Short Sea Shipping on the West Coast of Korea: Keys to Activating the Shipping Industry in Preparation for Korea Unification Era

Emerald - Tập 18 Số 2 - Trang 91-105 - 2020
Sung-WooLee, Sung-HoShin, Hee-SungBae

Tóm tắt

This study aims to analyze information on vessel traffic between the two Koreas with a probability distribution for each route/vessel type. The study will then conduct an estimate for maritime transport patterns of inter-Korean trade in the future. To analyze the flow of inter-Korean coastal shipping, this study conducted visualization analysis of shipping status between North and South Korea by year, ship type, and port using navigation data of three years from Port Logistics Information System (Port-MIS) sources during 2006 to 2008, which saw the most active exchanges between the two governments. Also, this study analyzes shipping status between the two governments as a probability distribution for each port and provides the prospects for future maritime transport for inter-Korean trade by means of Bayesian Networks and simulation. The results of the analysis are as follows: i) when North-South routes are reopened, the import volume for sand from North Korea will be increased; ii) investment in the modernization of ports in North Korea is required so that shipping companies can generate profit through economies of scale; iii) the number of the operating vessels including container ships between the two governments is expected to increase like when the tensions and conflict on the Korean Peninsula was release, especially between Busan port in South Korea and Nampo port in North Korea; and iv) among container ships, transshipment containers imported and exported through Busan Port will be shipped to North Korea by feeder transportation.

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Tài liệu tham khảo

Abdul Rahman, N. S. F., Yang, Z., Bonsall, S., Wang, J., 2015. A fuzzy rule-based Bayesian reasoning method for analysing the necessity of super slow steaming under uncertainty: Containership. International Journal of e-Navigation and Maritime Economy 3, 1-12. 10.1016/j.enavi.2015.12.001

Akhtar, M., Utne, I. B., 2014. Human fatigue’s effect on the risk of maritime groundings: A Bayesian network modeling approach. Safety Science 62, 427-440. 10.1016/j.ssci.2013.10.002

Alyami, H., Lee, P. T. W., Yang, Z., Riahi R., Bonsall, S., Wang J., 2014. An advanced risk analysis approach for container port safety evaluation. Maritime Policy and Management 41, 634-650. 10.1080/03088839.2014.960498

Baksh, A. A., Abbassi, R., Garaniya, V., Khan, F., 2018. Marine transportation risk assessment using Bayesian network: Application to Arctic waters. Ocean Engineering 159, 422-436. 10.1016/j.oceaneng.2018.04.024

Ducruet, C., 2008. Hub dependence in constrained economies: The case of North Korea. Maritime Policy & Management 35, 377-394. 10.1080/03088830802198241

Ducruet, C., Roussin, S., Jo, J. C., 2009. Going west? Spatial polarization of the North Korean port system. Journal of Transport Geography 17, 357-368. 10.1016/j.jtrangeo.2008.10.011

Hwang, J. H., Chun, W. H., 2018. Establishment of Maritime Cooperation in Accordance with Development of Inter-Korean Relations. Korea Maritime Institute, Seoul, Koea.

Im, J. G., 1995. Issues and future directions of inter-Korean Shipping Cooperation. Ocean & Fisheries 131, 18-36.

Jiang, M., Lu, J., Yang, Z., Li, J., 2020. Risk analysis of maritime accidents along the main route of the maritime silk road: A Bayesian network approach. Maritime Policy & Management, 1-18. 10.1080/03088839.2020.1730010

John, A., Yang, Z., Riahi, R., Wang, J., 2016. A risk assessment approach to improve the resilience of a seaport system using Bayesian networks. Ocean Engineering 111, 136-147. 10.1016/j.oceaneng.2015.10.048

Jung, B. M., 2008. Directions for the development of inter-Korean shipping. Ocean & Fisheries 286, 12-25.

Kim, B. J., 2002. North Korean port development and inter-Korean port exchange cooperation plan. Ocean & Fisheries 219, 19-39.

Kim, G. S., 1994a. Strengthening coastal shipping for Inter-Korean Shipping Cooperation (I). Monthly Maritime Korea 6, 39-43.

Kim, G. S., 1994b. Strengthening coastal shipping for Inter-Korean Shipping Cooperation (II). Monthly Maritime Korea 7, 45-51.

Kim, Y. Y., 1998. Current Status of the shipping industry in North Korea and Inter-Korean Cooperation in the Shipping Sector. Korea Institute for National Unification, Seoul, Korea.

Kim, Y. Y., 2011. Current status and tasks of North Korea’s shipping industry. Stratege 2114, 96-125.

