Examining the population change pattern and its influencing factors is an important foundation for promoting the construction of new-type urbanization with the county as the carrier and promoting the integrated development of urban and rural areas according to local conditions. This paper constructs an analytical framework of "pattern-scale-function-mechanism" of the demographic change of counties in the process of Chinese-style urban-rural modernization, and explores the internal logic of the demographic change of counties and urban-rural development in the process of Chinese-style urban-rural modernization. It comprehensively uses the methods of rank-size, specialization index and gradient boosting decision tree (GBDT) to investigate the population change of counties, and explore the relevant influencing factors and their heterogeneity. It's found that: 1) The proportion of county population to urban population is declining, and the population loss of county is more serious in the north of China than that in the south of China, and is concentrated in the northeast region and the inter-provincial border areas. 2) The population size system of the counties exhibits the relatively flattened feature, the population change of counties in different types of main functional areas is not significant. The population growth is closely related to the distance from the central city in counties which are the urbanization areas and the main producing areas of agricultural products. 3) Economic development is the key factor affecting the population change of counties, its influence degree is constantly increasing, the impact of infrastructure and public services on population change in counties has not changed much and tends to be stable, the impact of policies and locations on population changes in counties is relatively limited, and the fluctuation degree of different factors on the population change of counties has obvious spatial heterogeneity.

Based on the check-in spot data shared by users of Xiaohongshu platform and the POI data of Amap, this study explores the spatial distribution of urban Internet-famous recreational spaces (IRSs) and physical recreational spaces (PRSs) and their differences in main urban area of Changsha by the means of spatial analysis methods, and reveals its formation mechanisms using the grounded theory method according to online texts and interview transcripts. The results indicate that: 1) Overall, IRSs in Changsha's main urban area exhibit the distribution trend of a northeast-southwest orientation, while PRSs exhibit the distribution trend of a northwest-southeast orientation. The clustering intensity and scale distance of IRSs are both weaker than that of PRSs, showing a "polar-core with multiple points" distribution pattern with distinct core-periphery characteristics, while PRSs display a "single-core with multi-centered patchy" distribution. 2) Compared with PRSs, The high-cluster areas of IRSs in Changsha have notably shifted westward, primarily concentrating in high-vitality public recreational areas such as urban waterfronts, suburban mountainous regions, and commercial district. 3) The formation of IRSs' distribution characteristics is the result of the joint action of human-media-place and other factors. The characteristics and charms of urban PRSs provide a physical basis for the formation of IRSs' distribution characteristics. The popularity and influence of social media have strengthened the formation of IRSs' distribution characteristics, the change of the psychology and behavioural patterns of tourists is an important trigger for the formation of IRSs' characteristics. Based on the above, this research proposes specific measures for shaping IRSs from the perspectives of human, media, and place respectively.

Dominance degree of red resources which can reflect the regional red resource endowment and relative advantage is the material basis for the overall protection and utilization of red resources. Taking 1227 red resources belonging to the immovable cultural relics of Hunan Province as the research objects and the counties as the basic units, this article constructs a dominance degree measurement model of red resources from four aspects of richness degree, quality degree, agglomeration degree and accessibility degree, measures the dominance degree of red resources in Hunan Province comprehensively, and analyzes their spatial differentiation pattern. The results show that: 1) The red resources in Hunan Province show the agglomeration distribution pattern taking Sangzhi County as the high-density core area. 2) Richness degree and accessibility degree of red resources in Hunan Province are relatively high, but quality degree and agglomeration degree are relatively low. Furthermore, accessibility degree shows obvious "center-periphery" circular spatial distribution, while richness degree, quality degree and agglomeration degree of red resources mainly show scattered, clumpy, banded or sheet-like distribution. 3) The dominance degree of red resources in Hunan Province is at medium level, the quantitative structure of dominance degree of the county's red resources shows the fusiform characteristic. 4) The spatial pattern of the dominance degree of red resources in Hunan Province generally shows the pattern which is at high level in the eastern, central and southern Hunan, and at lower level in other areas.

Urban economic convergence is a significant criterion for judging the achievement of common prosperity. Based on the panel data of 285 cities in China from 2003 to 2022, this paper tests the convergence of urban economic growth in China using spatial error model (SEM), spatial Markov chain and kernel density estimation. It's found that: 1) There was an unconditional convergence trend in urban economic growth rate. Specifically, the convergence rates accelerated after controlling urban scale, financial situation, economic structure, economic openness, public service level and spatial error term. 2) The variation of urban economic level was gradually decreasing, but this trend mainly came from catching up with those cities outside the province, while the inter-city economic gaps of some provinces expanded during some periods. 3) The convergence of urban economy shows the global characteristic, and the three convergence clubs in eastern, central and western regions not only have convergence trends within themselves, but also have common convergence trends among clubs. 4) Urban economic convergence is dynamic. It divides urban economic development level into five categories in 2003 according to the quartile: lower level, low level, medium level, high level and higher level, which converges to steady states of 5%, 12%, 17%, 41% and 25% respectively after 100 times of Markov transition. The findings indicate that government financial behavior and market factor flow affect urban economic convergence, the complementarity of market mechanism and administrative mechanism helps to promote a higher level of dynamic and global common prosperity in the sense of economic geography.

Based on the data of Baidu search index of ChatGPT from December 2022 to June 2023 this article analyzes the evolution characteristics and influence mechanism of generative artificial intelligence (GenAI for short) attention degree by the ArcGIS, multivariable linear regression model, and spatial econometric model. The results show that: 1） GenAI attention degree showed the inverted-V evolution trend in China during the research period. 2) GenAI attention degree had the characteristics of regional agglomeration, which initially showed the distribution of a giant block shape with the Shandong Peninsula, the Yangtze River Delta and the Pearl River Delta as the cores, later evolved into the distribution of a small block shape. 3) Scientific and technological development, corporate development, advanced industrial structure, education level, degree of opening up, digital infrastructure and government support all had a significant positive effect on GenAI attention degree, and in addition to the digital infrastructure, the other influencing factors have the spatial spillover effect, which is the main reason for the regional aggregation of GenAI attention degree. Based on the research conclusions, this article proposes some suggestions that are increasing the technological investment and policy support for high-tech cities, establishing a high-level talent training system, improving relevant regulations and ethical standards to promote the development of GenAI industry and optimize the layout of high-tech industry.

