Research on the impact of manufacturing servitization on environmental pollution:spatial econometric analysis of sulfur dioxide based on 284 prefecture-level cities

Using China’s regional input–output table,the paper constructs indicators of manufacturing servitization,matches manufacturing servitization at the regional level with city data,and uses spatial econometrics to empirically analyze the impact of manufacturing servitization on urban sulfur dioxide(SO_(2))emissions within the classical Environmental Kuznets Curve(EKC)framework.The results show that manufacturing servitization can reduce SO_(2) emissions.Producer servitization and consumptive services can both significantly reduce industrial SO_(2) emissions.Transportation and warehousing servitization,information servitization,leasing,and commercial servitization,technology research and development servitization significantly reduce SO_(2) emissions;technology research and development servitization,in particular,have the largest influence coefficient,while the reduction effect of servitization in the wholesale and retail and finance sectors is not significant.The study also found that servitization reduced the SO_(2) emissions through technological innovation and industrial structure upgrading.

Analysis of spatial distribution characteristics and driving factors of ethnicminority villages in China using geospatial technology and statistical models

This study aims to reveal the spatial structural characteristics of 1,652 Ethnic-Minority Villages(EMV)in China and to analyze the mechanisms driving their spatial heterogeneity.EMV are a special type of settlement space that preserve a large number of historical traces of the ethnic culture of ancient China.They are important carriers of China’s excellent traditional culture and are key to the implementation of rural revitalization strategies.In this study,1652 EMV in China were selected as the research subjects.The Nearest Neighbor Index,kernel density,and spatial autocorrelation index were employed to reveal the spatial structural characteristics of minority villages.Neural network models,spatial lag models,and geographical detectors were used to analyze the formation mechanism of spatial heterogeneity in EMV.The results indicate that:(1)EMV exhibit significant spatial differentiation characterized by“single-core with multiple surrounding sub-centers,”“polarization between east and west,”“decreasing quantity from southwest to east coast to northeast to northwest,”and“large dispersion with small agglomeration.”(2)EMV are mainly distributed in areas rich in intangible cultural heritage,with high vegetation coverage and low altitude,far from central cities,and having limited arable land and an underdeveloped economy and transportation,particularly in shaded or riverbank areas.(3)Distance from the nearest river(X3),distance from central cities(X8),national intangible cultural heritage(X9),and NDVI(X10)were the main driving factors affecting the spatial distribution of EMV,whereas elevation(X1)and GDP(X5)had the weakest influence.As EMV are a relatively unique territorial spatial unit,the identification of their spatial heterogeneity characteristics not only deepens the research content of settlement geography,but also involves the assessment,protection,and development of Minority Villages,which is of great significance for the inheritance and utilization of excellent ethnic cultures in the era.

Analysis on the Spatial Agglomeration and Coupling of Socioeconomic Factors in Qinghai Tourism Under the Background of“Belt and Road”

Qinghai is the strategic base and important fulcrum of the Belt and Road Initiative while tourism is a strategic pillar industry in Qinghai Province.Due to its rich tourism resources and unique ecological environment,the integration of tourism in Qinghai into the Belt and Road has attracted great attention of the Asian Development Bank(ADB).With the spatial data of tourism elements POI and the statistical data of 44 counties in Qinghai to analyze the characteristics and influencing factors of the spatial agglomeration of tourism in Qinghai,the paper conducts research on spatial coupling and concludes with the following results:The spatial agglomeration of tourism in Qinghai presents the distribution pattern of“one circle and one belt”;economic density and population density play an important role in the formation of the spatial agglomeration pattern of tourism with some spatial spillovers;Belt and Road has a significant impact on the promotion of tourism agglomeration in Qinghai.The paper suggests that tourism in Qinghai should fully integrate into the Belt and Road,giving full play to the guiding role of Belt and Road in the allocation of social and economic resources,and optimizing the spatial layout.

The spatial econometric analysis of the impact of internet on provincial innovation in China

Researches in the impact of the information technology on R&D activities have been noticed since this century to provide a foundation for the relationship between information technology and R&D activities.Using methods of spatial econometrics,this paper examines the impact of Internet on innovation and its spatial spillovers between Chinese provinces over 2001-2007.This paper find that Internet plays an important role in innovative activities,and spatial spillovers of the provinces to its neighbors are positive but weak when spatial effect of endogenous spatial lag variable is taken into consideration.

Agricultural Non-point Source Pollution in China:Evaluation,Convergence Characteristics and Spatial Effects

In this study,an inventory analysis approach was used to investigate the intensity of agricultural non-point source pollution(ANSP)and its spatial convergence at national and provincial levels in China from 1999 to 2017.On this basis,spatial factors affecting ANSP were explored by constructing a spatial econometric model.The results indicate that:1)The intensity of China's ANSP emission showed an overall upward trend and an obvious spatial difference,with the values being high in the eastern and central regions and relatively low in the western region.2)Significant spatial agglomeration was shown in China's ANSP intensity,and the agglomeration effect was increasing gradually.3)In the convergence analysis,a spatial lag model was found applicable for interpretation of the ANSP intensity,with the convergence rate being accelerated after considering the spatial factors but slower than that of regional economic growth.4)The spatial factors affecting the ANSP intensity are shown to be reduced by improving agricultural infrastructure investment,labor-force quality,and crop production ratio,while the expansion of agricultural economy scale and precipitation and runoff have positive impact on ANSP in the study region.However,agricultural research and development(R&D)investment showed no direct significant effect on the ANSP intensity.Meanwhile,improving the quality of the labor force would significantly reduce the ANSP intensity in the surrounding areas,while the precipitation and runoff would significantly increase the pollution of neighboring regions.This research has laid a theoretical basis for formulation and optimization of ANSP prevention strategies in China and related regions.

Spatial Spillover and the Factors Influencing Public Service Supply in Sichuan Province, China

This article examines the spatial characteristics of public service supply and the factors influencing such supply in cities of Sichuan Province, China using spatial-autocorrelation and spatial econometric models with statistical data in 2012. The results demonstrate that expenditures on different types of public services present different spatial autocorrelation patterns. Although the spatial differences in basic public service expenditures are relatively small, a clear fan-shaped spillover to the east can be seen in Chengdu City. Chengdu also shows high clustering of advanced public service expenditures, being a typical core-periphery pattern. Post-earthquake reconstruction expenditures are clustered in the "5.12 Wenchuan earthquake" region and spill over toward cities to the east. The efficiency of public services in the mountainous areas in western Sichuan is low and exhibits a pattern of low-low spatial autocorrelation. The efficiency of public service supply is affected by economic, social, political and geographical factors. Based on the results of this analysis, we recommend a supply strategy that incorporates different types of public services and a specialized public service supply strategy for mountainous areas. Overall public service efficiency should be enhanced by focusing on narrowing the gap in farmers' income among regions and accelerating urbanization. Decision-makers should consider moresupportive policies with regard to providing basic public services in mountainous areas to ensure an equalized supply of basic public services. To enhance the efficiency of advanced public service supply, additional growth pole should be encouraged and incentivized; however, investments are required to drive the development of the peripheral regions through regional economic integration. Both software and hardware types of infrastructure are required to supply services efficiently during post-disaster reconstruction.

Impact of Operating Conditions on the Productivity of Star-Rated Hotels in China's Mainland: Verification from Spatial Metrology

Room occupancy rate is a key indicator of star-rated hotel management quality. This paper takes Cobb-Douglas production function as the theoretical framework. Spatial Moran index of autocorrelation, Spatial Lag Model(SLM) and Spatial Error Model(SEM) are used to analyze the star-rated hotels labor productivity of 31 provincial regions in China's Mainland based on the star-rated hotels statistical data of year 2016. The spatial correlation and spatial difference of the star-rated hotels labor productivity is discussed. This paper studies the impact of three factors on spatial characteristics of star-rated hotels labor productivity in China's Mainland. The econometric estimation results show that:(1) Star-rated hotels labor productivity present significant spatial dependence and spatial difference in China's Mainland.(2) The estimation results of Ordinary least Squares(OLS) are reliable.(3) The reliability of the results obtained by the Spatial Error Model(SEM) analysis is the highest, and has a stronger explanatory power to the spatial relationship of star-rated hotels labor productivity in China's Mainland. The average room occupancy rate has more influence on the labor productivity of the provincial star-rated hotels than the impact of capital and labor.

