “production-living-ecological” space in the Hehuang region of Qinghai Province are analyzed by using the ArcGIS spatial analysis method, land use transfer matrix and qualitative and quantitative methods. The results show that the ecological space in this area accounts for about 72%, followed by production space at about 23%, and living space at about 5%. The production space and living space are mainly distributed in the valley area of the main and tributaries of the Yellow River, of which the mainstream of Huangshui accounts for the main part. The Hehuang area has the largest ecological space area, which is distributed in contiguous areas. The production space area is the second, and the spatial distribution is scattered, mainly distributed in the Xining Basin and the narrow river valley area. The living space is the smallest in this area, and it is scattered in the form of points and lines. The transformation of “Production-Living-Ecological” space mainly occurs between “production-ecological” space and “life-production” space. With the continuous development of population and economy, the frequency and intensity of “production-ecological” space and “life-production” space conversion in the Hehuang area of Qinghai Province are increasing. Among them, the living space generally showed an increasing trend, and the growth in the mainstream of Huangshui was the most significant. The production space in the north and east showed an increasing trend, while the production space in the central, western and southern parts of the country showed a decreasing trend. The ecological space in the north and east showed a decreasing trend, but the ecological space in the central, western and southern parts of the country increased. According to the spatial area, transformation characteristics and functional synergy of the “production-living-ecological” space, four dominant functional types were divided: Ecological function-dominant, production-ecological function complex, ecological-production function complex and life-production function complex, and three human-land relationship regional system models were summarized: The valley-type urban human-land relationship regional system, the river valley-type urban-rural human-land relationship regional system, and the mountainous nomadic human-land relationship regional system. It is believed that each type of area should be developed according to local conditions and zoning and classification according to its natural environment foundation and social and economic development conditions, to realize the synergy of “production-living-ecological” functions and the sustainable development of Qinghai Hehuang area.

The level of elderly care facility development in prefecture-level cities is measured using the density of elderly care institutions (number of institutions per square kilometer) and the density of elderly care beds (number of beds per 10,000 people aged 65 and over). The results reveal that: (1) Both the density of elderly care institutions and elderly care beds exhibit significant spatial differentiation, with the former showing greater heterogeneity; (2) Four main demand-side factors (regional income level, gender structure, ethnic structure, and air quality) as well as two main supply-side factors (medical resources and service labor) significantly affect the level of elderly care facilities. (3) Through the Dagum Gini coefficient and Shapley decomposition, this article finds that: among the national inequality in elderly care facilities, the inter-provincial net gap is the largest, followed by the inter-provincial overlap, and the intra-provincial inequality is the smallest, so when implementing policies to reduce national inequality in elderly care facilities, priority should be given to provinces at the national level, followed by prefecture-level cities at different levels at the national level; (4) The degree of influence of each factor on the intra-provincial inequality of elderly care facilities varies greatly, so each province should conduct tailored and specific analyses to reduce these inequalities effectively.

This article is based on intercity patent transfer data, with prefecture level cities as spatial units, and uses methods such as social network analysis and cluster analysis to examine the pattern of intercity innovation flow network in the Yangtze River Economic Belt. It also delves into the functional characteristics of each city in the network. Research shows that: (1) The intensity of intercity innovation connections in the Yangtze River Economic Belt is unevenly distributed, with a few cities having close innovation connections while most cities have loose innovation connections. Overall, a “core-edge” structure is formed, with the Yangtze River Delta urban agglomeration as the core and attracting and radiating towards the middle and upper reaches of the region. (2) The Yangtze River Economic Belt presents a cross regional innovation flow pattern characterized by three major urban agglomerations as the main body. There is a clear threshold range for the intensity of intercity innovation flow within different distance ranges, with intercity innovation flow concentrated within 400 km and showing a certain distance attenuation feature. (3) The status of each city node in the network is significantly different, with significant spatial differentiation. Cities with higher centrality are mainly distributed in the Yangtze River Delta urban agglomeration downstream of the economic belt. The core cities of the Yangtze River middle reaches urban agglomeration and the Chengdu Chongqing urban agglomeration also have higher network centrality. Each city can be further divided into five functional types based on its node value and innovation function in the innovation network, namely the first city, core hub city, important node city, regional node city, and local node city.

