This paper uses the Super-SBM-DEA model to measure the green innovation efficiency of 54 prefecture-level cities (autonomous prefectures) in the Yellow River Basin from 2007 to 2021, uses the modified gravity model and social network analysis method to explore the spatial network characteristics of green innovation efficiency, and uses panel regression to analyze the economic growth effects of the spatial network of green innovation efficiency. The results show that: 1) The green innovation efficiency and its network structure in the Yellow River Basin are constantly optimized. From 2007 to 2021, the green innovation efficiency increased from 0.51 to 0.69, with increasingly dense network connections, stable network structures, and better network connectivity; 2) The green innovation efficiency and its network structure in the lower reaches of the Yellow River Basin are better than those in the upper and middle reaches. From 2007 to 2021, the average annual growth rate of green innovation efficiency in the lower reaches was 6.14%, which was 2.28 and 4.33 percentage points higher than that in the upper and middle reaches, respectively; 3) Core cities such as Lanzhou, Xi'an, Taiyuan, Zhengzhou, and Jinan have better promoting effects on network structure optimization and regional economic growth than peripheral cities;4) The green innovation network structure of the Yellow River Basin has a positive impact on economic growth, with significant spatial spillover effects.
Inclusive green development aims to achieve coordinated development of the economy, society and natural systems, which is an important underpinning for achieving Chinese modernization. It provides an important basis for promoting high-quality development by exploring the spatial imbalance and formation mechanism of inclusive green development in the Yangtze River Economic Belt, and can provide a model for other regions. This paper defines the concept of inclusive green development based on the composite ecosystem of economy-society-nature, and constructs an evaluation system to measure the inclusive green development of 108 cities in the Yangtze River Economic Belt from 2003 to 2019. Then we describe the characteristics of spatial imbalance and dynamic evolution, and analyze the formation mechanism of spatial disequilibrium by using the geographic detector. The study shows that: 1) the inclusive green development is steadily improving in the Yangtze River Economic Belt from 2003 to 2019, and its spatial distribution shows a ladder pattern of downstream>midstream>upstream. 2) The spatial imbalance of inclusive green development increased first and then decreased in the Yangtze River Economic Belt, with the inflection point occurring in 2008. The intra-regional differences were the main source and inter-regional differences are relatively small. 3) The dynamic evolution of the spatial unbalanced of inclusive green development in the Yangtze River Economic Belt shows that the absolute differences increase in the whole region and each region. But the trend of polarization gradually disappears. 4) The social inclusion dimension factors are the main cause of the disequilibrium of inclusive green development space in the Yangtze River Economic Belt as a whole and in various regions. The environmental inclusion dimension factors also gradually play an important role, and the interaction of factors has a stronger effect on the disequilibrium of inclusive green development space in the Yangtze River Economic Belt than the single factor.
Understanding the economic impact of transportation hubs by analyzing passenger travel characteristics is crucial for promoting effective interaction between hubs and urban economies. This study addresses the challenges of current methodologies, particularly the difficulties in data acquisition and the limited exploration of the intricate relationships between passenger travel variations and the economic contributions of hubs. To overcome these challenges, Latent Class Analysis (LCA) is employed to profile passenger travel characteristics, which informs the development of economic metrics using a combined Grey Relational Analysis (GRA) model. The proposed Passenger Hub Economic Contribution Measurement Model (PHECM) is tested using major railway hubs in Beijing as a case study. The findings highlight that travel purpose is a significant factor in passenger profiling. Furthermore, the economic contribution of a hub is influenced by a combination of factors, including passenger occupation, travel time, purpose, and regional aspects, rather than solely by macro-level operational indicators. Overall, this model facilitates comparative analyses of economic contributions among different hubs and between hubs and the administrative district, providing valuable data to inform hub service policies.
