Currently, global Fintech innovation has become a core area of financial competition among countries. Based on the Orbis global intellectual property database, this study analyzed the development trends of global Fintech innovation from 1962 to 2022 and compared the technological knowledge capabilities between China and traditional financial powerhouses such as the United States, the United Kingdom, and Japan. The findings are as follows: 1) From 1962 to 2022, there has been a significant increase in both the quantity and knowledge diversity of Fintech patents, accompanied by deepening integration with five major technological categories: "electronic information technology", "big data", "mobile Internet", "blockchain", and "artificial intelligence". Also, the integration among different types of technological innovations continued to intensify. 2) In terms of the application of technological knowledge in Fintech, traditional financial countries had a clear advantage in the field of electronic information technology, while China has excelled in big data and mobile Internet, driving the widespread adoption of digital payments and smart financial platforms. Moreover, China dominates in multiple key technological fields such as electronic information technology, blockchain, and artificial intelligence. However, China's application capabilities in financial services remain relatively weak, representing a key area for future improvement in its Fintech development. In terms of Fintech technological knowledge combinations, China and the United States exhibited the strongest knowledge integration in information technology, with notable competitive strength in the combined innovations of biometric technology with e-commerce and electronic payments. 3) Traditional financial countries maintain a high degree of similarity in their technological knowledge application and integration capabilities, while significant differences exist between China and these countries. Based on the conclusions of this study, China not only needs to focus on technological breakthroughs in emerging fields such as blockchain and artificial intelligence but can also deepen international cooperation to achieve collaborative breakthroughs in common technological challenges. By establishing strategic partnerships and knowledge sharing, China can accelerate its innovation capabilities and contribute to the global development of Fintech.

Development zones serve as core carriers of industrial agglomeration and are important engines of regional economic growth. However, during their transformation and upgrading, they often encounter challenges such as industrial homogeneity and blind competition. To address these issues, it is essential to actively respond to policy initiatives that aim to build a symbiotic and complementary industrial system in development zones and foster positive interactions among them. This study focused on 97 national-level development zones in the Yangtze River Delta region and, based on the theory of technology interaction, employed technology complementarity and competition index, social network analysis, and quadratic assignment procedure (QAP) methods to analyze the change and influencing factors of technology interaction from 1985 to 2021. The findings indicate that: 1) The technology interaction in the national-level development zones in the Yangtze River Delta region has gone through three stages—fluctuation at a low level, differentiated growth and decline, and synchronous growth—and presented a dynamic change process from competition and complementarity to technology complementarity. 2) The trends in technology interaction between national-level economic development zones and high-tech zones were generally similar, but the latter exhibited a higher intensity of interaction. 3) As the technology interaction network matures, the technology complementarity network has evolved into a "multi-core, multi-level, and wide-coverage" diamond-shaped structure, with increasingly close connections among the communities, while the technology competition network presents a decentralized "multi-point blossoming" pattern. 4) In the early stage, technology interaction was significantly influenced by administrative boundaries and hierarchical differences between cities. In the middle of the development stage, cross-regional cooperation emerged, and the impact of urban hierarchy increased. In the later stage, geographical proximity and industrial structure similarity became the primary drivers, reflecting a shift from government-led, city connection-dependent to market-driven, self-initiated cooperation. This study expands the theoretical boundaries of technology interaction, further deepens the research progress of coordinated development of development zones, and provides a contribution of knowledge based on the fundamental structure of technology elements.