Sister-city Ties and Chinese Outward Foreign Direct Investment:A Spatial Econometric Analysis

This paper employs dynamic spatial econometric methods to analyze the impact of the sister-city relationship on Chinese outward foreign direct investment(OFDI)using a linked country-level dataset from 2003 to 2016.The results show strong and robust evidence that the sister-city relationship has been a crucial OFDI location determinant in host countries and their neighbors.Specifically,the sister-city tie between China and the host country has stimulated Chinese OFDI in host countries.Moreover,Chinese OFDI in host countries would be reduced if China concluded sister-city ties with their neighbors to which we refer as the neighboring effect.Further mechanism tests show that sister cities have promoted OFDI in host countries via four channels:reducing political risk,decreasing information asymmetry,narrowing institutional distance,and mitigating cultural differences.This tendency for sister-city links to promote OFDI has varied substantially depending on OFDI entry modes(i.e.,greenfield or cross-border mergers and acquisitions),motivation(i.e.,resource-,market-,technology-,or efficiency-oriented OFDI),and Sino–foreign geographical relationships(i.e.,Belt and Road Initiative countries or other countries).

Is there regional convergence between Morocco and its OECD partner countries in terms of well-being?

Morocco wants its 12 regions to play the role as the main lever of its public policies to initiate harmonized spatial multidimensional development. In the context of this goal and Morocco’s openness over the past two decades to bilateral and multilateral cooperation in an effort toward regional integration, this article studies the convergence of 389 regions in 36 countries(Morocco and 35 of its partner member countries in the Organization for Economic Co-operation and Development(OECD)) between 2000 and 2019 in terms of well-being. To this end, we considered the territorial dimension of β-convergence models for well-being and its four domains(economic, social, environmental, and governance). Then, we adapted the absolute β-convergence model by taking into account the existence of spatial heterogeneity according to five specifications of spatial models. Thus, apart from environmental domain, we found that β-convergence of regions is significant for well-being and three of its domains(economic, social, and governance). These convergences are made by a spatially autocorrelated error model(SEM). However, the speed and period of convergence are relatively low for social domain, partly explaining the very exacerbated tensions at the territorial level. The fastest convergence was achieved in governance domain, followed by economic domain. This suggests that emerging countries must pay particular attention to national public action in favor of social cohesion at the territorial level. The lack of convergence in environmental domain calls for common actions for all countries at the supranational level to protect the commons at the territorial level.

Quantifying the Temporal and Spatial Spread of COVID-19:Empirical Evidence from Shanghai

The worldwide spread of COVID-19 has caused a grave threat to human life, health, and socio-economic development. It is of great significance to study the transmission mechanism of COVID-19 and evaluate the effect of epidemic prevention policies. This paper employs a spatial dynamic panel data(SDPD) model to analyze the temporal and spatial spread of COVID-19, incorporating the time-varying features of epidemic transmission and the impact of geographic interconnections.Empirical studies on the COVID-19 outbreak in Shanghai during early 2022 show that the intra-regional transmission of COVID-19 dominated the cross-regional one. Additionally, strict policies are found to effectively reduce the transmission risk of COVID-19 and curb the spillover effect of the epidemic in Shanghai on other regions. Based on these results, we provide three policy suggestions. Furthermore,this research methodology can be extended to investigate other infectious diseases, thereby providing a scientific framework and theoretical basis for evaluating the spread risk of pandemics and formulating appropriate strategies.