This paper employs the super-efficient SBM model in conjunction with the global Malmquist-Luenberger (GML) index to assess and decompose the green total factor productivity (GTFP) of China and ASEAN countries spanning the period from 2011 to 2021. The analysis delves into both the spatial and temporal characteristics of GTFP, scrutinizing the static and dynamic comparisons to elucidate the driving forces behind the observed changes in each country. Furthermore, the study explores intra-regional GTFP transfer trends and spillover effects utilizing the Markov chain and spatial lag methodologies. The findings reveal that China and the ASEAN region emerge as pivotal entities globally with respect to GTFP. Notably, the overall GTFP in both China and the ASEAN region exhibits a fluctuating downward trajectory. However, discernible variations in GTFP indices and developmental trends are evident among individual countries, indicating a lack of long-term convergence and the presence of a "club convergence" phenomenon. Technological efficiency enhancements are identified as catalysts for elevating the level of green production in the region. The overall GTFP profile portrays a "high in the middle and low around" pattern, indicating spatial concentrations of higher GTFP amidst lower surroundings. This spatial distribution is accompanied by notable inter-country spillover effects, wherein high GTFP countries positively influence neighboring counterparts through resource sharing, thereby demonstrating a catalytic effect on regional GTFP improvement. Conversely, negative spillovers are observed in low GTFP countries, driven by resource competition and culminating in heightened competition for environmental regulation. In summary, the study unveils intricate spatial and temporal dynamics in GTFP, offering insights into the interplay of technological efficiency, resource sharing, and environmental regulation within the region.
This paper analyzes the spatial spillover effects of U.S. inflation on 14 OECD sample countries from 2019 to 2022 using the Spatial Durbin Model (SDM) and the TVP-SV-VAR model. The study finds that: 1) U.S. inflation exhibits significant spatial spillover effects, with all sample countries experiencing sustained positive shocks, though the intensity of these effects varies due to regional economic and geographical characteristics. 2) The spillover effects follow a "core-periphery" geographic attenuation pattern, where geographically proximate countries experience stronger and more persistent impacts. 3) The role of competition policy in regional inflation governance differs: the EU employs competition policy to ensure the effective implementation of a unified monetary policy and a single market, whereas emerging markets focus on using competition policy to curb excessive market concentration and accelerate supply chain restructuring. 4) Spatially adjacent regions adopt coordinated governance mechanisms and shorten supply chain distances to enhance resilience against risks. Moreover, early and proactive competition policy interventions significantly improve inflation control effectiveness. Based on these findings, China can enhance policy efficiency by: closely monitoring U.S. inflation trends; leveraging its geographic characteristics to regulate market concentration through competition policy; shortening supply chain distances; and optimizing the spatial configuration of key commodity supply chains. Additionally, strengthening the role of competition policy in inflation governance, improving coordination with other policies, and implementing differentiated competition law enforcement strategies tailored to various inflation drivers can help mitigate the spatial transmission speed and impact of imported inflation.
Based on the panel data of 102 countries or regions along the Belt and Road route from 2013 to 2021, this paper empirically explores the relationship between the Belt and Road Initiative and the development of digital economy of countries along the route using a multi-period difference-in-differences model. The results show that: 1) The Belt and Road Initiative promotes the development of digital economy of countries or regions along the route by improving the institution quality, strengthening the scientific research and innovation, and increasing the urbanization level of countries or regions along the route. These results still remain robust through various robustness tests. 2) The Belt and Road Initiative has a significant impact on the development of digital economy of countries or regions along the route, which is differentiated. It will promote the development of digital economy in high-income countries or regions along the route in all aspects, and improve the construction of digital infrastructure in low-income countries or regions. It has a significant positive impact on the digital economy development of countries or regions along the route, as well as their neighbour and non-neighbouring countries. Accordingly, it puts forward corresponding policy recommendations on how to make full use of the Belt and Road Initiative to promote the development of the digital economy in countries along the route.