Based on the digital inclusive finance index and the resilience index of the agricultural industry chain measured by macro and micro data of agricultural research, production, marketing and service, this study theoretically and empirically explores the spatial effect of digital inclusive finance development on the resilience of agricultural industry chain. It's found that: 1) The level of digital inclusive finance and the resilience level of the agricultural industry chain both generally show the rising trend with significant regional disparities, there exists a spatial pattern of "high-high" concentration in eastern region and "low-low" concentration in central and western regions. 2) Digital inclusive finance can expand the coverage of traditional finance, ease the financial constraints of agriculture-related enterprises, promote the upgrading of industrial structure and the extension of the chain, and improve the resilience of the agricultural industry chain. There are spatial spillovers and regional heterogeneity, and have positive effects on its coverage breadth, depth of utilization and digitization degree. 3) Digital inclusive finance can promote the enhancement of agricultural industry chain resilience through promoting agricultural technological innovation. To enhance the resilience of the agricultural industry chain, digital inclusive finance needs to promote the construction of digital infrastructure, innovative financial products and services, and strengthen the construction of agricultural science and technology support systems.

This paper establishes a comprehensive evaluation index system for achieving common prosperity in Zhejiang Province from the aspects of income distribution gaps, disparities in regional urban-rural development, shared public services, material economy, spiritual and humanistic needs, ecological environment, and social harmony. This system investigates the development characteristics and influencing factors of common prosperity of Zhejiang Province at provincial and prefectural levels. The results show that: 1) From 1990 to 2020, the level of common prosperity in Zhejiang Province increased from 42.36% to 76.06%. From 2005 to 2020, the level of common prosperity showed a stable upward trend at prefectural level. 2) From 2005 to 2020, the overall level of common prosperity improved across prefecture-level cities from 2005 to 2020, regional disparities among these cities also widened. 3) Income distribution gaps gradually replaced the material economy as the primary obstacle at the criterion level for common prosperity in Zhejiang Province. The influence of the ecological environment on the development of common prosperity in Zhejiang Province has gradually increased, while the impact of common public services has decreased. The Gini coefficient emerged as the most extensive and profound obstacle factor at the criterion level for common prosperity among prefecture-level cities in Zhejiang Province. To promote the development of common prosperity in Zhejiang Province, it proposes the following strategies: improving the mechanism for public services to ensure high-quality common services, boosting residents' income to broaden the path from the well-off to the less privileged, advancing ecological civilization to firmly establish a path for green development, and encouraging regions to strive for excellence and disseminate exemplary experiences.

Based on the population data of Pingyao County for 7 periods since the Republic of China, this paper analyzes the spatio-temporal evolution characteristics, influencing factors and mechanism of the village-level population in Pingyao County of North China in 1920-2010 from three aspects of spatial distribution, scale structure and population change by the means of GIS spatial analysis, rank-size model, Geodetector, and multi-scale geographically weighted regression. The results indicate that: 1) Driven by urbanization, the population distribution in Pingyao County has gradually evolved from a "dual-core two-wing" pattern to a single-core pattern in 1920-2010. Hotspots of rural population are mainly concentrated in the county seat and its surrounding areas, while coldspots are mainly distributed in hills and low mountain regions. The cold and hot spots of the rural population have gradually decreased, the spatial agglomeration of the rural population has weakened. 2) The hierarchical structure of the population has changed from "pyramid" structure to "olive" structure and then gradually evolves to "inverted pyramid" structure, with fluctuations in population size differentiation. Since 1990, the distribution of population size has tended to be concentrated. 3) The village-level population in Pingyao County has undergone a cyclical evolution from negative growth to medium growth and then to negative growth. While the sequence of population evolution across different topographic regions was similar, the specific evolutionary processes were not synchronized. 4) The distribution of population in Pingyao County is the result of the combined effects of topographic conditions, geographical location, and arable land area, etc. There are differences in the influence mode and direction, the change of influence degree and the spatial difference of the effect are different. With the development of urbanization, the influence of arable land area has shown a weakening trend, while the influence of location factors such as the distances from county, township and road has strengthened. In the process of promoting the integration of urban and rural areas in the county, it is necessary to respect the evolution laws of the county population in a long period of time. The structure and layout of county industries should be adjusting to enhance the radiation capacity of county towns and townships to the countryside. The county road system should be improved and county-town-village linkages should be strengthened in order to slow the decline of rural populations and avoid the hollowing out of rural population.

Promoting coordinated regional development is an important approach to basically achieving modernization with Chinese characteristics. On the basis of summarizing the new trends and referential experiences of regional coordinated development during the "14th Five-Year Plan" period in China, this article puts forward four laws of economic geography that are applicable to the current stage of regional coordinated development in our country. Specifically: 1) National modernization and coordinated regional development are symbiotic, there exists no national modernization with pronounced disparities in inter-regional economic development levels. 2) The structural characteristics of regional geographical functions and the redistribution process of economic gains among regions determine the equilibrium state of living standards and economic development levels between urban and rural areas and among regions. 3) The different from the period of building a moderately prosperous society is that human resources and technological progress have become dominant and decisive factors in the economic development processes of both developed and underdeveloped regions during the modernization period. 4) Regionally differentiated development relying on comparative advantages serves as the cornerstone for enhancing the overall efficacy of national modernization, and increasing the value of ecological products is the key focus of institutional reform for promoting coordinated regional development. Finally, this article also conducts an initial discussion on the adaptive strategies for promoting coordinated regional development during the "15th Five-Year Plan" period.

Based on the measurement index system of the development level of China's active aging industry from 2006 to 2022, this article uses the methods of Dagum Gini coefficient and variance decomposition to decompose the spatial differences in the development level of active aging industry in eight major regions of China, and relies on coefficient of variation method and spatial panel data model to reveal their σ and β convergence characteristics. It's found that: 1) During the sample observation period, the level of development of China's active aging industry continued to rise, but exhibited significant characteristics of structural instability and regional imbalances. 2) The inter-regional difference was the main source of overall regional disparities, and the largest source of structural difference was the differences of the friendly environment dimension. 3) The σ convergence test results show that the development level of active aging industry showed σ convergence characteristics in eight major regions of China. Except for the northeastern region which did not have absolute β convergence or conditional β convergence, and the southern coastal region which did not have conditional β convergence, the differences in the development level of active aging industry showed gradually diminishing trend after considering factors such as economic development level, population age structure, government policy orientation, and scientific and technological innovation, which ultimately converges to the same steady-state level. This article will provide factual basis for a clear understanding of the development pattern of China's active aging industry, and provide policy insights on how to promote the national strategy of actively responding to population aging in a gradient manner and promote balanced development of the aging industry.