From the perspective of spatiotemporal evolution, this study analyzes the spatiotemporal evolution of the “three-function space” in the Zhengzhou Metropolitan Circle and its closely collaborating area from 2010 to 2022. It quantitatively analyzes the evolution characteristics, scale, and evolution mechanisms of the three types of spaces, providing necessary data support and theoretical basis for optimizing the spatial pattern, high-quality development, and subsequent spatial planning of the Zhengzhou Metropolitan Circle. The research results show that the land composition within and around the Zhengzhou Metropolitan Circle is predominantly agricultural. During the study period, there is significant evolution among the “three-function space” with a large-scale expansion of urban areas and varying degrees of reduction in other space types. The increase in the total amount of urban space mainly came from the conversion of agricultural space, while changes in ecological space are primarily distributed along the Yellow River and the mountainous terrain in the southwestern part of the metropolitan area, mainly due to the conversion between green ecological space and agricultural space. The spatial distribution of the mutual conversion types of the “three-function space” in the study area shows certain degrees of aggregation or dispersion, with different spatial change distributions following specific patterns. The scale of spatial evolution is influenced by factors such as economic and social conditions and natural geographic factors, with varying mechanisms of influence for different conversion types and differing intensities of impact from the same factors.

To investigate the factors influencing Chinese and Russian tourists ’travel intentions to Northeast China, this study empirically examines the mechanisms through which short videos and satisfaction affect tourist behavior intentions using structural equation modeling. The results show that: (1) Emotional image is a relatively important factor in the pathway by which short videos influence Russian tourists’ travel intentions; (2) The production, operation, and promotion of videos about Northeast China have not yet formed an effective feedback mechanism, failing to effectively stimulate cross-border tourism among Russian tourists; (3) Tourism facilities and services in Northeast China are key factors influencing the willingness of both Chinese and foreign tourists to revisit. Finally, based on the conclusions drawn from this study, suggestions are proposed for enhancing the image of tourist destinations in the three northeastern provinces, improving service quality, and transforming the development of the tourism industry.

This study investigated the spatiotemporal characteristics and influencing factors of tourism network attention along the Sichuan-Tibet Highway using Baidu Index and Douyin topic view counts, with quantitative analysis, spatial visualization, and geodetector methods applied across multiple geographic scales. The results revealed that: (1) Temporally, tourism network attention exhibited a “rise-then-decline” trend with dual features of seasonal fluctuations and interannual heterogeneity.(2) Spatially, source regions demonstrated economically and geographically oriented patterns, while destination attention showed an east-high-west-low distribution with localized concentration and widespread dispersion. Scenic area attention presented an east-west high/middle-low and south-high-north-low pattern, contrasting with county-level polarization effects.(3) The observed disparities stemmed from multi-factor interactions involving internet penetration, economic status, population distribution, transportation accessibility, and tourism resource endowment. The findings suggest that future planning should prioritize balancing seasonal tourism demands, promoting equitable development across destinations, and enhancing digital media engagement to optimize regional tourism governance.

This paper takes the Grass Skyline as an example, and explores the impact of tourists’ perceived value on behavioral intentions through a combination of qualitative and quantitative methods. The grounded theory is used to explore and identify the dimensions of tourists’ perceived value of scenic byways and to develop scales. At the same time, quantitative research methods are used to test the impact of perceived value on behavioral intentions. Qualitative studies indicate that the perceived value of scenic byway tourists consists of five dimensions: perceived cost, landscape environmental value, driving experience value, tourism service value, and emotional value, with a total of 15 items in the scale. Quantitative studies show that landscape environmental value, driving experience value, tourism service value, and emotional value have a significant impact on behavioral intentions, while perceived cost has no significant impact on behavioral intentions.

Taking Jinggang Ancient Town in Changsha City, Hunan Province as a case study, this research adopts a constructivist perspective and employs questionnaire surveys and Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore the impact of tourists’ perceived authenticity of regional culture on place attachment, as well as the influence of place attachment on tourist loyalty. It also reveals the intrinsic connections and mediating roles among the dimensions of place attachment. The results show that both perceived of the objective and constructive authenticity of regional culture significantly affect place dependence, place identity, and affective attachment, but only constructive authenticity perception has a significant impact on social bonding. There are positive relationships among place dependence, place identity, affective attachment, and social bonding. All dimensions of place attachment significantly influence tourist loyalty and play different mediating roles between the perceived authenticity of regional culture and tourist loyalty.

