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This study presents the case of China's Jiangsu Province. The spatial-temporal pattern evolution of different manufacturing sectors is discussed using spatial analysis technology (spatial autocorrelation and standard deviation ellipses). The Granger test is used to analyze the relationship between the change in the manufacturing industry spatial agglomeration and regional economic differences. The following conclusions are drawn: 1) The spatial agglomeration trend of most manufacturing sectors is weakening. Much of the manufacturing sector, like the rubber and plastic product industries, has been transferred from southern to northern Jiangsu. 2) From the scale, only a minority of these enterprises possess substantial registered capital. The capital injection scale of more manufacturing enterprises is insignificant. At the same time, manufacturing companies with substantial financial resources are increasingly inclined to choose less-concentrated areas when choosing new investment areas. 3) The reduction of regional economic differences is considered to be the Granger-cause for the decline of the spatial agglomeration degree of the manufacturing industry in Jiangsu Province. Analyzing the spatiotemporal pattern of the manufacturing industry in Jiangsu Province will provide specific policy reference values for the manufacturing industry and economic development of Jiangsu province. In addition, for companies of different sizes, the findings of this paper also provide valuable references on how they can choose suitable investment locations according to their size in the future., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The study of spatio-temporal evolution characteristics and factors affecting the coordinated development of population and green economy (CD_PGE) in Shandong province, China, has significant decision-making implications for promoting high-quality and sustainable regional development. Based on 2001 to 2020 panel data for each city and economic zone in Shandong province, this paper constructs an evaluation model for the CD_PGE systems. Using growth elasticity models, geographic concentration models, kernel density estimation models, spatial autocorrelation, analysis of population and regional green economy development in Shandong Province from the perspective of spatial agglomeration coupling, spatial and temporal coupling coordination patterns, and evolutionary characteristics. In addition, we use the fixed effect models and panel quantile models to empirically test the effects of coordinated demographic and green economy development. The results show that: (1) In terms of demo-graphic and economic development characteristics, Shandong's demographic and green economy development trends are good, but there are still many challenges. (2) According to the time series evolution and spatial distribution characteristics, the degree of CD_PGE in Shandong Province is on the rise, and the level of spatial distribution is distinct. (3) From the spatio-temporal dynamical grid evolution of the degree of CD_PGE, the CD_PGE is characterized by significant spatial clustering, but with large regional differences. (4) From an impact factor perspective, both market mechanisms and government intervention have a significant impact on the degree of CD_PGE, but the direction and extent of the impact vary.

Talents are not only an important strategic resource for promoting regional development but also a core element for maintaining competitiveness. We organize the evaluation index system of regional talent attraction into the following four aspects: regional development, industry development, income and regional environment. Combined with the talent possession of 31 provinces (cities) from 2010 to 2018, we establish a regression equation of the relationship between the evaluation index and talent possession by using a stepwise regression and the Bayesian prior function. Simultaneously, we apply the spatial autocorrelation analysis method to measure the correlation and agglomeration degree of the talent attraction level of provinces and municipalities in China. The results reveal the following. (1) From 2010 to 2018, the talent attractiveness level of China's provinces shows a steady upward trend with an average annual growth rate of 5.804%. The regional environment has the highest score, and the income level has the lowest score. (2) The level of talent attraction in China shows a decreasing trend from east to west, and the ranking in 2018 was "East Coast > North Coast > Southern Coast > Middle Yangtze River > Middle Yellow River > Southwest > Northeast > Greater Northwest". The trend of spatial agglomeration is apparent and gradually increases over the years. The numbers of hot and cold spots are relatively large and concentrated in the eastern coast and western region, respectively. (3) The level of economic development, quality of people's life, and level of the development of the tertiary industry have a great impact on the attractiveness of talents. Talents also pay more attention to regional medical, education and transportation indicators. These research results can provide some guidance and references for the formulation of talent introduction policies in various provinces and municipalities.

The study of spatio-temporal evolution characteristics and factors affecting the coordinated development of population and green economy (CD_PGE) in Shandong province, China, has significant decision-making implications for promoting high-quality and sustainable regional development. Based on 2001 to 2020 panel data for each city and economic zone in Shandong province, this paper constructs an evaluation model for the CD_PGE systems. Using growth elasticity models, geographic concentration models, kernel density estimation models, spatial autocorrelation, analysis of population and regional green economy development in Shandong Province from the perspective of spatial agglomeration coupling, spatial and temporal coupling coordination patterns, and evolutionary characteristics. In addition, we use the fixed effect models and panel quantile models to empirically test the effects of coordinated demographic and green economy development. The results show that: (1) In terms of demo-graphic and economic development characteristics, Shandong's demographic and green economy development trends are good, but there are still many challenges. (2) According to the time series evolution and spatial distribution characteristics, the degree of CD_PGE in Shandong Province is on the rise, and the level of spatial distribution is distinct. (3) From the spatio-temporal dynamical grid evolution of the degree of CD_PGE, the CD_PGE is characterized by significant spatial clustering, but with large regional differences. (4) From an impact factor perspective, both market mechanisms and government intervention have a significant impact on the degree of CD_PGE, but the direction and extent of the impact vary. [ABSTRACT FROM AUTHOR]

Talents are not only an important strategic resource for promoting regional development but also a core element for maintaining competitiveness. We organize the evaluation index system of regional talent attraction into the following four aspects: regional development, industry development, income and regional environment. Combined with the talent possession of 31 provinces (cities) from 2010 to 2018, we establish a regression equation of the relationship between the evaluation index and talent possession by using a stepwise regression and the Bayesian prior function. Simultaneously, we apply the spatial autocorrelation analysis method to measure the correlation and agglomeration degree of the talent attraction level of provinces and municipalities in China. The results reveal the following. (1) From 2010 to 2018, the talent attractiveness level of China's provinces shows a steady upward trend with an average annual growth rate of 5.804%. The regional environment has the highest score, and the income level has the lowest score. (2) The level of talent attraction in China shows a decreasing trend from east to west, and the ranking in 2018 was "East Coast > North Coast > Southern Coast > Middle Yangtze River > Middle Yellow River > Southwest > Northeast > Greater Northwest". The trend of spatial agglomeration is apparent and gradually increases over the years. The numbers of hot and cold spots are relatively large and concentrated in the eastern coast and western region, respectively. (3) The level of economic development, quality of people's life, and level of the development of the tertiary industry have a great impact on the attractiveness of talents. Talents also pay more attention to regional medical, education and transportation indicators. These research results can provide some guidance and references for the formulation of talent introduction policies in various provinces and municipalities. [ABSTRACT FROM AUTHOR]

Under the background of "the Belt and Road" and "the economic corridor of China, Mongolia and Russia" initiatives, it is of great significance to study the temporal and spatial economic pattern in the Russian Federation. Based on the economic development difference index, regional economic grade index, global trend analysis tool and spatial autocorrelation model, this paper analyzes the temporal and spatial pattern evolution characteristics of Russian economic differences from 2002 to 2020. The results are as following. First, although the economic imbalance among various federal subjects has been decreasing, the economic polarization has been still severe between the prosperous developed regions and the stagnant backward regions during 2002–2020. Russia's economy shows a trend of changing from significant positive correlation in strong agglomeration space to positive correlation in weak agglomeration space, and then to random distribution. Second, there has been great differences of the economic development among various federal subjects. The economic grade of the Russian federal subjects presents a significant spatial differentiation pattern. The Russian Federation's economic resources are concentrated in the first-class federal subject (Moscow City), second-class federal subjects (Tumen Region, Moscow Region and Saint-Petersburg city) and a few third-class federal subjects (Yamalo-Nenetsky Autonomous Area, Khanty-Mansiysky Autonomous Area, Republic of Tatarstan, Krasnodar Territory, Sverdlovsk Region, etc). Third, the Russian Federation's economy presents "High Core, Low Periphery", "High West, Low East" and "High south, Low north" spatial differentiation pattern. The economic hot regions coincide with the high-class economic regions, which are mainly distributed in the contiguous areas of Ural Federal District and Volga Federal District, as well as the Moscow City, Moscow Region, Saint-Petersburg city, Krasnodar Territory and Rostov Region. The economic cold regions coincide with the low-class economic regions, which are mainly located in the Far East Federal District, the east of Siberian Federal District, the north of North West Federal District and the south of North-Caucasian Federal District. Finally, we suggest the recommendation for policy makers in Russia. And we propose the future research ideas. [ABSTRACT FROM AUTHOR]

Three-dimensional landscape patterns are an effective means to study the relationship between landscape pattern evolution and eco-environmental effects. This paper selects six districts in Xi'an as the study area to examine the spatial distribution characteristics of the three-dimensional architectural landscape in the city's main urban area using three-dimensional information on the buildings in 2020 with the support of GIS. In this study, two new architectural landscape indices—landscape height variable coefficient and building rugosity index—were employed in landscape pattern analysis, whilst a system of rigorous and comprehensive three-dimensional architectural landscape metrics was established using principal component analysis. A mathematical model of weighted change of landscape metrics based on the objective weighting method was applied to carry out scale analysis of the landscape patterns. Spatial statistical analysis and spatial autocorrelation analysis were conducted to comprehensively study the differentiation of three-dimensional architectural landscape spatial patterns. The results show that the characteristic scale of the three-dimensional landscape pattern in Xi'an's main urban area is around 8 km. Moreover, the three-dimensional landscape of the buildings in this area is spatially positively correlated, exhibiting a high degree of spatial autocorrelation whilst only showing small spatial differences. The layout of the architectural landscape pattern is disorderly and chaotic within the second ring, whilst the clustering of patch types occurs near the third ring. Moreover, the building density in the Beilin, Lianhu, and Xincheng districts is large, the building height types are rich, and the roughness of the underlying surface is high, such that these are key areas to be improved through urban renewal. The height, volume, density, morphological heterogeneity, and vertical roughness of the architectural landscape vary amongst functional areas within the study area. This paper is the first to apply the study of spatial heterogeneity of three-dimensional landscape patterns to Xi'an. It does so in order to provide a quantitative basis for urban landscape ecological design for urban renewal and the rational planning of built-up areas, which will promote the sustainable development of the city's urban environment. [ABSTRACT FROM AUTHOR]

Perceptual recognition of tourist destinations is vital in representing the destination image, supporting destination management decision-making, and promoting tourism recommendations. However, previous studies on tourist destination perception have limitations regarding accuracy and completeness related to research methods. This study addresses these limitations by proposing an efficient strategy to achieve precise perceptual recognition of tourist destinations while ensuring the integrity of user-generated content (UGC) data and the completeness of perception dimensions. We integrated various types of UGC data, including images, texts, and spatiotemporal information, to create a comprehensive UGC dataset. Then, we adopted the improved Inception V3 model, the bidirectional long short-term memory network (BiLSTM) model with multi-head attention, and geographic information system (GIS) technology to recognize basic tourist feature information from the UGC dataset, such as the content, sentiment, and spatiotemporal perceptual dimensions of the data, achieving a recognition accuracy of over 97%. Finally, a progressive dimension combination method was proposed to visualize and analyze multiple perceptions. An experimental case study demonstrated the strategy's effectiveness, focusing on tourists' perceptions of Datong, China. Experimental results show that the approach is feasible for studying tourist destination perception. Content perception, sentiment perception, and the perception of Datong's spatial and temporal characteristics were recognized and analyzed efficiently. This study offers valuable guidance and a reference framework for selecting methods and technical routes in tourist destination perception. [ABSTRACT FROM AUTHOR]

It is significant to research the ecological risk of land use landscape to promote ecological conservation and restoration. The characteristics of land use dynamic change in Baili Rhododendron National Forest Park were analyzed based on GlobeLand30 data for three periods in 2000, 2010 and 2020. With the support of the landscape ecological risk evaluation model and spatial analysis methods, the features of spatial and temporal differentiation of ecological risk and its spatial correlation in the study area were evaluated. The results show that (1) the landscape pattern changed visibly from 2000 to 2020, the comprehensive land-use dynamics increased from 8.53% to 9.66%, and the land use dynamics are greatest and change most dramatically on construction sites; (2) the landscape ecological risk level of the study area as a whole showed a declining trend, and 96.82% of the ecological risk plot index decreased, and the risk distribution was dominated by lower risk, medium risk and higher risk areas; (3) landscape ecological risk was spatially positively correlated across all time periods, and the spatial aggregation was gradually weakened, with the distribution of LH and HL areas dispersed and the distribution of HH and LL areas concentrated. The overall landscape ecological risk index has witnessed a decline, indicating a positive trajectory in the development of the ecological environment. [ABSTRACT FROM AUTHOR]

Influenced by urban expansion, population growth, and various socio-economic activities, land use in the Yangtze River Delta (YRD) area has undergone prominent changes. Modifications in land use have resulted in adjustments to ecological structures, leading to subsequent fluctuations in carbon storage. This study focuses on YRD region and analyzes the characteristics of land use changes in the area using land use data from 2000 to 2020, with a 10-year interval. Utilizing InVEST Model's Carbon Storage module in combination with PLUS model (patch-generating land use simulation), we simulated and projected future land use patterns and carbon storage across YRD region under five scenarios including natural development (ND), urban development (UD), ecological protection (EP), cropland protection (CP), and balanced development (BD). Upon comparing carbon storage levels predicted for 2030 under the five scenarios with those in 2020, carbon stocks decrease in the initial four scenarios and then increase in the fifth scenario. In the initial four declining scenarios, CP scenario had the least reduction in carbon storage, followed by EP scenario. The implementation of policies aimed at safeguarding cropland and preserving ecological integrity can efficaciously curtail the expansion of developed land into woodland and cropland, enhance the structure of land use, and mitigate the loss of carbon storage. [ABSTRACT FROM AUTHOR]

To offer a foundational science for the land spatial planning of Beijing Tianjin sandstorm source area, the remote sensing images of Duolun County in Inner Mongolia from 2000 to 2020 were used to obtain the spatial information of production, living and ecological space(PLES). In order to construct the index system of the carrying capacity of the PLES, 24 indicators were chosen from the perspectives of ecological space, living space, and production space. AHP method, TOPSIS Model with entropy combination weight, coupling coordination model and obstacle degree model are used to analyze the coupling coordination scheduling and obstacle degree of the PLES carrying capacity. The findings exhibited that (1) the distribution area of ecological space and production space decreased, while the living space area increased slightly; (2) The carrying capacity of production space showed a weak growth trend, the carrying capacity of production space, living space and the PLES space showed a weak downward trend; (3) The coupling degree and coupling coordination degree between two spaces show a slow downward trend; (4) The obstacle degree of the carrying capacity of production space and living space has increased, while the carrying capacity of ecological space is decreasing. Livestock carrying capacity is the most important obstacle restricting the carrying capacity of production space. The scale of construction land has the greatest obstacle to the carrying capacity of living space, the degree of desertification has the greatest obstacle to the carrying capacity of ecological space, and soil organic matter has the greatest obstacle to the comprehensive carrying capacity of the PLES. [ABSTRACT FROM AUTHOR]

Based on the analysis of the spatiotemporal evolution characteristics of producer services agglomeration and urban green development efficiency in China, this study measures the influence and spatial spillover effects of producer services agglomeration on urban green development. Research results reveal that the specialization agglomeration level of producer services has undergone a dynamic decline process, demonstrating spatial characteristics where the east exhibits higher levels than the west, and the north surpasses the south. In contrast, the diversification agglomeration level of producer services has demonstrated a consistent upward trajectory, characterized by a spatial distribution that is broadly scattered but concentrated on a smaller scale. Regarding China's urban green development, its efficiency shows a dynamic upward trend and displays characteristics of agglomeration and contiguous development in space. Overall, both modes of producer services agglomeration have beneficial diffusion impacts on urban ecological advancement. Furthermore, the impact of this agglomeration on the efficiency of green development notably varies across regions and industries. [ABSTRACT FROM AUTHOR]