Based on the dual-dimensional (physical and virtual) evaluation index system, this study uses the methods of kernel density analysis, bivariate spatial autocorrelation and GeoDetector to analyze the spatial variation and influencing factors of the comprehensive development level of red scenic spots in old revolutionary area of Dabieshan Mountains. The results show that: 1) From the perspective of evaluation results, the top ten typical red scenic spots in the comprehensive score are mostly located in the center of the old revolutionary area of Dabieshan Mountains, and the development of Jinzhai and Xinxian is the most prominent. The Jinzhai County Revolutionary Museum is the highest virtual development level with a score of 0.76, and the forrmer site of Zhongyuan Military Region ranks highest in the physical development level with a score of 0.73. 2) The comprehensive development of red scenic spots displays the spatial pattern of "high-level aggregation in the middle of research area and peripheral low-level dispersion". However, overall development of red scenic spots remains low, with insufficient synergy between physical and virtual dimensions to form a virtuous circle. 3) The overall development of red scenic spots presents the agglomeration effect of "dual-core areas and multiple growth poles". The main core and the main growth pole are formed in Xinxian and its surrounding areas, and the secondary core and the secondary growth pole are formed near Jinzhai. 4) The significant HH points are mainly concentrated in Shihe District, Pingqiao District and Yu 'an District. The spatial dispersion of significant LL points and significant LH points is prominent, and there is no obvious agglomeration effect. The significant HL points are concentrated at the junction of Xinxian and Macheng, Yingshan and Yuexi. 5) The construction of scenic spots and regional development environment are the main driving factors, and the interaction between the proportion of red scenic spots and the total amount of post and telecommunication business has a significant impact on the comprehensive development of red scenic spots.

Clarifying the impact mechanism of spatial qualities on regional price levels and improving the mechanism of spatial qualities leading to talent regional migration will, to some extent, enrich and develop existing theories in New Spatial Economics. This article constructs a analysis framework of New Spatial Economics to explain the formation mechanism of quality premium, that is, spatial qualities drives the total price index up through industrial product premium. Furthermore, it empirically explores whether the quality premium exists and whether it exhibits non-linear effects due to threshold effect. The study finds that: 1) Spatial qualities significantly improves regional price levels, confirming the existence of the quality premium phenomenon. 2) There is a threshold effect of quality premium based on economic development, talent scale, and urbanization, all of which show a trend of gradually increasing quality premium. 3) There are differences in the trend of quality premium in ecological environment, public services, cultural and entertainment amenities, and infrastructure.

This article embeds the input-output table between regions in China into the GTAPV11 database, constructs a global generalized equilibrium model embedded with 31 provinces in China, and simulates the impact of US tariffs on major economies and Chinese regions under the background of Trump 2.0. The research results indicate that: 1)The GDP of the United States has significantly declined, while China has demonstrated strong resilience to external shocks through its domestic circulation and diversified exports. Other economies such as the European Union, Japan, South Korea, and ASEAN have generally benefited from trade transfer effects. 2)The southeastern coastal regions (such as Guangdong and Shanghai) and inland areas with higher levels of vertical specialization have been greatly impacted, while other regions have not been significantly affected; 3) Although the imposition of tariffs by the United States has a protective effect on some key industries in the short term, it will have significant negative effects in the long run; Although China's key industries have been impacted in the short term, they are showing a long-term growth trend with the adjustment of the domestic supply chain. 4) Labor-intensive industries in various provinces have generally declined, but border provinces may benefit against the trend due to lower labor costs; Technology industries are more affected in export-oriented and processing trade provinces, while they show strong resilience in provinces with more complete industrial systems; The supply chain integration industry represented by the transportation equipment manufacturing industry has shown good shock resistance.

A resilient urban economic system under the complex economic situation has become an inevitable requirement for social and economic development, and the vigorous vitality of digital economy provides impetus for the enhancement of urban economic resilience. This study analyzes the spatio-temporal evolution process and characteristics of digital economy and urban economic resilience in China, tests the impact of digital economy on urban economic resilience, and further analyzes the time series evolution and structural of its impact. The results show that: 1) The level of urban economic resilience shows a multi-point scattered distribution, and there is a significant spatial differentiation between the north and the south. 2) The digital economy can significantly enhance the resilience of urban economy. 3) The structure analysist shows that digital innovation elements, digital industrialization and industrial digitalization have a great impact on urban economic resilience. The time series analysis shows that the enhancement effect of the improvement of the development level of digital economy on the resilience of urban economy is increasing year by year, among which the impact of digital industrialization, industrial digitalization and digital innovation factors on the resilience of urban economy also has an increasing time series analysis. According to the research conclusions, this paper puts forward relevant development suggestions.

Adequate mobility of labor resources is an important part of smooth domestic circulation. This article explores the impact and transmission mechanism of the digital economy on labor mobility by using conditional Logit model with the data of China Migrants Dynamic Survey in 2011-2018. It's found that: 1) The digital economy significantly promotes labor mobility, and the conclusion still holds after a series of robustness tests and endogeneity treatments such as replacing the independent variables. 2) From the perspective of cities, the development of the digital economy mainly significantly promotes labor mobility in areas located in the west of the Hu Huanyong Line and large cities. From the perspective of individual, the digital economy promotes labor mobility more strongly for males and labor force with low-skill level. 3) The digital economy promotes labor mobility mainly through the channels of reducing individual search costs, regional transaction costs, increasing employment opportunities and reducing inter-regional barriers. The research conclusions provide new arguments for the optimal allocation of labor resources in the process of digital economy development, which is an important inspiration for the optimal allocation of resources in the construction of a unified national market.

Global Production Networks (GPNs) and regional development are the hotspots and frontiers of international economic geography. However, it should pay more attention on the local enterprise networks dominated by strategic partners of leading firms (SPLFs) in GPNs. Based on the typical case of Foxconn in Zhengzhou, this paper explains the influence of strategic partners of leading firms on regional industry development by building an analytical framework including power relationships, institutional arrangement and industrial development. The findings can be summarized as follows: 1) After Foxconn landed in Zhengzhou, its power relationship attracted some of its original suppliers to move to Zhengzhou. The local government relies on shaping the industrial development ecology and the preferential policies towards Foxconn which aim to develop the local electronic information industry to attract a large number of non-Apple mobile phone companies to gather in Zhengzhou. 2) The intelligent terminal (mobile phone) industry in Zhengzhou Airport Economy Zone (ZAEZ) has formed a triple enterprise network, which is Foxconn system enterprise network, Foxconn crossover enterprise network, and non-Apple mobile enterprise network guided by local government. 3) The formation of the largest production base of Apple mobile phones and the global intelligent terminal (mobile phone) manufacturing base has accelerated the adjustment of the industrial structure in the undertaking areas. 4) The power relationship of SPLFs in GPNs and the institutional arrangements of local governments played an important role in the agglomeration of intelligent terminal (mobile phone) companies and the formation of enterprise networks. This study characterizes the local enterprise networks of SPLFs in GPNs in latecomer regions and expands the research on power relationships of GPNs.

Cultural innovation fosters the unique cultural tourism resources, products and services, stimulates the demand for upgraded tourism consumption, enhances the added value of tourism and strengthens the competitiveness of destinations. This paper employs the entropy method to measure the levels of tourism high-quality development and cultural innovation in 30 provincial-level regions in China from 2013 to 2022, analyzes the driving mechanism of cultural innovation on the tourism high-quality development by the means of the methods of fixed effect model and mediation effect test. It explores the spatial effect of cultural innovation on tourism high-quality development with the help of spatial Durbin model. The results show that: 1) The effect of cultural innovation significantly enhances the level of high-quality development of regional tourism. 2) Industrial digitization and industrial structure optimization play positive mediating roles in tourism high-quality development. 3) Cultural innovation has a significant negative spatial spillover effect on the high-quality development of tourism, that is, the advancements of cultural innovation in neighboring provincial-level regions will inhibit the high-quality development of tourism in local provincial-level regions. 4) The impact of cultural innovation on the tourism high-quality development varies significantly due to differences in economic scale, geographical advantages and cultural resource endowments. Notably, the effect of cultural innovation is not significant in western China, while the indirect effect of cultural innovation effect is stronger in coastal regions.

This study reveals the correlation characteristics and interactive mechanism between the rural tourism resource endowment and transportation patterns in karst mountainous regions, with Guizhou Province as the case study using the methods of spatial analysis and accessibility analysis. The results indicate that: 1) Rural tourism resources in Guizhou exhibit an overall cohesive and even distribution pattern, showing the characteristics of being concentrated in the south of Guizhou and scattered in the north of Guizhou, dense in the east of Guizhou and sparse in the west of Guizhou. The highway network demonstrates regional scale effects around the hinterland of central Guizhou and the ethnic group settlements in southeastern Guizhou. 2) The advantage of rural tourism resources presents a dual-peak and triple-valley pattern and concentrates in Qiandongnan Miao and Dong Autonomous Prefecture, the advantage of transportation presents a triple-peak and triple-valley pattern and mainly distributes in Guiyang City, Zunyi City, and Tongren City. The coupling coordination degree between rural tourism resources and transportation network in Qiandongnan Miao and Dong Autonomous Prefecture is the best. 3) The spatial imbalance between rural tourism resources and transportation network is influenced by the cultural history and social environment, showing a trend of shifting towards the southeast. The coordinated development of rural tourism economy in Guizhou is greatly influenced by regional social development, among which road network density and regional GDP are important factors affecting the collaborative process. In the future, it should deeply consider the integrated development strategy of transportation and tourism industries in karst mountainous regions, and empower the road-derived tourism vitality.

As an emerging marketing channel, live-streaming e-commerce plays a vital role in promoting the sales and distribution of agricultural products. This paper selects Douyin, a representative live-streaming e-commerce platform, as a case study. Leveraging machine learning and data mining technologies, we collected 43,000 pieces of live-streaming e-commerce data and 867 observational samples. Using structural equation modeling (SEM), we comprehensively analyzed the influence mechanism of live-streaming e-commerce on agricultural product sales performance, considering multiple factors including anchor personal characteristics, anchor activity levels, livestream popularity, and livestore characteristics.The results indicate that: 1) Anchor personal characteristics, activity levels, and livestream popularity significantly enhance agricultural product sales performance. 2) Follower count exerts a significant positive effect on sales, and the aforementioned anchor and livestream characteristics further boost sales through the mediating effect of follower count. 3) The impact exhibits heterogeneity across different follower tiers. The influence of anchor personal characteristics grows stronger with larger follower bases. Furthermore, the effects of anchor activity, livestream popularity, and follower count may reverse (i.e., become negative) due to factors such as audience maturity, sensitivity to waiting times (e.g., delivery), and variations in consumption preferences.Finally, this paper proposes policy recommendations for the government, platforms, and anchors to optimize the live-streaming e-commerce model, boost agricultural product sales, and increase farmer income. These findings provide micro-level decision-making insights for comprehensively promoting rural revitalization.

Developing new quality productive forces is an inherent requirement and an important focus for promoting high-quality development. This paper constructs an evaluation index system from three dimensions: technological innovation capability, industrial transformation and upgrading, and innovative allocation of production factors to measure the level of new quality productive forces in 30 provinces in China from 2011 to 2022. The Moran's I, kernel density estimation, Markov chain transition matrix, Dagum Gini coefficient, and convergence model are used to reveal the spatiotemporal evolution pattern, regional differences, and convergence characteristics of new quality productivity development. Furthermore, the obstacle degree model and geographic detector model are used to explore the influencing factors of new quality productivity development. The findings reveal that: 1) During the research period, the level of new quality productivity in China steadily increased over time, with a clear decreasing distribution pattern of "high in the east and low in the west". 2) The development level exhibits a positive spatial correlation, with high-level neighboring regions positively impacting their adjacent areas. 3) From the perspective of regional differences, there are large regional disparities in the development level of China's new quality productivity, with the contribution of inter-regional differences taking the first place, followed by intra-regional differences, and that there are significant absolute β-convergence and conditional β-convergence characteristics in the whole country as well as the three major regions of the eastern, central, and western regions. 4) From the perspective of influencing factors, scientific and technological innovation capacity is the core factor in cultivating and developing new quality productivity, openness, informatization, labor force level, and transportation infrastructure are the main driving factors that lead to the spatial differentiation characteristics of new quality productivity across the country as well as in the eastern, middle, and western regions.

Green innovation is an important pathway to achieve a win-win scenario between environmental protection and economic growth in the Yangtze River Economic Belt (YREB). Based on the green patent data of 108 cities at or above the prefecture level in the YREB from 2010 to 2022, this paper comprehensively employs the methods of spatial autocorrelation model, kernel density estimation and Markov chain to systematically examine the spatial heterogeneity evolution and convergence characteristics of green innovation in the YREB. The results show that: 1) The spatial distribution of green innovation presents a significant agglomeration characteristic in the YREB, with the downstream region forming an innovation hub, while the interregional correlation effects are prominent. 2) The dynamic evolution trend indicate that the overall level continues to improve and there is a path-dependent feature, and the innovation evolution of neighboring cities presents a synergistic effect. 3) Regional disparities display convergence trends, with the upstream region converging the fastest, while the convergence intensity gradually weakens from the upstream to the downstream. Therefore, this paper proposes that it should implement regional differentiation policies and strengthen cross-domain collaborative innovation to promote the balanced development of green innovation in the YREB.

This article intends to systematically interpret the connotation characteristics of digitalization in the tourism industry, and use CiteSpace bibliometric analysis tool to conduct a horizontal comparative analysis of the author co-occurrence, research hotspots, topic clustering, and cutting-edge trends in tourism digitalization research both domestically and internationally. The results indicate that: 1) The digitalization of the tourism industry refers to the phenomenon and process of realizing the digital transformation of all elements, links, and chains of the tourism industry, with digital infrastructure as the prerequisite, digital economic environment as the key support, digital investment in tourism as the core content, and digital benefits of tourism as the ultimate manifestation based on the digital infrastructure. 2) Since 2000, the research results on digitalization of the tourism industry at home and abroad have steadily increased, and the gap between the number of domestic publications and that of foreign countries in the same period has gradually narrowed. However, the number of highly recognizable authors is relatively small, and the degree of communication and cooperation among research institutions is low. 3) From the results of keyword network co-occurrence, domestic research mainly involves high-frequency words such as tourism digitalization, smart tourism, tourism informatization, online tourism, tourism big data, etc. Foreign research focuses more on tourism activities, smart tourism, virtual reality technology, non-contact tourism, smart tourism destinations, COVID-19 epidemic and other hot spots. 4) Domestic research mainly focuses on three fields: the integration and innovation of digital tourism, the application of digital technology, and strategic policy guidance. Foreign research focuses on three directions: the construction of digital cultural tourism scenes, the intelligent utilization of tourism resources, and the application of digital technology in tourism. However, there is a lack of synchronization and consistency in the timing of keyword emergence and content. Based on the above, the article discusses and looks forward to strengthening academic cooperation at home and abroad, refining the research field of digital tourism enterprises, strengthening the research on digital transformation of the tourism industry, and forward-looking research on digital governance of the entire tourism industry.

Based on the theory of geological information Tupu, this study defines the spatial units of tourism resources from a multi-scale perspective and constructs four types of spatial information Tupu for tourism resources at different scales: spatial scale, spatial correlation, spatial combination, and spatial structure. Taking Hainan Island as a case study for empirical analysis, it reveals the spatial variation patterns of multi-scale tourism destinations. It's found that: 1) The characteristic scales of all tourism resources and cultural tourism resources in Hainan Island are consistent, whereas natural tourism resources exhibit significant differences in characteristic scales. At the full-scale level, the characteristic scale for cultural tourism resources is 600 meters, whereas that of natural tourism resources is 14 kilometers. Additionally, the optimal scale for cities and counties is less than 2 kilometers. 2) Tourism resources exhibit distinct spatial correlation characteristics under various terrain conditions. It demonstrates stronger correlation in the eastern region of Hainan Island within a 5-kilometer range, while in the western region of Hainan Island, a stronger correlation is observed within a 12-kilometer range. 3) Based on characteristic scale, The combination of natural tourism resources with other type of tourism resources is relatively concentrated in the southern region, whereas the combination of cultural tourism resources with other type of tourism resources are sparsely distributed, mainly in the northern and eastern regions. The combination of natural tourism resources and cultural tourism resources is primarily concentrated in the southeastern, northern, and central regions. 4) As the spatial structure scale of tourism resources changes, the tourism spatial development in the future will also undergo corresponding transformations. The connectivity lines of the tourism resource complex within Hainan Island form a grid distribution pattern. The areas with the highest accessibility include the first-level hotspot area in Haikou, the second-level hotspot area in central Sanya, and the third-level hotspot area in Baisha. Future tourism spatial planning should emphasize the construction of east-west tourism routes. Moreover, based on transportation accessibility, tourism products of varying types should be designed to connect different categories of scenic spots.

In recent years, the demand-side perspective has been increasingly introduced into the study of evolutionary economic geography, which has gradually formed a wave of "demand turn". The purpose of this paper is to summarize the theoretical foundations and empirical progress of evolutionary economic geography research from the demand-side perspective, and to present the prospects of future research topics in light of the limitations of the research and the requirements of China's current economic construction. Demand-side evolutionary economic geography research focuses on four main research topics: the evolution of the market, the impact of demand on the path of regional industrial evolution, regional economic resilience, and the evolution of industrial clusters, but it neglects the evolutionary patterns of markets other than export markets, the driving force of demand on the complexity of the regional economy, demand-side proximity and relatedness, and demand-side research on a macro-national scale. Facing the limitations of the research and the requirements of China's economic construction, future research should emphasize exploring the role of demand in shaping economic complexity, the formation mechanism of market segmentation based on the evolutionary perspective, and the role of domestic demand in resisting external demand shocks.

This study quantitatively evaluates the coordination level between pollution reduction and carbon reduction in 30 provincial-level regions in China from 2006 to 2020. It analyzes the spatiotemporal evolution trend of this coordination level using the Dagum Gini coefficient and spatial Markov chain. Additionally, it empirically tests the impact of green technology innovation on the coordination level between pollution reduction and carbon reduction. The research findings are as follows: 1) The overall trend of the coordination level between pollution reduction and carbon reduction in China is increasing, exhibiting a "club convergence" phenomenon. The spatial difference of the coordination level between pollution reduction and carbon reduction shows a downward trend in China and three major regions. 2) Green technology innovation plays a significant role in enhancing the coordination level between pollution reduction and carbon reduction, while environmental regulation and government financial support significantly enhance its promoting role. 3) Energy consumption intensity reveals the mechanism of green technology innovation affecting the coordination level between pollution reduction and carbon reduction, environmental regulation and government financial support play negative and positive regulatory roles on this impact mechanism, respectively. 4) Heterogeneity analysis reveals that green technology innovation has a significant promoting role in the coordination level between pollution-carbon reduction for central and western regions, but not for eastern region.

