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dc.contributor.authorJie Guo; Xin Lao; Tiyan Shen
dc.date.accessioned2019-03-10T11:49:50Z
dc.date.available2019-03-10T11:49:50Z
dc.date.issued2019
dc.identifier.other%28ASCE%29UP.1943-5444.0000497.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4254338
dc.description.abstractThe extant quantitative methodologies to identify industrial clusters usually lack the combination of both industrial linkages and enterprise proximity information. To rectify this situation, this paper employs the location-based method, which considers both industrial linkages in the input–output (IO) table and enterprises’ microlocations, to identify industrial clusters in the Beijing–Tianjin–Hebei area in China. Using data on industrial enterprises larger than a designated size in 2012, we choose 5 km as the distance threshold after robustness tests and identify 19 industrial clusters. The result indicates that Beijing is superior in both cluster number and cluster type for the entire region, and enterprises in Hebei and Beijing clusters have a larger economic scale than those in Tianjin. The corresponding policy implication is that local governments of the Beijing–Tianjin–Hebei area should pay more attention to industrial cooperation and coordination across the administrative boundaries, such as shifting manufacturing enterprises from Beijing to Hebei, to promote industrial clustering. The proposed method in this study has distinct advantages over other methods in terms of reflecting the essence of industrial clusters, providing scientific evidence for policy making, and opening up a new avenue for quantitative and referenced empirical studies on industrial clusters from the perspective of individual enterprises.
dc.publisherAmerican Society of Civil Engineers
dc.titleLocation-Based Method to Identify Industrial Clusters in Beijing-Tianjin-Hebei Area in China
dc.typeJournal Paper
dc.journal.volume145
dc.journal.issue2
dc.journal.titleJournal of Urban Planning and Development
dc.identifier.doi10.1061/(ASCE)UP.1943-5444.0000497
dc.page04019001
dc.treeJournal of Urban Planning and Development:;2019:;Volume ( 145 ):;issue: 002
dc.contenttypeFulltext


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