Urban Agglomerations in China: Characteristics and Influencing Factors of Population Agglomeration

Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy has developed rapidly in the recent decades of China,and the UAs have also developed rapidly.However,as a large population country,the population distribution and changes of UAs in China has unique characteristics.Using the fifth,sixth and seventh population census data,spatial auto-correlation and spatial econometric models,we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China’s UAs.Results revealed that:1)from 2000 to 2020,the population gradually converged into UAs,and the characteristics of population agglomeration in different development degree of UAs differ.The higher the development degree of UA,the higher the population agglomeration degree.Besides,UAs are the main area with the most significant population agglomeration degree,and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space.The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities.2)Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs.The main factors of population gather into UAs are similar with the outside UAs,but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020.Meanwhile,the other factors,such as high-quality public services,good urban living environment conditions,high-quality medical and educational resources,are also important factors to promote urban population gather into UAs.This study provides a basis for formulating the development planning of UAs in China,and enriches the relevant theoretical research of population evolution and influencing factors of UAs.

Assessing the dynamics of human activity intensity and its natural and socioeconomic determinants in Qinghai-Tibet Plateau

Investigating the spatiotemporal variation of human activity intensity and its determinants is a crucial basis for further revealing the mechanism of human-environment interaction and optimizing the human development mode.In this study,the human activity intensity on the Qinghai-Tibet Plateau(QTP)from 1990 to 2020 was measured based on the quantitative model of land use data and the actual regional background,and the under-lying natural and socioeconomic determinants were investigated using spatial econometric methods.The results demonstrate that(1)the human activity intensity in QTP has increased by 11.96%,and there are differences in different spatial scales;the areas with high human activity intensity are distributed in the Hehuang Valley where Xining City and its surrounding areas are located,as well as the One-River and Two-River Area where Lhasa City and surrounding areas are located.(2)Human activity intensity has significant positive spatial spillover,suggesting that local changes will cause changes in the same direction in adjacent areas.(3)The human activ-ity intensity in QTP is affected by various determinants.Concerning socioeconomic factors,the economic level has no significant impact on the human activity intensity in QTP,which differs from the general regional law.Both urbanization and traffic conditions have a significant positive effect,and the impact intensity continues to increase.Concerning natural factors,topographic relief has a significant positive effect;the impacts of temper-ature and vegetation coverage have changed from insignificant to a significant positive effect;the impacts of precipitation and river network density have not been verified;there is no linear relationship between altitude and human activity intensity in the entire QTP,while it exists in local regions.Finally,this study proposes three policy implications for the realization of a more harmonious human-environment relationship in QTP.

Protection of Innovative Achievements,Spatial Spillover,and Internal Structural Upgrading of the Productive Service Industry-Empirical Evidence from 28 Provinces in China

This study measured the level of innovation achievement protection and the degree of internal structural upgrading of the productive service industry in 28 provinces of China from 2000 to 2022.Exploratory spatial analysis methods were used to test the spatial correlation between the two variables,and the spatial impact of innovation achievement protection on the optimization of the internal structure of the productive service industry was examined at the national and sectoral levels.The results showed three main aspects of this system.(1)The agglomeration level of innovation achievement protection and internal structure optimization of the productive service industry between regions in China continued to increase during the sample period,and there was a clear similarity and synchronicity in the spatial evolution of the two variables.(2)The overall improvement in the protection level of innovative achievements is conducive to promoting the internal structural upgrading of China’s productive service industry.However,there are significant differences in the degree to which the protection of innovative achievements affects the internal structural upgrading of the productive service industry in the four major regions of the East,Central,Northeast,and West.The protection of innovative achievements in the East and Central regions significantly promotes the internal structural optimization of the productive service industry,while this effect is not significant in the western and northeastern regions.(3)The results of the robustness test indicate that the impact of internal structural upgrading of the productive service industry in the previous year on the level of innovation achievement protection is not significant.The interference from abnormal values of the internal structural upgrading of the productive service industry in various regions and the influence of municipalities directly under the central government on the regression results are not significant.After replacing the main variable,the coefficient of the innovation achievement protection level remained significantly positive.The conclusions of this study supplement and improve the theory of innovation achievement protection and industrial transformation and upgrading,providing decision-making support for improving the level of innovation achievement protection and promoting the internal structural upgrading of the productive service industries in China.