Countries promote trade liberalization of environmental goods (EGs) based on environmental goals while implementing trade protection measures driven by economic objectives. These dual forces collectively shape the trade environment for China's EGs. Based on the China Customs data from 2009 to 2023, this paper examines the export patterns of China's EGs to destination countries, employs a panel data model to analyze the effects of trade liberalization and trade protection, and conducts heterogeneity analyses from the aspects of the provincial level, product, and destination country. The results indicate that: 1) From 2009-2023, the export scale of China's EGs initially increased but subsequently declined, with a noticeable downward trend emerging from 2021. Developed countries accounted for 63.7% of China's total EGs export, while developing countries represented 58.1% of incremental export growth. 2) Trade liberalization positively impacts the export of EGs, whereas trade protection exerts a inhibitory effect on the export of EGs. 3) Provinces with stronger innovation capabilities demonstrate higher export competitiveness and can effectively mitigate the negative impacts of trade protection. 4) Trade liberalization promotes the EGs export with lower export technological sophistication, whereas trade protection shows no differential impact across EGs. 5) Trade liberalization does not significantly increase exports to developed countries, while trade protection negatively affects exports to all types of destination countries. 6) Lower carbon emission intensity and larger market size in destination countries amplify the positive effects of trade liberalization. The findings suggest that continuously promoting technological innovation and advocating trade liberalization policies are essential strategies for China to sustain its global competitive advantage in EGs.

Considering that rural e-commerce has become an important channel for linking smallholder farmers to large markets, and that many major production areas of geographical indications (GIs) are encouraging farmers to participate in rural e-commerce, it is necessary to investigate the online premium of GIs and its underlying mechanisms. Based on actual transaction data of rice products from JD.com, this paper utilizes the hedonic price model to estimate the online price premium of GIs more accurately and examines the indirect mechanism of GIs generating online price premiums from the perspectives of online reputation and traceability. The results of the study show that: 1) GIs are able to generate online price premiums, but online price premiums decrease as the price range increases. 2) GIs help accumulate a good online reputation and promote the use of product traceability codes, which in turn generates online price premiums. 3) The online price premium of GIs varies across regions, with GI rice from western areas or non-major grain-producing regions able to generate a higher online price premium. 4) Functional labels such as selenium-enriched, low-protein, and germ weaken the online price premium of GIs, while there is no evidence that organic certification substitutes for GIs.

This paper selects 88 counties in Guizhou Province as the research object and constructs a county tourism competitiveness evaluation index system covering four dimensions: development, resources, elements, and management. It measures the tourism competitiveness scores of each county using the entropy weight-TOPSIS method and systematically analyzes the spatiotemporal evolution characteristics of these scores. Based on the obstacle degree model, the main obstacle factors constraining the enhancement of county tourism competitiveness in Guizhou Province are further identified and analyzed. The results indicate that: 1) From 2014 to 2023, the overall competitiveness of county-level tourism in Guizhou Province has steadily improved, accompanied by a notable spatial agglomeration effect. However, the development gap between regions has widened, exhibiting a structural differentiation pattern characterized by "the strong becoming stronger and the weak becoming weaker". 2) The spatial distribution of tourism competitiveness across counties in Guizhou is markedly uneven. Counties with high competitiveness are mainly concentrated in economically developed and well-connected areas such as Guiyang, Zunyi, and Liupanshui, while remote mountainous and ethnic minority regions exhibit relatively weak competitiveness. 3) The core obstacles limiting the improvement of county tourism competitiveness include poor ecological environment quality, weak economic foundations, and inadequate transportation accessibility. 4) The main categories of barriers faced by counties include development-related, resource-related, factor-related, and management-related obstacles. Due to disparities in resource endowments and stages of development across counties, there is significant heterogeneity in both the types of obstacles encountered and their degrees of influence.

The optimization of spatial pattern in consumption competitiveness holds significant importance for unleashing consumption potential and promoting the integrated development of urban agglomeration consumption. This paper delves into consumption competitiveness from the aspects of actual competitiveness and potential competitiveness, evaluates the consumption competitiveness of 242 cities at prefecture level or above in China. It utilizes Moran's I and the gravity model to primarily dissects the spatial patterns of consumption competitiveness in five seminal urban agglomerations. Furthermore, it analyzes the driving factors of consumption competitiveness by the means of the Geodetector. The results show that: 1) Consumption competitiveness is on the rise, exhibiting a geographical pattern characterized by higher levels in the east and lower levels in the west, with a trend of expansion from coastal to inland areas and diffusion from highly competitive cities to their surrounding regions. 2) While the interconnectedness of consumption competitiveness among the five urban agglomerations is gradually intensifying, the correlations within each agglomeration exhibit distinct characteristics. 3) Consumption competitiveness demonstrates spatial clustering and positive spatial correlation. Specifically, urban agglomerations such as Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta exert a positive spillover effect, whereas provincial capitals in the central and western regions exhibit a siphon effect. 4) The levels of financial development, government support, and digital industry progression are primary factors influencing the spatial disparities in consumption competitiveness, and the interaction between different factors shows an enhanced relationship.

Based on the data of Douyin, this paper reveals the spatial distribution pattern and structural characteristics of the network attention degree of scenic-spot villages in Zhejiang Province and explores its influencing factors by the means of. The methods of rank-size, kernel density, nearest neighbor index and GeoDetector. The research findings are as follows: 1) The scenic-spot villages with higher network attention degree have obvious advantages, while the scenic-spot villages with high and low network attention degrees have poorly development. 2) The kernel density distribution of the network attention degree of scenic-spot villages presents a T-shaped spatial agglomeration structure which have five core agglomeration areas. 3) The kernel density distribution of the network attention degree of three types of scenic-spot villages presents a spatial pattern which is one area with low-level kernel density, two areas with high-level kernel density, and distinct differentiation. 4) The regional economic level and service industry support are important factors affecting the spatial distribution of the network attention degree of scenic-spot villages. Vegetation coverage rate, the living standards of rural residents, and the network penetration level also affect the spatial distribution of the network attention degree of scenic-spot villages. Moreover, the results of the interaction detection of influencing factors show that the effect of multiple factors is stronger than that of a single factor. 5) The influencing degrees of the driving factors for three types of scenic-spot villages are different. The network penetration level is the most influential factor for the spatial distribution of the network attention degree of scenic-spot villages which belong to the type of characteristic leisure. The regional economic level is the most influential factor for the spatial distribution of the network attention degree of scenic-spot villages which belong to the types of folk-custom and culture, and nature-ecology. However, vegetation coverage rate and air quality are the factors with relatively large influence on the spatial distribution of the network attention degree of scenic-spot villages which belong to the type of nature-ecology.

