Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Measuring polycentric structures of megaregions in China: linking morphological and functional dimensions

Chen, Wei, Golubchikov, Oleg and Liu, Zhigao 2021. Measuring polycentric structures of megaregions in China: linking morphological and functional dimensions. Environment and Planning B: Urban Analytics and City Science 48 (8) , pp. 2272-2288. 10.1177/2399808320974687

[thumbnail of 2020-golubchikov-EPB.PDF]
PDF - Accepted Post-Print Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Preview


The idea of megaregions, which focuses on polycentricity, competitiveness, and integration attracts much attention in research and policy. China has used megaregions as a normative governance framework that leverages polycentric regional development for balancing economic competitiveness and spatial development. This paper explores to what extent these megaregions actually reveal polycentric versus monocentric structures. The analysis demonstrates a divergence between the morphological and functional organization of China’s megaregions. Five types of megaregions are identified as per the relationships between the morphological and functional dimensions. Functionally, the Pearl River Delta, Shandong Peninsula, and Yangtze River Delta are among the most polycentric megaregions. The majority of others, even where morphologically polycentric, do not exhibit high degrees of functional polycentricity. The study demonstrates a problematic nature of megaregions as a governance agenda for regional polycentricity. It argues that if China genuinely wants to achieve greater levels of polycentricity and spatial cohesion, differentiated policies should be implemented for megaregions.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Geography and Planning (GEOPL)
ISSN: 2399-8083
Date of First Compliant Deposit: 8 December 2020
Date of Acceptance: 19 October 2020
Last Modified: 14 Dec 2021 16:41

Citation Data

Cited 7 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics