Strategic emerging industries, as an important component of new quality productive forces, serve as a key pillar of the modern industrial system and a significant driving force for the Chinese-style modernization. Based on data from Chinese listed companies in strategic emerging industries and their investment-related enterprises, this study systematically analyzed the development trends, spatial pattern changes, and regional division of labor and collaboration patterns of related enterprises in China's strategic emerging industries from the end of the 13th Five-Year Plan period to the end of the 14th Five-Year Plan period. The study revealed that during the 14th Five-Year Plan period, China's strategic emerging industries maintained a positive development trend, particularly standing out during the economic recovery phase in the post-pandemic era. From an industry perspective, related enterprises in strategic emerging industries have increasingly concentrated in key areas such as manufacturing, research and development, business, and finance, while spatially further clustering in major urban agglomerations, including the Beijing-Tianjin-Hebei region, the Yangtze River Delta area, the Pearl River Delta area, Chengdu-Chongqing, and the middle reaches of the Yangtze River, as well as some key provincial capital cities. This has formed an overall pattern centered around the five major urban agglomerations. Both spatial distance and hierarchical distance have imposed constraints on the spatial expansion of strategic emerging industries, and spatial distance played a stronger constraining role. Significant differences existed between different industries within this framework. From the perspective of factors influencing the spatial layout of related enterprises in strategic emerging industries, the entire industries generally tended to locate in areas with a high concentration of core enterprises and their associated businesses, showing a preference for cities with advanced industrial structures. However, spatial layout preferences varied across specific types of industries.

Under the requirements of high-quality development, optimizing and evaluating land resource allocation in resource-based ecologically fragile regions is key to achieving coordinated economic, social, and ecological development. Taking the Lunan Economic Circle as an example, the multi-objective optimization algorithm and entropy-weight TOPSIS were employed to determine the quantitative optimization scheme of land use in 2030; the PLUS model was employed to predict the optimized spatial layout of land use; and the SBM model was employed to measure the multi-period ecological efficiency to quantitatively evaluate the reliability of land use optimization results. The results show that: 1) With the rigid constraint of the arable land red line, although the acreage of arable land in the region decreases by 2030, it remains above the safety baseline, while the areas of construction land, forest land, grassland, and water bodies increase, achieving optimization of total land use and structure. 2) After optimization, scattered arable land is converted to construction land; sloping arable lands in the Yishan-Mengshan-Nishan area are restored to forest and grassland; the wetland ecological space of the Nansi Lake expands; and unused land near mountains and suburbs is orderly developed, resulting in a more rational spatial pattern. 3) After optimization, as the area of ecological land expands, the gross ecosystem product of all counties is improved, and the overall ecological efficiency of the region will improve from 0.29 in 2020 to 0.33 after optimization in 2030, with further reduction in regional disparities. In conclusion, multi-objective optimization considering the economic-social-ecological functions of land can effectively allocate land resources, promote the ecological transition of these resource-based ecologically fragile regions, and accelerate regional sustainable development.

As the digital economy expands, rural tourism micro-enterprises (RTMEs) face challenges in both digital transformation and resilience building. Digital literacy, a key driver of digitalization, is crucial for fostering innovation and resilience, but the mechanisms behind its impact remain unclear. This study investigated how digital literacy influences innovation and resilience in RTMEs, with a particular focus on the mediation role of innovation. Using a mixed-methods approach combining fsQCA and regression analysis, the study surveyed 72 RTMEs from Shuanglang and Wenlin Villages in Yunnan Province, China. A complex mediation model of "digital literacy-innovation vitality-resilience" was proposed. The fsQCA identified key digital literacy configurations, while regression analysis examined their direct and indirect effects on resilience. The findings show that: 1) Five distinct digital literacy configurations foster high innovation vitality, forming a "perception-capture-transformation" chain with multiple equivalent pathways. 2) Innovation vitality acts as a complex mediator between digital literacy and resilience, with some configurations promoting resilience and others hindering it. 3) Digital literacy dimensions are dynamically complementary, with digital survival skills being crucial for aligning innovation and resilience. Without these skills, misalignment between the two occurs. This study provides a theoretical framework for understanding digital literacy's role in enhancing resilience and offers practical recommendations for RTMEs to optimize their digital capabilities. By identifying context-specific pathways, it suggests tailored strategies for sustainable development in rural tourism.

