scholarly journals Research on the Structural Features and Influential Factors of the Spatial Network of China’s Regional Ecological Efficiency Spillover

2020 ◽  
Vol 12 (8) ◽  
pp. 3137
Author(s):  
Jingrong Xu ◽  
Dechun Huang ◽  
Zhengqi He ◽  
Yun Zhu
Keyword(s):  
Sustainable Development ◽  
Network Analysis ◽  
Influential Factors ◽  
Spatial Network ◽  
Analysis Method ◽  
Ecological Efficiency ◽  
Important Indicator ◽  
Correlation Relationship ◽  
Edge Structure ◽  
Spatial Spillover

A regional coordinated development strategy is an important measure that is often used to implement sustainable development in China. However, many obstacles greatly limit the realization of regional ecological coordinated sustainable development. In this paper, ecological efficiency is utilized as an important indicator of sustainable development, and the network analysis method is used to explore the spatial correlation relationship of regional ecological coordinated sustainable development. This paper calculates the ecological efficiency of each region using the Window slacks-based measure (Window-SBM) model, formulates the spatial network of regional ecological efficiency spillover through the vector auto-regressive (VAR) Granger causality model, and analyzes the spatial spillover relationship and influencing factors of regional ecological efficiency by using the social network analysis method. It is found that the spillover network of ecological efficiency in each region presents a typical core-edge structure. In addition, there is an obvious hierarchical structure among blocks with different directions and functions. Industrial structure, economic development, and geographical proximity have a positive impact on the spatial spillover of regional ecological efficiency, while environmental regulation has a negative impact. Finally, relevant policy suggestions are put forward.

scholarly journals The Spatial Correlation and Explanation of the Evolution of China’s Regional Human Capital Structure—Based on Network Analysis Method

2020 ◽  
Vol 13 (1) ◽  
pp. 212
Author(s):  
Xiao Dai ◽  
Liang Yan
Keyword(s):  
Human Capital ◽  
Network Analysis ◽  
Capital Structure ◽  
Regional Development ◽  
Spatial Correlation ◽  
Clustering Coefficient ◽  
Eastern Region ◽  
Spatial Network ◽  
Analysis Method ◽  
The Difference

Human capital is an important catalyst for technology to play its role and the key to ensuring regional sustainable development. The current research on human capital mainly considers the imbalance of its stock and regional distribution without of the overall description of human capital structure and an analysis of its spatial correlation. Therefore, this article first builds a model of human capital structure evolution (HCSE) based on primary human capital, advanced human capital combined with economic geographic weight matrix, then uses the network analysis method to make a new deconstruction of the spatial correlation characteristics and the factors of China’s regional HCSE from 2009 to 2018. The results show that: (1) China’s HCSE has experienced regional accumulation in 2012, 2015, and 2018, having more prominent path dependence characteristics, which moreover vary significantly with China’s provinces, that is, the eastern region is dominated by the path of outward overflow, and the central and western regions alternate inward input and outward output; (2) The spatial network of HCSE in China is stable and multi-superimposed. During the sample investigation period, the overall network density first increased and then decreased, the largest regional clustering coefficient and transmission efficiency appeared in 2014; (3) The eastern region (Beijing, Shanghai, and Guangdong as the core) is at the center of network spillover, playing a pivotal role as well as an intermediary and bridge role; conversely, the western region plays a central role in promoting the spatial network of HCSE to the direction of external dependence, while most of the central region has a diminished role in the evolution of spatial association networks; (4) The spatial correlation of HCSE in China is mainly affected by three types of factors: the urbanization level, the investment scale, and the degree of regional development. The greater the difference in urbanization levels is, the closer the spatial correlation of HCSE and the higher its network efficiency is; while the difference in investment scale and regional development has the opposite effect.

How influential factors affect aviation networks: A Bayesian network analysis

2021 ◽  
Vol 91 ◽  
pp. 101995
Author(s):  
Yue Wang ◽  
Collin Wai Hung Wong ◽  
Tommy King-Yin Cheung ◽  
Edmund Yangming Wu
Keyword(s):  
Network Analysis ◽  
Bayesian Network ◽  
Influential Factors

scholarly journals Study on Relative Carrying Capacity of Land Resources and Its Zoning in 31 Provinces of China

2021 ◽  
Vol 13 (3) ◽  
pp. 1459
Author(s):  
Wei Zhou ◽  
Ayman Elshkaki ◽  
Shuai Zhong ◽  
Lei Shen
Keyword(s):  
Sustainable Development ◽  
Carrying Capacity ◽  
Coastal Region ◽  
Land Resources ◽  
Parameter Setting ◽  
Single Factor ◽  
Important Indicator ◽  
The Sustainable Development ◽  
Land Carrying Capacity ◽  
Human And Nature

Land carrying capacity is an important indicator to quantitatively assess and judge the extents of sustainable economic developing and coexistent harmonizing between human and nature. The significance of land carrying capacity has been highlighted recently by the Sustainable Development Goals (SDGs) of the United Nations, which set clear requirements for arable, construction, and ecological lands. Theories and models of land carrying capacity, however, are suffering from the interference of artificial parameter setting and poor applicability. This paper attempts to overcome these limitations and propose a single factor assessment of the carrying capacity of cultivated land, construction land, and ecological land in terms of the relative carrying capacity from the perspective of a single factor assessment. Through mutual comparison, we found that the deviation caused by simulated parameter setting has been eliminated, and the relative status of each province and/or region in China has been obtained, which could provide a reference for the management and utilization of land resources. We argue that China can achieve basic self-sufficiency in both space capacity and food production without placing pressure on the global sustainable development. The results also indicate that carrying capacity state of the advanced development areas such as the eastern coastal region is relatively poor, while the carrying capacity state of the western region is relatively good.

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