Intra-urban residential mobility represents a common and complex socio-spatial phenomenon, marked by the relocation of individuals or families within the same city, essentially constituting a re-selection of housing. Notably, education-led residential mobility is increasingly becoming one of the dominant modes of family migration within large cities. This study integrates Pierre Bourdieu's theory of fields into the analytical framework for examining education-led residential mobility. Utilizing data from 5,000 relocation questionnaires in Nanjing, it systematically explores the spatio-temporal characteristics, underlying mechanisms, and social effects of education-led residential mobility. The findings reveal: 1) Education-driven relocation forms a relatively independent and multi-agent social field characterized by competitiveness and capital transformation driven by capital (instrumental) and habitual (logical) practices; 2) Families involved in education-led residential mobility generally possess higher socio-economic attributes and engage in competition for educational resources through their capital's scale and structure, with economic capital being the primary driving factor, while class and cultural habits significantly contribute to their decisions; 3) This form of mobility highlights the supply-demand contradiction in quality compulsory education, leading to issues such as the capitalization of educational resources and gentrification of school districts, exacerbating resource allocation imbalances and social spatial segregation. The disparity in educational quality within cities is both a cause and a consequence of education-led residential mobility. Analyzing the field of education-led residential mobility is crucial for a systematic understanding of the deep-seated social mechanisms behind educational differentiation and mobility, providing theoretical support and practical guidance for government efforts aimed at achieving educational equity through optimizing field rules and instituting pathways for balanced inter-school development.
The exhibition industry features high connectivity, strong driving force, and robust integration, providing strong support for advancing the dual circulation strategy. By utilizing the three-level parent-subsidiary relationship data of foreign exhibitors at the 2018 and 2019 China International Import Expo (CIIE), this study constructed the city network. Combining social network analysis (SNA) and the geographical concentration of enterprise origins, this study analyzed the structural characteristics and interaction effects of the internal and external circulation networks from the perspectives of control, betweenness, autonomy, enterprise attractiveness, regional attractiveness, and specialization.The results are as follows: 1）The density of the urban circulation network has increased, with control concentrated in a few core node cities. These networks exhibit distinct subgroups, alongside significant differences in scale and density, and core nodes are mainly distributed in economically developed regions. 2）High-value areas for the structural characteristics of external networks are distributed in the core cities of various urban agglomerations, while peripheral cities within each agglomeration have also experienced relatively rapid growth. 3）Control in internal circulation exerts a positive impact on enterprise attractiveness, regional attractiveness, and specialization. Betweenness has a positive impact on both enterprise and regional attractiveness, but a negative impact on specialization. Autonomy has a negative impact on enterprise attractiveness, yet a positive impact on regional attractiveness and specialization. 4）Enterprise attractiveness in external circulation has a positive impact on control, betweenness, and autonomy. Regional attractiveness and specialization have a negative impact on control and betweenness, but a positive impact on autonomy.
This study takes Shenzhen as a case, based on patents and POI data, explore the spatial agglomeration characteristics of knowledge-based and industrial-based innovation activities and analyzes the differential impact of multidimensional amenity on two types of innovation. The results show that: 1)The spatial agglomeration characteristics of innovation activities in Shenzhen show a spatial pattern of collaborative development between the urban core area and the surrounding area, and the spatial agglomeration of knowledge-based and industrial-oriented innovation activities shows significant differentiation characteristics. The former forms a spatial pattern of "core + scattered points" while the latter presents the characteristics of "core + gathering points". 2) Leisure and socialization, education, and transportation amenity significantly contribute to the spatial agglomeration of innovation activities. The spatial agglomeration of knowledge-based innovation activities focuses on the education and socialization amenity, while the industrial innovation activities tend to transportation and socialization amenity. 3) The influence of amenity factors on the spatial agglomeration of innovation activities in different areas of Shenzhen is different. The influence of comfort factors on the spatial agglomeration of innovation activities in different areas of Shenzhen is also different. The urban core area relies on transportation, culture, education and industry factors to form knowledge-based and industrial activity agglomeration areas; the northern development area is affected by transportation and social comfort and presents an industrial orientation; the eastern development area has no significant agglomeration of both types of innovation activities.