Spatiotemporal Dynamics of Green Total-factor Water-use Efficiency and Its Influencing Factors in China

In this study,we developed an evaluation index system for green total-factor water-use efficiency(GTFWUE)which reflected both economic and green efficiencies of water resource utilization.Then we measured the GTFWUE of 30 provinces/municipalities/autonomous regions(hereafter provinces)in China(not including Tibet,Hong Kong,Macao,Taiwan as no data)from 2000 to 2018 using a minimum distance to the strong frontier model that contained an undesirable output.We further analyzed the regional differences and spatial correlations of GTFWUE using these values based on Global and Local Moran’s I statistics,and empirically determined the factors affecting GTFWUE using a spatial econometric model.The evaluation results revealed that the GTFWUE differed substantially between the regions.The provinces with high and low GTFWUE values were located in the coastal and inland areas of China,respectively.The eastern region had a significantly higher GTFWUE than the central and western regions.The GTFWUEs for all three regions(eastern,central,and western regions)decreased slowly from 2000 to 2011(except 2005),remained stable from 2012 to 2016,and rapidly increased in 2017 before decreasing again in 2018.We found significant spatial correlations between the provincial GTFWUEs.The GTFWUE for most provinces belonged to the high-high or low-low cluster region,revealing a significant spatial clustering effect of provincial GTFWUEs.We also found that China’s GTFWUE was highly promoted by economic growth,population size,opening-up level,and urbanization level,and was evidently hindered by water endowment,technological progress,and government influence.However,the water-use structure had little impact on GTFWUE.This study fully demonstrated that the water use mode would be improved,and water resources needed to be used more efficiently and green in China.Moreover,based on the findings of this study,several policy recommendations were proposed from the aspects of cross-regional cooperation,economy,society,and institution.

Can Talent Policies Attract Population Inflows?—An Empirical Analysis Based on Spatial Panel Modeling

To analyze the spatial influence mechanism of talent policy on population flow, this study compares the government work reports of 31 provinces between 2008 and 2020, and quantifies regional talent policies in nine aspects, including talent evaluation and incentives, utilizing a comprehensive, standardized, and continuous approach. Additionally, this paper develops a spatial econometric analysis model and expands on the conventional neighborhood, distance, and economic matrices by constructing a spatial weight matrix that reflects talent flow. The findings indicate that population movement exhibits spatial clustering patterns. The regional government's talent policy, primarily based on talent evaluation and incentives, positively influences population inflow. Moreover, during the implementation of talent policies, local governments demonstrate cooperative relationships. The inter-regional spillover effect between talent evaluation and talent incentives is significantly positive. In other words, a stronger local talent evaluation policy, along with robust talent incentives, encourages population inflow from neighboring provinces. However, this conclusion may vary in different regions and over time. Recently, the spatial spillover effect of population inflow and the impact of talent policies have not shown significant results. Additionally, the attractiveness of talent evaluation in the eastern region surpasses that of talent incentives, while the opposite holds true for the central and western regions. This study investigates the impact of local government talent policies on population inflow and its spatial spillover effect, offering theoretical support for intergovernmental cooperation.

Strategic Interaction in Spending on Environmental Protection:Spatial Evidence from Chinese Cities

In China, the responsibilitY of protecting the environment lies largely with local governments. Within the framework of spatial econometrics, we investigate empirically the consequence of such an institutional setting. Using city-level data for China, the present study finds that city governments behave strategically in making spending decisions regarding environmental protection. This paper finds that a city government appears to cut its own spending as a response to the rise in environmental protection spending by its neighbors. Hence, environmental protection tends to be underprovided. As a result, we suggest that centralizing the environmental protection responsibility to a higher level of government would be beneficial in terms of controlling pollution in China.

Revealing Spatial Spillover Effect in High-Tech Industry Agglomeration from a High-Skilled Labor Flow Network Perspective

Understanding the high-tech industrial agglomeration from a spatial-spillover perspective is essential for cities to gain economic and technological competitive advantages.Along with rapid urbanization and the development of fast transportation networks,socioeconomic interactions between cities have been ever-increasing,traditional spatial metrics are not enough to describe actual inter-city connections.High-skilled labor flow between cities strongly influences the high-tech industrial agglomeration,yet receives less attention.By exploiting unique large-scale datasets and tools from complex network and data mining,the authors construct an inter-city high-skilled labor flow network,which was integrated into spatial econometric models.The regression results indicate that spatial-spillover effects exist in the development of high-tech industries in the Yangtze River Delta Urban Agglomeration region.Moreover,the spatial-spillover effects are stronger among cities with a higher volume of high-skilled labor flows than among cities with just stronger geographic connections.Additionally,the authors investigate the channels for the spillover effects and discover that inadequate local government expenses on science and technology likely hamper the high-tech industrial agglomeration,so does the inadequate local educational provision.The increasing foreign direct investments in one city likely encourages the high-tech industrial agglomeration in other cities because of the policy inertia toward traditional industries.

