Economic Regions In China Research Articles

A study on regional differences and convergence of nursing human resource levels in the Yangtze River Economic Belt: an empirical study

BackgroundThe Yangtze River Economic Belt, as a core economic region in China, is facing the dual challenges of an aging population and growing healthcare demand, and the balanced development and optimal allocation of nursing human resources is crucial to the region’s healthcare system. An in-depth study of the regional differences and convergence of nursing human resources in the region will provide a key basis for policy makers to achieve equity and efficiency in healthcare services and meet the growing demand for healthcare.AimTo analyze the regional differences and convergence characteristics of nursing human resource levels in the Yangtze River Economic Belt, and to provide scientific references for optimizing regional nursing human resource allocation.MethodsBased on the panel data of 107 cities in the Yangtze River Economic Belt from 2010 to 2020, the regional differences and their sources were analyzed by using Dagum’s Gini coefficient, and the convergence characteristics were examined by the coefficient of variation and spatial convergence model.ResultsThe average value of the number of nursing human resources in the Yangtze River Economic Belt is 2,132,300 people, with obvious regional differences, and the hypervariable density difference (53.01%) is the main source of the regional differences; there are obvious trends of σ-convergence and conditional β-convergence of the level of nursing human resources in the overall and the three major regions of the upstream, midstream, and downstream, and different factors have different moderating effects on the speed of spatial convergence in the other areas.ConclusionThe implementation of precise policies for nursing human resources in different regions of the Yangtze River Economic Belt steadily reduces the regional differences between the upper, middle, and lower reaches and enhances the spatial linkage between regions of nursing human resources to improve the quality of nursing human resources.

Dynamic evolution and spatial spillover effect of agricultural green development on eight economic regions in China

Promoting the green development of agriculture is of great significance to realize agricultural and rural modernization in China. Based on the existing research, this paper innovatively explores the dynamic and spatial effects of agricultural green development in the eight newly zoned regions of China's economy. Based on the panel data of 30 provinces in China from 2013 to 2022, this paper selects 20 indicators to measure the level of agricultural green development from five dimensions such as ecological protection, resource conservation, environment-friendly, green supply and economic growth by entropy weight method and uses non-parametric estimation method to analyze the dynamic evolution trend of agricultural green development in the whole country and its eight economic regions. Then, a spatial econometric model is constructed to further explore the influence mechanism and spatial spillover effect of each influencing factor on agricultural green development. The findings demonstrate that the level of agricultural green development in 30 provinces of China continuously improved during the study period, but the dynamic evolution trend characteristics in the whole country and its eight economic regions are not the same. Specifically, the development differences between the whole country, the northeast region, the eastern coast, the southern coast and the northwest region increased, while that between the northern coast, the Yellow River basin and the middle reaches of the Yangtze River first increased and then decreased, and that in the southwestern region gradually narrowed. There is a significant spatial spillover effect on agricultural green development and its influencing factors. Moreover, there is heterogeneity in the influence characteristics and spatial spillover effects of various influencing factors on agricultural green development among the eight economic regions. Therefore, it is proposed that eight economic regions in China should formulate differentiated development strategies, focus on educational and technological innovation etc., and further promote agricultural green development.

Spatio-temporal variations of habitat quality and its driving factors in the Yangtze River Delta region of China

Global biodiversity is still being lost at an alarming rate. How to slow the destruction of habitats to protect biodiversity is an urgent issue. As one of the most rapidly developing and active economic regions in China, the habitat quality assessment and impact factor analysis in the Yangtze River Delta region are important for promoting socio-economic development and improving the local ecological environment. The InVEST mode and Geodetector method was used to explore the spatial and temporal variations of the habitat quality and its driving factors in the Yangtze River Delta region. The results show that the averaged habitat quality index showed a decreasing trend during 1980–2020, which accounted about 71.86 % of the Yangtze River Delta region. The habitat quality showed an overall spatial pattern of high in the south and low in the north, and the regional distribution of low habitat quality was dominated. The Moran's I values were larger than 0.8 during 1980–2020, showing a significant positive spatial correlation and a high degree of spatial clustering. The high-high clusters of habitat quality were mainly located in the southwest of the study area, while the low-low clusters were mainly located in the north. During 2025–2060, the habitat quality under the three scenarios exhibited SSP1-RCP19 > SSP2-RCP45 > SSP5-RCP85 and all showed a trend of decreasing in the north of the study area and increasing in the south. Under the two scenarios SSP1-RCP19 and SSP2-RCP45, the habitat quality generally showed an increasing trend, while under the SSP5-RCP85 scenario, it showed a decreasing trend. The slope, DEM, precipitation, construction land index and their interactions played a dominant role in the spatio-temporal variations of the habitat quality. Therefore, the slope, DEM, precipitation and construction land index should be considered when formulating habitat quality protection countermeasures.