As a core element of urban environments, the vitality of public green spaces serves as a key indicator for measuring the efficiency of urban environmental services and residents' well-being. This study took 93 public green spaces in the main urban area of Nanjing City as empirical cases. It integrated multi-source heterogeneous data, including Baidu Huiyan population location data, street view images, points-of-interest (POIs), road networks, and social media photographs. By comprehensively applying geographic detector analysis, the multi-scale geographically weighted regression (MGWR) model, and the four-quadrant analysis method, the study innovatively constructed a park green space vitality analysis framework based on the interaction between subjective and objective environments from both the global and local perspectives. This enables a multi-scale analysis of the spatiotemporal differentiation characteristics and underlying causes of public green space vitality in Nanjing City. The findings reveal that: 1) The vitality of Nanjing's public green spaces exhibits significant spatial differentiation, presenting a gradient pattern characterized by high-vitality clustering in the central-eastern areas and low-vitality diffusion in the periphery. 2) Globally, user preferences for service facilities and green view index are the core drivers explaining green space vitality, with notable coupling effects among factors. 3) Locally, the influencing mechanisms of green space vitality display significant spatial heterogeneity, with high variability in factors such as service facilities, decorative elements, and functional mix, while the impacts of functional density and infrastructure remain relatively stable. 4) The differentiated synergy of four key factors—transport accessibility, functional configuration, streetscape, and user visual preferences—proves effective in enhancing public green space vitality. The theoretical framework developed in this study implements an analytical strategy of multi-scale diagnosis-spatial differentiation identification-targeted regulation, providing policymakers with scientific tools including hotspot identification, deficiency diagnosis, and intervention priority assessment to support precision planning strategies based on spatial heterogeneity.

Traffic collisions present a global public safety challenge, and they arise from the combined effects of human, vehicle, road, and environment factors within urban transportation systems. While existing studies have predominantly focused on the impact of the built environment on traffic collisions, limited attention has been given to travelers' subjective perception of safety and its interaction with road network characteristics. Using street links in the main urban area of Wuhan City as the basic unit of analysis, this study employed street view imagery and machine learning techniques to evaluate perceived safety at the street link level. Using a four-way decomposition model, we quantitatively analyzed the controlled direct effect (CDE), the reference interaction without mediation (INT_ref), the pure mediated effect (PIE), and the mediated interaction (INT_med) through which road network characteristics influence traffic collisions via perceived safety. The results show a significant correlation between perceived safety and traffic collisions, indicating the presence of a "perception bias". Furthermore, topological and geometric characteristics of road networks influence traffic collisions through both the CDE and the PIE mediated by perceived safety. Betweenness centrality, diversion ratio, and mean geodesic length also affect traffic collisions through INT_ref and INT_med with perceived safety, whereas the near-line ratio operates through INT_ref with perceived safety. Among these pathways, the CDE plays the dominate role, while INT_ref, PIE, and INT_med contribute minor proportions, demonstrating that perceived safety moderates the magnitude but not the direction of the total effect. The findings elucidate the complex mechanisms by which urban road network characteristics affect traffic collisions from the perspective of perceived safety, providing a theoretical basis for developing road safety design strategies that integrate both objective and subjective considerations.

Against the backdrop of global poverty reduction and China's efforts to consolidate the achievements of poverty alleviation, transport-related social exclusion in mountainous rural areas—stemming from geographic and individual factors—has emerged as a significant determinant of relative poverty. Taking Huangping County in Guizhou Province as a case study and drawing on household survey data from 2019, this study constructed a measurement framework for transport-related social exclusion and employed a binary logit model to empirically analyze its relationship with relative poverty. The results reveal that: 1) Physical disability and lack of motor vehicles were key drivers of relative poverty, as they respectively undermined labor capacity and restricted spatial mobility, thereby exacerbating barriers to social participation. 2) There was marked heterogeneity among different groups regarding the impact of transport disadvantages. Males, individuals of working age, and those with only primary education were more sensitive to disability and lack of transport means, reflecting the high dependence of productive and employment activities on transportation. 3) For groups with junior high school education and above, relative poverty was constrained by a diverse set of factors, including subjective health, transport expenditure, and travel safety, indicating a shift in multidimensional development needs as education levels rise. 4) Frequent travels to the county seat were negatively correlated with relative poverty, suggesting that active integration into the regional economic network can effectively reduce the risk of relative poverty. This study demonstrated that social exclusion and mobility constraints arising from transport disadvantages are important triggers of relative poverty in contemporary mountainous rural areas. The research expanded the micro-level perspective of transport-led poverty reduction, confirmed the role of transport-related social exclusion in the formation of relative poverty, and provided a scientific basis for precisely identifying impoverished groups and formulating differentiated policies.

