Knowledge Polycentricity of China’s Urban Agglomerations

Ma, Haitao; Xu, Xuanfang

doi:10.1061/(asce)up.1943-5444.0000828

Cited by 4 publications

(2 citation statements)

References 38 publications

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“…Innovative activities initially take place in the active interaction between innovative subjects in the city, as geographic proximity reduces uncertainty and resolves coordination problems in balancing risks and costs of innovation (Boschma, 2005;Ma et al, 2021). Regional innovation system theorists such as Cooke (Cooke, 2001) pointed out that the richer the local innovation resources and the closer the internal connections, the healthier the network innovation system and the stronger the competitiveness (Ma and Xu, 2022). The unintended spillover effects generated by the linkage of innovation agents within cities cannot be ignored on the overall regional resilience.…”

Section: Innovation Network Resilience On the Node Levelmentioning

confidence: 99%

Towards innovation resilience through urban networks of co-invention: A case study of cities in China

Xu²,

Li³

et al. 2022

Front. Earth Sci.

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The intensified competition for innovation among countries and the various risks that come with it have made innovation resilience a central concern of the international community in recent years. The concepts of resilience and innovation are inextricably intertwined; however, both theoretical discussions and case studies on innovation resilience are in the “embryonic” stage. This article attempts to integrate the system and nodes of network resilience, the potential and connectivity of city resilience, and the hierarchy and assortativity of urban network resilience to construct a theoretical analysis framework of intercity innovation network resilience and conduct a case study on the resilience of a patent cooperation network among 338 prefecture-level cities in China during 2017–2019. The results show that the systemic resilience of Chinese urban innovation networks exhibits relatively low hierarchical and yearly decreasing disassortative characteristics, and the node resilience shows a spatial pattern of being high in the southeast and low in the northwest, as well as higher innovation resilience in cities with higher administrative levels. The results provide insights into the overall systemic and internal structural characteristics of innovation resilience in Chinese urban networks and also expand the application of resilience concepts in the field of innovation research from the perspective of urban networks.

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Section: Innovation Network Resilience On the Node Levelmentioning

confidence: 99%

Towards innovation resilience through urban networks of co-invention: A case study of cities in China

Xu²,

Li³

et al. 2022

Front. Earth Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The monocentric development mode of urban agglomerations refers to a dominant core city in the urban agglomeration that drives the development of all other cities within the agglomeration. On the other hand, the polycentric development mode refers to multiple cities sharing the function of a core city [18][19][20], while other cities are connected by a complex transportation network around several core cities [21][22][23]. Compared to the monocentric spatial structure, the polycentric spatial structure of urban agglomerations theoretically has a better economic structure, a more mature market development, a more obvious agglomeration effect, a superior location effect and a scale effect [24].…”

Section: Introductionmentioning

confidence: 99%

Polycentric Spatial Structure Evolution and Influencing Factors of the Kunming–Yuxi Urban Agglomeration: Based on Multisource Big Data Fusion

Zhang

Zhao

et al. 2023

Land

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The polycentric spatial structure is the most common spatial form of urban agglomerations, so exploring the evolution of this structure and analyzing its influencing factors is of great significance for the optimization of the spatial structure of urban agglomerations. However, there are relatively few studies on the topic that fuse multisource big data analysis, especially in the urban agglomeration of Western China. Therefore, this study uses a fusion of nighttime light (NTL) data, point of interest (POI) data and LandScan data to identify the polycentric spatial structure and its evolution in the Kunming–Yuxi (Kunyu) urban agglomeration and analyzes the factors that have dominated its evolution at different periods using geographic detectors. Results show that the fusion of multisource big data are more in line with the actual development process of the Kunyu urban agglomeration and the factors that have dominated the spatial evolution at different periods vary but the government and sectors have gradually become increasingly important. This study provides a feasible path for exploring urban spatial evolution through the fusion analysis of multisource big data in the Kunyu urban agglomeration and provides a reference for the key directions of urban agglomeration planning and development at different periods.

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Identification and Evaluation of the Polycentric Urban Structure: An Empirical Analysis Based on Multi-Source Big Data Fusion

Zhou

Zhu

2022

Remote Sensing

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Identifying and evaluating polycentric urban spatial structure is essential for understanding and optimizing current urban development. In order to accurately identify the urban centers of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), this study firstly fused nighttime light data, POI data, and population migration data based on wavelet transform, then identified the polycentric spatial structure of the GBA by carrying out cluster and outlier analysis, and evaluated the level of different urban centers byconducting geographical weighted regression analysis. Using data fusion, we identified 4579.81 km² of the urban poly-center area in the GBA, with an identification accuracy of 93.22%. Although the number and spatial extent of the identified urban poly-centers are consistent with the GBA development plan outline, the poly-center level evaluation results are inconsistent with the development plan, which shows there are great differences in actual development levels among different cities in the GBA. By identifying and grading the polycentric spatial structure of the GBA, this study accurately analyzed the current spatial distribution and could provide policy implications for the GBA’s future development and planning.

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Knowledge Polycentricity of China’s Urban Agglomerations

Cited by 4 publications

References 38 publications

Towards innovation resilience through urban networks of co-invention: A case study of cities in China

Towards innovation resilience through urban networks of co-invention: A case study of cities in China

Polycentric Spatial Structure Evolution and Influencing Factors of the Kunming–Yuxi Urban Agglomeration: Based on Multisource Big Data Fusion

Identification and Evaluation of the Polycentric Urban Structure: An Empirical Analysis Based on Multi-Source Big Data Fusion

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