Chinese athletes in ethnic minorities: Social support, ethnic identity, pride, and subjective well-being

We delved into the intricate relationships of social support, ethnic identity, pride, and subjective well-being among Chinese athletes who belong to an ethnic minority. The study's focus was on 877 athletes from diverse economic regions in China, who participated in the 11th Zhengzhou National Minority Traditional Sports Games in 2019. The results showed that social support was positively correlated with ethnic identity, pride, and subjective well-being among Chinese athletes from ethnic minorities. Social support directly influenced the athletes' subjective well-being, as well as indirectly impacting it by affecting their ethnic identity and/or pride. By addressing critical research gaps, this study has contributed to a more nuanced understanding of well-being within the context of cultural diversity and sports participation. The insights derived from this study can inform interventions aimed at enhancing the overall experiences and achievements of athletes in ethnic minorities.

Extended-Range Forecast of Winter Rainfall in the Yangtze River Delta Based on Intra-Seasonal Oscillation of Atmospheric Circulations

The Yangtze River Delta (YRD) is an important economic region in China. Heavy winter rainfall may pose serious threats to city operations. To ensure the safe operation of the city, meteorological departments need to provide forecast results for the Spring Festival travel rush weather service. Therefore, the extended-range forecast of winter rainfall is of considerable importance. To solve this problem, based on the analysis of low-frequency rainfall and the intra-seasonal oscillation of atmospheric circulation, an extended-range forecast model for winter rainfall is developed using spatiotemporal projection methods and is applied to a case study from 2020. The results show that: (1) The precipitation in the YRD during the winter has a significant intra-seasonal oscillation (ISO) with a periodicity of 10–30 d. (2) The atmospheric circulations associated with winter rainfall in the YRD have a significant characteristic of low-frequency oscillation. From a 30-day to a 0-day lead, large modifications appear in the low-frequency atmospheric circulations at low, mid, and high latitudes. At low latitudes, strong wet convective activity characterized by a negative OLR combined with a positive RH700 correlation coefficient moves northwestward and covers the entire YRD. Meanwhile, the Western Pacific subtropical high (WPSH) characterized by a positive Z500 anomaly enhances and lifts northward. At mid and high latitudes, the signal of negatively correlated Z500 northwest of Lake Balkhash propagates southeastward, indicating the cold is air moving southward. Multiple circulation factors combine together and lead to the precipitation process in the YRD. (3) Taking the intra-seasonal dynamical evolution process of the atmospheric circulation as the prediction factor, the spatiotemporal method is used to build the model for winter mean extended-range precipitation anomaly tendency in the YRD. The hindcast for the recent 10 years shows that the ensemble model has a higher skill that can reach up to 20 days. In particular, the skill of the eastern part of the YRD can reach 25 days. (4) The rainfall in the 2019/2020 winter has a significant ISO. The ensemble model could forecast the most extreme precipitation for 20 days ahead.

An Empirical Study on the Short-term Impact of the Environmental Protection Fee-to-Tax Reform on Corporate Investment Efficiency