Koo, M. G., 2019. Inter-Korean maritime cooperation under the peace regime on the Korean peninsula?: Joint development of fisheries shipping and offshore oil fields. International Development and Cooperation Review 11, 1-16. 10.32580/idcr.2019.11.3.1

Lee, K. Y., Kim, G. S., Kim, B. K., Kong, Y. D., 2018. A Study on Cooperation Projects in Port & Logistics Sector for the Improvement of Inter-Korean Relations. Korea Maritime Institute, Seoul, Korea.

Lee, S. W., 2018., Direction of North Korean port development for logistics integration and expansion on the Korean Peninsula. KDI Review of the North Korean Economy 20, 23-41.

Nadkarni, S., Shenoy, P. P., 2001. Bayesian network approach to making inferences in causal maps. European Journal of Operational Research 128, 479-498. 10.1016/S0377-2217(99)00368-9

Park, H. G., Park, D. H., 2019. Evaluation of port choice factors in the west coast bay of North Korea. Journal of Shipping and Logistics 35, 407-428. 10.37059/tjosal.2019.35.3.407

Park, S. J., Lee, S. W., 2017. Inter-Korean Maritime and Fishery Relation 1945–2015. Korea Maritime Institute, Seoul, Korea.

Rahman, A., Yang, Z. L., Bonsall, S., Wang, J., 2012. A proposed rule-based Bayesian reasoning appoarch for analysing steaming modes on containerships. Journal of Maritime Research 9, 27-32.

Salleh, N. H. M., Riahi, R., Yang, Z., Wang, J., 2014. A fuzzy Bayesian belief network approach for assessing the operational reliability of a liner shipping operator. Proceedings of the Second International Conference on Advances in Economics, Management and Social Study, New York, NY.

Salleh, N. H. M., Riahi, R., Yang, Z., Wang, J., 2017. Predicting a containership’s arrival punctuality in liner operations by using a Fuzzy Rule-Based Bayesian Network (FRBBN). Asian Journal of Shipping and Logistics 33, 95-104. 10.1016/j.ajsl.2017.06.007

Seo, D. W., Ko, J. O., Lee, S. H., 2012. Recent development in technologies for short sea shipping and its implications. Journal of Navigation and Port Research 36, 883-888. 10.5394/KINPR.2012.36.10.883

Statistics Korea, 2020. Inter-Korean maritime transport volume. Available at: http://www.index.go.kr/potal/stts/idxMain/selectPoSttsIdxSearch.do?idx_cd=1269 (Accessed 31 April 2020)

Shin, S. H., Lee, P.T.W., Lee, S. W., 2019. Lessons from bankruptcy of Hanjin Shipping Company in chartering. Maritime Policy and Management 46, 136-155. 10.1080/03088839.2018.1543909

Trucco, P., Cagno, E., Ruggeri, F., Grande, O., 2008. A Bayesian belief network modelling of organisational factors in risk analysis: A case study in maritime transportation. Reliability Engineering and System Safety 93, 845-856. 10.1016/j.ress.2007.03.035

Wan, C., Yan, X., Zhang, D., Qu, Z., Yang, Z., 2019. An advanced fuzzy Bayesian-based FMEA approach for assessing maritime supply chain risks. Transportation Research Part E: Logistics and Transportation Review 125, 222-240. 10.1016/j.tre.2019.03.011

Wang, G. W. Y., Yang, Z., Zhang, D., Huang, A., Yang, Z., 2017. Application of Bayesian networks in analysing tanker shipping bankruptcy risks. Maritime Business Review 2, 177-198. 10.1108/MABR-12-2016-0032

Wang, L., Yang, Z., 2018. Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China. Reliability Engineering and System Safety 180, 277-289. 10.1016/j.ress.2018.07.021

Yang, Z., Abujaafar, K.M., Qu, Z., Wang, J., Nazir, S., Wan, C., 2019. Use of evidential reasoning for eliciting Bayesian subjective probabilities in human reliability analysis: A maritime case. Ocean Engineering 186, 106095. 10.1016/j.oceaneng.2019.05.077

Yang, Z., Yang, Z., Yin, J., 2018a. Realising advanced risk-based port state control inspection using data-driven Bayesian networks. Transportation Research Part A: Policy and Practice 110, 38-56. 10.1016/j.tra.2018.01.033

Yang, Z., Yang, Z., Yin, J., Qu, Z., 2018b. A risk-based game model for rational inspections in port state control. Transportation Research Part E: Logistics and Transportation Review 118, 477-495. 10.1016/j.tre.2018.08.001

Zhang, D., Yan, X. P., Yang, Z. L., Wall, A., Wang, J., 2013. Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze river. Reliability Engineering and System Safety 118, 93-105. 10.1016/j.ress.2013.04.006

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Emerald

Tập 18 Số 2

91-105

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