The improvement of people's quality of life and the solid promotion of common wealth in the new era are greatly supported by the important foundation of the high community built environment quality(CBEQ). In this paper, Lanzhou, the center city of Northwest China, is taken as an example, and the subjective evaluation index system of CBEQ under the perspective of common wealth is constructed based on the questionnaire data. The results show that: The distribution of CBEQ is significantly influenced by the Yellow River, displaying an east-west axial belt-like core-edge spatial characteristic. High-quality communities tend to be in close proximity to surrounding high-quality and higher-quality communities, forming a spatial aggregation phenomenon of high-quality communities. From a sub-dimensional perspective, the overall spatial distribution of environmental livability is balanced, but there is the phenomenon of inverse centralization. The convenience of life presents the spatial agglomeration characteristics of single-center and axial belt. Social stability forms the spatial distribution characteristics of single-center and dotted with the district government as the core. Spiritual affluence presents the spatial structure characteristics of multi-center of different levels. The primary factors, such as land price, urban planning, distance to the district administrative center, average years of education, and public space, have always played a fundamental role, while the secondary factors, such as distance to the station, population, distance to the subway station, density of the community's road network, type of land use, average years of residency, and average elevation, play a key role, and their interaction contributes to the formation of the spatial differentiation pattern of CBEQ. The interactions between them contributed to the formation of the spatial differentiation pattern of CBEQ. Among them, the force of land price, distance from the community to the subway station, distance from the community to the station, and public space continued to increase.
Based on the quantitative assessment of the economic resilience of 121 counties in Hunan Province from 2006 to 2020, the article discusses in depth the effect and mechanism of tax and fee reduction on the economic resilience of counties. The results show that: 1)Tax and fee reductions help to enhance the economic resilience of counties. 2)Tax and fee reductions significantly enhance counties' economic resilience by improving the level of foreign investment, the degree of marketisation, and the level of innovation capacity in counties. 3)Tax and fee reductions have a positive spatial spillover effect on counties' economic resilience, indicating that a county's tax and fee reductions not only have a positive impact on its own economic resilience, but also have a positive radiation effect on surrounding counties. Furthermore, the promotion effect of tax and fee reductions on the economic resilience of counties in the eastern part of Hunan, counties with stronger economic strength, and counties in the Changzhutan Economic Circle is more significant.
The improvement of regional innovation quality is an important component of the development of new quality productivity. Based on the "Buzz-and-Pipeline" theory, this article uses the invention patent information of 41 prefecture level and above cities in the Yangtze River Delta region from 2003 to 2022 as raw data to define and characterize the local and nonlocal homogeneous and heterogeneous connections, measure and compare their impact on the quantity and quality of regional innovation, and analyze the role of technology gatekeepers in knowledge coupling. The research results find that: 1)The nonlocal homogeneous connections in the Yangtze River Delta exhibit the characteristics of "concentrated intensity and low density", while heterogeneous connections exhibit the characteristics of "balanced intensity and high density". 2)The positive effects of heterogeneous connections at different scales on the quantity and quality of regional innovation are significantly stronger than those of homogeneous connections. The construction of a global "pipeline" is crucial for improving the quality of regional innovation. 3)Local "buzz" can significantly positively regulate the impact of nonlocal heterogeneous connections on the quantity and quality of regional innovation. 4)The technological gatekeepers maintains a high proportion of heterogeneous connections in different technical categories, playing a key role in the process of knowledge coupling at different scales. The research conclusion deepens the understanding of the "Buzz-and-Pipeline" theory from the perspectives of homogeneous and heterogeneous knowledge flow, and has certain reference value for the development of new quality productivity.
Against the backdrop of the 20th National Congress of the Communist Party of China's proposition that "high-quality development is the primary task for comprehensively building a modern socialist country," this paper addressing the constraints on internal supporting conditions faced by the high-quality development of regional economy, adopts the panel regression model and spatial econometric methods to systematically explore the impact mechanism and spatial spillover effect of industrial intelligence on the high-quality development of regional economy. The findings reveal that:1) Industrial intelligence significantly promotes high-quality development of regional economy, with robust regression outcomes after robustness tests. 2) The promotional effect of industrial intelligence on high-quality regional economic development decreases sequentially across eastern, central, western, and northeastern regions; it is more pronounced in large cities compared to small and medium-sized cities. 3) Industrial intelligence drives market integration and enhances total factor productivity (TFP), thereby positively influencing high-quality regional economic development. 4) A positive spatial spillover effect exists in the impact of industrial intelligence on high-quality regional economic development. Based on these findings, the paper proposes pathways to effectively leverage industrial intelligence for promoting high-quality regional economic development through technological innovation, industrial collaboration, and policy guidance.
