scholarly journals Analysis on the Economic Spatial Linkage Gravity Model of the Urban Agglomeration in Northeast Zhejiang

2018 ◽  
Author(s):  
Ying ZI
Keyword(s):  
Gravity Model ◽  
Urban Agglomeration

scholarly journals Integration Development of Urban Agglomeration in Central Liaoning, China, by Trajectory Gravity Model

2021 ◽  
Vol 10 (10) ◽  
pp. 698
Author(s):  
Ruren Li ◽  
Shoujia Li ◽  
Zhiwei Xie
Keyword(s):  
Gravity Model ◽  
Gravitational Force ◽  
Main Idea ◽  
Correlation Coefficients ◽  
Urban Agglomeration ◽  
Economic Research ◽  
The Core ◽  
Proposed Model ◽  
Two Indices ◽  
Spatial Trajectory

Integration development of urban agglomeration is important for regional economic research and management. In this paper, a method was proposed to study the integration development of urban agglomeration by trajectory gravity model. It can analyze the gravitational strength of the core city to other cities and characterize the spatial trajectory of its gravitational direction, expansion, etc. quantitatively. The main idea is to do the fitting analysis between the urban axes and the gravitational lines. The correlation coefficients retrieved from the fitting analysis can reflect the correlation of two indices. For the different cities in the same year, a higher value means a stronger relationship. There is a clear gravitational force between the cities when the value above 0.75. For the most cities in different years, the gravitational force between the core city with itself is increasing by years. At the same time, the direction of growth of the urban axes tends to increase in the direction of the gravitational force between cities. There is a clear tendency for the trajectories of the cities to move closer together. The proposed model was applied to the integration development of China Liaoning central urban agglomeration from 2008 to 2016. The results show that cities are constantly attracted to each other through urban gravity.

scholarly journals Spatial Network Structures of Urban Agglomeration Based on the Improved Gravity Model: A Case Study in China’s Two Urban Agglomerations

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yubo Zhao ◽  
Gui Zhang ◽  
Hongwei Zhao
Keyword(s):  
Gravity Model ◽  
Yangtze River Delta ◽  
Urban Agglomeration ◽  
Spatial Distance ◽  
Range Limit ◽  
Population Mobility ◽  
Urban Agglomerations ◽  
City Network ◽  
The City

Research on urban agglomerations from the perspective of network spatial structure is important to promote their sustainable development. Based on online and traditional data, this paper first improves three aspects of the traditional spatial gravity model—city quality, the gravitation coefficient, and city distance—considering urban center functional intensity and population mobility tendencies. The resulting improved directional gravity model is applied to analyze the structure of the city network for two urban agglomerations in China, the Beijing-Tianjin-Hebei urban agglomeration (BTHUA) and the Yangtze River Delta urban agglomeration (YRDUA). The results of the study are as follows: (1) the existing urban connections have obvious hierarchies and imbalances, with the YRDUA urban hierarchical connections being of larger scale. (2) Cities are closely connected, but city networks are unbalanced, though the YRDUA has more balanced urban development. (3) Each node city has a clear radiation range limit, and spatial distance remains an important constraint on urban connections. The backbone network of the BTHUA has a triangular shape and trends toward a “sparse north and dense south,” while the YRDUA is characterized by multiple axes and an overall distribution that trends toward a “dense north and sparse south.” (4) Cities with poor comprehensive strength are more likely to be captured, forming an attract and be attracted relationship. (5) The BTHUA and the YRDUA each form three communities.

B2C e-commerce logistics network optimization model

2022 ◽  
Vol 30 (3) ◽  
pp. 0-0
Keyword(s):  
Gravity Model ◽  
Network Structure ◽  
Network Optimization ◽  
Optimization Model ◽  
Operation Mode ◽  
Cost Optimization ◽  
Urban Agglomeration ◽  
Logistics Network ◽  
Definition Of ◽  
Full Investigation

In this paper, considering the characteristics of e-commerce logistics and the problems arising from the construction of logistics network, based on the full investigation and research of the B2C electricity supplier operation mode, we have studied and summarized the research results of scholars at home and abroad aiming at the related problems, and summarized and summarized the methods and steps of logistics network optimization in the whole country. First, we established the logistics network structure.The definition of network level, node function and connection between nodes is carried out. Then, through the improved urban agglomeration order gravity model, the scope of self logistics city is screened. Finally, the link of logistics network structure is scheduled for completion with the goal of cost optimization.

scholarly journals B2C E-Commerce Logistics Network Optimization Model

2022 ◽  
Vol 30 (3) ◽  
pp. 1-19
Author(s):  
Xiaheng Zhang
Keyword(s):  
Gravity Model ◽  
Network Structure ◽  
Network Optimization ◽  
Optimization Model ◽  
Operation Mode ◽  
Cost Optimization ◽  
Urban Agglomeration ◽  
Logistics Network ◽  
Definition Of ◽  
Full Investigation