Exploring the way to implement differentiated strategies according to the development characteristics of different types of urbanization is the key theoretical and practical problem for realizing the sustainable and healthy development of China's new urbanization. Based on the census data of 2010 and 2020, this study identified five types of urbanization of the population in the West Taiwan Strait urban agglomeration, including the local urbanization type, the in-situ urbanization type, the nearby urbanization type, the inter-provincial urbanization type, and the undetermined registered residence urbanization type, starting from the household registration and current residence of the population and the definition of "urban" in the urban-rural division. The ESTDA exploratory spatial-temporal data analysis and spatial Durbin model were used to explore the spatial-temporal characteristics and influencing factors of each type of urbanization. The results show that: 1) With regard to the spatial distribution, all urbanization types exhibited a macro-level pattern characterized by either overall improvement or gradient diffusion. Specifically, the in-situ urbanization type and the local urbanization type demonstrated significant advancement in overall levels during the study period. Meanwhile, the nearby urbanization type, the inter-provincial urbanization type, and the undetermined registered residence urbanization type manifested gradient diffusion distributions. These formed distinct spatial patterns: the in-situ urbanization type diffused radially from prefectural-level city cores; the local urbanization type exhibited a coastal-to-inland decreasing gradient; while the inter-provincial urbanization type and the undetermined registered residence urbanization type showed concentrated coastal agglomeration with dispersed inland distribution. 2) In terms of the spatial-temporal evolution, significant spatial autocorrelation persisted across all urbanization types, with overall agglomeration features remaining stable yet undergoing notable shifts. The high-high cluster region of the in-situ urbanization type expanded from the Chaoshan area to establish a dual-core structure encompassing Chaoshan and Shangrao. Concurrently, the primary high-high cluster zone of the local urbanization type shifted westward. For the nearby urbanization type, the inter-provincial urbanization type, and the undetermined registered residence urbanization type, their low-low clusters coalesced into a contiguous belt along the Fujian-Jiangxi border, whereas their respective high-high clusters maintained strong coastal concentration. 3) With regard to the driving mechanisms, the spatial framework was initially established by natural geographical conditions. Historically evolved clustered sociocultural networks further facilitated diversified urbanization pathways. Governmental influence operated through dual channels: direct intervention via open policies, the household registration system, administrative division adjustments, and urban-rural demarcation; and indirect steering through regulatory control over economic development, social factors, and spatial planning elements.

Under the background of population decline, the number of cities in China with shrinking urban population continues to increase, posing challenges to the allocation of urban construction land resources. This study, based on multi-source population and land use data and taking Northeast China as a case example, constructed a hierarchical constraint plus multi-scenario simulation forecasting method to predict urban population changes from 2020 to 2035. It further identified construction land development risks from the perspectives of "static coordination" and "dynamic adaptation", proposing ideas for optimized land allocation. The study found that: 1) Urban population forecasts reveal a continued decline in Northeast China, with a growing number and intensifying severity of shrinking cities. The spatial pattern exhibits a clear "core growth-peripheral shrinkage" characteristic, with resource-based and old-industrial cities facing particularly severe shrinkage. 2) Urban population changes show diverse types, with differentiated pressures on land allocation transformation, dominated by "deepening shrinkage" and "falling into shrinkage" types, and significant interprovincial differences. 3) The region is characterized mainly by "static scale redundancy" and "insufficient dynamic adaptation" in the human-land relationship, with widespread redundancy in prefecture-level cities' construction land and most cities still following expansion-based land allocation patterns at the baseline period. 4) Risk identification of construction land highlights deep-seated conflicts; different levels of land allocation risks exist in 30 shrinking cities. High-risk cities form a "land-asset decline cycle" and urgently need to explore "value pathways" within "land reduction". By constructing a systematic logical framework linking population forecasting and land use risk, this study innovated population prediction methods and provided a comprehensive diagnosis of land use risks, offering valuable exploration for guiding optimized construction land allocation in shrinking cities.

Exploring innovative paths and models for rural revitalization and development transformation through the participation of multiple agents has become a core focus of rural geography in response to national strategic demands in China. Drawing upon the symbiosis theory and taking Gengche Town in Suqian City of Jiangsu Province as a case study, this study examined the mechanism by which stakeholders establish and maintain symbiotic relationships to jointly advance rural transformation and development. The findings indicate that the central government, local governments, and local actors—represented primarily by rural elites—constitute the fundamental symbiotic units in the rural transformation symbiotic system. Among them, the central government is responsible for strategic planning, local governments for policy experimentation and implementation, while rural elites and residents act as the driving force for transformation through bottom-up entrepreneurial activities. Rural transformation is embedded in a symbiotic environment characterized by multi-scalar linkages of macro-intermediate-endogenous elements. Shifts in national strategies and the rise of e-commerce economy provide the macro external context for transformation, whereas the social networks of rural acquaintances and the collaborative atmosphere among online entrepreneurs form the endogenous environment. Local governments serve as intermediaries between the national and rural scales, coordinating the interests of all parties and facilitating resource integration. Given the differences in interests, resources, and capabilities among the symbiotic units, they have developed symbiotic models such as mutual benefit, complementarity, and mutual assistance to bridge these gaps and enhance symbiotic effect.

Under the strategy of ecological conservation and high-quality development in the Yellow River Basin, the implementation of residential relocation projects is an inevitable choice to comprehensively promote high-quality development and rural revitalization in the Yellow River beach area. Based on the theories of human-environment relationship and regional high-quality development, this study used quantitative analysis methods such as a multi-factor comprehensive evaluation model and geographical detectors, combined with field research and text analysis, to investigate the spatial characteristics and driving mechanisms of residential relocation in the Yellow River beach area of Henan Province. The results show that: 1) There are significant spatial differences and hierarchical differentiation in the driving forces for residential relocation in the beach area, with higher driving forces concentrated in the central area and higher resistance mainly distributed on the eastern side. 2) The overall tendency for residential relocation in the beach area is mainly at medium to high levels, but there are significant differences among counties (districts), exhibiting a "centralized" spatial distribution pattern with Zhengzhou as the "center". 3) The two-dimensional mapping analysis result shows that residents of 53.85% of the counties (districts) in the beach area are still in a state of low-level driving and resistance for relocation. This low-level development status may increase the risk of residential relocation driving factor identification, especially for resistance factors, thereby posing significant uncertainty and potential challenges to the effectiveness of residential relocation in the beach area. 4) The spatial characteristics of the driving forces for residential relocation in the beach area are the result of the mutual influence and combined action of various impact factors, with income levels, geographical location, policy support, and individual factors being the primary driving factors. The research results can provide scientific references for the differentiated formulation and precise implementation of relocation policies for residents in the Yellow River beach area, as well as for the assessment of relocation risks.

The reconstruction of rural living spaces is a profound aspect of building livable, business-friendly, and beautiful villages, and examining its process is of great significance. Taking tourism gentrification as the entry point and based on Bourdieu's field theory, this study constructed an analysis framework of "rural living space field structure-transformation mechanism deconstruction". Using Shiwei Village in Eerguna City, Inner Mongolia as an example, this study systematically analyzed the reconstruction of rural living spaces and its mechanisms during the process of tourism gentrification. The study found that: 1) Tourism gentrification in Shiwei Village showed distinct temporal and spatial characteristics, having gone through the embryonic stage, the primary stage, and the development stage, transforming from the original field to a tourism field. 2) Rural living space is a field, and based on the daily behavioral activities of residents, four sub-fields—residence, consumption, employment, and social interaction—can be derived. Therefore, a four-element analytical framework for the reconstruction of rural living spaces was constructed and its reconstruction characteristics were analyzed. 3) The rural living space field is full of competitions and games among different actors. Within the field, "power-capital-habit" interact with each other, based on which we deconstructed the transformation mechanism of the living space field in Shiwei Village. The study aimed to deepen rural living space studies from a theoretical perspective. It is not only an exploration of applying field theory in the field of geography, but also provides a new analytical framework for the reconstruction of rural living spaces and the clarification of the complex problems and mechanisms behind it.

Enhancing human well-being while mitigating environmental stress is an essential component of the sustainable development strategy for lake regions. This study constructed and computed the index of environmental intensity of human well-being (EIWB) for the region around Poyang Lake. Applying the Dagum Gini coefficient and the Logarithmic Mean Divisia Index (LMDI) decomposition method, this study examined the spatiotemporal differentiation characteristics and driving effects of the EIWB in the region from 2007 to 2022. The findings are as follows: 1) During 2007-2022, the region around Poyang Lake exhibited a trend of coordinated development characterized by a continuous improvement in comprehensive human well-being and a gradual alleviation of environmental pollution, with a significant reduction in the EIWB. Both the lakeside area and the periphery area registered significant decreases in the EIWB, while the lakeside area exhibited a relatively higher level compared to the periphery area. 2) The spatial differences of the EIWB in the region around Poyang Lake initially contracted before expanding. The differences within regions surpassed the differences between regions and the differences between river basins exceeded those within river basins. The key to narrowing the spatial differences of EIWB in the region around Poyang Lake is in reducing the differences within regions and the differences between river basins. 3) Technological effect and intensification effect were the primary drivers behind the decrease in the EIWB in the region around Poyang Lake, the lakeside area, and periphery area, and the effect was more significant in the lakeside area than at the periphery. Population agglomeration effect, economic growth effect, and well-being transformation effect served to counteract this decline. The research findings provide a decision-making basis for promoting the sustainable enhancement of human well-being in major lake regions in China, and offer a reference for formulating differentiated green transformation strategies for lake areas.