Based on the patent data of inter-city cooperation applications, this study deeply analyzed the structural characteristics, community division, node level, axis level, network temporal and spatial evolution etc. Meanwhile, combined with the multi-dimensional proximity framework, the influencing factors of the contextual spatio-temporal evolution of the innovation network are studied. The main conclusions of this paper are as follows: First, within the Yellow River Basin, the scale of the innovation network has continuously expanded, with increased network connectivity and improved flow efficiency. The number of innovation network communities has decreased, with modularity declining year by year, and a noticeable enhancement in the degree of community aggregation. The hierarchy of urban nodes has significantly improved, showing a clear trend of lower-tier cities transforming into higher-tier ones. The connections along urban axes have significantly strengthened, presenting a distinct multi-core radiation layout. Second, innovation cooperation between cities within the Yellow River Basin and those outside the basin has continuously strengthened, with innovation connections becoming increasingly close and the smoothness of innovation cooperation significantly improved. The hierarchy of nodes in the internal-external innovation network has notably upgraded, and the number of core cities in the network has been on the rise. The hierarchy of urban axes has also continuously improved, with primary and secondary axis connections continuing to expand. Beijing's position in the network stands out, and its innovation linkages with the Yellow River Basin have continuously intensified. Third, Jinan, Xi'an, Qingdao, Zhengzhou, and Lanzhou are core nodes within the internal innovation network of the Yellow River Basin. Cities such as Beijing, Nanjing, Chengdu, Shanghai, and Wuhan serve as core nodes in the external network. Fourth, Geographical proximity, institutional proximity, and social proximity play a positive role in the evolution of both the internal and external innovation networks within the Yellow River Basin. Cognitive proximity can to some extent have an inhibiting effect on the innovation network. The impact of cultural proximity on the internal innovation network of the Yellow River Basin has shifted from inhibition to promotion.
Digital transformation is a crucial driving force for enhancing regional collaborative innovation capabilities. Based on an exploration of the theoretical mechanisms through which digital transformation impacts regional collaborative innovation, this study focuses on the 19 counties dataset of the Changsha-Zhuzhou-Xiangtan metropolitan area, as the research object to test the regional collaborative innovation effect and its mechanism of digital transformation. And this study uses a random forest model to explore the partial dependence of collaborative innovation on regional digital transformation. The empirical results indicate that digital transformation in the counties of Changsha-Zhuzhou-Xiangtan metropolitan area significantly promotes collaborative innovation. The driving effect is particularly evident in areas with lower government intervention, less local fiscal pressure, and higher regional administrative levels. Furthermore, the study found that knowledge-related diversity positively moderates the collaborative innovation effects of regional digital transformation, while knowledge-unrelated diversity plays a negative moderating role. The influence of regional digital transformation on collaborative innovation is more significant than traditional economic factors such as industrial structure. Additionally, the regional collaborative innovation effect of digital transformation exhibits certain nonlinear characteristics.
Based on panel data from 284 prefecture-level cities across China's eight comprehensive economic regions from 2005 to 2021, this study employs kernel density estimation, the Dagum Gini coefficient, and its decomposition method to analyze the dynamic distribution and regional disparities of eco-environmental quality. The coefficient of variation and maximum likelihood estimation (MLE) methods are further used to test for potential σ-convergence and β-convergence. In addition, spatial econometric models are constructed to explore the factors influencing the convergence of eco-environmental quality both nationwide and across the eight comprehensive economic regions. The main findings are as follows: 1)Eco-environmental quality in China consistently exhibits a spatial pattern of being "high in the east and low in the west, high in the north and south but low in the middle." 2)The overall Gini coefficient of China's eco-environmental quality shows a fluctuating upward trend, with interregional disparities contributing the most to the overall inequality and showing a tendency to expand. 3)Eco-environmental quality has improved nationwide and in the southern coastal economic region; however, except for the Southwest Comprehensive Economic Region, other regions display a distinct bimodal distribution, indicating polarization. 4)No σ-convergence is observed in eco-environmental quality among the comprehensive economic regions, but both absolute and conditional β-convergence are present. Moreover, when considering the influence of control variables, the β-convergence process demonstrates significant spatial spillover effects.
