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

The competitiveness of China’s leading regions: benchmarking their knowledge-based economies

Huggins, Robert, Luo, Shougui and Thompson, Piers 2014. The competitiveness of China’s leading regions: benchmarking their knowledge-based economies. Tijdschrift voor economische en sociale geografie 105 (3) , pp. 241-267. 10.1111/tesg.12065

Full text not available from this repository.

Abstract

China's spectacular economic growth has been spatially uneven, with much development occurring in eastern coastal areas. In particular, three metropolitan ‘super-regions’ have become China's most competitive knowledge-based economies, consisting of the Pearl River Delta, the Yangtze River Delta, and the Bohai Gulf Region. This paper benchmarks the competitiveness of these regions, with a view to exploring which region is best positioned to become the most dominant knowledge-based economy over time. Through the theoretical lens of dynamic comparative advantage, it is shown that each region has hugely increased its competitiveness through improvements in the capacity to absorb and diffuse knowledge. It is further shown that due to multi-dimensional advantages the Yangtze River Delta, incorporating the Shanghai metropolis, is best positioned to become the dominant hub of China's future knowledge economy. It is concluded that China's leading regions will require further economic policy adjustments in order to secure their future competitiveness.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Geography and Planning (GEOPL)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HC Economic History and Conditions
Uncontrolled Keywords: Competitiveness; Benchmarking; Knowledge; Dynamic comparative advantage; Innovation; Growth; Regions; China
Publisher: Royal Dutch Geographical Society KNAG
ISSN: 1467-9663
Last Modified: 07 Nov 2019 09:04
URI: http://orca-mwe.cf.ac.uk/id/eprint/71195

Citation Data

Cited 6 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item