Residential mobility is an important way to understand urban social and spatial transformation and mechanisms of problem occurrence, and test the social and spatial effects of urban policies. Based on a comprehensive analysis of aggregated data on migration cities and micro-level non-aggregated studies, this study takes Anqing City as an example and used data from 3367 migration surveys, to map out residents' mobility network at the community level with the help of social network analysis. It examined the role of the community in residents' mobility and the spatiotemporal characteristics and change in the interaction between the community and residents' mobility. The results indicate that: 1) The community is the "medium" through which structural factors influence micro behaviors. Structural factors have an important impact on residents' mobility behavior through different types of communities. It manifests as the existence of structurally "transitional" communities within the residents' mobility network. The "transition" communities serve as the initial "settlement" areas for migrant populations entering the city and as a "springboard" for urban residents moving to other communities. Over time, the structural "transition" communities have evolved from work unit-related communities to those surrounding large-scale wholesale markets, low-income housing projects, old communities, communities prone to environmental risks, relocation and resettlement communities, and urban villages. 2) Micro-scale relocation behavior promotes the change of community attributes and the evolution of communities. It is manifested as the mobility intense community transitioning from the original work unit-related community to neighboring communities and surrounding communities with environmental risks. Communities "detach" from within the community boundaries and move towards neighboring communities and cities. 3) The combined effect of "structure-community-behavior" and the differences in the roles of the three at different times have promoted the interaction between communities and relocation and the spatiotemporal change of the residents' relocation network. This research provides an important reference for understanding community changes and realizing good governance in the community.

Narrowing the health gap between different older adult groups is a key aspect of advancing the national strategy for healthy aging. This study used self-reported health data of the population aged 60 years old and above in 124 counties in Guangdong Province from the 2010 and 2020 population census data. The proportion of those reporting "good health" was used as an indicator to measure the health status among the older adult population in different counties. Exploratory spatial data analysis (ESDA) and the spatial Durbin model (SDM) were applied to analyze the spatiotemporal patterns and determinants of the health status of migrant and local older adult populations in the province. There were three main findings. First, the overall health status of the older adult population in Guangdong Province showed an upward trend. Significant inter-county disparities were observed between migrant and local older adult populations. Counties with higher levels of health status were predominantly concentrated on the economically developed Pearl River Delta, while counties with lower levels of health status were located in the peripheral areas of the province. Second, the health status of migrant older adults was significantly higher than that of their local counterparts. This health advantage exhibited spatial and temporal variations. Third, economic development and the availability of medical and healthcare facilities were associated with the health status of local older adults. In contrast, factors such as neighborhood deprivation, Normalized Difference Vegetation Index, water coverage, PM_2.5 concentration, the proportion of migrants, and household size were more strongly related to the health status of migrant older adults. These findings provided valuable insights for optimizing public service resources allocation and promoting regional development in the context of healthy aging.

Cropland serves as the cornerstone of agricultural production and food security, with its quantity and spatial configuration exerting a direct influence on crop production efficiency. Although Africa possesses vast land resources, the availability of arable land remains limited, posing serious challenges to regional food security. Accurately identifying the distribution and spatial characteristics of cropland, as well as uncovering its relationship with crop yield, provides a critical foundation for formulating agricultural development strategies and food security policies. However, the accuracy of existing land use products in Africa remains limited, making them insufficient for large-scale cropland monitoring. In recent years, phenological parameters, which capture the temporal dynamics of vegetation growth, provide a promising approach for improving the accuracy of cropland extraction. To better understand cropland changes and their impact on cereal yields across Africa, this study employed the GLASS-LAI product and a phenology-based method to extract cropland distributions for 2010 and 2020. By integrating land use data and crop yield statistics, we assessed how cropland fragmentation and surrounding land composition influence cereal production. The results indicate that: 1) The cropland extraction results based on phenological parameters achieved high accuracy, with overall classification accuracy exceeding 0.9 according to the confusion matrix. 2) From 2010 to 2020, cropland fragmentation increased in most African countries, with a significant negative correlation between fragmentation and cereal yields observed in regions such as West Africa. 3) The proportion of built-up areas and water bodies surrounding croplands showed a stronger influence on cereal yield than other land use types. 4) In addition to fragmentation and built-up land proportion, economic development and climatic factors are key drivers of yield variation, with clear regional differences in their explanatory power. This study uncovers the mechanisms linking cropland landscape patterns and cereal yield performance in Africa, providing scientific evidence to support locally adapted strategies for improving agricultural productivity and informing targeted food security policies.