Tunpu culture in Central Guizhou is a unique regional cultural phenomenon. This study focused on 37 Tunpu traditional villages in Anshun City, Guizhou Province, and their intangible cultural heritage (ICH) projects at or above the provincial level, using a comprehensive evaluation model, a factor contribution model, and the kernel density estimation method to evaluate the living state of ICH within these villages. Furthermore, it identified the types of the living state of ICH in villages and revealed corresponding spatial distribution patterns. The results show that: 1) The overall living state of ICH in Tunpu traditional villages is suboptimal, with pronounced polarization across different dimensions. 2) Anshun Dixi Opera exhibits the highest levels in both its living state and stability among the individual ICH projects, and the largest number of villages in the study area have advantages in the living state of performance ICH. 3) The types of the living state of ICH in Tunpu traditional villages are classified as: synergistic advantage, characteristic agglomeration, potential activation, enhancement driven, restoration and improvement, and adjustment and restructuring. Spatially, the high-density core area is located at the border between Xixiu and Pingba districts. 4) Overall, the average living state of ICH in Tunpu traditional villages is higher in Xixiu District than in Pingba District. The research results are in line with the actual situation, and provide a scientific basis for the sustainable development of ICH in Tunpu traditional villages.

Amid accelerating global population aging, elderly sojourn behavior has emerged as a critical phenomenon with profound socioeconomic implications. The geographic mobility patterns and settlement intentions of elderly sojourners are reshaping urban demographic landscapes and recalibrating public resource allocation dynamics, posing novel governance challenges for destination cities. This study used Sanya City (China's premier tropical coastal retirement destination) as a representative case to investigate elderly sojourn dynamics through a tripartite analytical framework. Using origin-destination (O-D) matrix analysis based on elderly preferential travel card data (2016-2020), we first delineated the spatiotemporal change of elderly sojourners' mobility patterns. Subsequently, multilevel logistic regression models based on the 2021 questionnaire survey data (N=150) revealed determinants of their settlement intentions. Finally, we put forward differentiated governance strategies. The results show that: 1) There was a phased spatial progression characterized by Northeast China dominance (51.17% of elderly sojourners)-regional node expansion-nationwide dispersion-COVID-19 induced contraction, and the migration showed a seasonal tidal effect, with the majority of the migrant population aged 65-75 years. 2) Elderly sojourners in Sanya demonstrated higher education level and family disposable income, typically accompanied by a spouse and suffering from chronic diseases. Their settlement intention was significantly affected by family factors, migration patterns, and community environment. Those in the family-oriented migration and long-term migration categories had a higher probability of settling down, while a housing area exceeding 65 m² and a residence adjacent to hospitals can significantly improve their willingness to stay. 3) Based on migration cycles and settlement intentions, elderly sojourners were categorized into four groups: seasonal long-term sojourners, seasonal short-term sojourners, permanent long-term sojourners, and permanent short-term sojourners. This research expanded the theoretical framework of elderly sojourn research through its multiscalar methodology integrating macro-scale mobility mapping with micro-level behavioral analysis, offering evidence-based policy recommendations for elderly sojourner-responsive urban governance. The findings particularly inform destination cities' strategies for joint management mechanism, seasonal infrastructure management, and differentiated community services tailored to elderly sojourn characteristics in aging societies.

