4.7 Article

An empirical analysis of maritime cluster evolution from the port development perspective - Cases of London and Hong Kong

Journal

TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
Volume 105, Issue -, Pages 219-232

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tra.2017.05.015

Keywords

Maritime cluster evolution; Port development; Maritime service; Symbiosis theory; Lotka-Volterra model

Funding

  1. Nanyang Technological University, Singapore

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The maritime industry has adopted the concept of clustering to promote the growth of related maritime sectors. Based on the theoretical development of maritime cluster evolution in the current research literature, components and functions of maritime clusters are observed to have changed over time. However, very few empirical studies have been conducted on maritime cluster evolution that reflect the diverse components and their interactions within a cluster. Particularly, there is insufficient literature that systematically studies the relationship between ports and other maritime sectors, though the port is deemed to play an important role among sectors in maritime cluster development. This paper aims to fill these 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 the latter cluster possesses a supportive port while the former does not. Grounded on the symbiosis theory, this paper examines the evolution of maritime clusters empirically through investigating the interactions between a port and other sectors within a maritime cluster with the Lotka-Volterra model. Empirical results show that advanced maritime services, namely marine insurance and shipbroking, benefit from port development in London. However, these maritime services sectors are in pure competition with the port sector in Hong Kong. The research provides reference for policy makers on the dynamic development path of maritime clusters in practice. (C) 2017 Elsevier Ltd. All rights reserved.

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