Disaster resilience building has become a key strategic choice and innovative governance path to deal with the threat of flood disasters. Based on the survey data of 54 villages and 685 farming households in flood-prone areas of Sichuan Province, this study constructed a disaster resilience framework from three dimensions of resistance, recovery, and adaptability. Based on three typical landforms of the region—plain, hill, and mountain, the entropy method and grey correlation degree model were used to evaluate the disaster resilience of villages and farming households and reveal its scale-related characteristics. The results show that: 1) Village-scale disaster resilience was at the medium and low levels, and mainly distributed in mountainous and hilly areas; At the subdimension level resistance showed the highest values, followed by recovery and adaptability. 2) Disaster resilience at the farming household scale was at the medium and low levels, and there was no significant spatial distribution difference between regions. At the subdimension level resistance showed the highest values, followed by adaptability and recovery. 3) There was a certain continuity of disaster resilience at the village and farming household scales, and the difference in the level of disaster resilience at the farming household scale was more obvious. In the corresponding relationship of resilience at different scales and regions, the correlation of medium disaster resilience level was stronger, especially in plain areas. 4) There was a correlation effect between scales. Emergency response, accessibility of government aid, and village cohesion at the village scale had the greatest impact on the disaster resilience of farming households, and this pattern was highly consistent under different terrain conditions. Collective collaboration, human resources, and disaster prevention awareness at the farming household scale were the primary factors affecting village resilience, and there were regional differences in the dominant factors in different terrain areas—plain areas emphasized collective cooperation, hilly areas emphasized transformation ability, and mountainous areas relied on human resources.The research results provide a scientific basis for formulating differentiated regional disaster prevention policies, which is of great practical significance for enhancing the effectiveness of multi-scale collaborative governance and building resilient rural areas.

Reconstructing the timing of past mountain glaciations is critical for understanding regional climate evolution and geomorphic development. Single-grain post-infrared infrared-stimulated luminescence (pIRIR) dating using K-feldspar has recently been applied to glacial and glaciofluvial sediments in high mountain regions, such as the Tibetan Plateau. However, challenges and issues still exist, and the reliability of the method requires further validation. In this study, we assessed the feasibility of applying single-grain K-feldspar pIRIR dating to glaciofluvial deposits from the headwaters of the Urumqi River in the eastern Tianshan Mountains—a region known for well-preserved Quaternary glacial landforms and detailed stratigraphic sequences. Two sediment samples were collected from a glaciofluvial lens near the Hongwuyue Bridge site. Both single-grain quartz OSL and K-feldspar pIRIR measurements were attempted. The quartz grains exhibited low luminescence intensity, resulting in unreliable age estimates. In contrast, dose recovery tests indicated that the K-feldspar pIRIR₁₁₀ and K-feldspar pIRIR₁₇₀ protocol are well suited for the local sediments. After excluding scattered signals using the normalized median absolute deviation (nMAD) method, equivalent dose distributions were modeled using the central age model (CAM). The IR₁₁₀ and pIRIR₁₇₀ ages were found to be consistent, with final pIRIR₁₇₀ ages of 21.9 ± 2.4 ka and 22.1 ± 2.4 ka for the two samples. These ages agree well within reasonable error range and correspond with previous glacial chronologies from the Shangwangfeng moraine complex. The results demonstrate that single-grain K-feldspar pIRIR dating, when properly screened and modeled, can yield reliable ages for glaciofluvial sediments, providing a valuable tool for reconstructing mountain glacier histories.