This paper uses non-financial A-share listed companies in China from 2010 to 2020 as research samples, utilizing the quasi-natural experiment conducted through the implementation of the "Environmental Protection Tax Law". The study investigates the short-term impact of the environmental protection fee-to-tax policy on corporate investment efficiency using a generalized difference-in-differences approach. The results indicate that the implementation of the environmental protection fee-to-tax policy significantly suppresses corporate investment efficiency in the short term and increases firms' inefficient investment. Furthermore, it is found that the policy exacerbates the problem of corporate overinvestment, whereas its impact on underinvestment is not significant. After conducting robustness tests by substituting the dependent variables, the conclusion remains valid. Subsequent heterogeneity analysis was conducted, differentiating between state-owned controlling enterprises and non-state-owned controlling enterprises based on the proportion of state capital, compared to state-owned controlling enterprises, the impact of the policy is more significant on non-state-owned controlling enterprises; Additionally, the policy effects across different economic regions of China were analyzed, revealing that the policy's effect is most significant in the eastern region, significant in the western region, but not significant in the central region. The conclusions of this study further enrich the empirical evidence of the micro-effects of environmental regulation, extending the research on the effects of the environmental fee-to-tax policy, and also provide suggestions for policymakers to formulate effective market-incentive-based environmental regulatory policies.

Weight Loss Using an mHealth App Among Individuals With Obesity in Different Economic Regions of China: Cohort Study.

With the increasing prevalence of obesity, weight loss has become a critical issue in China. Self-managed weight loss through a mobile health (mHealth) app may be a prospective method. However, its practicability in different economic regions of China is unknown. This study aims to evaluate the effectiveness of self-managed weight loss through an mHealth app among individuals with obesity in different economic regions of China and to demonstrate the feasibility of online self-management for weight loss. A total of 165,635 Chinese adults who signed up for the mHealth app were included to analyze the body composition characteristics of individuals from different economic regions by χ2 analyses. Furthermore, 2 types of participants with obesity using mHealth monitoring, including 74,611 participants with a BMI ≥24.0 kg/m2 and 22,903 participants with a normal BMI but an excessive percentage of body fat (PBF), were followed for 6 months to explore the weight loss and fat loss effects in different economic regions of China and to find independent predictors associated with weight loss success by 2-tailed Student t test and multivariable logistic regression analysis. There were 32,129 users from low-income regions and 133,506 users from high-income regions. The proportion of users with obesity in low-income regions was higher than in high-income regions, both based on BMI (15,378/32,129, 47.9% vs 59,233/133,506, 44.4%; P<.001) and PBF classification (19,146/32,129, 59.6% vs 72,033/133,506, 54%; P<.001). Follow-up analyses showed that the weight loss effect among participants with overweight or obesity in low-income regions was greater than in high-income regions (mean -4.93, SD 6.41 vs mean -4.71, SD 6.14 kg; P<.001), while there was no significant difference in fat loss (mean -2.06%, SD 3.14% vs mean -2.04%, SD 3.19%; P=.54). In the population with normal-weight obesity, the weight loss (mean -2.42, SD 4.07 vs mean -2.23, SD 4.21 kg; P=.004) and fat loss effects (mean -1.43%, SD 2.73% vs mean -1.27%, SD 2.63%; P<.001) were stronger in high-income regions than in low-income regions. In addition, multivariable logistic regression analyses showed that age, baseline PBF, skeletal muscle rate, and measurement frequency were related to weight loss, whereas gender and baseline body metabolic rate only showed a correlation with weight loss in the population in high-income regions. This study found a high proportion of mHealth app users with obesity in low-income regions. Individuals with overweight and obesity in different economic regions of China experienced significant weight loss and fat loss using an mHealth app. Moreover, individuals in high-income regions paid more attention to body fat and had better fat reduction effects. Therefore, promoting self-monitoring of weight and PBF through an mHealth app could be an important intervention that could be implemented across all regions of China.

Changing Responses of PM2.5 and Ozone to Source Emissions in the Yangtze River Delta Using the Adjoint Model.

China's industrial restructuring and pollution controls have altered the contributions of individual sources to varying air quality over the past decade. We used the GEOS-Chem adjoint model and investigated the changing sensitivities of PM2.5 and ozone (O3) to multiple species and sources from 2010 to 2020 in the central Yangtze River Delta (YRDC), the largest economic region in China. Controlling primary particles and SO2 from industrial and residential sectors dominated PM2.5 decline, and reducing CO from multiple sources and ≥C3 alkenes from vehicles restrained O3. The chemical regime of O3 formation became less VOC-limited, attributable to continuous NOX abatement for specific sources, including power plants, industrial combustion, cement production, and off-road traffic. Regional transport was found to be increasingly influential on PM2.5. To further improve air quality, management of agricultural activities to reduce NH3 is essential for alleviating PM2.5 pollution, while controlling aromatics, alkenes, and alkanes from industry and gasoline vehicles is effective for O3. Reducing the level of NOX from nearby industrial combustion and transportation is helpful for both species. Our findings reveal the complexity of coordinating control of PM2.5 and O3 pollution in a fast-developing region and support science-based policymaking for other regions with similar air pollution problems.

