| Author: | Li, Mengchi |
| Title: | Economic analysis of location behaviour for maritime service cluster |
| Advisors: | Luo, Meifeng (LMS) |
| Degree: | Ph.D. |
| Year: | 2020 |
| Subject: | Shipping -- Economic aspects Industrial clusters Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Logistics and Maritime Studies |
| Pages: | x, 111 pages : color illustrations |
| Language: | English |
| Abstract: | Maritime service clusters benefit both business operations and the national economy. They have a long history, and have contributed significantly to both global and regional economic development, but only in recent decades has their research gained much attention. Recently, the shifting of maritime commercial centers from Europe to Asia has triggered the movement of maritime service businesses. As such businesses are globalized and footless, their location behavior has become a hot topic for researchers in many historical maritime countries, as well as emerging ones. Against this background, the following questions arise: What is the current situation with regard to studies of maritime clusters, especially maritime service clusters? What factors affect the formation of a maritime service cluster, and how do these factors in particular affect their development? What is the evolution pattern of maritime service clusters? To answer these questions, we have conducted three studies examining the location behavior for high-level maritime service clustering. Firstly, a review study on current research into maritime clusters was conducted. We find that most of the researches into maritime clusters are similar to the studies of general industry clusters, with little consideration given to the unique nature of the shipping industry. This study analyses the key elements in maritime cluster studies over the past 20 years, including conceptual development, categories of maritime clusters, research methods, factors for clustering, studies on specific clusters, and the relationships among maritime businesses. From the study we find that research into maritime service clustering is lacking. Misunderstandings about the relationship between the International Maritime Center and maritime clusters are also clarified. Such analysis allows us to identify possible problems in the current studies and to point out any insufficiencies so as to meet the needs of maritime cluster development. Secondly, we utilized an empirical study to analyze important factors affecting the location selection decisions of maritime service businesses. Stated preference approaches and discrete choice models are utilized to analyze the contribution of factors to the preference of three alternative locations (Shanghai, Singapore and Hong Kong), taking into account the impact of the specific nature of the surveyed firm and current location. The results show that increasing government support in Hong Kong will have greater effect on improving its attractiveness to maritime business sectors than that in Singapore and Shanghai. Improving the business legal environment in Shanghai can increase its attractiveness more than that in Singapore and Hong Kong. Also, we find that firms in places other than Shanghai, Singapore and Hong Kong prefer to move into Shanghai, whereas firms in Hong Kong retain high loyalty to their own location. Finally, considering the trade-offs in policy alternatives, the possible ways for Hong Kong and Shanghai to increase their attractiveness is also provided. The findings of this research identify new directions for setting up public policies and corresponding measures for developing maritime service clusters in these three places. Thirdly, a theoretical model was built to investigate how maritime service clusters develop and evolve under competition. The evolutionary cluster model consists of two parts: short-run equilibrium and long-term development. To model short-run equilibrium, two maritime service clusters compete for clients, based on Hotelling's model. To study long-term development, maritime service firms enter and exit clusters according to their profits. Cluster effect is considered in the model. The short-term optimal condition of the model is identified, and long-term evolution of the maritime service cluster is discussed based on the simulation results. The study investigated maritime service clusters from the angle of competition. The forecast on the ultimate development of clusters provides policy makers with a reference for developing local maritime service clusters. |
| Rights: | All rights reserved |
| Access: | open access |
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