Given the multitude of risks and challenges faced by the water ecological environment during urbanization, enhancing water ecological resilience and improving the water ecological environment have emerged as crucial topics in China's economic and social development, as well as its ecological civilization construction. This study proposes a research hypothesis on the relationship between new urbanization and water ecological resilience. Employing various econometric models such as the extended STIRPAT model, dynamic panel model, panel threshold effect model, dynamic panel mediating effect model and dynamic panel difference-in-difference model, empirical tests were conducted to examine the impact of new urbanization on water ecological resilience in central China. The findings indicate that: (1) there exists a U-shaped curve relationship with a threshold effect between new urbanization and water ecological resilience; this conclusion remains valid even after conducting several robustness tests including extreme value treatment, re-measurement of independent variables, and replacement of econometric models. (2) In regions with lower levels of new urbanization, new urbanization exerts more significant stress effect on water ecological resilience through economic scale effect, population scale effect, investment pulling effect and foreign trade effect; whereas in regions with higher levels of new urbanization, new urbanization exerts more significant positive effect on water ecological resilience through factors agglomeration effect, technological progress effect, human capital effect, industrial structure effect and marketization effect. (3) Compared to non-pilot cities, the implementation of comprehensive pilot policies for new urbanization has significantly improved the water ecological resilience of cities in central China and the promotion of new urbanization of pilot cities contributes to enhancing water ecological resilience. [ABSTRACT FROM AUTHOR]

To gain a scientific understanding of the cross-system impact of coastal zones and promote the sustainable development and protection of coastal areas, we constructed a spatial benefit evaluation system that encompassed both terrestrial and marine systems, focusing on the ecological, economic, and social dimensions. We employed the entropy method, moving average method, and Mann-Kendall trend test to quantitatively characterize the spatial benefits of the coastal zone in Fujian Province, China, and the evolution of the marine climate from 2005 to 2020. Building on this, the grey relational analysis method was applied to investigate the correlation between spatial benefits and marine climate and to explore the trends and magnitude of the impact of marine climate on spatial benefits. During the study period, the spatial benefits of the coastal zone in Fujian Province exhibited a fluctuating pattern of an initial increase followed by a decrease, with spatial benefits varying among cities. The role of the economic system in enhancing spatial benefits was not considerable. Changes in the marine climate aligned with the global warming trend, with the most considerable changes observed in sea level and tropical cyclone frequency and intensity, which are sensitive to human activities. There was a high degree of correlation between coastal zone spatial benefits and marine climate, with seawater salinity being most closely related to spatial benefits, while tropical cyclones showed the weakest correlation. The results of this study support sustainable development efforts in coastal zones. [ABSTRACT FROM AUTHOR]

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang. [ABSTRACT FROM AUTHOR]

In this work we show how global self-organized patterns can come out of a disordered ensemble of point oscillators, as a result of a deterministic, and not of a random, cooperative process. The resulting system dynamics has many characteristics of classical thermodynamics. To this end, a modified Kuramoto model is introduced, by including Euclidean degrees of freedom and particle polarity. The standard deviation of the frequency distribution is the disorder parameter, diversity, acting as temperature, which is both a source of motion and of disorder. For zero and low diversity, robust static phase-synchronized patterns (crystals) appear, and the problem reverts to a generic dissipative many-body problem. From small to moderate diversity crystals display vibrations followed by structure disintegration in a competition of smaller dynamic patterns, internally synchronized, each of which is capable to manage its internal diversity. In this process a huge variety of self-organized dynamic shapes is formed. Such patterns can be seen again as (more complex) oscillators, where the same description can be applied in turn, renormalizing the problem to a bigger scale, opening the possibility of pattern evolution. The interaction functions are kept local because our idea is to build a system able to produce global patterns when its constituents only interact at the bond scale. By further increasing the oscillator diversity, the dynamics becomes erratic, dynamic patterns show short lifetime, and finally disappear for high diversity. Results are neither qualitatively dependent on the specific choice of the interaction functions nor on the shape of the probability function assumed for the frequencies. The system shows a phase transition and a critical behaviour for a specific value of diversity. [ABSTRACT FROM AUTHOR]

The health of older adults is crucial for the overall health of the entire life cycle. Based on population sampling survey data and census data from 131 prefecture level units in the Yangtze River Economic Belt (YREB) during 2010–2020, this study used exploratory spatial data analysis, geographical detector, stepwise regression analysis, and GTWR model to analyze the spatiotemporal pattern and influencing factors of the health level of older adults in the YREB. The results show that the health level of older adults in the YREB slightly increased from 2010 to 2020, with the most significant improvement in the upstream region and the most significant decline in the midstream region. The older adults' health level in the YREB displays a gradient decreasing pattern of the downstream, midstream, and upstream regions. The health level of older adults in the YREB is influenced by a combination of natural and social environment factors. Areas with lower altitude and moderate humidity climates are more conducive to the health of older adults. The increase in influencing factors such as population migration rate, per capita GDP, average years of education, per capita housing construction area, per capita park green area, and green coverage rate in built-up areas is conducive to improving the health level of older adults, while lower number of health institutions per 1,000 people and higher household support rate are not conducive to improving the health level of older adults. In addition, over time, the health-promoting effect of natural environmental factors is enhanced from 2010 to 2020, and the influence of annual precipitation on shaping the spatial pattern of older adults' health level became more obvious. Although the promoting effect of population migration on the health level of older adults tends to weaken, it remains the primary factor affecting the spatiotemporal differentiation of older adults' health level in the YREB. The impact of social development on the health level of older adults has changed from a positive health effect (improvement) to a negative health effect (loss). The health-promoting effect of living environment factors is enhanced. The health-inhibitory effect of household support rate increased, and showed a gradient decreasing pattern from downstream to midstream to upstream. The findings of this study can provide a more in-depth understanding of the spatiotemporal pattern of the health level of older adults in the YREB and the factors influencing it, improve the health level of older adults in the region, and promote the development of healthy and active aging in the YREB, and improve the human health. At the same time, this study also supplements the related research on aging and the health level of the elderly. Firstly, it can provide reference for the research on the health of old adults in other countries and regions around the world. Secondly, it can also provide a basis for research on aging and the health of old adults in cities and counties under YREB. [ABSTRACT FROM AUTHOR]

The impact of logistics development on the economy covers many aspects, such as production, cost, employment, international trade, etc. It is an indispensable part of the modern economy, which helps to improve overall economic efficiency and social prosperity. This study studies the spatiotemporal dynamic evolution characteristics of China's logistics development from 2008 to 2018 and explores its impact on economic growth in multiple dimensions of time and space. The research findings indicate the following: (1) From 2008 to 2018, China's logistics development level (LDL) exhibited a clear upward trend. The differences between the eastern, central, and western regions showed fluctuating downward patterns, ultimately converging towards a high-level concentration. Concerning spatial distribution, China's logistics development demonstrated a trend towards the west and south. However, the spatial pattern of "strong in the east and weak in the west " has existed for a long time. Moreover, the "T-shaped" pattern between coastal provinces and those along the Yangtze River Basin deepened, and the LDL in the central and western regions significantly improved. (2) The advancement of China's LDL effectively promotes its economic growth, confirming that the Belt and Road Initiative enhances the role of logistics development in driving economic growth. Regarding regional differences, logistics development positively influences economic growth in the eastern and western regions, with a less significant impact on the central region. Regarding the strength of influence, logistics development has a more substantial effect on promoting high-ranking provinces in the entire country, the eastern region, and the central region, as well as boosting economic growth in low-ranking provinces in the western region. [ABSTRACT FROM AUTHOR]

The green economy has been advocated globally as a solution to environmental issues. In China, it is considered a national strategy for future economic development. This study utilizes methods such as Industry Network, Maximum Spanning Tree (MST) method, Leiden Community Clustering (LCC) algorithm, and Weaver-Thomas (WT) model to explore the contribution and position of the green economy and industries in China's economic development. The findings are as follows: (1) The density of China's green industry network has experienced a process of initially tightening and then loosening, ultimately tending towards stability. (2) The trunk structure of China's industrial network remains relatively stable, forming an industrial structure with electricity, heat production and supply as the core. (3) China's industrial and green industry communities continue to improve and become more cohesive, but some green industries are still on the periphery of communities. (4) The ability of green industries to pull other industries is weak, and the subsequent promotion momentum needs to be improved. However, the green industry still has enormous room for growth and potential to unleash its long-term positive multiplier effects. More attention and support need to be given by managers and decision-makers, so that it can make better contributions to society and the economy. [ABSTRACT FROM AUTHOR]

