TY - JOUR
T1 - Developing a Framework for Spatial Effects of Smart Cities Based on Spatial Econometrics
AU - Liu, Kongling
AU - Wang, Mengjun
AU - Li, Jianchang
AU - Huang, Jingjing
AU - Huang, Xuhui
AU - Chen, Shuhang
AU - Cheng, Baoquan
N1 - Publisher Copyright:
© 2021 Kongling Liu et al.
PY - 2021
Y1 - 2021
N2 - The rapid urbanization in China has already put heavy pressures on imperfect infrastructure, especially for fundamental urban functions such as power and water supply, traffic, education, and healthcare. The emergence of smart cities can help cope with the rapidly expanding demands on urban infrastructure. However, the development of smart cities in China is just in its infancy, and there is still a lack of clear understanding of the development path of smart cities. This article focuses on the development of smart cities in China. It aims to (a) judge whether there is spatial autoregression in the construction of smart cities in 83 Chinese cities and (b) identify key influencing factors in the development of smart cities in China through a spatial econometric model developed by GeoDa software. The results show that there exists spatial autoregression in the development of smart cities in China. Four key influencing factors (governmental support, innovative level, economic development, and human capital) are identified. Based on these findings, suggestions for future promoting development of smart cities in China are put forward. This research can deepen the understanding of the spatial effects of smart cities and provide valuable decision-making references for policy makers.
AB - The rapid urbanization in China has already put heavy pressures on imperfect infrastructure, especially for fundamental urban functions such as power and water supply, traffic, education, and healthcare. The emergence of smart cities can help cope with the rapidly expanding demands on urban infrastructure. However, the development of smart cities in China is just in its infancy, and there is still a lack of clear understanding of the development path of smart cities. This article focuses on the development of smart cities in China. It aims to (a) judge whether there is spatial autoregression in the construction of smart cities in 83 Chinese cities and (b) identify key influencing factors in the development of smart cities in China through a spatial econometric model developed by GeoDa software. The results show that there exists spatial autoregression in the development of smart cities in China. Four key influencing factors (governmental support, innovative level, economic development, and human capital) are identified. Based on these findings, suggestions for future promoting development of smart cities in China are put forward. This research can deepen the understanding of the spatial effects of smart cities and provide valuable decision-making references for policy makers.
UR - http://www.scopus.com/inward/record.url?scp=85108460565&partnerID=8YFLogxK
U2 - 10.1155/2021/9322112
DO - 10.1155/2021/9322112
M3 - Article
AN - SCOPUS:85108460565
SN - 1076-2787
VL - 2021
JO - Complexity
JF - Complexity
M1 - 9322112
ER -