World Regional Studies ›› 2022, Vol. 31 ›› Issue (6): 1310-1320.DOI: 10.3969/j.issn.1004-9479.2022.06.2020645
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Ting WANG1(), Peixue LIU2(), Guoping WU1, Jianxin ZHANG1, Aixin ZHENG1, Zhipei ZHU1
Received:
2020-09-15
Revised:
2020-12-18
Online:
2022-11-15
Published:
2022-11-22
Contact:
Peixue LIU
王婷1(), 刘培学2(), 吴国平1, 张建新1, 郑艾欣1, 朱知沛1
通讯作者:
刘培学
作者简介:
王婷(1997-),女,硕士研究生,研究方向为产业集聚与演变,E-mail:wt_nju@163.com。
基金资助:
Ting WANG, Peixue LIU, Guoping WU, Jianxin ZHANG, Aixin ZHENG, Zhipei ZHU. Spatial pattern evolution of cultural enterprises and the heterogeneity of its influential factors in Nanjing[J]. World Regional Studies, 2022, 31(6): 1310-1320.
王婷, 刘培学, 吴国平, 张建新, 郑艾欣, 朱知沛. 南京市文化企业空间格局及其影响因素 异质性研究[J]. 世界地理研究, 2022, 31(6): 1310-1320.
t\t+1 | HHt+1 | LHt+1 | LLt+1 | HLt+1 |
---|---|---|---|---|
HHt | Ⅳ(0.838) | Ⅰ(0.108) | Ⅲ(0.027) | Ⅱ(0.027) |
LHt | Ⅰ(0.07) | Ⅳ(0.791) | Ⅱ(0.14) | Ⅲ(0) |
LLt | Ⅲ(0.022) | Ⅱ(0.141) | Ⅳ(0.793) | Ⅰ(0.043) |
HLt | Ⅱ(0.25) | Ⅲ(0) | Ⅰ(0.071) | Ⅳ(0.679) |
Tab.1 Local Moran's I transition probability matrix
t\t+1 | HHt+1 | LHt+1 | LLt+1 | HLt+1 |
---|---|---|---|---|
HHt | Ⅳ(0.838) | Ⅰ(0.108) | Ⅲ(0.027) | Ⅱ(0.027) |
LHt | Ⅰ(0.07) | Ⅳ(0.791) | Ⅱ(0.14) | Ⅲ(0) |
LLt | Ⅲ(0.022) | Ⅱ(0.141) | Ⅳ(0.793) | Ⅰ(0.043) |
HLt | Ⅱ(0.25) | Ⅲ(0) | Ⅰ(0.071) | Ⅳ(0.679) |
变量类型 | 变量名称 | 简写 | 定义与解释 |
---|---|---|---|
交通 | 地铁站点 | SUBW | 地铁站点数量 |
路网密度 | RDEN | 研究单元内路网密度 | |
经济 | 生产要素成本 | LAND | 商业用地土地价格 |
资源 | 旅游景区 | SCEN | 4A及以上景区数量 |
文博物馆 | MUSU | 文博物馆数量 | |
文化产业园 | DEVE | 市级以上文化产业园区数量 | |
高等院校 | COLL | 高等院校数量 | |
企业集聚 | 产业历史基础 | NUMB | 十年前每个单元集聚的文化企业数量 |
Tab.2 Explanations of variables of location choice of cultural enterprises
变量类型 | 变量名称 | 简写 | 定义与解释 |
---|---|---|---|
交通 | 地铁站点 | SUBW | 地铁站点数量 |
路网密度 | RDEN | 研究单元内路网密度 | |
经济 | 生产要素成本 | LAND | 商业用地土地价格 |
资源 | 旅游景区 | SCEN | 4A及以上景区数量 |
文博物馆 | MUSU | 文博物馆数量 | |
文化产业园 | DEVE | 市级以上文化产业园区数量 | |
高等院校 | COLL | 高等院校数量 | |
企业集聚 | 产业历史基础 | NUMB | 十年前每个单元集聚的文化企业数量 |
变量 | OLS模型 | GWR模型 | ||
---|---|---|---|---|
回归系数 | 回归系数 | |||
常数 | 0.010 | 0.259 | 0.012 | 0.436 |
SUBW | 0.133** | 2.129 | 0.138** | 2.144 |
RDEN | 0.155** | 1.965 | 0.155** | 1.967 |
LAND | 0.126* | 1.890 | 0.145** | 2.041 |
SCEN | 0.048 | 0.910 | 0.051 | 0.927 |
MUSU | 0.005 | 0.069 | 0.004 | 0.084 |
DEVE | 0.053* | 1.750 | 0.054* | 1.765 |
COLL | 0.158*** | 2.734 | 0.151*** | 2.585 |
NUMB | 0.370*** | 4.226 | 0.367*** | 5.163 |
R2 | 0.823 | 0.872 | ||
调整后R2 | 0.808 | 0.848 | ||
AICc | 132.949 | 118.235 |
Tab.3 Estimation results of OLS and GWR parameters
变量 | OLS模型 | GWR模型 | ||
---|---|---|---|---|
回归系数 | 回归系数 | |||
常数 | 0.010 | 0.259 | 0.012 | 0.436 |
SUBW | 0.133** | 2.129 | 0.138** | 2.144 |
RDEN | 0.155** | 1.965 | 0.155** | 1.967 |
LAND | 0.126* | 1.890 | 0.145** | 2.041 |
SCEN | 0.048 | 0.910 | 0.051 | 0.927 |
MUSU | 0.005 | 0.069 | 0.004 | 0.084 |
DEVE | 0.053* | 1.750 | 0.054* | 1.765 |
COLL | 0.158*** | 2.734 | 0.151*** | 2.585 |
NUMB | 0.370*** | 4.226 | 0.367*** | 5.163 |
R2 | 0.823 | 0.872 | ||
调整后R2 | 0.808 | 0.848 | ||
AICc | 132.949 | 118.235 |
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