A study of the economic growth effects of market integration: An examination of 27 cities in the Yangtze River Delta city cluster.

The city cluster of the Yangtze River Delta is a highly dynamic and competitive economic region in China. The integration of the market across the 27 cities is crucial in driving economic growth in the area. This paper aims to provide policymakers with recommendations on promoting regional integration, enhancing the structure, and improving overall performance. By utilizing the benefits and resources of each community more effectively, greater economic gains can be achieved. The findings of this study can also be applied to other Chinese towns or business areas. Market integration is a necessary foundation for regional integration, as it enables the seamless movement of goods and factors throughout the region while simultaneously reducing entry barriers and supporting the creation of a unified market. Unfortunately, the "vassal economy" model has impeded the region's economic growth. The integration of regional markets is crucial for economic growth. However, it is equally important to create industrial clusters with central towns as their hubs. The Yangtze River Delta urban agglomeration is a prime example of one of six world-class city clusters demonstrating how market integration can result in high-quality economic progress. The paper's primary discoveries are threefold: firstly, there has been a progressive elevation in the level of market integration among the 27 cities within the Yangtze River Delta city cluster, characterized by increasingly intimate connections concerning trade, investment, and population mobility. Secondly, this heightened market integration exerts a catalytic impact on the real economic growth of the Yangtze River Delta city cluster, particularly concerning regional industrial restructuring, transformation, and upgrading. Finally, market integration is poised to expedite the industrial division of labor and synergistic development between the cities, thus promoting a concentration of advanced manufacturing and new industries in the central cities and furthering the development of profitable industries in the central individual cities.

Research on the Level of Agricultural Green Development, Regional Disparities, and Dynamic Distribution Evolution in China from the Perspective of Sustainable Development

Green development is a concept of sustainable development, aiming to protect the environment and ecosystems while meeting economic development needs. In the field of agriculture, green development has emerged as a crucial pathway for reconciling the conflicts between agricultural development and ecological conservation. To investigate the level of green development in Chinese agriculture, regional variations, and the evolutionary patterns, this paper is based on the framework of sustainable development theory. This study establishes a comprehensive evaluation system for agricultural green development and applies methods such as entropy-weighted TOPSIS, Dagum’s Gini coefficient, kernel density estimation, Moran’s I index, and Markov chains to analyze the level of agricultural green development, regional disparities, and dynamic evolution in China. The findings of this study reveal that: (1) The overall level of agricultural green development in China is steadily improving, with notable differences in the level of agricultural green development among different regions and provinces. There are significant disparities in agricultural green development between regions, and the overall disparities exhibit a fluctuating downward trend characterized by periods of increase followed by decrease. The regional disparities are identified as the primary cause of the overall disparities in agricultural green development in China. (2) The eight major economic regions in China are experiencing steady development in agricultural green practices, but there are varying degrees of polarization due to different development speeds. (3) This study also highlights a clear spatial positive correlation in the level of agricultural green development in China, with most provinces showing clustering in the first and third quadrants, indicating a “high–high” (H-H) and “low–low” (L-L) agglomeration pattern. (4) The study reveals that the level of agricultural green development in China exhibits a certain degree of stability. Over time, the probability of transitioning from lower-level regions to neighboring higher-level regions increases, and the agricultural green development level in neighboring regions can influence the spatial transfer probability within a given region. Therefore, agricultural green development demonstrates significant spatial dependence.

