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Maritime cluster evolution based on symbiosis theory and Lotka–Volterra model

Citation

Zhang, W and Lam, JSL, Maritime cluster evolution based on symbiosis theory and Lotka-Volterra model, Maritime Policy and Management, 40, (2) pp. 161-176. ISSN 1464-5254 (2013) [Refereed Article]

Copyright Statement

Copyright 2013 Taylor & Francis

DOI: doi:10.1080/03088839.2012.757375

Abstract

Over the past few years, the concept of cluster has been regarded and adopted as a useful policy tool in analyzing maritime industry development. However, there is a lack of studies on the theoretical development of maritime cluster evolution in the existing literature. This paper aims to investigate the dynamic symbiosis derived from maritime cluster evolution. The research leads to a new path to investigate maritime cluster by employing the symbiosis theory in ecology and the Lotka–Volterra model. The paper first develops the concept of maritime cluster classification and evolution. Then, it analyses the compatibility and analogy of biotic community with maritime cluster. In order to study the interaction relationships among maritime sectors, the Lotka–Volterra model is introduced. The model is used to group the revenues of maritime sectors in pairs. These revenues are in turn grouped into a number of comparative pairs accordingly. The model is further advanced to forecast the trend of maritime clusters by studying the existence of an equilibrium point and its stability with the estimated functions. The original approach would deepen the understanding on maritime cluster and stimulate future research. The study also draws insights for policy makers in maritime nations.

Item Details

Item Type:Refereed Article
Keywords:maritime cluster
Research Division:Economics
Research Group:Other Economics
Research Field:Economics not elsewhere classified
Objective Division:Education and Training
Objective Group:Other Education and Training
Objective Field:Workforce Transition and Employment
Author:Zhang, W (Dr Vera Zhang)
ID Code:112395
Year Published:2013
Web of Science® Times Cited:13
Deposited By:Maritime and Logistics Management
Deposited On:2016-11-08
Last Modified:2016-12-06
Downloads:0

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