In recent years, extreme weather events are increasingly frequent, severely impacting human mobility and socioeconomic activities. Ensuring the robustness of intra-city mobility is essential for the development of resilient cities. However, existing studies primarily focused on physical infrastructure or routine mobility patterns, with insufficient understanding of the spatial mechanisms of human mobility changes under external disturbances. This study constructed the "weather-environment-behavior" framework by combining spatial behavior and disaster risks. Based on mobile phone signaling data, the spatiotemporal characteristics of human mobility in Shanghai under the influence of Typhoon Bebinca are identified, and the driving mechanisms including weather conditions, traffic environment, built environment, and socioeconomic factors are analyzed through geographically weighted regression (GWR). Key findings include: 1) Human mobility in Shanghai was severely impacted during the typhoon and lasted for a long time, showing a clear "decline-recovery" process and rebound after the disaster. Mobility intensity showed negative correlation with weather conditions in time series. 2) Mobility patterns showed ring-shaped spatial differentiation, with the central urban area and distant suburbs experiencing severe fluctuations and impacts, while the near suburbs were less affected. In temporal terms, the central urban area exhibited gradual response patterns, while the peripheral area exhibited sensitive response patterns. 3) Changes of mobility were influenced by different factors in a spatially non-stationary manner: central urban areas were primarily affected by rainfall duration and travel distance, suburban areas were primarily affected by travel intensity and land use mix, while remote suburban areas were influenced by factors including transportation infrastructure, land use functions, and public service levels. Socioeconomic factors contributed to shock mitigation in most peripheral areas. It will be helpful to enhance the adaptability of the city by alleviating overcrowding in urban centers, defining the dominant functions of new towns, increasing employments, and improving infrastructures. This study aimed to provide a scientific basis for urban planning, traffic management, and emergency response, promoting urban safety, resilience, and sustainable development.

In the era of financialization turn, high-end financial service capabilities with high professionalism and high added value have become one of the core competencies for cities to participate in regional capital allocation. However, most of the existing studies measure urban financial service capabilities within the framework of static analysis, lacking a dynamic network perspective based on the actual financial connections between cities and attention to the high-end financial service capabilities of cities. This study overcome some limitations of the traditional network construction methods by focusing on the relationship between listed enterprises and related advanced producer services (APS) during the initial public offering (IPO) process of listed enterprises. The study incorporated the IPO-raised funds into the weight to construct a multi-stage high-end financial service network for Chinese cities from 1993 to 2023. The social network analysis method was adopted to measure and evaluate the high-end financial service capabilities of cities, and the formation mechanism was systematically analyzed in combination with the bidirectional fixed effects model. The research findings are as follows: 1) The urban financial network in China presented a hierarchical core-periphery structure and a spatial pattern of dense in the east and sparse in the west, and the regional network pattern was consistent with the overall economic development level. 2) The high-end financial service capabilities of Chinese cities presented a core-periphery structure centered on Beijing-Shanghai-Shenzhen, and polarization was increasingly prominent over time. 3) The empirical results based on the "input-demand-institutional" analysis framework reveal the core formation mechanism of a city's high-end financial service capacity: The reserve of financial industry talents enhances the quality of high-end service supply by increasing a city's human capital, and the city's innovation capacity mainly plays a role by driving the demand for high-end financial services through the listing of science and technology innovation enterprises. The administrative hierarchy of cities promotes the aggregation of elements and the construction of an innovative ecosystem through institutional empowerment in large cities, indirectly driving capacity improvement. The dynamic weighted network method developed in this research overcome the limitations of traditional frequency statistics, more scientifically and comprehensively revealing the spatial pattern of high-end financial service capabilities in Chinese cities, and provides a solid empirical basis for understanding its formation mechanism.

Declining resource-based cities, as "problem regions" in China's regional development, have seen cross-regional investment becoming an important means to accelerate inter-regional flows of production factors and promote their own transformation and development with the reduction of their comparative advantages. Based on data of cross-regional investments by enterprises in China's declining resource-based cities from 2001 to 2022, this study analyzed the characteristics of investment scales, investment distances, and investment field characteristics, adopted the social network analysis method to analyze the evolution trend of the cross-regional investment networks by enterprises, and further examined the influencing factors from both the push and pull perspectives. The results show that: 1) The scale of cross-regional investment by enterprises in China's declining resource-based cities gradually increased from 2001 to 2022, and cities in central China gradually became the main cross-regional investment subjects. There was a significant local preference in the process of enterprise cross-regional investment, but medium and long-distance investments had increased in recent years, showing the feature of "contraction at both ends and expansion in the middle". 2) Manufacturing and producer services were not only the main sectors for outward investment but also key recipient sectors. Over time, the invested producer services had experienced obvious changes from wholesale and retail trade to scientific research and technical services. 3) The complexity and intensity of the enterprise cross-regional investment network continued to increase; however, the spatial structure remained relatively decentralized, with weak connections between cities. During the study period, the polarization of the strongest ties had weakened, and structural adjustment within the network was evident. 4) The enterprise cross-regional investment network exhibited a significant modular structure, with new nodes increasingly integrating through cross-module collaboration, highlighting a growing hierarchical trend. Additionally, the enterprise cross-regional investment network was transitioning from a distinct core-periphery structure towards a more balanced state. 5) The influencing factors varied significantly across different stages. The economic vitality of declining resource-based cities and the geographical distance between the investing and receiving cities consistently remained the primary factors affecting cross-regional investment by enterprises. This study contributes to a deeper understanding of the spatial structure and key influencing factors of enterprise cross-regional investment in declining resource-based cities, providing a scientific support for optimizing the path selection and decision making of cross-regional investment and promoting regional coordinated development. The research findings may serve as a reference for other types of resource-based cities.

