TY - JOUR
T1 - Moving towards a sustainable and innovative city
T2 - Internal urban traffic accessibility and high-level innovation based on platform monitoring data
AU - Jin, Peizhen
AU - Mangla, Sachin Kumar
AU - Song, Malin
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/5
Y1 - 2021/5
N2 - Quantitative evaluation of the impact of traffic accessibility within large cities on innovation quality is conducive to a better understanding of urban governance and sustainable development. This paper analyzed the impact of traffic accessibility on regional and enterprise innovation using the big data from a floating car track monitored by the platform in five large cities in China. The study found that there is significant heterogeneity in the quantity, structure, and spatial distribution characteristics of high-level innovation. For every 1% increase in the speed of traffic in townships and blocks, the number of invention patent applications in Type-I cities with a population between three and five million will increase by 4.175%, and the positive impact on low-tech patent applications will be clearer. With improved traffic accessibility, the high-level innovation in super-large cities and Type-I cities tends to focus on spatial diffusion. Evidence from the multiscale geographically weighted regression (MGWR) shows that even within the same type of city, the sensitivity of high-level innovation of enterprises in different spatial locations to traffic speed is significantly heterogeneous. This suggests that future infrastructure construction and traffic system optimization should focus on more sensitive enterprise clusters.
AB - Quantitative evaluation of the impact of traffic accessibility within large cities on innovation quality is conducive to a better understanding of urban governance and sustainable development. This paper analyzed the impact of traffic accessibility on regional and enterprise innovation using the big data from a floating car track monitored by the platform in five large cities in China. The study found that there is significant heterogeneity in the quantity, structure, and spatial distribution characteristics of high-level innovation. For every 1% increase in the speed of traffic in townships and blocks, the number of invention patent applications in Type-I cities with a population between three and five million will increase by 4.175%, and the positive impact on low-tech patent applications will be clearer. With improved traffic accessibility, the high-level innovation in super-large cities and Type-I cities tends to focus on spatial diffusion. Evidence from the multiscale geographically weighted regression (MGWR) shows that even within the same type of city, the sensitivity of high-level innovation of enterprises in different spatial locations to traffic speed is significantly heterogeneous. This suggests that future infrastructure construction and traffic system optimization should focus on more sensitive enterprise clusters.
KW - High-level innovation
KW - Multi-scale geo-weighted regression
KW - Spatial heterogeneity
KW - Traffic accessibility
UR - https://www.scopus.com/pages/publications/85102833972
U2 - 10.1016/j.ijpe.2021.108086
DO - 10.1016/j.ijpe.2021.108086
M3 - 文章
AN - SCOPUS:85102833972
SN - 0925-5273
VL - 235
JO - International Journal of Production Economics
JF - International Journal of Production Economics
M1 - 108086
ER -