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Industry cluster presents a dynamic nature. Based on the theoretical development of maritime cluster evolution in research literature, the components and functions of maritime cluster are observed to have changed over time and geographical dimension. However, we find no empirical analysis on maritime cluster evolution that reflects the diverse components and their interactions within a cluster. Particularly, there is no prior research analysing interactions between port and other maritime sectors, though the port is deemed to play an important role among the sectors in maritime cluster development. This paper aims to fill such research gaps by analysing two cases - London and Hong Kong. London is considered as an international maritime service centre, while Hong Kong is en route to be an international maritime service centre, with different port positions within their clusters. In line with the analogical analysis between biotic community and maritime cluster, symbiosis theory and Lotka-Volterra model are adopted. The model is to investigate the reciprocal influence among these maritime sectors which determines the formation and development of a maritime cluster in the future. With empirical analysis confirming such analogies in London and Hong Kong cases, the paradigms and solutions in biotic community can be applied to deal with problems that occur in the maritime cluster. This research, from an interdisciplinary study point of view, accomplishes an empirical study on maritime cluster evolution with an original and insightful model. It also provides reference for policy makers on the dynamic development path of maritime clusters in practice.

Item Type:	Refereed Conference Paper
Keywords:	Maritime Cluster Evolution
Research Division:	Commerce, Management, Tourism and Services
Research Group:	Transportation, logistics and supply chains
Research Field:	Transportation, logistics and supply chains not elsewhere classified
Objective Division:	Transport
Objective Group:	Water transport
Objective Field:	Water transport not elsewhere classified
UTAS Author:	Zhang, W (Dr Vera Zhang)
ID Code:	115303
Year Published:	2013
Deposited By:	Maritime and Logistics Management
Deposited On:	2017-03-15
Last Modified:	2017-06-15
Downloads:	2 View Download Statistics