Knowledge complexity is a core variable for assessing regional innovation quality and predicting economic growth potential, yet existing studies have insufficiently examined its spatiotemporal heterogeneity and driving mechanisms at micro scales such as towns and subdistricts. Drawing on invention patent data for township‑level units (towns and subdistricts) in the Pearl River Delta region from 1990 to 2022, this study measured the knowledge complexity index (KCI) and, by combining spatial autocorrelation analysis with a multi‑scale geographically weighted regression (MGWR) model, explored the spatiotemporal dynamics of knowledge complexity. The results show that: 1) The overall change of knowledge domains followed a pattern of "ICT‑led and multi‑field synergy", while knowledge domains in strategic emerging industries such as biomedicine and new energy exhibited breakthrough spatial configurations. 2) The spatial pattern of knowledge complexity followed a gradient of "core agglomeration and peripheral lag", evolving from an initially scattered distribution into a polycentric network structure centered on the Guangzhou-Shenzhen science and technology innovation corridor. 3) The driving effects of knowledge structure displayed pronounced spatiotemporal heterogeneity, with related variety continuously strengthening the positive impact of technological relatedness on knowledge complexity, whereas unrelated variety showing a stage‑specific trajectory of first promoting and then differentiation—exerting a generally positive effect on knowledge complexification in the early period, but in the later period remaining significantly positive only in the Guangzhou-Foshan core area. 4) The spatial configuration of innovation factors played a key role in shaping the differentiation of knowledge complexity. Local governments need to adopt gradient‑adaptive strategies: core areas should reinforce networks of technological relatedness, while peripheral areas should prioritize the cultivation of specialized cluster advantages. This study can provide scientific references for breaking low‑end lock‑in, reshaping a high‑quality innovation landscape, and constructing spatial coordination mechanisms in the Pearl River Delta region.

Against the backdrop of technological revolution reshaping regional development patterns, the Nanjing Metropolitan Area—a key hub for the Yangtze River Delta's influence on central and western China—plays a crucial role in regional high-quality development through its innovation integration. This study used high-tech corporate investment, talent mobility, and county patent transfer data from 2000 to 2023 to construct a multidimensional innovation network for the Nanjing Metropolitan Area. Employing complex network analysis, the siphoning and trickle-down model, and the quadratic assignment procedure (QAP) regression method, it systematically explored the structural change, spatial effects, and driving mechanisms of this innovation system. The results show that: 1) The innovation network exhibited a spatial radiation pattern centered on Nanjing. The siphoning and trickle-down effect of the Nanjing growth pole has shifted from strong siphoning-weak trickling to collaborative development. Technology flows have transitioned from siphoning to trickling dominance, capital flows continued to spill over, and talent siphoning intensity has decreased. 2) Adjacent counties and districts of prefecture-level cities are categorized into five types of border effects: shielding, penetration, contact, filtering, and integration. Nanjing-Ma'anshan and Wuhu-Xuancheng formed technology flow integration boundaries, while Changzhou-Xuancheng and Nanjing-Yangzhou exhibited talent flow integration boundaries; Some boundaries between Nanjing-Zhenjiang and Nanjing-Chuzhou exhibited filtering effects on capital flows due to administrative gradient differences, specifically manifested as high-intensity innovation diffusion from Nanjing to Jurong, Nanqiao, and Lai'an. 3) Economic development and enterprise development levels exerted differentiated influences on multidimensional innovation linkages across different periods. Labor income disparities exhibited a significant negative correlation with innovation linkages, while fiscal science and technology investments, development zones, and the number of universities significantly promoted innovation linkages. Geographic, technological, and institutional proximity facilitated factor mobility. This study revealed the complex mechanisms underlying innovation integration within the Nanjing Metropolitan Area from the perspective of multidimensional innovation networks, aiming to provide a theoretical foundation and practical reference for regional collaborative innovation development.