Logistics resilience is a significant representation of sustainable development ability and a necessary support for high-quality economic development. In order to explore the influencing factors and realization mechanism of the improvement of logistics resilience of the Yangtze River Economic Belt and the high-quality and sustainable development of the economy, this paper comprehensively considers factors of the supply and demand relationship of the logistics market, industrial structure and ecological environment, and evaluates the urban logistics resilience of the Yangtze River Economic Belt by using POI data and statistical data. Combined with the spatial Durbin model, the influencing factors and spatial spillover effects of inter-city logistics resilience were revealed. This study found that the urban logistics resilience in the lower reaches of the Yangtze River has been high. Except Chongqing and Shanghai, the COVID-19 epidemic happened in 2020 led to a significant decrease in logistics resilience. In the meanwhile, every 1% increase in the logistics resilience of the city will promote the logistics resilience of the adjacent cities by 0.145%. Economic condition and urban development potential have positive effects on logistics resilience of the city and its adjacent cities. The economic condition has a direct effect coefficient of 0.166 and an indirect effect coefficient of 0.181, The direct and indirect effects of urban development potential are significantly positive, and the coefficients are 0.001 and 0.006, respectively. The level of information, government support and ability of technological innovation are helpful for the improvement of urban logistics resilience while hindering the enhancement of logistics resilience in adjacent cities. The research area can be extended in the future and more influencing factors can be considered in the future. [ABSTRACT FROM AUTHOR]

Lithium has broad applications in several emerging industries and fields, including high energy batteries, energy storage, aerospace, and controlled nuclear reactions. Currently, the discrepancy between the supply and demand for lithium resources increases, and its distribution is uneven. Within the framework of the "Belt and Road" Initiative, the lithium trade pattern evolves constantly. However, the trade pattern of lithium in the nations along the "Belt and Road" is likely to face substantial repercussions in modern world of unilateral protectionism and geopolitical conflicts. Taking the social network analysis approach as a tool, this study first examines the characteristics of the lithium trade network structure as it has evolved over the years in the Belt and Road countries, from 2000 to 2022. Additionally, this study uses the quadratic assignment problem approach to analyze the factors influencing the evolution of the lithium trade network. The study shows that: (1) The spatial patterns of import and export trade network of lithium in countries along the route has a certain path dependence. And the market is mainly concentrated in East Asia, Central and Eastern Europe, South America and Southeast Asia. (2) The network density of the countries along the route has increased year after year, but it remains low. And the fluctuation of the network's reciprocity has increased, with a huge magnitude of variation. The number of core countries in the network has decreased over time, but the core-periphery structure has stayed largely steady. China, Chile, and South Korea are the network's main node countries. (3) Regarding the influencing factors, the differences in economic and technological development between these countries have a beneficial impact on the formation of lithium trade; whether or not regional trade agreements have been signed, the differences about average tax rates for mineral products, bordering countries, and similar languages and cultures are all conducive to the establishment of close trade links. The contribution of this essay is of paramount importance for understanding different countries' role along the Belt and Road in the lithium trade network pattern, and promoting regional trade cooperation. [ABSTRACT FROM AUTHOR]

In the digital era, digital economy has a far-reaching impact on the collaborative agglomeration of manufacturing and service industries. This research aims to examine the economic relationship between digital economy and industrial collaborative agglomeration. Based on a panel data set of 286 Chinese cities, this research employs Tobit model, moderating effect model, and mediating effect model to conduct data analysis. It is found that digital economy has a nonlinear relationship with industrial collaborative agglomeration, and this relationship is a U-shape. Moderating effect analysis reveals that government intervention significantly regulates the role of digital economy in industrial collaborative agglomeration. Mediating effect analysis indicates that digital economy promotes industrial collaborative agglomeration through entrepreneurial activity. Heterogeneity analysis shows that the facilitating effect of digital economy on collaborative agglomeration in high-end industries comes earlier than in middle- and low-end industries. Moreover, this research finds that digital economy plays a significant role in industrial collaborative agglomeration in central and western regions of China but not in the eastern region. To enhance the impact of digital economy on industrial collaborative agglomeration, it is crucial to strengthen the engagement of the government and ensure the availability of digital technology. [ABSTRACT FROM AUTHOR]

Introduction: Physical health is fundamental to a country's socio-economic advancement. An in-depth exploration of the spatial distribution and dynamic evolution of national physical fitness across China is crucial for enhancing the country's overall physical health. This study aims to provide valuable insights into the geographical and temporal patterns of physical fitness, informing strategies for national physical fitness improvement. Methods: Employing data from China's national physical fitness monitoring of 31 provinces, cities, and districts for the years 2005, 2010, and 2015, this study utilizes the Gini coefficient, its decomposition, and nonparametric density estimation methods. These techniques are applied to analyze the spatial disparities and temporal trends in national physical fitness levels among different demographics, including the overall population, males, females, and urban and rural residents. Results: The study reveals that the regional disparity in China's national physical fitness initially narrowed and then expanded across the general population, females, and in both urban and rural areas, while consistently increasing among males. In terms of geographical distribution, the East, Middle, and West regions show significant heterogeneity, with the East-West gap being the most pronounced (Gini coefficients of 0.0249, 0.0230, 0.0263). The contribution rate of regional gaps was highest (54.40% -64.69%), followed by regional disparities (24.78% -27.15%), and the contribution of hypervariable density difference was the smallest (10.53% -19.75%). Despite a slight improvement in overall national physical fitness, the absolute regional disparities have further widened. Conclusions: Provinces with lower levels of national physical fitness demonstrate a 'club convergence' trend, indicating regional clustering of similar fitness levels. Additionally, a 'catch-up effect' is evident in rural areas, particularly in provinces with historically lower levels of national physical fitness. These findings suggest the need for region-specific public health strategies to address the growing disparities in national physical fitness across China. [ABSTRACT FROM AUTHOR]

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) represents a significant economic zone with a diverse financial landscape. Understanding the spatial distribution of financial resources within this area is crucial for promoting balanced economic growth and financial development. This study investigates the spatial patterns of financial agglomeration in the GBA, identifying key influencing factors and assessing their impact on the region's financial landscape. We employ the entropy value method to evaluate financial agglomeration levels across the GBA's cities. Additionally, we use spatial econometric techniques to analyze the spatial correlations and the Geo-Detector model to determine the primary factors influencing financial agglomeration. The analysis reveals an overall increase in financial agglomeration, with significant disparities among cities. Key factors driving this agglomeration include transportation infrastructure, overseas trade, foreign direct investment (FDI), and technological advancements. Hong Kong and Shenzhen display notable unevenness in the distribution of financial industries. The interplay between finance, technology, and industrial sectors suggests considerable development potential. Understanding and optimizing the spatial distribution of financial resources is essential for fostering high-quality financial development and sustainable economic growth in the GBA. This study provides insights that can inform policy decisions aimed at enhancing financial integration and cooperation within the region. [ABSTRACT FROM AUTHOR]

In the process of hikers' choosing a destination, searching for information is one of the important elements, playing a decisive role in decision-making. Based on the Baidu Index for "hiking," this paper analyzes the spatial and temporal characteristics of and factors that influenced network attention to hiking in China from 2016 to 2021. The study found that (1) Network attention to hiking in China was generally relatively stable across the period studied, with highly uneven distribution between different months. The search volume was higher on weekends, and mobile searches increased year by year, far exceeding computer searches. (2) Different regions in China experienced different levels of network attention, with the highest levels in the east, followed by the center, and the lowest in the west. Except for East China, network attention to hiking was highly unevenly distributed within each region. (3) The COVID-19 pandemic increased the geographical concentration index and coefficient of variation but reduced the primacy index. A region's level of economic development, degree of network development, population size, and population age structure are proposed as factors that affect network attention to hiking. [ABSTRACT FROM AUTHOR]