This paper takes the Dabie Mountain old revolutionary base area as its research object, analyzing the spatiotemporal characteristics and main influencing factors of the adaptation between rural human settlements and residents' well-being in 47 counties (cities) within the area from 2006 to 2022. A system dynamics (SD) model was used to simulate and predict the rural human settlements, residents' well-being, and their adaptation degree. The results indicate that: 1)The quality of rural human settlements and the level of residents' well-being in the Dabie Mountains old revolutionary base area have continuously improved, but regional development disparities persist. 2)The adaptation degree between the quality of human settlements and the level of residents' well-being in the Dabie Mountain old revolutionary base area generally shows an upward trend, though developmental differences exist among Hubei, Henan, and Anhui provinces. 3)Infrastructure improvement is the core driver for enhancing the quality of rural human settlements and the level of residents' well-being in the Dabie Mountains old revolutionary base area. Economic development, ecological construction, and optimization of public services can synergistically promote rural sustainable development and residents' well-being. 4)Economic development-oriented and resource development-oriented pathways perform prominently, while stable development-oriented and cultural development-oriented pathways maintain high levels of residents' well-being. In contrast, the population development-oriented pathway performs relatively weakly. Furthermore, there is differentiation in the optimal path selection among the three provinces. Based on these findings, recommendations include strengthening the level of agricultural mechanization, improving cultural and welfare facilities, implementing differentiated regional development strategies, optimizing development pathway selections, increasing infrastructure investment, and promoting the comprehensive revitalization of rural areas in the Dabie Mountains old revolutionary base area.
In the new era, the rural collective economy is transforming into a diversified development model, and rural operation has become an important way to achieve rural revitalization. This study builds an analysis framework based on the symbiosis theory, takes 26 typical rural cases in the Yangtze River Delta as samples, and uses the fuzzy set qualitative comparative analysis method to conduct configuration analysis on the influencing factors and development paths of rural operation performance. The results show that: 1) Single condition does not constitute a necessary condition for high performance of rural operation, and capital investment, collective governance and industrial transformation play a key role in combination; 2) There are five symbiotic paths for high rural operation performance, namely, industrial upgrading path under government-enterprise cooperation, technology driven path under collective leadership, industry driven path under village-enterprise cooperation, industry and technology driven path under village-enterprise cooperation, and resource utilization path under multi-party cooperation; 3) Under specific conditions, there is a complementary relationship between capital investment and industrial transformation, and there is a substitution effect between collective governance, government support and resource endowment, and collective leadership and governance ability is an important factor to solve the dilemma of rural operation resources. Rural development should focus on the synergistic adaptation effect of operational factors from a holistic perspective, formulate rural development strategies according to local conditions, and focus on the important role of capital investment, collective governance and industrial transformation in promoting high-level rural operations. The research results provide theoretical basis and practical reference for rural choice of differentiated development path in the new era.
It is difficult to reveal the overall characteristics of the change of agricultural labor force and its coupling relationship with agricultural mechanization by focusing on the reduction or aging of agricultural labor force, feminization, childishness and low education. By constructing an evaluation index for agricultural labor force weakness and agricultural mechanization, this study quantitatively measured the development of agricultural labor force weakness and agricultural mechanization in China and its provinces from 2003 to 2023. Then, the coupling coordination degree model was employed to analyze the spatiotemporal evolution characteristics of the two systems, and the quadrant diagram model was further used to reveal the evolutionary pathways of provincial grain production under varying coupling coordination conditions. Finally, the spatial econometric model was used to quantitatively reveal the impact of the coupling coordination between the two and other agricultural production factors on China's grain production. The results showed that:1) The weakness of China's agricultural labor force showed a two-stage change from 2003 to 2023, with a fluctuating decline from 2003 to 2009 and a steady increase from 2010 to 2023, while the level of agricultural mechanization continued to improve. 2) In 2003, the coupling coordination degree of agricultural labor weakness and agricultural mechanization decreased from west to east. In 2009, the coupling coordination degree decreased from west to east and from south to north. In 2015 and 2023, the coupling coordination degree was degraded and greatly improved, respectively. 3) In the two periods from 2003 to 2009 and 2010 to 2015, the coupling coordination degree of agricultural labor weakness and agricultural mechanization decreased in more than 60% of provinces, but grain output increased, and the opposite was true in 2016 to 2023. 4) The improvement of the coupling coordination degree of agricultural labor weakness and agricultural mechanization in 2003-2009 and 2010-2015 had a significant positive spatial spillover effect on grain production, however in 2016-2023, the spatial spillover effect on grain production turned to significantly negative.
