Tropical Geography ›› 2022, Vol. 42 ›› Issue (6): 928-938.doi: 10.13284/j.cnki.rddl.003489
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Jie Zhang(), Kerong Sheng(
), Chuanyang Wang
Received:
2021-05-19
Revised:
2021-07-05
Online:
2022-06-05
Published:
2022-05-27
Contact:
Kerong Sheng
E-mail:chamjay@163.com;shengkerong@163.com
CLC Number:
Jie Zhang, Kerong Sheng, Chuanyang Wang. Spatial Evolution and Underlying Factors of the Urban Financial Network in China[J].Tropical Geography, 2022, 42(6): 928-938.
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Table 1
Hierarchical differentiation of financial network
排名 | 2001年 | 2019年 | 2001年 | 2019年 | |||||
---|---|---|---|---|---|---|---|---|---|
城市 | 总连通度(NNC) | 城市 | NNC | 城市对 | 网络连通度(CDC) | 城市对 | CDC | ||
1 | 上海 | 13 639 904 | 北京 | 28 802 583 | 北京-上海 | 397 798 | 北京-上海 | 818 810 | |
2 | 北京 | 12 822 954 | 上海 | 26 977 210 | 上海-重庆 | 363 386 | 北京-重庆 | 669 145 | |
3 | 重庆 | 12 779 281 | 重庆 | 26 165 772 | 上海-广州 | 350 890 | 上海-重庆 | 630 603 | |
4 | 广州 | 11 928 266 | 天津 | 21 166 940 | 北京-广州 | 344 244 | 北京-天津 | 610 718 | |
5 | 天津 | 11 260 002 | 广州 | 20 911 141 | 北京-重庆 | 334 574 | 北京-广州 | 603 054 | |
6 | 苏州 | 8 066 321 | 成都 | 17 685 426 | 天津-上海 | 323 817 | 天津-上海 | 567 332 | |
7 | 佛山 | 7 655 184 | 苏州 | 14 272 003 | 广州-重庆 | 309 367 | 上海-广州 | 563 311 | |
8 | 成都 | 7 506 994 | 武汉 | 13 967 334 | 北京-天津 | 308 729 | 天津-重庆 | 500 363 | |
9 | 武汉 | 7 173 426 | 深圳 | 13 313 325 | 天津-重庆 | 299 349 | 北京-成都 | 500 335 | |
10 | 杭州 | 7 049 403 | 杭州 | 13 069 765 | 天津-广州 | 281 963 | 广州-重庆 | 482 618 |
Table 2
Results of k-cores analysis
k-核 | 城市 | 数量/个 |
---|---|---|
6-核 | 北京、天津、上海、杭州、苏州、深圳、广州、重庆、成都、西安、武汉 | 11 |
5-核 | 北京、天津、上海、杭州、苏州、深圳、广州、重庆、成都、西安、武汉、南京、沈阳、佛山、大连、宁波、福州、哈尔滨 | 18 |
3-核 | 北京、天津、上海、杭州、苏州、深圳、广州、重庆、成都、西安、武汉、南京、沈阳、佛山、大连、宁波、福州、哈尔滨、昆明、长春、无锡、长沙、郑州、石家庄 | 24 |
2-核 | 北京、天津、上海、杭州、苏州、深圳、广州、重庆、成都、西安、武汉、南京、沈阳、佛山、大连、宁波、福州、哈尔滨、昆明、长春、无锡、长沙、郑州、石家庄、泉州、温州、南宁、南通、青岛、济南 | 30 |
1-核 | 北京、天津、上海、杭州、苏州、深圳、广州、重庆、成都、西安、武汉、南京、沈阳、佛山、大连、宁波、福州、哈尔滨、昆明、长春、无锡、长沙、郑州、石家庄、泉州、温州、南宁、南通、青岛、济南、常州、 南昌、太原、合肥 | 34 |
Table 3
The core-periphery structure of financial network
地位 | 2001年 | 2019年 | |||
---|---|---|---|---|---|
城市 | 数量/个 | 城市 | 数量/个 | ||
核心 | 上海(0.31)、北京(0.29)、重庆(0.28)、广州(0.27)、天津(0.25)、苏州(0.18)、佛山(0.17)、成都(0.17)、武汉(0.16)、杭州(0.16)、福州(0.15)、西安(0.13)、宁波(0.13)、大连(0.13)、沈阳(0.12)、哈尔滨(0.12)、深圳(0.11) | 17 | 北京(0.32)、上海(0.30)、重庆(0.27)、天津(0.23)、广州(0.23)、成都(0.19)、苏州(0.15)、武汉(0.15)、深圳(0.14)、杭州(0.14)、西安(0.14)、佛山(0.13)、福州(0.13)、宁波(0.12)、大连(0.12)、沈阳(0.12)、哈尔滨(0.11)、南京(0.11)、郑州(0.11)、无锡(0.10)、昆明(0.10)、长春(0.10)、石家庄(0.10)、长沙(0.09)、青岛(0.09) | 25 | |
边缘 | 无锡(0.10)、昆明(0.10)、长春(0.10)、南京(0.10)、济南(0.10)、青岛(0.10)、温州(0.09)、泉州(0.09)、南昌(0.09)、长沙(0.09)、南宁(0.09)、南通(0.08)、东莞(0.08)、太原(0.08)等 | 268 | 济南(0.09)、温州(0.09)、南通(0.08)、泉州(0.08)、南宁(0.08)、常州(0.08)、南昌(0.08)、合肥(0.08)、太原(0.08)、东莞(0.08)、唐山(0.07)、保定(0.07)、金华(0.07)、兰州(0.07)、乌鲁木齐(0.07)等 | 260 |
Table 4
Analysis results of QAP regressions
解释变量 | 多值无向网络 | 二值无向网络 | |||||
---|---|---|---|---|---|---|---|
estimate | Proportion As Large | Proportion As Small | estimate | Proportion As Large | Proportion As Small | ||
R2 | 0.865 | 0.366 | |||||
intercept | 0.081 76*** | - | - | 0.409 30*** | - | - | |
value | 0.009 13*** | 0.000 | 1.000 | 0.148 03*** | 0.007 | 0.993 | |
capital | 0.011 96*** | 0.000 | 1.000 | 0.104 77** | 0.049 | 0.951 | |
knowledge | 0.008 97*** | 0.005 | 0.995 | 0.115 60** | 0.013 | 0.987 | |
open | 0.017 42*** | 0.000 | 1.000 | 0.142 47*** | 0.003 | 0.997 | |
distance | -0.005 54*** | 1.000 | 0.000 | -0.110 90*** | 1.000 | 0.000 | |
east | 0.008 89*** | 0.000 | 1.000 | 0.080 37** | 0.023 | 0.977 | |
lag2001 | 0.849 26*** | 0.000 | 1.000 | 0.521 14*** | 0.000 | 1.000 |
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