Taking Yubei Village in the Nanxi River Basin as a case study, this research investigates the evolution of settlement spatial patterns across five periods: 1960, 2007, 2012, 2018, and 2024. Utilizing Geographic Information Systems (GIS) and space syntax analysis, along with historical imagery and field surveys, the study systematically quantifies the spatial transformations of Yubei Village. The results indicate that the village's boundary morphology evolved from a compact cluster to a finger-like pattern with clustered tendencies. The architectural layout shifted significantly from a centralized configuration to a multi-centered, dispersed structure, while the street network transformed from a simple radial form to a more intricate grid system. Policy guidance played a crucial role in shaping the spatial evolution of the settlement, alongside economic, cultural, and natural factors, which collectively drove the village's preservation and development. Based on these findings, the study proposes strategies and recommendations for the conservation and development of traditional settlement forms, aiming to provide theoretical support and practical guidance for the protection of traditional villages in the Nanxi River Basin and beyond.

Focusing on the counties within the Chengdu-Chongqing Urban Agglomeration, this study constructed a multi-level system for human well-being by integrating the frameworks of sustainable development goals (SDGs), millennium ecosystem services assessment, and the functional structure of human well-being in China. Subsequently, employing a coupling coordination degree model, random forest, and geographically and temporally weighted regression model, examined the intrinsic coupling and development levels between ecosystem services and human well-being from 2000 to 2020, while investigating their influencing factors. The results are as follows: (1) From 2000 to 2020, the overall value of ecosystem services in the Chengdu-Chongqing urban agglomeration shows a slow decline, with significant spatial differentiation. Meanwhile, the human well-being index increases from 0.31 to 0.54. (2) Over 90% of counties within the Chengdu-Chongqing urban agglomeration experience a rise or stabilization in the coupling coordination degree during this period. Internally, ecosystem services increasingly lag behind human well-being. The coupling coordination degree exhibits low-low clustering in the central urban areas of Chengdu, Chongqing, and Neijiang, while high-high clustering is observed in the peripheral mountainous regions. (3) Urbanization is consistently the dominant factor in coupling coordination, exerting negative effects similar to those of industrial levels. Conversely, increases in vegetation cover, the proportion of the tertiary industry, and the narrowing of income disparities collectively contribute to promoting coupling coordination.

Taking the Central Yunnan Urban Agglomeration as an example, the coupling relationship characteristics of the ecosystem services value (ESV) and human well-being (HWB) were elucidated using the coupling coordination degree model and trend surface. The spatio-temporal heterogeneity of the influence of driving factors on the coupling coordination degree is analyzed from a global and local integrated perspective based on the optimal parameters-based geographical detector (OPGD) as well as the spatio-temporal geographically weighted regression model (GTWR). The results show that: (1) Between 2010 and 2020, ESV in the Central Yunnan Urban Agglomeration initially decreased before subsequently increasing, while HWB improved to varying degrees across most areas, although it remains relatively low overall. (2) Significant spatial disparities in the ESV-HWB coupling coordination degree were noted, with a general trend towards coordinated development. The coupling coordination types form concentric patterns from the center to the periphery, characterized by “dysfunction decline-near dysfunction-reluctant coordination-coordinated development.” The spatial trend demonstrates a “U-shaped” curve, with higher values in the north and east and lower values in the south and west. (3) Proximity to water bodies emerged as the dominant factor positively influencing the coupling coordination degree, whereas population density, intensity of human activities, and road network density negatively impacted the coordination.

The paper utilized spatial autocorrelation, standard deviation ellipse, and the STIRPAT model embedded in panel geographically and temporally weighted regression model (PGTWR) to study the spatial and temporal evolution of urban carbon emissions and their influencing factors in the Huaihe River Eco-economic Belt from 2006 to 2021. The findings reveal an increasing trend in overall urban carbon emissions within the basin, accompanied by a strengthening agglomeration trend of carbon emissions, resulting in an eastern hotspot and a western cold spot. The carbon emission expands from southeast to northwest, concentrates in the southwest, and its center of gravity shifts eastward. Furthermore, it is found that a single local point's carbon emission is influenced by all cities’ spatial spillover effects within the basin over a maximum period of 13 years. The impact of each factor exhibits temporal and spatial heterogeneity: industrial structure, economic development, crop yield intensity, and energy intensity have weakened promotional effects over time; conversely, population growth's promotional effect has gradually increased. Inhibitory effects such as population urbanization, urban expansion intensity, capital inflows, and urban spatial structure have strengthened overall. Regarding spatial distribution patterns, the central and western cities are more affected by factors like energy intensity, economic development, population growth, and urbanization of population; meanwhile, eastern cities exhibit stronger influence from factors such as crop yield intensity and urban expansion intensity. Industrial structure has a strong impact on resource-based cities. Additionally, the inhibitory effect of capital inflows primarily observes in the western part, while the inhibitory effect of urban spatial structure concentrates in northern areas.