Rural civilization is the soul of rural revitalization strategies. As a booster of rural civilization, the civilized village is an indispensable force to promote the modernization of rural areas, in the meanwhile, the study of its spatial distribution has important theoretical significance and practical value in deepening the theory of rural geography, promoting the development of rural civilization, and helping rural revitalization. Considering civilized villages as the study topic, the spatial and temporal distribution characteristics and geographic context were discussed using spatial analysis methods. The number of civilized villages in the country has shown a clear upward trend since 2005. The spatial distribution pattern of civilized villages in China shows unbalanced patterns with a higher concentration in the east and south. Civilized villages in China present significant patterns of clustering with an increasing degree of spatial clustering, showing a multi-core spatial distribution pattern. Civilized villages in China demonstrate clear spatiotemporal clustering characteristics. A spatiotemporal hot spot cluster formed in the northwestern region from 2005 to 2011, and a spatiotemporal cold spot cluster formed in the southeastern region from 2005 to 2008. The spatial distribution of civilized villages in China has obvious geographical differentiation laws, and factors such as topography, climate, economy, transportation, and policy significantly affect their spatial distribution. [ABSTRACT FROM AUTHOR]

Purpose: The National Fitness Plan (NFP) is a vital initiative aimed at realizing Healthy China 2030. This study assessed spatial heterogeneity in the NFP development and the socioeconomic factors contributing to this inequality. Methods: Data from 31 administrative regions in 2021 were analyzed using four NFP development metrics. Spatial autocorrelation was evaluated using global Moran's I, followed by global and local regression models for non-random spatial patterns. Results: National physical fitness exhibited significant clustering (z = 5.403), notably a high-high cluster in East China. The global regression model identified three socioeconomic factors in the geographically weighted regression model: per capita disposable income and the number of public buses positively affected national physical fitness, while general public budget expenditure had a negative impact. Conclusions: Persistent unequal NFP development is projected due to income disparities in economically backward regions. To promote the NFP effectively, a cost-efficient strategy includes creating 15-minute fitness circles, especially by establishing public sports facilities in Western China communities. These findings inform policy priorities for advancing the NFP towards Healthy China 2030. [ABSTRACT FROM AUTHOR]

The transfer of land plays a crucial role in revitalizing land resources, acting as a catalyst for promoting the high-quality development of agriculture. The land transfer ratio is a crucial metric for assessing the progress of rural land transfer and the effective allocation of rural land resources. Thus, this study examines the rural land transfer ratio across 30 provinces in China from 2005 to 2020. The study explores the distribution characteristics of the ratio using the rank-size rule and trend surface analysis. The LISA space-time transition method is employed to analyze the spatial and temporal dynamics of the rural land transfer ratio and examine its convergence. The study aims to comprehensively analyze the spatial distribution characteristics and evolutionary patterns of rural land transfer in China, illustrating the convergence and influencing factors during the development process. The results indicate that: (1) The rural land transfer ratio in China is generally increasing, with a spatial pattern showing an upward trend from west to east and from north to south. The main spatial contrast is between the eastern and western regions, with a relatively minor distinction between the southern and northern regions. (2) The LISA space-time transition highlights a significant spatial locking effect in China's rural land transfer ratio, suggesting strong spatial integration in its evolution. (3) Clear indications of σ convergence, absolute β convergence, and club convergence are evident in China's rural land transfer ratio. This suggests a gradual reduction in internal disparities among provinces and regions, where areas with higher land transfer ratios influence spatial spillover effects on adjacent lower areas. (4) Factors such as transportation infrastructure, irrigation, water conservancy construction, and farmers' per capita income collectively influence the spatial and temporal evolution of China's rural land transfer ratio, with dominant driving factors varying across different periods. [ABSTRACT FROM AUTHOR]

Based on the background of urbanization in China, we used the dynamic spatial panel Durbin model to study the driving mechanism of ozone pollution empirically. We also analyzed the spatial distribution of ozone driving factors using the GTWR. The results show that: i) The average annual increase of ozone concentration in ambient air in China from 2015 to 2019 was 1.68μg/m3, and 8.39μg/m3 elevated the year 2019 compared with 2015. ii) The Moran's I value of ozone in ambient air was 0.027 in 2015 and 0.209 in 2019, showing the spatial distribution characteristics of "east heavy and west light" and "south low and north high". iii) Per capita GDP industrial structure, population density, land expansion, and urbanization rate have significant spillover effects on ozone concentration, and the regional spillover effect is greater than the local effect. R&D intensity and education level have a significant negative impact on ozone concentration. iv) There is a decreasing trend in the inhibitory effect of educational attainment and R&D intensity on ozone concentration, and an increasing trend in the promotional effect of population urbanization rate, land expansion, and economic development on ozone concentration. Empirical results suggest a twofold policy meaning: i) to explore the causes behind the distribution of ozone from the new perspective of urbanization, and to further the atmospheric environmental protection system and ii) to eliminate the adverse impacts of ozone pollution on nature and harmonious social development. [ABSTRACT FROM AUTHOR]

Agricultural ecological efficiency is an important tool with which to measure the coordination of the sustainable development of agricultural economies and ecological environments. In this paper, a super-efficiency slacks-based measures model was used to measure the agricultural ecological efficiency in Hebei Province. The characteristics of spatial and temporal evolution patterns were explored using a spatial Markov transfer matrix. The results showed that (i) based on measurements, the agricultural ecological efficiency in Hebei Province showed regional differences in four regions (eastern, northern, central and southern Hebei) and 141 counties; (ii) from the perspective of evolutionary characteristics of agricultural ecological efficiency, the overall development of in Hebei Province was good, with more concentrated spatial distribution and more obvious direction, while the type of transfer of agricultural ecological efficiency in Hebei Province showed strong stability that was significantly affected by geographical neighborhood conditions and the club convergence phenomenon; (iii) from the perspective of the long-term evolutionary trend of agricultural ecological efficiency, the areas adjacent to counties with low efficiency had limited potential for improvement, and the areas adjacent to counties with high grade had great potential. However, it was difficult to achieve large-scale improvement in agricultural ecological efficiency in Hebei Province, whether the impact of geospatial backgrounds was considered or not. [ABSTRACT FROM AUTHOR]

Food security is a goal and means of global sustainable development, and an important component of China's national security. Based on grain production data from 2000 to 2020, 31 provinces (cities, autonomous regions) in China were used as research units to analyze the spatiotemporal differences and driving forces of grain production in China using a combination of local correlation index, center of gravity transfer model, and geographic detector. The results as follows, ① During the research period, China's total grain production showed a decrease followed by an increase, and the yield per unit area of grain showed an increasing trend. Corn has become the "largest staple food" in China; ② During the research period, the focus of China's grain production continued to shift northward, with Heilongjiang, Henan and Shandong provinces becoming the main grain production areas, with Henan being the province where China's grain production center was located. Among the factors affecting grain yield, the effective irrigation area (0.971) has the strongest explanatory power. Finally, countermeasures and suggestions were proposed from five aspects, stabilizing grain production, reducing grain inventory pressure, implementing regional grain security responsibilities, improving grain circulation efficiency, promoting high-quality grain engineering construction, adjusting grain production structure, strictly implementing farmland protection responsibilities, scientifically applying pesticides, fertilizers and other production materials, emphasizing agricultural infrastructure construction and stabilizing the number of agricultural labor force. [ABSTRACT FROM AUTHOR]

Because the complexity of the external environment has put great pressure on the agricultural economy, making it vulnerable, it is necessary to promote a system of resilience in the agricultural economy so that Chinese agriculture can continue to persevere in the face of serious external uncertainties. Therefore, this paper investigates the spatio-temporal pattern and evolution of the distributional dynamics of China's county-level agricultural economic resilience based on 2000–2020 data covering 2,545 counties. The results are as follows: first, from 2000 to 2020, the mean value of China's county-level agricultural economic resilience showed an obvious upward trend, which indicates that China's agricultural economy gradually increased its ability to resist risks and continued to develop in a favourable manner. Specifically, the county-level agricultural economic resilience index of the northeast region grew the most significantly, while the index of county units in the western region was relatively low. Second, the centre of gravity of the spatial distribution of China's agricultural economic resilience gradually migrated to the northwest, showing a dominant direction from northeast to southwest and a tendency to develop from southeast to northwest. Third, the spatial differences in China's agricultural economic resilience generally showed an upward trend, while county-level differences were the main source of the overall differences, followed by inter-provincial differences, inter-municipal differences and inter-regional differences. Additionally, the contribution of county-level differences to the overall differences fluctuated within the range of 54%-58%. Fourth, there is a possibility of localized convergence in China's agricultural economic resilience, which is continuous in spatial effects and has obvious positively correlated spatial effects at different times and in different county spaces. [ABSTRACT FROM AUTHOR]