Based on panel data from 31 provinces in China from 2009 to 2022, this paper used the entropy-weighted TOPSIS method to construct an evaluation index system for the high-quality Development of agricultural insurance from three dimensions: development scale, operational efficiency, and growth capacity. The study employed the Dagum Gini coefficient, Kernel density estimation, Markov chains, and an obstacle factor model to systematically analyze the spatiotemporal patterns, regional differences, evolutionary trends, and main obstacle factors of high-huality agricultural insurance development in China. Additionally, geographic detectors were used to identify core driving factors. The findings reveal that: 1) The level of China's high-quality agricultural insurance development has continuously improved, with significant but gradually narrowing interprovincial disparities; 2) A spatial pattern of "high in the west and low in the east" has emerged, with interregional differences being the dominant factor contributing to overall variation; 3) Growth capacity is the most critical dimension in the evaluation system, with agricultural insurance claims growth rate, premium subsidy growth rate, and premium depth identified as key obstacle factors; 4) High-quality development is driven by multiple interacting factors, with interaction effects generally stronger than individual factor effects. The education level of farmers significantly influences development and enhances the impact of other factors through interaction. Based on these findings, the paper proposed policy recommendations to promote the high-quality development of Chinese agricultural insurance, such as tailoring policies to local conditions, promoting regional coordination, enhancing technology transfer, and improving farmers' education levels.
Clarifying the co-evolution mechanism between tourism economy and ecological security resilience has great significance in promoting the high-quality development of border areas and the construction of ecological barriers. This paper constructs the evaluation index systems of tourism economy and ecological security resilience in China's land border provinces, and explores their co-evolution mechanism and influential factors using the linear weighting method, Harken model, and GTWR model. The results show that: 1) The tourism economy index of the border provinces grows rapidly, and the ecological security resilience index is stable to good. The tourism economy is higher in the southwestern and northeastern border areas, and the ecological security resilience of Tibet is far ahead of the others. 2) Tourism economy is an ordinal parameter that dominates the co-evaluation of the system, and the co-evaluation mechanism of the system is still in the primary stage. The system synergy of the border provinces has been improving during the study period, and all the border provinces will be out of the system dysfunction level in 2019. Liaoning, Yunnan, and Guangxi will be the first to enter the high-quality coordination level. 3) In terms of influential factors, the level of economic development, the level of urbanization, government intervention, human capital, and technological innovation have a predominantly positive impact on the system co-evaluation, while environmental regulation has a predominantly negative impact.
Using methods of average nearest neighbor analysis, kernel density estimation, spatial clustering degree, hot spot analysis, optimal parameters-based geographical detector, and based on geographical nature principle, the spatial distribution characteristics and influencing mechanism of national tourism resorts are analyzed. The conclusions are as follows: 1) There are significant differences in the spatial distribution pattern of tourism resorts in China. As a whole, Hu Huanyong Line is the boundary of "more in the east and less in the west", and presents a spatial pattern of "large dispersion, small agglomeration, bow and arrow", which is clustered in Yangtze River Delta urban agglomeration, city clusters in the middle reaches of the Yangtze River, Chengdu-Chongqing urban agglomeration, Central Plains urban agglomerations. The hot areas present a spatial pattern of "three main and two secondary", distributed in the Yangtze River Delta region, the junction of Henan and Shanxi provinces, the junction of Hubei, Sichuan, Chongqing and Guizhou provinces, the Bohai Rim, and several cities in the middle reaches of the Yangtze River. 2) The spatial distribution of national tourism resorts is influenced by three major geographic factors and their synergies. The income level has the least impact on the spatial distribution of national tourist resorts, while the market size has the greatest impact. Vegetation coverage, market size and human capital are the most influential of the three geographical characteristics. The internal elements of the second geographical nature and their interaction with the elements of the third geographical nature have the greatest influence. 3) The coupling and coordination of the three geographical characteristics form the influencing mechanism of the spatial distribution pattern of national tourism resorts. The first geographical nature provides the basic background, the second geographical nature shows the dominant role, the third geographical nature plays an active regulatory role, and the three geographical nature forms the spatial distribution pattern of the national tourism resort through the nonlinear enhancement effect and the double factor synergistic strengthening effect.