Adopt a super-efficiency slack-based measure (SBM) model incorporating undesirable outputs, a composite-index methodology, and a coupling-coordination framework measure the ecological civilization construction efficiency, common prosperity level and the coupling coordination of the two in Zhejiang Province, and uses the Tobit model to detect the influencing factors of the coupling coordination degree. Results shows: (1) Between 2005 and 2020, Zhejiang Province's ecological-civilization construction efficiency traced a “rise-fall-recovery” trajectory: Jiaxing, Hangzhou, and Ningbo registered the most pronounced gains; Lishui and Zhoushan consistently sustained comparatively high efficiency levels; and total-factor productivity increased in the majority of cities; (2) Between 2005 and 2020, the coupling-coordination degree between ecological-civilization construction and common prosperity exhibited an “initial ascent-subsequent decline-subsequent surge” pattern, evolving from a state on the verge of disorderly regression to an intermediate coordinated-development phase; (3) Empirical analysis indicates that industrial-structure upgrading, technological advancement, educational attainment, environmental regulation, and urbanization exerted significant positive effects on the coupling coordination of ecological-civilization construction and common prosperity in Zhejiang, whereas resource agglomeration and aggregate economic growth produced inhibitory impacts.

Xichuan County, Henan Province, the core water source area of South-to-North Water Diversion Middle Route Project, is taken as the research area. According to the accounting standard of Gross ecosystem product (GEP), the GEP accounting of Xichuan County is carried out by using statistics, remote sensing and meteorological data, and arcgis spatial analysis methods. The results showed that the total ecosystem production value of Xichuan County was 113.823 billion yuan in 2020. In terms of ecosystem service functions, the value of ecological regulation services was the largest, which was 98.967 billion yuan, accounting for 86.95% of GEP, while the value of ecological material products and ecological cultural services were relatively small, accounting for 9.579 billion yuan and 5.277 billion yuan, accounting for 8.42% and 4.63%. In terms of ecological regulation services, the value of water resource regulation is the largest, accounting for 43.68% of GEP, followed by the value of climate regulation, water purification and flood regulation and storage. From 2000 to 2020, the water ecosystem of Xichuan County has the greatest change, with an increase of 189.72 km², and the ecological service function of the water ecosystem is the most significant. The results of accounting reflect that Xichuan County's ecosystem is in good condition and the value of ecological services is considerable, which can provide a reference for the assessment of the effectiveness of basin ecological protection, the efficient transformation of “two mountains” and the assessment of local government's green political performance.

This study comprehensively used fixed panel models, threshold models, and spatial econometric models to investigate the impact of the coupling coordination between rural revitalization and new urbanization on common prosperity. The results show that: (1) The coupling coordination between rural revitalization and new urbanization can promote the development of common prosperity, but there are dimensional and regional heterogeneity, with the industrial dimension and the western region having the greatest impact on common prosperity. (2) The impact of coupling coordination degree on common prosperity exhibits a non-linear feature of progressive marginal effects. At the same time, the level of digital economy and industrial structure upgrading has played a threshold effect in the coupling and coordination of rural revitalization and new urbanization on common prosperity. (3) The coupling and coordination of rural revitalization and new urbanization effectively promote the development of common prosperity in the local area, and the accompanying spatial spillover effects can also promote the improvement of common prosperity levels in other surrounding regions.

With the implementation of the rural revitalization strategy, China's rural collective economy has undergone enormous changes and played an important role in promoting the realization of common prosperity in rural areas. Based on a questionnaire survey of villages and farmers in eight counties (cities) of Weifang City, Shandong Province in 2023, the impact and mechanism of rural collective economy on farmers’ subjective well-being were systematically examined. The results show that: (1) The average level of rural collective economic development is relatively high, but the regional development is imbalanced, and there are obvious differences between villages. The subjective well-being among farmers is relatively high;(2)With basic regression using OLS model, it is found that the rural collective economic development can significantly improve the subjective well-being of farmers. The conclusion is still valid after checking the endogeneity of the model by using the 2SLS method, and the robustness test of the PSM sample matching;(3)In terms of the mechanism of effect, using stepwise regression, bootstrap and other mediation effect models to verify the existence of the “collective economy-social capital-subjective well-being” pathway, the rural collective economy will reduce the subjective well-being of farmers through the reduction of social capital, and the mediation effect accounted for 4%.