This study analyzed the spatial flow path of carbon sequestration services based on the flow of ecosystem services, and constructed a one-to-one carbon compensation mechanism linking the subject and object of compensation, to provide a theoretical reference and scientific support for optimizing the carbon compensation policy for the coordinated development of the ecology and economy. Taking the Yangtze River Delta (YRD) urban agglomeration as the study area, the study clustered the standard explicit comparative advantages in the socioeconomic, ecological environment, and land use structure aspects, identified carbon compensation and compensated areas, revealed the spatial transfer paths of carbon sequestration services within the YRD urban agglomeration by combining with the fracture point and field strength model, and then calculated the amount of carbon compensation based on the contribution of carbon sinks of the cities. The results of the study indicate that: 1) Carbon emissions in the YRD urban agglomeration showed a continuous upward trend, while carbon sequestration showed a downward trend. Spatially, carbon emissions and carbon sequestration showed opposite distribution patterns, with carbon emissions characterized by "high in the east, low in the west and high in the north, low in the south" and carbon sequestration characterized by "high in the west, low in the east and high in the south, low in the north". 2) During the study period, the flow of carbon sequestration services in the YRD urban agglomeration was mainly in the direction of southwest-northeast, with a clear preference for proximity, where Xuancheng was the most stable and largest carbon sequestration service output area, and Nanjing (adjacent to Xuancheng) was the largest input area. In 2022, the carbon compensation payment of Nanjing was 41036500 yuan. In conclusion, the scale of carbon deficits in the YRD urban agglomeration has been expanding, and there was an obvious spatial mismatch between carbon revenues and expenditures, so the construction of a cross-regional carbon compensation mechanism is a realistic demand for realizing the dual carbon goals.

Against the backdrop of evolving regional population mobility patterns and spatial transformations from urbanization, county-level units in inland regions of China have emerged as significant arenas for nearby urbanization in recent years. This study developed an indicator for the propensity of intra-county mobility. It employed a coupling and coordination degree model and an evaluation method for coordination influence to investigate the evolution of the preference for localized population mobility in counties within central China from 2010 to 2020, along with its coupling and coordination relationship with multi-dimensional urbanization at the county level. The findings reveal that: 1) Population mobility in these counties was characterized by a dominance of long-distance migration alongside an accelerated trend towards nearby movement. Differences in mobility choices appeared across provinces, influenced by their varying stages of economic development. The gap in the preference for intra-county mobility between regular counties and county-level cities was minimal, underscoring the fundamental role of county seats in absorbing locally oriented population flows. 2) The coupling and coordination between the preference for intra-county mobility and demographic urbanization was generally high. The most notable improvement was observed in the coordination with social urbanization. However, the economic subsystem had begun to show an inhibiting effect on the overall coupling degree. The dominant influence on coordination imbalance was shifting away from being primarily driven by the social service system towards being increasingly constrained by lagging economic development. 3) The differentiation of county types and the evolution of their multi-dimensional coupling relationships resulted from the combined effects of local retention forces and external pull factors. Government initiatives, through institutional innovation and improved public services, strengthened local retention and promoted coordinated development between intra-county mobility and social urbanization. Nonetheless, the relative lag in the supply of industrial factors led to an absence of production-oriented pull forces. This, combined with the persistent effect of external pull factors, created a constraining effect from the economic subsystem and introduced risks associated with exogenous urbanization. This research deepens the understanding of the change of population mobility patterns and the mechanisms underlying county urbanization pathways. It can provide a reference for promoting healthy and sustainable nearby urbanization.