This study employs multi-platform web crawlers to collect travelogues about Xinjiang from 2023, utilizing ArcGIS spatial analysis methods to examine the spatiotemporal distribution characteristics of tourist sentiment across 38 counties and cities in the region. A multiscale geographically weighted regression (MGWR) model is further applied to explore the influencing factors behind the spatial distribution of tourist sentiment. The results indicate that: 1) Temporally, tourist sentiment exhibits periodic fluctuations on a weekly basis and seasonal variations within monthly cycles; 2) Spatially, significant regional disparities are observed, with an overall pattern of "Northern Xinjiang > Eastern Xinjiang > Southern Xinjiang." The spatial distribution type is characterized as agglomerative, forming a hierarchical clustering pattern described as "one primary core with three secondary cores." Moreover, spatial correlation varies considerably: Huocheng County, Huoerguosi City, Nileke County, Tekes County, and Xinyuan County in Northern Xinjiang are identified as high-high clustering areas of tourist sentiment, while Yuli County in Southern Xinjiang is the only low-low clustering area. 3) Tourist sentiment is influenced by both internal and external factors. Ecological quality, climate comfort, tourism resource endowment, transportation accessibility, and industrial structure all exert positive effects, with ecological quality and climate comfort demonstrating spatial heterogeneity.
Building a systematic and continuous heritage corridor is a key step in promoting the comprehensive protection and rational utilization of cultural heritage. Taking the Guanlong Ancient Trail linear cultural heritage as the research object, this study explores the characteristics of heritage nodes and network attributes through cognitive network structure analysis, and identifies potential heritage corridors using the minimum cumulative resistance model and circuit theory model in conjunction with heritage clusters as heritage sources. By integrating and optimizing potential corridors based on factors such as heritage centrality evaluation, actual transportation conditions, and corridor relative resistance, this study constructs the cultural heritage system of the Guanlong Ancient Trail. The results indicate that: 1) The heritage network of the ancient Guanlong Ancient Trail linear cultural heritage presents a spatial pattern of "multiple cores and clustered groups". 2) The application of the "kernel density estimation + block model" collaborative division of heritage source areas can effectively enhance the scientific nature of the division of heritage source areas. 3) The potential heritage corridors in the study area were manually corrected, and after optimization, a three-level corridor system of "core-main-secondary" was constructed. Based on this, the development and application strategies of the cultural heritage corridor system were proposed, with the aim of providing reference and inspiration for the overall protection and coordinated development of linear cultural heritage in the northwest region and even the whole country.
The bidirectional coagglomeration of the cultural and tourism industries (CTI) reflects the asymmetric spatial relationship between the two industries, serving as a crucial spatial manifestation of their integration and holding significant value for the revitalization and development of Northeast China. Using data of cultural and tourism enterprises from 36 prefecture-level cities in Northeast China between 2004 and 2022, this study explores the impact mechanism of CTI bidirectional coagglomeration on economic development, calculates the CTI bidirectional coagglomeration index, and analyzes its effects on economic development. The findings indicate that: 1) The coagglomeration of the tourism industry into the cultural industry is stronger than vice versa. During the sample period, the overall level of CTI bidirectional coagglomeration remained relatively stable, with cities experiencing faster improvement mainly concentrated in economically advanced areas such as Shenyang, Dalian, Anshan, Changchun, and Harbin. 2) Global OLS regression results show that CTI bidirectional coagglomeration significantly promotes economic development, with the coagglomeration of the cultural industry into the tourism industry exerting the strongest positive effect. 3) Local Geographically and Temporally Weighted Regression results reveal that the impact of CTI bidirectional coagglomeration on economic development exhibits spatiotemporal heterogeneity, initially positive in 2004 but turning negative by 2022, indicating diseconomies of CTI bidirectional coagglomeration in Northeast China. The results provide a theoretical basis for promoting CTI bidirectional coagglomeration to foster economic development and deepen the study of the relationship between CTI bidirectional coagglomeration and economic development.