The concept of human capital provides an important research perspective for understanding the relationship between industry and people. The spatial coordinated evolution between human capital and industrial structure is of great significance in optimizing resource allocation and stimulating regional development potential. The Beijing-Tianjin-Hebei region is in the crucial period of industrial structure upgrading and innovation-driven development. This study demonstrates the spatial pattern evolution of the human capital level and industrial structure upgrading level at the county level, and explores their spatial coupling and synergy. The results show that: 1) The levels of human capital and industrial structure upgrading in the Beijing-Tianjin-Hebei region have been increasing rapidly in 2000-2020, resulting in the average degree of coupling coordination between them in this region transmitted from low-level coordinating stage to medium-level coordinating stage. 17% of counties reached the high-level coordinating stage, mainly distributed in municipal districts around large cities such as Beijing and Tianjin. 2) The spatial pattern of the degree of coupling coordination presents the core-periphery structure, which means that human capital and industrial structure upgrading have a spatially interacted impact. This relationship can be hampered by the administrative boundary and has been enhanced in the north of Beijing-Tianjin-Hebei region while reduced in the south of Beijing-Tianjin-Hebei region. 3) Although the level of educational human capital has been increasing rapidly, the spatial polarization is still within the region, indicating the spatial mismatch between education and industry is the main challenge to achieving regional synergistic development. The results provide suggestions and references for allocating regional human capital rationally and promoting the high-quality development of the Beijing-Tianjin-Hebei region.

In the context of a media-driven society, the generation and evolution of media image of landmark landscapes have emerged as a pivotal manifestation of the reconstruction of human-land relationship, as well as a spatial practice that embodies the interplay between regional culture and technological advancements. Grounded in the theoretical framework of media geography, this paper selects five typical landmark landscapes in Hunan Province as case studies, and systematically explores the characteristics, processes, and mechanisms of the generation of the media image of typical landmark landscapes in Hunan comprehensively by the means of the methods of text analysis and keyword co-occurrence. It's found that: 1) The generation of media image of typical landmark landscapes in Hunan is endogenously driven by Huxiang culture, which gives the landscapes a significant degree of recognizability and a foundation for cultural identity. 2) Media technology as an external driving force to promote the upgrading transformation of landmarks from "physical entities" to "digital-cultural complexes". 3) The transformation of media image of Hunan landmarks is fundamentally the outcome of the synergistic effects of cultural embeddedness, technological integration and public participation. The place sense of media can be regarded as an interconnected process involving these three elements. Therefore, scientifically grasping the dynamic logic behind the evolution of media image can provide valuable insights for the management of landmark landscapes, the revitalization of cultural heritage and the integration of cultural and tourism practice in Hunan Province. This, in turn, can bolster the region's cultural competitiveness and support tourism sustainability development.

A precise comprehension of urban residents' preference degree for scenic spots and their intergenerational differences is a foundational premise for enhancing the precision service of the tourism industry. Taking Beijing, Xi'an, Chengdu, Shanghai, Wuhan, and Changchun as case cities, this paper constructs the index of preference degree for scenic spots and quantitatively analyzes the intergenerational differences of 6 generations of urban residents' preference on the basis of the 516 visiting rate data of 136 high-level scenic spots. The research yields the following insights: 1) Urban residents' preferences for scenic spots and their intergenerational differences adhere to the Pareto's Principle, 20% of scenic spots with high preference degree, 80% of scenic spots with medium and low preference degree, 20% of scenic spots do not have intergenerational difference in preference degree, 80% of scenic spots have intergenerational difference in preference degree. 2) Urban residents' preferences for scenic spots exhibit an intergenerational transmission effects, characterized by a "three generations in one group" pattern with the 70s as the boundary. 3) Urban residents' preference degree for scenic spots is primarily associated with the scenic spot popularity, with minimal correlation to O-D distance, scenic spot nature and grade. 4) Older generational groups demonstrate higher visitation rates and larger travel spaces, although urban residents born after the year 2000 exhibit unique behavioral patterns.

Based on the collection data of Douyin users on tourist attractions of eastern China, this paper uses multi-distance spatial cluster analysis to analyze the spatial pattern of network attention of tourist attractions of eastern China with high attention of Douyin, uses spatial autocorrelation analysis to analyze its spatial differentiation pattern, and uses geographic detectors to explore its possible influencing factors. The research shows that: 1) The tourist attractions of eastern China with high network attention degree in Douyin are mostly distributed in coastal cities, and there are also significant differences in the number of tourist attractions with high network attention degree in Douyin among coastal cities. At the prefecture level, the network attention degree of tourist attractions of eastern China in Douyin shows an unbalanced distribution pattern, which is higher in the middle of eastern China and lower in both sides of eastern China. 2) Tourist attractions of eastern China with high-level network attention degree in Douyin show the agglomeration distribution pattern. 3) The network attention degree of tourist attractions of eastern China in Douyin shows a positive spatial correlation, and the degree of spatial agglomeration is relatively high. The spatial correlation pattern of network attention degree of tourist attractions of eastern China in Douyin basically corresponds to the differentiation pattern at the prefecture level. The high-value areas are mainly distributed in the central part of eastern China, while the medium and low-value areas are inlaid in the rest areas of eastern China. 4) The interactions of total passenger transport, the number of A-level scenic spots, permanent resident population and the number of mobile phone users at the end of the year have significant impact on the network attention degree of of tourist attractions in Douyin.