Promoting the adaptation of digital financial inclusion and inclusive green growth is a practical necessity for contiguous poverty-stricken areas to consolidate the achievements of poverty alleviation and achieve common prosperity. Most existing studies have focused on the impact of digital financial inclusion on the single system of inclusive green growth, lacking empirical analysis of the adaptive relationship among the two. Based on the panel data of 71 county-level units in the Wuling Mountains Area from 2014 to 2022, this study adopted the comprehensive adaptation evaluation model, exploratory spatiotemporal data analysis, and spatiotemporal geographically weighted regression model to systematically reveal the spatiotemporal dynamic characteristics of the adaptation ofdigital financial inclusion and inclusive green growth, as well as the spatiotemporal non-stationarity of its influencing factors. The results show that: 1) During the study period, the adaptation level of digital financial inclusion and inclusive green growth in the Wuling Mountains Area had shown a steadily increasing trend. The whole adaptation type had changed from relatively unadaptable to moderately adaptable during the research period of 2014-2022. 2) The spatial integration of the digital financial inclusion and inclusive green growth in the Wuling Mountains Area was relatively strong, and the local spatial structure was relatively stable. There were transfer inertia and path lock-in phenomena. The local spatial structures in the individual regions of Chongqing and Guizhou fluctuated more significantly. 3) The adaptation of digital financial inclusion and inclusive green growth in the Wuling Mountains Area was mainly influenced by factors such as economic foundation, government support, educational level, and information technology level. The intensity and direction of influence of each factor exhibited significant temporal and spatial non-stationarity. Due to the constraints of topographical conditions, the impact of transportation accessibility on the inter-provincial border areas was relatively small. Theoretically, unlike existing studies that unilaterally explore how digital financial inclusion affects inclusive green growth, this study, based on the construction of a theoretical framework for the adaptation between digital financial inclusion and inclusive green growth, quantitatively measured the bidirectional interaction between the two systems. This is conducive to enriching the research scope of adaptation theory and expanding the research content on the relationship between digital financial inclusion and inclusive green growth. Practically, this study not only clarified the key driving factors of the adaptation between digital financial inclusion and inclusive green growth, but also explored the spatiotemporal non-stationarity of different influencing factors, responding to the contemporary demand for formulating policies to consolidate the achievements of poverty alleviation in accordance with local conditions. It has practical significance for promoting the digital transformation and high-quality development of the Wuling Mountains Area in a coordinated and interactive manner.

Service-oriented specialized villages possess significant developmental potential, thus urgently requiring categorized comparisons and theoretical analysis of their distribution patterns. This study, grounded in the "first and second nature" theory, employed spatial analysis and an optimal multivariate stratification geographical detector to examine the distribution of China's service-oriented specialized villages by industry type. The findings reveal that while leisure tourism and e-commerce villages share broadly similar distribution patterns, characteristics, and drivers, their spatial distribution reflects common underlying rules. Specifically: 1) In terms of distribution patterns, service-oriented specialized villages are densely concentrated in eastern coastal regions such as the Beijing-Tianjin, southern Jiangsu, and eastern Zhejiang areas. Leisure tourism villages exhibit a "dual-core" pattern, while e-commerce villages display a "single-core" pattern with a more southeastern distribution extent and center of gravity. 2) In terms of distribution characteristics, service-oriented specialized villages are primarily located in areas with advantages in both "first and second nature" factors—namely, flat terrain, warm and humid climate, proximity to small and medium rivers, high population density, developed economy, convenient transportation, and favorable location. Leisure tourism villages have overall lower threshold requirements for these factors compared to e-commerce villages. 3) In terms of distribution drivers, the spatial patterns of service-oriented specialized villages result from the combined influence and interaction of both "first and second nature" factors. Among these, "second nature" factors, particularly the locational element of town-village relationships, play a dominant and amplifying role, while population and economic factors also exert considerable influence. This study extends the application of the "first and second nature" theory and deepens the understanding of the distributional differences and influencing factors of service-oriented specialized villages.

In the context of accelerated urbanization and burgeoning tourism, the spatial configurations of traditional villages, emerging from extensive interactions between social and spatial dynamics, are undergoing significant degradation and manifesting complex heterogenization challenges. This study focused on Banliang Village in Hunan Province using qualitative methodologies including in-depth interviews and participant observation, to develop a comprehensive socio-spatial interaction analytical framework. The research investigated the mechanisms of transformation from social structures to spatial arrangements, alongside the reciprocal impacts of spatial factors on the perpetuation of social structures, thereby elucidating the underlying principles and suggesting potential restoration strategies. The findings include: 1) An examination of the evolution of spatial forms, ranging from individual buildings to street and lane spaces and overall spatial configurations, in relation to the social hierarchy characterized by social stratification, relational networks, and economic structures, revealed that social stratification influences the architectural forms of individual buildings, while variations in morphology reinforce class divisions; social interactions shape the layout of streets and lanes, which in turn modify social relations; and the economic framework directs the trajectory of spatial evolution, with spatial configurations exerting a counterbalancing effect on economic transformations. 2) A proposed spatial restoration pathway for Banliang Village is articulated through the dual lenses of "society shaping space" and "space reciprocating to society". This research contributes to the discourse on the mutual construction of society and space, enhancing the understanding of the intrinsic logic governing traditional village spatial configurations and providing innovative perspectives for the planning and preservation of these vital cultural landscapes.

