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A platform for research: civil engineering, architecture and urbanism
The Spatial Pattern and Influencing Factors of Urban Knowledge-Intensive Business Services: A Case Study of Wuhan Metropolitan Area, China
Knowledge-intensive business services (KIBSs) are key links in leading the sustainable development of cities. Studying the spatial pattern and influencing factors of urban KIBSs can help improve the utilization of KIBS resources. Taking the Wuhan metropolitan area as a case study, based on data from industrial and commercial registration enterprises, this study uses the multi-ring buffer zone analysis and kernel density estimation method to analyze the spatial pattern of KIBS, and uses a negative binomial regression model to detect the influencing factors of the spatial pattern of KIBS. The results show that: (1) KIBSs are mainly distributed in the inner suburbs, presenting a multi-center spatial pattern, exhibiting the law of agglomeration along entrepreneurial streets, headquarter bases, science and technology parks, university clusters, business centers, and industrial bases. Obvious differences exist in the spatial patterns of KIBS sub-sectors. (2) Land price, traffic conditions, office space, commercial environment, technology factors, industry diversity, incubation environment, investment environment, manufacturing foundation, agglomeration factors, and policy factors are the main factors affecting the spatial patterns of KIBSs. There are differences in the impact of influencing factors on KIBS sub-sectors. The results can provide a decision-making basis for the rational layout and planning of urban KIBSs in the post-industrial era.
The Spatial Pattern and Influencing Factors of Urban Knowledge-Intensive Business Services: A Case Study of Wuhan Metropolitan Area, China
Knowledge-intensive business services (KIBSs) are key links in leading the sustainable development of cities. Studying the spatial pattern and influencing factors of urban KIBSs can help improve the utilization of KIBS resources. Taking the Wuhan metropolitan area as a case study, based on data from industrial and commercial registration enterprises, this study uses the multi-ring buffer zone analysis and kernel density estimation method to analyze the spatial pattern of KIBS, and uses a negative binomial regression model to detect the influencing factors of the spatial pattern of KIBS. The results show that: (1) KIBSs are mainly distributed in the inner suburbs, presenting a multi-center spatial pattern, exhibiting the law of agglomeration along entrepreneurial streets, headquarter bases, science and technology parks, university clusters, business centers, and industrial bases. Obvious differences exist in the spatial patterns of KIBS sub-sectors. (2) Land price, traffic conditions, office space, commercial environment, technology factors, industry diversity, incubation environment, investment environment, manufacturing foundation, agglomeration factors, and policy factors are the main factors affecting the spatial patterns of KIBSs. There are differences in the impact of influencing factors on KIBS sub-sectors. The results can provide a decision-making basis for the rational layout and planning of urban KIBSs in the post-industrial era.
The Spatial Pattern and Influencing Factors of Urban Knowledge-Intensive Business Services: A Case Study of Wuhan Metropolitan Area, China
Zilu Ma (author) / Yaping Huang (author)
2024
Article (Journal)
Electronic Resource
Unknown
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