In this paper, considering the characteristics of e-commerce logistics and the problems arising from the construction of logistics network, based on the full investigation and research of the B2C electricity supplier operation mode, we have studied and summarized the research results of scholars at home and abroad aiming at the related problems, and summarized and summarized the methods and steps of logistics network optimization in the whole country. First, we established the logistics network structure.The definition of network level, node function and connection between nodes is carried out. Then, through the improved urban agglomeration order gravity model, the scope of self logistics city is screened. Finally, the link of logistics network structure is scheduled for completion with the goal of cost optimization.

scholarly journals The relationship between Liaoning urban agglomeration based on Gravity Model

2020 ◽  
Vol 194 ◽  
pp. 05044
Author(s):  
Zhi Jing
Keyword(s):  
Gravity Model ◽  
Data Visualization ◽  
Central City ◽  
Urban Agglomeration ◽  
Liaoning Province ◽  
Southern City ◽  
The Relationship ◽  
City Group

.This paper simulates the economic gravitation between 14 prefecture level cities of Liaoning province by gravity model, and achieves data visualization through ArcMap and Ucinet . It is concluded that the central city group of Liaoning is composed of Shenyang, Liaoyang, Benxi, Anshan, Fushun and Tieling.The southern city group of Liaoning is composed of Dalian, Yingkou, Panjin, Huludao and Jinzhou.

scholarly journals Comparative analysis of Beijing-Tianjin-Hebei urban agglomeration, Yangtze river delta urban agglomeration, Guangdong, Hong Hong and Macau Bay area based on gravity model

2019 ◽  
Author(s):  
Nan Huihui ◽  
◽  
Lu Qing ◽  
Zhao Qian ◽  
◽  
...  
Keyword(s):  
Hong Kong ◽  
Gravity Model ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
Urban Agglomerations ◽  
Bay Area ◽  
The Yangtze River Delta

Beijing-Tianjin-Hebei urban agglomeration, Yangtze River Delta urban agglomeration and the Guangdong, Hong Kong, Macau Greater Bay Area are China's three major urban agglomerations, including China's political, economic, financial and technological centers, which are important engines of the Chinese economy. The purpose of this study is to compare these three urban agglomerations from the economy, government management and spatial interactions. The major methodology of the study is gravity model. Since there are no clear official regulations for the scope of the three major urban agglomerations, we should define the scope and core areas at first, making them at a comparable level. First of all, the economy of the three major urban agglomerations in the wide area range are similar, while the core area of Beijing-Tianjin-Hebei urban agglomeration is the weakest in per capita GDP. In the perspective of government management, the Beijing-Tianjin-Hebei urban agglomeration is policy-oriented and pays more attention to regional balanced development. The Yangtze River Delta urban agglomeration mainly focus on economic development. Under the policy of reform and opening up, Guangdong, Hong Kong, Macau Bay Area is seeking more regional cooperation with Hong Kong and Macau. In terms of spatial interactions, the Beijing-Tianjin-Hebei urban agglomeration presents a dual-core structure between Beijing and Tianjin. The other urban nodes in Hebei Province are not obvious, and the regional connections are weak, leading to unbalanced development. The Yangtze River Delta urban agglomeration presents the characteristics of a networked structure, and the cities in the entire region are closely connected and have a tendency to be integrated both in economy and transportation. The Guangdong, Hong Kong and Macau Greater Bay Area has formed a strong core composed of cities such as Guangzhou, Shenzhen, Hong Kong, Macau and Dongguan, which are closely linked with each other, but weakly connected with external region.

Internal migration in Italy. Long-run analysis of push and pull factors across regions and macro-areas of the country.

2016 ◽  
Vol 13 (3) ◽  
pp. 443-454
Author(s):  
Piras Romano
Keyword(s):  
Gravity Model ◽  
Internal Migration ◽  
Empirical Studies ◽  
Great Majority ◽  
Pull Factors ◽  
Push And Pull Factors ◽  
Long Run ◽  
Italian Regions ◽  
Migration Flows ◽  
Push And Pull

The great majority of empirical studies on internal migration across Italian regions either ignores the long-run perspective of the phenomenon or do not consider push and pull factors separately. In addition, Centre-North to South flows, intra-South and intra-Centre-North migration have not been studied. We aim to fill this gap and tackle interregional migration flows from different geographical perspectives. We apply four panel data estimators with different statistical assumptions and show that long-run migration flows from the Mezzogiorno towards Centre-Northern regions are well explained by a gravity model in which per capita GDP, unemployment and population play a major role. On the contrary, migration flows from Centre-North to South has probably much to do with other social and demographic factors. Finally, intra Centre-North and intra South migration flows roughly obey to the gravity model, though not all explicative variables are relevant.

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