The convergence of relational economic geography (REG) and evolutionary economic geography (EEG) offers novel insights into the formation mechanisms of regional emerging industries. Taking the biopharmaceutical industry in the Suzhou Industrial Park (SIP) as a case study, this study employed field research and empirical analysis to unravel the impact of dynamic strategic coupling on regional industrial change. Key findings include: 1) Developing regions rapidly transplant emerging industries through "dual-dependent coupling", yet excessive reliance on external actors poses sustainability risks. 2) External shocks (for example, financial crises) trigger decoupling, creating opportunities for governmental agency to upgrade coupling modes from dependency to functional coupling, thereby achieving value chain leapfrogging and industrial diversification. 3) Locational opportunity windows from industrial transfer must align with local conditions (for example, locational advantages, policy demands) to foster emerging industries. 4) The industrial base and entrepreneurial culture in neighboring regions empower local path creation through knowledge spillovers and synergy. This study enriches the analytical framework for the change of regional emerging industries and deepens the understanding of the influence mechanism of strategic coupling on such change, which is of great policy significance for addressing external shocks and promoting the upgrading of coupling models.

Agricultural industrial chain resilience is crucial for ensuring stable production and increased output of national grain and key agricultural products. Based on the panel data from 80 prefecture-level regions in central China from 2011 to 2022, this study measured agricultural industrial chain resilience using the entropy weight method, and investigated its spatiotemporal differentiation patterns and influencing factors through kernel density estimation and geographical detector analysis. The findings reveal that: 1) From a temporal perspective, the resilience of the agricultural industrial chain in China's central region has demonstrated a consistent strengthening trend, with the southern zone exhibiting marginally higher resilience levels compared to the northern zone. 2) From a spatial perspective, the resilience of agricultural industrial chain in central China exhibited significant spatial correlation. High-resilience regions have expanded from Hunan and Hubei toward the Qinling-Huaihe line. Dagum Gini coefficient analysis confirmed the pronounced regional disparity between northern and southern regions. 3) Geographical detector analysis identified logistics distribution capability, economic development level, and consumption capacity as key influencing factors. Interactive effects between agricultural technology R&D and labor supply significantly enhanced resilience, indicating an ongoing transition of driving forces from traditional production factors to technological innovation and market demand. Policy recommendations include: strengthening infrastructure such as agricultural technology innovation and rural logistics distribution; advancing industrial chain collaboration through cross-regional agricultural professional services; and institutionalizing agriculture-related policies and risk governance frameworks. This research provides empirical evidence and decision-making references for optimizing agricultural industrial layouts in central China.

Border areas are important gateways for opening up to the world, but few studies have explored the characteristics and influencing factors of its foreign trade in sufficient depth. Yunnan Province is an important gateway connecting China's market to the Southeast Asian markets, holding an important position in China's opening up in the new era. Therefore, using the Chinese customs database from 2003 to 2022, this study conducted a comprehensive analysis of the spatiotemporal change and influencing factors of the trade pattern for Yunnan Province based on year-market-product. The main conclusions of this study are as follows: 1) In terms of market characteristics, Myanmar was both the largest export and import markets of Yunnan Province, and the Southeast Asian region occupied an important position in both the import and export patterns of Yunnan Province. The United States was an important export market for the province, while countries such as Saudi Arabia, Peru, Chile, and Kuwait were major sources of imports. 2) In terms of product characteristics, the export structure showed a trend of greening and sophistication, shifting from polluting products, such as chemicals and metals, to electronic products and plant products. Among the imported products, energy such as oil and natural gas as well as metals accounted for more than 50%. 3) In terms of market-product characteristics, there was a significant difference between the province's exports to the United States and Southeast Asian countries, with the former having a more balanced structure. Yunnan Province imported large quantities of mineral products from high-resource countries such as Saudi Arabia, and a relatively high proportion of plant products from tropical countries. The export scale of the province was positively influenced by the local industrial base and industrial policies as well as the institutional environment of the trade markets, and was constrained by the product supply capacity and geographical distance of the trade markets. Differently, the import scale of Yunnan Province was significantly positively correlated with the local industrial base and industrial policies, as well as the institutional environment, openness, and product supply capacity of the trading markets, and significantly negatively correlated with geographical distance. The key influencing factors of trade patterns varied for different types of products. This study provides policy implications for optimizing the foreign trade structure of the border region represented by Yunnan Province.