A Study of the Impact of COVID-19 on Urban Contact Networks in China Based on Population Flows

The emergence and enduring diffusion of COVID-19 has had a dramatic impact on cities worldwide. The scientific aim of this study was to introduce geospatial thinking to research related to infectious diseases, while the practical aim was to explore the impact on population movements and urban linkages in the longer term following a pandemic outbreak. Therefore, this study took 366 cities in China as the research subjects while exploring the relationship between urban contact and the outbreak of the pandemic from both national and regional perspectives using social network analysis (SNA), Pearson correlation analysis and multi-scale geographically weighted regression (MGWR) modeling. The results revealed that the number of COVID-19 infections in China fluctuated with strain variation over the study period; the urban contact network exhibited a significant trend of recovery. The pandemic had a hindering effect on national urban contact, and this effect weakened progressively. Meanwhile, the effect exhibited significant spatial heterogeneity, with a weakening effect in the eastern region ≈ northeast region &gt; central region &gt; western region, indicating a decreasing phenomenon from coastal to inland areas. Moreover, the four major economic regions in China featured border barrier effects, whereby urban contact networks constituted by cross-regional flows were more sensitive to the development of the pandemic. The geostatistical approach adopted in this study related to infectious disease and urban linkages can be used in other regions, and its findings provide a reference for China and other countries around the world to respond to major public health events.

Spatial Analysis of Tertiary Industry Evolution Based on Gravity Model: A Case of Central Plains Economic Region in China

The service and knowledge economy has emerged as the primary drivers of national economic growth, with the tertiary industry leading the way. To promote growth in the central plain region and achieve structural convergence of industries for sustainable, rapid, and healthy economic development, conducting a spatial structural analysis of the evolution of the industrial structure is essential. However, traditional statistical analysis needs to keep pace with the dynamic and non-linear relationships within and outside industries. In this paper, we propose a novel spatial analysis method based on the gravity model to examine the tertiary industry in China’s central plains economic region (CPER). By analyzing statistical data from 2018 to 2022, our results reveal that the economic linkage intensity (F-value) of the tertiary industry in CPER has increased over the years. Specifically, F-values for the high-end, general, and other service industries are 2815, 9882, and 14,826, respectively. The network density (D-value) indicates a single-core structure, with D-values of 0.71, 0.74, and 0.82 for high-end, general, and other service industries. Our findings suggest that the economic linkage network of the tertiary industry in CPER has matured, with solid industry integration and convergence of the regional financial industry structure. There is a high correlation (p &lt; 0.01) among various network structures in the service industry, and a stable and cohesive subgroup with multicentre characteristics is beginning to emerge. These findings provide valuable insights for the development of the tertiary industry in CPER during the later stage of the 14th Five-Year Plan in China.

Inequalities in Resource Distribution and Healthcare Service Utilization of Long-Term Care in China.

Long-term care (LTC) services help the elderly maintain their functional ability and live with dignity. In China, the establishment of an equitable LTC system is a primary focus of the current public health reform. This paper assesses levels of equality in resources for and utilization of LTC services between urban and rural areas and economic regions in China. We use social services data from the China Civil Affairs Statistical Yearbooks. Gini coefficients against elderly population size are calculated for the number of institutions, beds, and workers, and the concentration index (CI) against per capita disposable income is calculated for the number of disabled residents per 1000 elderly people and the number of rehabilitation and nursing services per resident. The Gini coefficients against the elderly population in urban areas indicate relatively good equality. In rural areas, the Gini coefficients have increased rapidly from relatively low values since 2015. The CI values in both urban and rural areas are positive, indicating that utilization is concentrated in the richer population. In rural areas, the CI values for rehabilitation and nursing have remained above 0.50 for the last three years, implying high levels of income-related inequality. The negative CI values for rehabilitation and nursing services in urban areas in the Central economic region and rural areas in the Western region imply a concentration of resource utilization toward poorer groups. The Eastern region shows relatively high internal inequality. Inequalities exist between urban and rural areas in the utilization of LTC services, despite similar numbers of institution and bed resources. Resource distribution and healthcare service utilization are more equal in urban areas, creating a low level of equilibrium. This urban-rural split is a source of risk for both formal and informal LTC. The Eastern region has the largest number of resources, the highest level of utilization, and the greatest internal variation. In the future, the Chinese government should enhance support for the utilization of services for the elderly with LTC needs.