Dynamic changes and convergence of China's regional green productivity:A dynamic spatial econometric analysis

Low-carbon economic development is at the heart of the post-pandemic green recovery scheme worldwide.It requires economic recovery without compromising on the environment,implying a critical role that green productivity plays in achieving the carbon neutrality goal.Green productivity measures the quality of economic growth with consideration for energy consumption and environmental pollution.This study employs the slacks-based measure directional distance function(SBM-DDF)approach and the Malmquist-Luenberger(ML)index to calculate green productivity and its components of 30 provinces in China between 2001 and 2018.Using a spatial panel data model,we empirically analyzed the conditionalβ-convergence of China's green productivity.We found that overall,since 2001,China's green productivity has demonstrated a continuous upward trend.When taking into account spatial factors,China's green productivity demonstrates a significant conditionalβ-convergence.In terms of regional effects,the results indicate that the green productivity of the eastern and western regions demonstrates club convergence,implying a more balanced green economic development.Moreover,the convergence rate of China's green productivity increases with the addition of environmental regulation variable,and so the corresponding convergence time decreases.It indicates that environmental regulations help to facilitate the convergence of China's green productivity,narrowing the gap between the regional green economic development.The findings provide guideline for achieving a low-carbon development and carbon neutrality from a regional green productivity perspective.

Green development and economic resilience:Evidence from Chinese resource-based cities

Resource-based cities are currently facing challenges due to ecological pollution and an unbalanced industrial structure,which hinders sustainable economic growth.The focus on green development as a strategy for economic growth and environmental protection is becoming increasingly popular.This study employs a spatial econometric model to explore the effect of green development on economic resilience in Chinese resource-based cities from 2011 to 2019,revealing a positive correlation between green development and economic resilience.For each 1 unit increase in green development,economic resilience increases by an average of 0.512 units.Furthermore,the analysis of heterogeneity reveals differences in the factors influencing various resource-based cities.In addition,provincial green policies bolster economic resilience by encouraging green development.This research aids in comprehending the balance between the economy and the environment.

Contributions of Social-ecological Drivers to Land Use Transitions in Protected Areas on the Tibetan Plateau:Shifting from Strong Intervention to a New Balance

The establishment and management of protected areas(PAs)often involve modifying traditional land use rights and changing the production and living activities of locals,which can lead to changes in the factors that drive land use transitions.Our understanding of the spatiotemporal patterns of land use transition and the contributions of social-ecological drivers remains incomplete.In this study,we focused on the Yarlung Zangbu Grand Canyon National Park and examined how social-ecological factors influence land use transitions by developing a theoretical model of land use transitions within PAs.Our findings revealed that cropland,shrubland,grassland,and wetland experienced net losses in area,while forestland,water,ice/snow,barren land,and impervious land exhibited fluctuating growth patterns from 1985 to 2020.The net decrease in grassland was 157425.60 ha,while the net increase in forest was 140709.20 ha.The quality of land habitat increased from 0.5158 to 0.6656.Land use dominant and recessive transitions displayed varying spatial characteristics and scales across different time periods.In particular,the degree of influence of policy factors on land use dominant transition declined from 0.0800 in 1985-1990 to -0.0432 in 2010-2020,while its influence on land use recessive transition declined from 0.00058 in 1985-1990 to 0 in 2010-2020.The results show that social-ecological factors intricately influenced different types of land use transitions,leading to a shift from a balanced state to a new equilibrium.These results enhance our understanding of the spatiotemporal patterns and complex dynamics of land use transitions within PAs,providing insights and practical implications for effective land management in PAs by considering the land-human relationships.