Sexual dimorphism is common throughout the animal kingdom, leading to sex-specific phenotypic differences. The common whitetail skimmer dragonfly, Plathemis lydia (Drury, 1773), is sexually dichromatic, where males of this species display a conspicuous white abdomen and females display a dark brown abdomen. Differences in abdomen conspicuousness between male and female P. lydia are likely attributed to differences in selective pressure where males use their white conspicuous abdomen during male-male territorial chases. We hypothesized that male P. lydia would exhibit wing morphology adaptations to better offset the costs of predation and territoriality and that these adaptations would differ from females. We used field-collected images to quantify differences in body length, wing length, wing area, wing shape, and wing loading between male and female P. lydia. Our results show that male P. lydia have significantly shorter fore and hind wings relative to body size with a higher wing loading when compared to females. We also found that male P. lydia have narrower and pointier fore and hind wings compared to females. These results are consistent with the idea that males are adapted for faster flight, specifically higher acceleration capacity, and higher agility whereas females are adapted for higher maneuverability. [ABSTRACT FROM AUTHOR]

Based on panel data from 2009 to 2021, covering 30 provinces in China, we have been constructed the Rural Financial Risk Index using the objective entropy weighting method to study rural financial risk in China systematically from the perspective of spatial distribution. Specifically, we discuss the spatial distribution, regional differences and dynamic evolution of rural financial risk across Chinese four different regions divided into the Northeast, East, Central and West. It's found that Local government debt and Land transfer income are the two primary determinants influencing the level of rural financial risk in China. Furthermore, we conclude the ranking value of rural financial risk across four regions that the central exhibits the highest level, followed by the West, the East, and finally the Northeast, where the reasons for such ranking results as follows. Firstly, although the highest level of risk among provinces in the West is equivalent to that in the Central, there exists a smaller minimum rural financial risk in the former compared to the latter. Then, it should be noted that there's a low-low agglomeration of rural financial risk in the Northeast, while it demonstrates a high-high agglomeration in the Central according to the Moran Index test analysis. Again, there's a declining trend in rural financial risk disparity within the region and an upward trend is observed when comparing different regions (except the East vs West), especially increase largely between the Northeast and Central in past two years after analyzing the decomposition of Dagum Gini coefficient. Moreover, we study the absolute differences and dynamic evolution in different four regions through three-dimensional diagram of kernel density estimation, and it's found that the change of rural financial risk in four regions moved to the right as a whole, while the tail distribution remains inconspicuous. The absolute difference is diminishing in the Northeast, and the two-level differentiation characteristics tend to weaken as a whole in the Central, with a disordered wave peak height observed in both the East and West. Finally, the article presents pertinent policy implications but limitations according to the research findings. [ABSTRACT FROM AUTHOR]

China eliminated rural poverty under current poverty standards in 2020. However, compared with rural poverty, urban poverty in China has been somewhat neglected. This paper aims to discover the changes and determinants of multidimensional urban poverty in Shandong Province, a representative province in Eastern China. Using a nationally representative panel dataset, the China Family Panel Studies, and the Dual Cutoff method, this study creates a multidimensional poverty index with four dimensions and 11 indicators to measure urban poverty in Shandong Province. This paper discovers that while the incidence of multidimensional urban poverty in Shandong Province decreased from 47.62% in 2010 to 36.45% in 2018, the intensity of multidimensional poverty only decreased from 41.27% to 37.25%, which indicates the inadequacy of urban anti-poverty efforts in Shandong Province. This paper also uses logistic regression to identify the determinants of multidimensional urban poverty. The findings suggest that income, health, drinking water, and durable goods are the main determinants of multidimensional urban poverty in Shandong Province. Based on these findings, this study provides targeted recommendations for future urban anti-poverty policies in Shandong Province. [ABSTRACT FROM AUTHOR]

Camouflage is a widespread and well-studied anti-predator strategy, yet identifying which patterns provide optimal protection in any given scenario remains challenging. Besides the virtually limitless combinations of colours and patterns available to prey, selection for camouflage strategies will depend on complex interactions between prey appearance, background properties and predator traits, across repeated encounters between co-evolving predators and prey. Experiments in artificial evolution, pairing psychophysics detection tasks with genetic algorithms, offer a promising way to tackle this complexity, but sophisticated genetic algorithms have so far been restricted to screen-based experiments. Here, we present methods to test the evolution of colour patterns on physical prey items, under selection from wild predators in the field. Our techniques expand on a recently-developed open-access pattern generation and genetic algorithm framework, modified to operate alongside artificial predation experiments. In this system, predators freely interact with prey, and the order of attack determines the survival and reproduction of prey patterns into future generations. We demonstrate the feasibility of these methods with a case study, in which free-flying birds feed on artificial prey deployed in semi-natural conditions, against backgrounds differing in three-dimensional complexity. Wild predators reliably participated in this experiment, foraging for 11 to 16 generations of artificial prey and encountering a total of 1,296 evolved prey items. Changes in prey pattern across generations indicated improvements in several metrics of similarity to the background, and greater edge disruption, although effect sizes were relatively small. Computer-based replicates of these trials, with human volunteers, highlighted the importance of starting population parameters for subsequent evolution, a key consideration when applying these methods. Ultimately, these methods provide pathways for integrating complex genetic algorithms into more naturalistic predation trials. Customisable open-access tools should facilitate application of these tools to investigate a wide range of visual pattern types in more ecologically-relevant contexts. [ABSTRACT FROM AUTHOR]

Understanding the evolution of rural landscapes in metropolises during rapid urbanization is crucial for formulating policies to protect the rural ecological environment. In this study, remote sensing and geographical information system data, as well as applied landscape index analysis, are used to examine the spatiotemporal evolution of rural landscape patterns in the Beijing-Tianjin region of China, which has experienced rapid urbanization. The relationships between land use/land cover changes and changes in rural landscape patterns are explored. The results revealed significant spatial differences in the rural landscapes in the Beijing-Tianjin region; farmland and forestland were the main types of landscapes, creating a "mountain-field-sea" natural landscape pattern. The conversion of rural landscapes in the Beijing-Tianjin region involved mainly the conversion of farmland to urban areas, with few exchanges between other landscape types. The urban areas in the Beijing-Tianjin region increased by 3% per decade; farmland decreased at the same rate. Additionally, the rural landscape patterns in the Beijing-Tianjin region were dominated by fragmentation, dispersion, and heterogeneity and moved from complex to regular. Water bodies displayed the most fragmented natural landscape; their number of patches increased by 36%, though their network characteristics were maintained. Forestland was the most concentrated natural landscape. In this study, theoretical support and a scientific reference for the optimization of rural landscape patterns and the improvement in rural living environments in rapidly urbanizing areas are provided. [ABSTRACT FROM AUTHOR]

An in-depth study of the mechanisms governing the generation, evolution, and regulation of differences in tourism economics holds significant value for the rational utilization of tourism resources and the promotion of synergistic tourism economic development. This study utilizes mathematical statistical analysis and GIS spatial analysis to construct a single indicator measure and a comprehensive indicator measure to analyze tourism-related data in the research area from 2004 to 2019. The main factors influencing the spatial and temporal differences in the tourism economy are analyzed using two methods, namely, multiple linear regression and geodetector. The temporal evolution, overall differences and differences within each city group fluctuate downwards, while the differences between groups fluctuate upwards. Domestic tourism economic differences contribute to over 90% of the overall tourism economic differences. Spatial divergence, the proportion of the tourism economy accounted for by spatial differences is obvious, the comprehensive level of the tourism economy can be divided into five levels. The dominant factors in the formation of the pattern of spatial and temporal differences in the tourism economy are the conditions of tourism resources based on class-A tourist attractions and the level of tourism industry and services based on star hotels and travel agencies. This study addresses the regional imbalance of tourism economic development in city clusters and with the intent of promoting balanced and high-quality development of regional tourism economies. [ABSTRACT FROM AUTHOR]

