scholarly journals Spatial differentiation and influencing factors of attended collection and delivery points in Nanjing city, China

2020 ◽  
Author(s):  
Muhammad Sajid Mehmood ◽  
Gang Li ◽  
Shuyan Xue ◽  
Qifan Nie ◽  
Xueyao Ma ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Spatial Differentiation ◽  
Nanjing City

scholarly journals Temporal-Spatial Differentiation and Optimization Analysis of Cultivated Land Green Utilization Efficiency in China

Land ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 158 ◽  
Author(s):  
Qianru Chen ◽  
Hualin Xie
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Spatial Differentiation ◽  
Utilization Efficiency ◽  
Added Value ◽  
Scale Model ◽  
Eastern Region ◽  
Cultivated Land ◽  
Land Utilization ◽  
Extension System

Cultivated land is closely related to national food security, rural economic development and social stability. The cultivated land pollution and carbon emissions caused by chemical fertilizers, pesticides, film residues, etc., in the process of cultivated land utilization pose a serious threat to the cultivated land ecosystem in China. The comprehensive analysis on the cultivated land green utilization efficiency (GUECL), its influencing factors, and optimization direction provides a valuable basis for the green utilization of cultivated land. Based on a panel data of 30 provinces (cities or districts) in China from 2001 to 2016, the GUECL in China under the constraints of pollution and carbon emissions was measured by using a super-efficient SBM-VRS (slack based model-variable return to scale) model. The influencing factors and optimization directions of the GUECL were analyzed through the Tobit model and slack values, respectively. The results show that the GUECL in China rose with fluctuations from 2001 to 2016. Since 2014, the eastern region has surpassed the western region and has become the region with the highest mean GUECL value. The room for resource conservation and pollution reduction varies in different regions of China. Farmers’ dependence on cultivated land and agricultural added value are positively related to the GUECL in China. Farmers’ occupational differentiation, agricultural machinery density, and agricultural disaster rate have had negative effects on the GUECL in China. The loss of the GUECL in China is mainly due to the redundancies of land input, pollution emission, and mechanical input. By analyzing these influencing factors and optimization directions, it is concluded that improving rural land transfer market and agricultural infrastructure construction, establishing a new agricultural technology extension system, and vigorously cultivating new professional farmers are the targeted measures to improve the GUECL.

scholarly journals Study on the Temporal and Spatial Differentiation of Provincial Tourism Efficiency in Eastern China and Influencing Factors

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Huadi Wang ◽  
Shaogui Xu ◽  
Qiuyi Xie ◽  
Jianying Fan ◽  
Nianxing Zhou
Keyword(s):  
Economic Development ◽  
Influencing Factors ◽  
Labour Force ◽  
Eastern China ◽  
Regional Distribution ◽  
Malmquist Index ◽  
Spatial Differentiation ◽  
Scale Efficiency ◽  
Resource Endowment ◽  
Temporal And Spatial

Tourism efficiency can be used to effectively measure the utilization of regional tourism resources and the state of tourism economic development. Based on the super efficiency DEA model, Malmquist index, and spatial econometric model, this article measures the static and dynamic tourism efficiency of 11 provinces and cities in eastern China for 2010 to 2019. In combining ArcGIS 10.0 and MATLAB 2016b software, this article studies the temporal and spatial differentiation of tourism efficiency in eastern provinces and cities and influencing factors. The results show that (1) the overall tourism efficiency of eastern provinces is at a high level and relatively stable, but the regional distribution is quite varied, and problems of spatial imbalance are prominent; (2) the overall tourism efficiency of eastern provinces is increasing, and the change index of technical efficiency contributes the most, followed by the change index of scale efficiency; and (3) industrial status, traffic conditions, tourism resource endowment, and the labour force are the main factors affecting the temporal and spatial differentiation of tourism efficiency in eastern provinces and cities, while the level of economic development and information technology have no significant impact.

scholarly journals Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors

Healthcare ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 231 ◽  
Author(s):  
Chenyu Lu ◽  
Shulei Jin ◽  
Xianglong Tang ◽  
Chengpeng Lu ◽  
Hengji Li ◽  
...  
Keyword(s):  
Health Status ◽  
Influencing Factors ◽  
Spatial Clustering ◽  
Temporal Stability ◽  
Spatial Differentiation ◽  
Entropy Method ◽  
Practical Significance ◽  
Measurement Models ◽  
Spatio Temporal ◽  
Urbanization Rate

Health is the basis of a good life and a guarantee of a high quality of life. Furthermore, it is a symbol of social development and progress. How to further improve the health levels of citizens and reduce regional differences in citizens’ health status has become a research topic of great interest that is attracting attention globally. This study takes 31 provinces (municipalities and autonomous regions) of China as the research object. Through using GIS (Geographic Information System) technology, the entropy method, spatial autocorrelation, stepwise regression, and other quantitative analysis methods, measurement models and index systems are developed in order to perform an analysis of the spatio-temporal comprehensive measurements of Chinese citizens’ health levels. Furthermore, the associated influencing factors are analyzed. It has important theoretical and practical significance. The conclusions are as follows: (1) Between 2002 and 2018, the overall health levels of Chinese citizens have generally exhibited an upward trend. Moreover, for most provinces, the health levels of their citizens have improved dramatically, although some provinces, such as Tianjin and Henan, showed a fluctuating downward trend, suggesting that the health levels of citizens in these regions displayed a tendency to deteriorate. (2) The health levels of citizens from China’s various provinces showed clear spatial distribution characteristics of clustering, as well as an obvious spatial dependence and spatial heterogeneity. As time goes by, the degree of spatial clustering with regard to citizens’ health levels tends to weaken. The health levels of Chinese citizens have developed a certain temporal stability, the overall health status of Chinese citizens shows a spatial differentiation of a northeast–southwest distribution pattern. (3) The average years of education and urbanization rate have a significant positive effect on the improvement of citizens’ health levels. The increase of average years of education and urbanization rate can promote the per capita income, which certainly could help improve citizens’ health status. The Engel coefficient, urban–rural income ratio, and amount of wastewater discharge all pose a significant negative effect on the improvement of citizens’ health levels, these three factors have played important roles in hindering the improvements of citizen health.

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