Understanding China's metro development: A comparative regional analysis

Economic growth and infrastructure development in China has appeared to be regionally imbalanced for many years during the post-reform period since 1978. The significant differences in transport infrastructure and facilities among various regions in China can be depicted as “stairs” descending gradually from the higher eastern coastal region to the lower west of China. Metro systems have been developed in both coastal and inland provinces, and they are now present in the four different economic regions of China. The findings in this paper show that the distribution of metro systems from the perspective of spatial and regional development in China tends to be mixed and diverse. Considering the length, numbers of lines and stations, there is a consistent pattern in the medians of the datasets for different regions, with no significant differences in the levels of metro development between coastal provinces and inland provinces, and among the four economic regions. However, the Eastern Region not only has the largest number of cities with extensive metro systems; it also has many prefecture-level cities and non-provincial capital cities with developed metro systems. The analysis also shows that economic and population factors are positively and significantly correlated with the scale of metro development in both coastal and inland regions, and these factors have stronger influence on the scale of metro systems in cities in the inland region compared with cities in the coastal region. In summary, the evidence suggests that the spatial and regional layouts of metro development in China are influenced by economic, population, and institutional and policy factors; the latter having an important role to play in reducing regional imbalances in metro infrastructure development.

Quantifying the Source Contributions to Poor Atmospheric Visibility in Winter over the Central Plains Economic Region in China

The Central Plains Economic Region (CPER) is one of the most polluted regions in China. Air pollution has caused visibility degradation due to the light extinction of fine particles (PM2.5). However, the source of light extinction and visibility degradation is still unclear. In this study, the nested air quality prediction model system coupled with an online tracer-tagging module has been used to quantify the contribution of emission sectors and regions to visibility degradation. The light extinction coefficients were well reproduced over CPER. The results showed that resident-related emissions, traffic and industry were the main sectors of visibility degradation over CPER, contributing 55~62%, 10~28%, and 9~19%, respectively. The contribution of local emissions and regional transport was also investigated, and the results showed that regional transport dominated the light extinction (56~68%), among which transport within Henan province contributes significantly (12~45%). Sensitivity tests showed that the reduction in the resident-related sector was more effective than that of the industry sector. Emission control of 40% in resident-related, industry, and traffic sectors over the whole region can achieve the goal of good visibility. This study will provide scientific suggestions for the control strategies development to mitigate visibility degradation over CPER.

Analysis and prediction of the temporal and spatial evolution of carbon emissions in China's eight economic regions.

Facing increasingly severe environmental problems, as the largest developing country, achieving regional carbon emission reduction is the performance of China's fulfillment of the responsibility of a big government and the key to the smooth realization of the global carbon emission reduction goal. Since China's carbon emission data is updated slowly, in order to better formulate the corresponding emission reduction strategy, it is necessary to propose a more accurate carbon emission prediction model on the basis of fully analyzing the characteristics of carbon emissions at the provincial and regional levels. Given this, this paper first calculated the carbon emissions of eight economic regions in China from 2005 to 2019 according to relevant statistical data. Secondly, with the help of kernel density function, Theil index and decoupling index, the dynamic evolution characteristics of regional carbon emissions are discussed. Finally, an improved particle swarm optimization radial basis function (IPSO-RBF) neural network model is established to compare the simulation and prediction models of China's carbon emissions. The results show significant differences in carbon emissions in different regions, and the differences between high-value and low-value areas show an apparent expansion trend. The inter-regional carbon emission difference is the main factor in the overall carbon emission difference. The economic region in the middle Yellow River (ERMRYR) has the most considerable contribution to the national carbon emission difference, and the main contributors affecting the overall carbon emission difference in different regions are different. The number of regions with strong decoupling between carbon emissions and economic development is increasing in time series. The results of the carbon emission prediction model can be seen that IPSO-RBF neural network model optimizes the radial basis function (RBF) neural network, making the prediction result in a minor error and higher accuracy. Therefore, when exploring the path of carbon emission reduction in different regions in the future, the IPSO-RBF neural network model is more suitable for predicting carbon emissions and other relevant indicators, laying a foundation for putting forward more scientific and practical emission reduction plans.