The structural analysis of tourism flow networks has been a focus of research both in China and internationally. However, previous studies have paid relatively little attention to analyzing tourism flow networks among counties, rarely examined network motif structures, and offered limited investigations into large-scale regional case study areas. Based on big data from online bookings, this study employed complex network and the weighted exponential random graph model to analyze the multi-dimensional structure of "overall-motif-node" levels of intercounty tourism flow network in the Yangtze River Economic Belt and influencing mechanisms. The results reveal that: This network exhibited sparse, scale-free, and small-world features, with tourism flow links primarily concentrated within provincial boundaries and weak inter-provincial connections. The network contained seven 3-node motifs, each forming a loop structure, revealing seven tourist trip patterns including "fully connected triad". Node centrality varied significantly between counties, demonstrating an obvious Matthew effect. The agglomeration and diffusion functions for tourism flow were coupled, with counties possessing strong comprehensive functions concentrated in the Yangtze River Delta urban agglomeration, as well as provincial capitals and key tourist cities in central and western regions. But counties with high betweenness centrality are mainly distributed in Sichuan, Chongqing and Yunnan. This network's formation was affected by endogenous structure, node attributes, and exogenous networks, driven jointly by endogenous forces, positive push forces, and negative resistance forces. Reciprocity provides endogenous motivations. Economic development levels, transportation conditions, and tourism resource endowments of counties serve as positive push forces, while distance from provincial capitals, consumer price, population density, as well as spatial and cultural distances generate negative resistance. This research is conducive to deepening the theoretical research on the network spatial structure of tourism flow among counties.

In recent years, the vigorous development of Douyin short videos has become a crucial channel for enhancing the brand awareness and resulting visitor flow of tourist attractions. Studying the online influence of scenic spots and its influencing factors based on Douyin's sales power is of great significance for improving the digital evaluation system of scenic spots and promoting their high-quality development. Taking the Douyin ticket sales of scenic spots as the measurement indicator, this paper applies methods such as rank-size, Kernel density,typological division and Geodetector to analyze the spatial differentiation of online influence and its influencing factors of China's 5A-level scenic spots. The research findings are as follows: 1) Rank-size characteristics indicate that high-ranked scenic spots account for only 10.45% of the total but demonstrate significant influence and cluster in areas such as the Beijing-Tianjin-Hebei region, the middle and lower reaches of the Yangtze River. Medium-ranked scenic spots are the most numerous, accounting for 71.29%, yet their internal hierarchy is indistinct. Low-ranked scenic spots exhibit substantial variations in influence. 2) From the overall spatial differentiation characteristics, the number of scenic spots of medium-high, medium, and medium-low grades is large, while that of high-grade and low-grade ones is small. The spatial pattern features a single high-density main core, two secondary cores with subordinate density distributions, and multiple low-density cores scattered across the country. 3) Spatial differentiation of ticket types indicates that high grade scenic spots in total ticket sales and subtype metrics show significant convergence, with dominant regions concentrated in the Yangtze River Delta, Sichuan-Chongqing area, and the central plains. 4) A comparison with traditional indicators shows that both the MBI and Douyin ticket sales reflect a "central agglomeration and sparse distribution at both ends" pattern, with high grade scenic spots sharing similar regional distributions. However, from the perspective of brand online influence, high and low grade scenic spots are fewer in number, indicating a relatively balanced and stable distribution. Based on these two indicators: Total ticket sales on Douyin and MBI (Meadin Brand Index), scenic spots are classified into five categories, providing practical guidance for marketing optimization, policy-led resource allocation, and accelerating tourist decision making. 5) Influencing factor analysis results indicate that the number of tourist receptions, favorites, and followers demonstrate strong explanatory power; likes, topics, and posts show moderate explanatory power; while regional per capita Gross Domestic Product has the weakest explanatory power.