Against the backdrop of rural revitalization and digital China initiatives, digital technology is increasingly integrated into the development of ethnic tourism villages. Drawing on individualization theory, this study examined how bottom-up digital practices by village residents drive village spatial restructuring. Focusing on Zhaoxing Dong Village in Guizhou Province as a representative case, we employed in-depth life-history interviews, field observations, and multi-actor semi-structured interviews. The research explored the individualized practices of village residents, exemplified by Ms. L, a representative intangible cultural heritage (ICH) bearer, who utilizes digital tools for cultural performance, entrepreneurial promotion, and community connection, alongside the resulting spatial effects. Our findings reveal that digital technology offers village residents new pathways for local development, enabling them to actively integrate digital tools with indigenous culture. This integration profoundly reshapes village space: 1) In the material space, functional hybridization occurs, such as traditional dye workshops combining production with live-streaming functions. Productive landscapes like indigo fields transform into tourist attractions through digital media. 2) In the social space, power structures shift, with groups possessing digital skills gaining enhanced decision-making influence. Decisionmaking increasingly emphasizes skill, while online communities supplement traditional mutual aid networks. 3) In the cultural space, symbolic reproduction takes place. Village residents translate local knowledge into shareable content through visual narratives. This process meets external audience demands while simultaneously boosting cultural identity and self-awareness among internal groups, particularly female residents.The restructuring of material, social, and cultural spaces intertwines and mutually reinforces itself through individualized practices. This study elucidated the mechanism by which village residents' individualized digital practices drive systemic spatial restructuring in ethnic tourism villages. It provides theoretical insights and practical implications for balancing cultural preservation and economic development in such villages in the digital era.

Against the backdrop of declining fishery resources and increasingly stringent marine governance in the South China Sea (SCS), traditional fishing livelihoods face severe challenges, prompting fishing towns such as Tanmen to seek transformation toward tourism development. In this process, the SCS fishing heritage has emerged as a vital form of cultural capital driving industrial transition. Drawing on long-term fieldwork in Tanmen, Qionghai City, Hainan Province, and employing the concept of authorized heritage discourse (AHD), this study examined how the SCS fishing heritage has been shaped and transformed into tourism resources through the interplay of national narratives, local transformation, and industrial logics. The findings reveal that this heritage is not a unidirectional construction imposed by the state but a dynamic outcome of interactions between multiple actors at the national and local scales. The AHD endows the SCS fishing heritage with cultural-political capital that serves national sovereignty narratives, while providing local tourism products with symbolic legitimacy and national value endorsement. The study further showed that the tourismization of AHD represents both a localization of national narratives and a strategic response by local actors seeking cultural and economic benefits. Through the analytical framework of landscape, symbols, and memory, the study revealed how the local governments and residents have converted fisher culture into consumable tourism resources, developing diverse sectors such as sightseeing, dinning, accommodation, and recreation, and forming a dynamic structure of national discourse formation-local translation-industrial practice. However, a top-down political orientation and limited community participation have led to the shallow expression of local culture. Additionally, outdated leisure fishery policies, complex administrative procedures, and weak benefit-sharing mechanisms continue to constrain local innovation and the live transmission of heritage. Based on the empirical findings, this study developed an analytical framework of heritage tourismization pathways, which addresses the lack of holistic perspectives in current research and elucidates the internal logic of heritage transformation into local tourism resources. The tourismization of the SCS fishing heritage not only provides new means for sustaining cultural identity amid the shrinking of traditional fishing spaces but also offers practical solutions for reconciling marine governance with fishermen's livelihoods. Accordingly, the study calls for improving leisure fishery policies and enhancing community participation mechanisms to promote the inheritance of the SCS fishing heritage and the sustainable transformation of traditional fishing towns.