Spatiotemporal Differentiation of the Coupling and Coordination of Production-Living-Ecology Functions in Hubei Province Based on the Global Entropy Value Method

Rapid urbanization and industrialization have brought about regional prosperity and pressure on the ecological environment, and the disorder of development has led to competition among the production-living-ecology functions. How to build livable cities, optimize the spatial layout of land, and promote the coordinated development of the production-living-ecology functions in various regions has become an important issue in the sustainable development and utilization of land space. In order to study the spatiotemporal conflict and coordination of the production-living-ecology functions with respect to the dramatic developments associated with the 21st century, this study took Hubei Province, which is the top-ranking economic region in China in recent years, as the study area and adopted the global entropy value method, triangle model, and coupled evaluation model to delineate an index system to measure the degree of conflict and coordination of the production-living-ecology functions in Hubei Province from 2000 to 2020, and also delineate zoning management based on statistical yearbook data. The results showed the following: (1) With respect to the time scale, the indices of the production-living-ecology functions in Hubei Province increased year by year, and the degree of coordination also increased yearly, from the stage of disorder with certain conflict to the stage of coordination with a high level of coupling. (2) On the spatial scale, the development of production-living-ecology functions in Hubei Province was unbalanced, which may be related to the overall development strategy of "two circles and one belt" in Hubei Province, with the eastern part of the province having a higher degree of coordination of the production-living-ecology functions and the western part having a lower degree of coordination. (3) Among the production-living-ecology functions, the ecological function of Hubei Province as a whole exhibited minimal change and maintained stable development, while the living and production functions underwent considerable development, indicating that Hubei Province has protected the orderly development of the ecological environment in the process of urbanization and new industrialization. (4) According to the development and coordination of the production-living-ecology functions in each region of Hubei Province, four development management zones were created: high-quality development zone, secondary development zone, balanced development zone, and development potential zone. Finally, policy suggestions are given for each zone.

Impact of Transport Infrastructure on Gross Regional Products

Purpose: This study examines the impact of transport infrastructure on the Gross Regional Products in Chinese economic regions. Methods: The study analyzes the impact of transport infrastructure on the Gross Regional Products according to the eight economic regions in China by using descriptive statistics and regression analysis methods. Results: The findings are that a) densities of railways and highways have strong impacts on Gross Regional Products per capita according to Chinese economic regions, b) impacts of densities of railways and highways on Gross Regional Products per capita differ among Chinese economic regions and c) construction of new transport infrastructure has a more positive impact on Gross Regional Products per capita compared to regions with already developed transport infrastructure. Implications: Region-specific features ought to be considered in making and implementing the economic development policy according to economic regions.

The role of internet development on green total-factor productivity—An empirical analysis based on 109 cities in Yangtze River economic belt

As one of the most important economic regions in China, the improvement of green total-factor productivity (GTFP) in Yangtze River economic belt has vital significance for economic transformation in China. Using 109 cities’ panel data from 2004 to 2018, slacks-based global data envelopment analysis was first applied to construct GTFP. On the basis, dynamic GMM and mediation effect models were used to investigate the role of internet development on GTFP. The empirical results illustrated that GTFP lacked endogenous driving force. However, internet development not only has significant direct positive effect on GTFP, but also indirectly promotes GTFP through technology innovation and industrial structure upgrade. And the mediation variables also have two-way positive impacts on internet development. After accounting robustness test, the empirical conclusions were still valid. Based on the analysis, our study provided scientific and reasonable policies to improve GTFP in Yangtze River economic belt.

Application of Human-Computer Interaction System in Regional Tourism Competitiveness Analysis under IoT Background.

With the continuous development of Internet of Things technology, this technology is not limited to the laboratory but is more and more applied in the process of commercialization. Large-scale machine communication is one of the three most important scenarios for 5G applications. Its features include larger uplink access, smaller data packets, higher device energy consumption requirements, lower device transmission speed, higher latency, and bursty communication. With the development of the Internet of Things in the 5G era, interpersonal interaction experience has been further optimized and welcomed by the market and adopt Qt/embedded multilayer menu design mode to improve our computer system interaction to facilitate the operation and Maintenance system. The software function of the human-computer interaction system has reached the expected result. By constructing the application of a human-computer interaction system in the analysis of regional tourism competitiveness, we analyze the temporal and spatial changes of tourism competitiveness in four major economic regions in China and combine multiple linear regression and geographic detector models to analyze China's tourism competitiveness. On this basis, we propose to further enhance the tourism competitiveness of areas with weak tourism development infrastructure and encourage potential tourism development areas to complement each other with high-quality resources between regions.