Exploring the patterns of change and influencing factors of business is an important basis for promoting the high-quality development of winter tourism destinations. Taking Chongli District of Zhangjiakou City, one of the venues for the Beijing Winter Olympics, as a typical winter tourism destination, this study constructed an industrial system for ice and snow tourism destinations, which took the core dominant formats as the main body to output major tourism products, used the extended synergistic formats to improve the market operation environment, and employed the supporting auxiliary formats to shape the basic development environment. It also clarified the functional relationships among different levels of industrial subsystems. It selected its point of interest (POI) data from 2005, 2010, 2015, 2022, and 2023 and used the ArcGIS spatial analysis method to analyze the spatial-temporal change characteristics of business in Chongli and its influencing factors. The results shows: 1) The number of POIs in the ice-snow tourism destination has demonstrated progressive growth from 2005 to 2023. Especially during the exponential growth stage driven by Winter Olympics preparations, all tourism sectors achieved unprecedented POI proliferation, particularly core dominant sectors that manifested the most substantial quantitative expansion. It also showed a stable development in the high-quality development stage. Significant spatial variations in business distribution have been observed, characterized by predominant concentration within southeastern townships and sparse distribution in northern regions, with dense clustering in southern areas. 2) Chongli's business formats exhibited an agglomerated spatial pattern, transitioning from a "single-core with multiple nodes" configuration to a "dual-core and dual-belt" structure during the study period, with progressively intensified clustering. Spatial diffusion analysis revealed that the distribution centroid is located at the boundary between Hongqiying Township and Xiwanzi Town on the whole. The standard deviational ellipse displayed a distinct northeast-southwest orientation, indicating pronounced directional spread. Spatial correlation analysis demonstrated strong positive spatial interdependence, with prominent clustering features. Low-low clusters significantly decreased, while high-high and high-low clusters gradually increased, indicating enhanced development levels across business formats. 3) The spatiotemporal change of winter tourism destination business formats is mainly driven by the combined effects of multiple factors: distance from administrative centers, socioeconomic development levels, collaborative development with tourism enterprises, transportation network distribution, altitude, slope, sports, and the winter Olympics policy impacts. Particularly during the rapid development stages, administrative centers and ice and snow policies played crucial catalytic roles in accelerating business format development, with the driving force gradually shifting to tourism-oriented enterprises as the primary growth engine.

Promoting the spatial and temporal adaptation of the cultural system and tourism system along the Long March Route is helpful for facilitating the orderly flow and optimal allocation of cultural and tourism production factors along the Long March Route, and it is of great significance to promote the high-quality development of cultural and tourism integration along the Long March Route and optimize the Long March National Cultural Park strategy. Taking 15 provinces within the scope of the construction of the Long March National Cultural Park as the research sample, this study constructed an evaluation indicator system for the culture-tourism system along the Long March Route, and comprehensively used the adaptability evaluation model, coupling coordination model, kernel density estimation, obstacle degree model, and optimal parameter geographical detector to analyze the characteristics of change of the integration development driven by the spatiotemporal adaptation of the culture-tourism system along the Long March Route from 2013 to 2022 and its mechanism. The key findings include: 1) The adaptation and integration levels of the culture-tourism system along the Long March Route showed a high degree of convergence in the spatial and temporal dimensions. With the dynamic adjustment and collaborative optimization of the culture-tourism system along the Long March Route, the integration level of culture and tourism in the region has shown a significant continuous deepening, which confirms the key driving role of system adaptability in the deep integration of culture and tourism. 2) The obstacles faced by the culture-tourism system in the process of adaptation showed significant differences. The driving factor analysis showed that talent reserve and financial support are the core leading forces to shape the adaptation pattern of the culture-tourism system, and industrial structure optimization and innovation potential mining played an important supporting role, jointly promoting the dynamic adaptation and coordinated development of the culture-tourism system. 3) The development of the integration of culture and tourism driven by the adaptation of the culture-tourism system along the Long March Route is essentially a process of wave-like advance and spiral rise, following the logical mechanism of "external drive-internal response-dynamic adjustment-deepening integration". That is, the external driving factors first break the original balance of the system and trigger the internal response mechanism; through dynamic adjustment paths such as resource integration and factor reorganization, system structure optimization and function upgrading are promoted, and finally the integration of culture and tourism is realized from primary coordination to deep integration.