Ports are critical centers of international trade and global logistics now that economic globalization has taken hold. The efficiency performance of port logistics is crucial to building an emerging pattern of development in which domestic and foreign dual cycles are complementary for China. This paper examines the efficiency performance of 19 ports within five major economic circles in China. It explores how their efficiency is distributed, and the configurations of efficiency improvement during the new normal of China's economy. First, the DEA-BCC model is employed to calculate the technical efficiency performance and distribution of each port from 2011 to 2020. Then, fuzzy-set qualitative comparative analysis (fsQCA) was applied to integrate and analyze the influencing factors. The results show as follows: (1) Each port group performed differently on efficiency rankings, as well as regional distributions. Among these, the port groups of the Bohai Rim region, the Yangtze River Delta region, and the Bohai Rim region continue to rank highly. (2) From the perspective of configuration analysis, the results suggest that government support is not necessary for port logistics with better economic endowments. However, it is critical for backward ones. (3) A rational industrial structure can enhance levels of infrastructure, openness, and information technology, improving port performance. The findings can provide theoretical and practical references for better promoting the development of Chinese port management.al references for better promoting the development of Chinese port management. [ABSTRACT FROM AUTHOR]

Cultural products constitute a significant portion of global trade, and understanding their export patterns can shed light on economic trends, trade dynamics, and market opportunities. This study conducted the spatio-temporal analysis of exports of cultural products, exploring the relationship between various influencing factors and their impact on the spatial distribution of these exports. Leveraging a diverse dataset encompassing 55 BRI countries for the period of 2005–2022, this research employs advanced spatial analysis techniques, including spatial autocorrelation and spatial regression models, to examine the spatial patterns and determinants of exports if cultural product exports. Moreover, this study delves into the multifaceted determinants affecting the spatial distribution of these exports. The findings of this study reveal significant spatio-temporal variations in the exports of cultural products. Spatial autocorrelation analysis indicates the presence of spatial clustering, suggesting that regions with high cultural product exports tend to be geographically close to each other. The spatial regression models further identify several key factors like economic development, productive capacities, cultural tourism, information development and human capital influence the spatial distribution of these exports. The findings of the study reveal that there is strong spatial relationship for exports of cultural products in BRI countries. The findings of this research contribute valuable insights for policymakers, businesses, and stakeholders regarding a deeper comprehension of the driving forces behind the spatial distribution of these cultural products, facilitating informed decision-making processes to optimize strategies for promoting and sustaining the trade of cultural products in an increasingly interconnected world. [ABSTRACT FROM AUTHOR]

China's tourism economy has experienced significant regional disparities. However, little attention has been paid to understanding the intricate mechanisms through which the interplay of influential factors gives rise to such disparities. Utilizing statistical data from the tourism economy of 31 provinces in mainland China, this study investigates regional tourism economic disparity through the asymmetric modeling of fuzzy set qualitative comparative analysis (fsQCA). The findings reveal that the causes of regional tourism economic disparity exhibit asymmetry; varying approaches contribute to the formation of high and low levels of tourism economy; the functioning of the most influential factors is impacted by other antecedent conditions, presenting an asymmetric non-linear effect; favorable transportation convenience is a necessary condition for a high level of tourism economy, while poor tourism attraction is a necessary condition for a low level of tourism economy. This research not only introduces a fresh perspective on regional tourism economic disparities, enabling an in-depth comprehension of the complex interactions and nonlinear functional mechanisms of influential factors, but also explores a region-based tourism development model, offering valuable practical guidance for policymakers in the tourism sector. [ABSTRACT FROM AUTHOR]

Urbanization is an inevitable outcome of the development of human society to a certain stage, and it is also an irreversible pattern of the concentration degree of human society. Based on multi-source data such as remote sensing images, ecological environment and socio-economic data, the evaluation index system of new urbanization is constructed from multi-dimensions of population, economy, society, space and ecology. To explore the spatio temporal evolution and driving factors of urbanization in 80 prefecture-level cities in central China from 2013 to 2021 by using entropy method, spatial autocorrelation model and geographic detector. The results show that: (1) The level of new urbanization continues to grow, with the average value rising from 0.1562 in 2013 to 0.2557 in 2021, and the regional differences are obvious, forming a circle structure with Wuhan, Zhengzhou and other provincial capitals as the center and weakening radiation to surrounding cities. (2) The agglomeration of ecological urbanization is significant, and the agglomeration trend is gradually enhanced. The high-high agglomeration areas tend to Xinzhou City, most prefecture-level cities in Hubei Province and some prefecture-level cities in Southern Hunan Province, while the low-low agglomeration areas tend to Changzhi City, most prefecture level cities in Henan Province and some prefecture-level cities in Northern Anhui Province. (3) The night light index, total retail sales of consumer goods, investment in fixed assets, proportion of built-up areas and urban economic density are the main driving factors affecting the level of new urbanization. (4) The interaction of driving factors shows double factor enhancement and nonlinear enhancement effects. [ABSTRACT FROM AUTHOR]

Low-carbon is a part of China's efforts to pursue the national strategy of "carbon peaking and carbon neutrality." Meanwhile, the path of low-carbon transformation of logistics has become a topic of global concern. This study constructs a technical framework of logistics carbon emissions (LCE), which is composed of carbon emission evaluation, carbon emission prediction and low-carbon strategy. All 13 prefecture-level cities in Jiangsu, China, are the application objects in empirical research. Then, the influence analysis of the LCE efficiency based on the panel Tobit model and the evolution of LCE under different scenarios are explored. The results show that: (ⅰ) during the study period (2013–2020), the LCE in Jiangsu showed an overall upward trend, with Xuzhou, Suzhou and Nanjing being the cities with the highest carbon emissions; (ⅱ) the static efficiency of LCE in Jiangsu is at a medium level, with fluctuations in Suzhou, Changzhou, Zhenjiang, Nantong, and Suqian caused by the technical change index; (ⅲ) economic level, industrial structure, fixed asset utilization rate, and ecological environment in Jiangsu are significantly positively correlated with LCE efficiency, while education popularization and energy intensity are negative; (ⅳ) LCE in Jiangsu has been drastically reduced in the low-carbon scenario compared to the baseline scenario. On the above basis, this study proposes suggestions for the low-carbon development strategies of logistics in Jiangsu. [ABSTRACT FROM AUTHOR]

Although efficiency analysis could reflect the state and quality of tourism's economic development, no research has been conducted investigating the spatiotemporal evolution and mechanisms of county-level tourism efficiency. We quantified tourism efficiency and its decomposition in 63 counties of Zhejiang, employing the bootstrap data envelopment analysis (DEA), hot spot analysis, and quantile regression to explore the spatiotemporal evolution and influencing factors of tourism efficiency, and examine its driving and constraining mechanisms. The results uncovered obvious upward trends in the tourism efficiency of Zhejiang's counties, with the mean value increasing from 0.285 to 0.688. Compared with scale efficiency, the influence of technological efficiency on the growth of comprehensive efficiency increased remarkably. Significant differences were evident in the spatial distributions of the identified hot and cold spots of comprehensive efficiency, which were respectively distributed in northern and southern Zhejiang. The distributions of decomposition efficiency were found to be spatially dependent. The driving mechanism of tourism efficiency involve two driving influences and two constraining influences, including economy and resource driving, market and traffic driving, industry and traffic constraining, and market and industry constraining. The findings of this study contribute to understanding of tourism efficiency growth in regional destinations and provide insights for strategic policymaking in various counties of Zhejiang. [ABSTRACT FROM AUTHOR]

With economic progression in China, Yellow River Basin serves as a critical economic belt, which has also been recognized as a cradle of Chinese culture. A watershed is a complex structure of social, economic, and natural factors, and the diversity of its components determines its complexity. Studies on the spatiotemporal distribution characteristics and factors influencing the tourism eco-efficiency at the watershed scale are crucial for the sustainable regional socio-economic development, maintaining a virtuous cycle of various ecosystems, and comprehensively considering the utilization and coordinated development of various elements. Based on tourism eco-efficiency, the coordination degree of regional human–land system and the sustainable development levels can be accurately measured. With the tourism eco-efficiency in the Yellow River Basin from 2009 to 2019, the present study considers 63 cities in the Yellow River Basin as the research area by adopting the super-efficiency slacks-based measure (Super-SBM) model. Methods such as trend surface analysis, spatial autocorrelation analysis, elliptic standard deviation analysis, and hot spot analysis were used to explore their spatiotemporal distribution and evolution characteristics. The geographical and temporal weighted regression (GTWR) model was used to determine the factors influencing the tourism eco-efficiency value. The findings are as follows: ①The level of tourism eco-efficiency in the Yellow River Basin is not high, exhibiting a fluctuating upward trend. ②The tourism eco-efficiency in the Yellow River Basin shows significant spatial interdependence and agglomeration. Furthermore, the track of the center of gravity moves from northeast to southwest. ③ The tourism eco-efficiency in the Yellow River Basin is affected by various factors, with the economic development level having the greatest influence. [ABSTRACT FROM AUTHOR]

