Airline Network in East Asia
1
조회
0
다운로드
2
인용
0
참고문헌
키워드
초록
Using Social Network Analysis (SNA), this paper examines the inter-country airlinelogistics relationships in East Asia. Based on the flight schedule data, which has beengathered by the authors, the overall features of airline logistics structure and the specificroles of each airport could be more clearly examined. The main results of this paper are as follows: Beijing has the highest DegreeCentrality, but excluding the domestic lines, Incheon has the highest Degree Centrality,which would imply that a relatively high Centrality of logistics for China’s airports is dueto the greater number of domestic lines. The focal hub status of Incheon airport is alsosupported by the fact that Incheon contains the highest Betweenness Centrality. Secondly, evaluated by types of brokerage role, Incheon has a remarkably strong roleas a liaison, which means Incheon airport functions as a transfer hub between two differentregions outside of Korea. However, considering only the to/from China airline links, HongKong has the highest score as a liaison. These conflicting results imply that as China’sairline transportation continuously increases, Hong Kong will become a strong rival toIncheon. Thirdly, in the analysis of Structural Hole which functions the broker and acts as ahub by linking unconnected airports, Incheon has the highest possibilities as a hub airport. However, only considering to/from China airlines, Hong Kong would dominate Incheon.
Abstract
Using Social Network Analysis (SNA), this paper examines the inter-country airlinelogistics relationships in East Asia. Based on the flight schedule data, which has beengathered by the authors, the overall features of airline logistics structure and the specificroles of each airport could be more clearly examined. The main results of this paper are as follows: Beijing has the highest DegreeCentrality, but excluding the domestic lines, Incheon has the highest Degree Centrality,which would imply that a relatively high Centrality of logistics for China’s airports is dueto the greater number of domestic lines. The focal hub status of Incheon airport is alsosupported by the fact that Incheon contains the highest Betweenness Centrality. Secondly, evaluated by types of brokerage role, Incheon has a remarkably strong roleas a liaison, which means Incheon airport functions as a transfer hub between two differentregions outside of Korea. However, considering only the to/from China airline links, HongKong has the highest score as a liaison. These conflicting results imply that as China’sairline transportation continuously increases, Hong Kong will become a strong rival toIncheon. Thirdly, in the analysis of Structural Hole which functions the broker and acts as ahub by linking unconnected airports, Incheon has the highest possibilities as a hub airport. However, only considering to/from China airlines, Hong Kong would dominate Incheon.
참고문헌 (17)
- Barthélemy, M., "Spatial Networks", Physics Reports, 499, pp.1~101 (2011)
- Borgatti, S. P., "On Social Network Analysis in A Supply Chain Context", Journal of Supply Chain Management, 45(2), pp.5~22 (2009)
- Burt, R. S., "Structural Holes: The Social Structure of Competition" (1992), Harvard University Press
- Burt, R. S., "Social Capital: Theory and Research", pp.31~56 (2001), Aldine de Gruyter
- da Rocha, L. E. C., "Structural Evolution of Brazilian Airport Network", Journal of Statistical Mechanics: Theory and Experiment, 4, pp.P04020~ (2009)
- Ducruet, C., "The SAGE Handbook of Transport Studies", pp.347~364 (2013), SAGE Publications
- Gould, R. V., "Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks", Sociological Methodology, 19, pp.89~126 (1989)
- Gudmundsson, S. V., "Multilateral Airline Alliances: Balancing Strategic Constraints and Opportunities", Journal of Air Transport Management, 12, pp.153~158 (2006)
- Guimera, R., "The Worldwide Air Transportation Network: Anomalous Centrality, Community Structure, and Cities'Global Roles", Proceedings of the National Academy of Sciences, 102(22), pp.7794~7799 (2005)
- Ha, H-K., "Analysis of the Logistics Patterns of Korea’s Free Economic Zones in Northeast Asia and the Implications", Journal of international logistics and trade, 3(2), pp.73~92 (2005)
- Kim, Y., "Structural Investigation of Supply networks: A social Network Analysis Approach", Journal of Operational Management, 29, pp.194~211 (2011)
- Kirkels, Y., "Brokerage in SME Networks", Research Policy, 39(3), pp.375~385 (2010)
- 이준엽, "Inter-Provincial Railroad Network in China", Journal of Intl Logistics and Trade, 10(2), pp.61~75 (2012), 정석물류통상연구원
- Scott, J., "Social network analysis: A handbook" (2000), Sage Publications
- Tracey, P., "Alliances, Networks and Competitive Strategy: Rethinking Clusters of Innovation", Growth and Change, 34, pp.1~16 (2003)
- Vicente, J., "Getting into Networks and Clusters:Evidence from the Midi-Pyrenean Global Navigation Satellite Systems(GNSS)Collaboration Network", Regional Studies, 45(8), pp.1059~1078 (2011)
- Wang, J., "Exploring the Network Structure and Nodal Centrality of China’s Air Transport Network: A Complex Network Approach", Journal of Transport Geography, 19(4), pp.712~721 (2011)