This paper constructs a comprehensive evaluation index system of platform economy from three dimensions:infrastructure, participating entities, and operating results, measures its development level in 31 provincial-level regions of China from 2013 to 2021. It uses the methods of modified gravity model and social network analysis to explore the spatial correlation characteristics and evolution process of platform economy development, and uses QAP regression model to verify its formation mechanism. It's found that:1) The spatial correlation of platform economy development in China is manifested as a typical network layer structure with multiple threads and a center-periphery structure. The spatial correlation of platform economy development has weakened, and the overall network structure still needs further optimization. 2) 10 provincial-level regions play the role of "engines" in the network, 7 provincial-level regions play the roles of "intermediaries" and "bridges" in the network, 10 provincial-level regions play the role of "central actors" in the network. 3) There is a significant spatial spillover effect among the net beneficiary sector, broker sector, bidirectional spillover sector, and net spillover sector, but there exist problems of reverse spillover and non-equilibrium. 4) The formation of spatial correlation in platform economy is influenced by multiple factors, the differences in economic development level, market competition level, technological innovation level, and social consumption level have significant positive impact on it, while differences in geographical distance, industrial structure, and platform infrastructure level have negative impact on it.

Forest wellness plays an important role in promoting public health. This paper takes ecological wellness suitability, landscape wellness suitability, dietary wellness suitability and cultural wellness suitability as the first-level criteria, and selects 18 indicators to construct the evaluation system of forest wellness suitability. Based on the above, it evaluates and zones the suitability of forest wellness in Hubei Province, and puts forward ideas and suggestions of product development in each region. It's found that: 1) The forest wellness suitability level is low in the plain areas of Hubei Province and high in the mountainous areas of Hubei Province. Overall, it presents the circular spatial differentiation pattern which is low in the middle of Hubei Province and high around the periphery of Hubei Province. 2) According to the suitability level and composition, the development of forest wellness industry in Hubei Province can be divided into four first-level regions (priority development zone, key development zone, local development zone and precise development zone) and eight second-level regions. 3) The development of forest wellness products in Hubei Province should be tailor to the person, the place, and the time, and implement a multi-level development strategy of diversification, specialization, synergy and empowerment.

This article uses social network analysis to analyze the structural characteristics and influencing factors of the global trade network of mobile games. The research shows that: 1) From an overall perspective, the global trade volume of mobile games has been increasing year by year, with a high degree of trade connectivity. 2) From a clustering perspective, China and the United States have been the core subgroup leading countries (regions), high-income and upper-middle-income countries (regions) are the main participants in mobile game trade. 3) From the perspective of import and export, the global trade network of mobile games has formed a structure with China and the United States as the main centers, South Korea and Japan as the secondary centers, and several high-income countries (regions) and a few middle-income countries (regions) in parallel. From the point of view of the control center, the countries (regions) that become the center are mostly due to geographic and tax advantages. 4) The differences of economic development have a significant positive effect on the establishment of trade relations and trade intensity in mobile games, technological differences and geographical distance have a significant negative effect on them. Membership or non-membership of the World Trade Organization does not have a significant positive effect on the establishment of trade relations, but it has a significant positive effect on the intensity of trade. The results of cultural proximity and institutional distance are not in line with the existing research conclusions, but in line with the actual situation of mobile games. 5) Further research shows that high-income countries (regions) have the high level of Internet development and strong internal supply capacity.

Based on the spatial interaction theories such as proximity diffusion and rank diffusion, this study takes spatial distance and scale differences to reflect the intercity relationships, and uses the methods of zero-inflated negative binomial regression, complementary cumulative distribution function and marginal effect analysis to systematically compare the transfer and diffusion characteristics of labor-intensive, capital-intensive and technology-intensive manufacturing industries in Beijing-Tianjin-Hebei region from 2000 to 2019, clarify disparities in spatial diffusion likelihood and intensity among these industries and analyze the differential effects of spatial distance and hierarchical distance. It's found that: 1)The high-intensity manufacturing investment links of Beijing-Tianjin-Hebei region are mainly concentrated among the cities of Beijing, Tianjin and Shijiazhuang. The growth of the population size of the investment source cities facilitates the transfer and diffusion of manufacturing industries in the Beijing-Tianjin-Hebei region, while the population size of the investment target cities exhibits a more complex influence on the diffusion of manufacturing industries. 2) Both spatial distance and hierarchical distance limit the spatial diffusion of three types of manufacturing industries in Beijing-Tianjin-Hebei region. Spatial distance always affects the diffusion possibility, and hierarchical distance always affects the diffusion intensity. 3) Unlike the broad influence of spatial distance, hierarchical distance exerts significant effects only within a specific threshold range. The threshold range for labor-intensive manufacturing is between 0.6 and 4.4, while for both capital-intensive and technology-intensive manufacturing, it is between 0.2 and 2.5.

This study measures the level of enterprises' algorithmic collusion at the provincial level using Baidu Index, and analyzes its spatial distribution characteristics and influencing factors in 31 provincial-level regions of China from 2018 to 2023 on the basis of a two-way fixed effects model and a spatial Durbin model. The research findings are as follows: 1) The level of enterprises' algorithmic collusion is relatively high in the eastern coastal and central regions, where collusion phenomena are more pronounced and concentrated, showing a gradient decline from the coastal region to the western and northeastern regions. 2) The overall spatial correlation pattern of enterprises' algorithmic collusion level in China is relatively stable. Locally, it shows the polarized characteristics of "high-high" and "low-low" agglomerations. The "high-high" agglomeration areas are mainly distributed in the central and eastern regions, while the "low-low" agglomeration areas are concentrated in the western region. 3) Internet infrastructure and human capital have a significant positive impact on the level of enterprises' algorithmic collusion. Spatial analysis confirms the influences of Internet infrastructure and human capital retain significant positive impact on the level of enterprises' algorithmic collusion within regions, though inter-regional spillover effects are not significant. Therefore, it is necessary to strengthen supervision and prevention in the eastern coastal regions, promote regional coordinated development, enhance the construction of network infrastructure, and improve human capital level to reduce the occurrence of enterprises' algorithmic collusion behaviors.

The high-quality development of tourism resorts is of great significance to build the world-class tourist destinations and meet the people's needs for a better life in China. Based on the methods of secondary data collection, semi-structured interviews and textual analysis, this paper explores the driving forces and models of domestic tourism resort development. It's found that: 1) Market, capital and government are three key dimensions of the development patterns of tourism resorts. 2) Domestic tourism resorts have experienced three phases of development since 1990s: policy incentive and market cultivation, institutional construction and rapid expansion, and high-quality development and innovation. 3) The interaction of market, capital and government prompts the formation of the unique development path of Chinese tourism resorts, and further facilitates three development types: demand-led type, investment-led type and policy-led type. This paper deepens the understanding of the evolution of tourism resorts in China, which contributes to the high-quality development of domestic resorts. It puts forward the driving mechanism of tourism resort development in non-Western contexts.