Improving green innovation efficiency (GIE) is the key to achieve high-quality economic development in China, and the introduction of foreign direct investment (FDI) has become an important path choice to promote the GIE. Based on the data of 30 provinces in China, this paper explores the linear and nonlinear effects of FDI on GIE from both quantity and quality perspectives, and further analyzes the mediating role of environmental regulation level. The results show that: (1) From 2011 to 2020, the GIE of all provinces in China generally shows an upward trend. (2) The quantity and quality of FDI have a significant positive impact on the improvement of GIE in China's provinces, and this impact has regional heterogeneity. (3) The quantity and quality of FDI can promote the improvement of GIE in China through the level of environmental regulation (ER). (4) With the level of knowledge accumulation and GIE as the threshold variables, the quantity and quality of FDI have a single threshold effect on the GIE of China's provinces. The conclusions of this study provide some policy implications for local governments to make full use of FDI to perform green innovation activities. [ABSTRACT FROM AUTHOR]

The ecological security of oasis cities in arid and semi-arid regions is highly susceptible to changes in regional landscape patterns and the degree of coordination between human activities and the environment. At the same time, the ecological security of urban landscapes also profoundly affects the success of regional economic and environmental coordination and development. This study is based on land use data from 1990, 2000, 2010, and 2020, as well as land use data from the natural development scenario (NLD), economic development scenario (ECD), ecological development scenario (ELD) and ecological-economic development scenario (EED) simulated by the patch-generating land use simulation (PLUS) model in 2030. From the perspective of production-living-ecological land (PLEL), it analyzes the changes in the past and future landscape ecological security and coupling coordination characteristics of Bole. The results show that from 1990 to 2020, Bole was mainly dominated by grassland ecological land (GEL) and other ecological land (OEL), accounting for a total proportion of 69.51%, with a large increase in production and living land area; the average value of landscape ecological risk is decreasing, and the landscape ecological security of Bole is developing towards benignity; the area of highly coupled coordination zone is decreasing continuously, while that of basic coordination zone and moderate coordination zone is increasing continuously. Under the 2030 EED scenario, the overall changes in various types of land use are not significant, and the average value of landscape ecological risk is the smallest, but it is higher than that in 2020 as a whole; under EED scenario, the area of highly coordinated zone and moderate coordinated zone is the largest among four scenarios, and the best coupling coordination level among the four scenarios. Landscape ecological security and its coupling coordination will be affected by land use patterns. Optimizing regional land use patterns is of great significance for improving urban landscape ecological security and sustainable high-quality development. [ABSTRACT FROM AUTHOR]

Objectives: The China sports lottery contributes to sports and welfare causes. This study aims to construct a macro forecasting model supporting its sustained growth aligned with Vision 2035. Methods: The modeling employed a distributional regression. Sales data of the China sports lottery from 2011 to 2022 were chosen as the response variable, alongside various macro- and event-level explanatory factors. Results: A gamma distribution best fit the data. In the stable model spanning 2011–2019, urbanization, population dynamics, and FIFA emerged as significant contributors (Chi–square p < 0.05) to the location shift parameter. These three factors retained their significance in the 2011–2022 shock model, where shock itself notably impacted sales (p < 0.001). Utilizing the shock model, we simulated the trajectory of the China sports lottery up to 2035. China's demographics changes are poised to create structural headwinds starting in 2026, leading to an anticipated decline in sales driven by population shifts from 2032 onward. However, the FIFA effect is projected to continue fortifying this sector. Conclusions: Beyond offering original insights into the sales trajectory until 2035, specifically concerning new urbanization, negative population growth, and the FIFA effect, this macro forecasting framework can assist in addressing the policy priority of balancing growth with risk mitigation. We recommend policymakers connect market development with mass sports, potentially garnering a dual boost from the growing population of older consumers and the inherent benefits of a "FIFA (mass sports)" effect. A people-centered approach to the China sports lottery could significantly contribute to the long–range objectives of achieving common prosperity outlined in Vision 2035. [ABSTRACT FROM AUTHOR]

The contemporary economic landscape has placed significant emphasis on the digital economy and economic resilience, progressively emerging as pivotal focal points for examining the high-quality development of economic systems. However, there remains to be more research on several critical topics. This includes the characteristics of coordinated development between the digital economy and economic resilience systems and their interdependence. In response, this study formulates a comprehensive evaluative framework for digital economy development and regional economic resilience, grounded in the intrinsic mechanisms of both domains. It conducts a thorough evaluation employing entropy weight-TOPSIS methodology. Additionally, leveraging coupling theory, a coordination model's coupling degree serves as the foundational framework for scrutinizing the symbiotic advancement of the digital economy and economic resilience, along with their interdependent nature. The research sample comprises data from 31 provinces and municipalities in China (excluding Hong Kong, Macao, and Taiwan) from 2011 to 2020. Spatial autocorrelation and Geodetector methodologies probe the evolutionary traits and driving factors underlying the coordinated developmental relationship between these two systems. The findings indicate an upward trajectory in China's annual comprehensive development index for digital economy development (from 0.233 to 0.458) and regional economic resilience (from 0.393 to 0.497). The coupling and coordination between the two systems, measured from 0.504 in 2011 to 0.658 in 2020, demonstrate a consistent growth pattern with an average annual increase of 3.01%. These levels exhibit continuous improvement, with comprehensive economic zones manifesting hierarchical results within the coupling range of [0.5, 0.8]. Notably, agglomeration development evinces a pronounced spatial positive correlation, while local Moran scattering points are primarily concentrated in localized migration leaps. Factors such as foreign-funded enterprises' total import and export volume, online payment capability, and fiber-optic cable length greatly influence the coupling relationship. In contrast, other variables exhibit a lower and more fluctuating degree of weighted impact. This study establishes a foundation for the synergistic and effective development of the digital economy and economic resilience within the Chinese region. Simultaneously, it offers valuable insights for research of related subjects in global contexts. [ABSTRACT FROM AUTHOR]

Resource-based regions support national economic development and are essential sources of basic energy and raw materials. In the post-pandemic era, however, there are practical situations to deal with, such as a fractured industrial chain, a weaker industrial structure, and a sharp reduction in economic benefits. Based on data collected from 68 cities in China, from 2010 to 2021, with 816 observations, this paper explores the industrial development process of resource-based regions in China and the change in the toughness of the industrial structure under the impact of COVID-19. The paper studies and analyzes industrial development trends, industrial structure toughness, and spatial spillover effects. The methods used are the Markov chain model and the Industrial Structure Advancement Index. By building the spatial Dubin model, the paper analyzes the spatial spillover effect of regional industrial development. It decomposes the spillover effect using the partial differential model based on regression. The results show that, during the study period, the comprehensive development level of industries in resource-based regions in China was slowly improving and tended to stabilize after entering the post-pandemic era. The evolution of an advanced industrial structure is significantly heterogeneous among regions, and each region has different toughness. The impact of COVID-19 has reduced the toughness of China's resource-based regions' industrial structure. The spatial spillover effect of regional industrial development is significant. Labor force, technology input, and industrial-structure optimization have different impacts on the industrial development of neighboring regions. In the post-pandemic era, China has used new management methods for more innovation. In order to achieve low-carbon, environmental protection, and sustainable development of resources, realize the rapid recovery of the toughness of industrial structure in China's resource-based cities, and reduce the impact of the COVID-19 pandemic, China proposes to expand the supply of resources, improve the allocation of resources, optimize the direction, promote the rational flow and efficient aggregation of various factors, and enhance the impetus for innovation and development. [ABSTRACT FROM AUTHOR]