Thanh bên bài viết
APPLICATION OF THE ANALYTIC NETWORK PROCESS (ANP) TO EVALUATE THE SIGNIFICANCE OF ECONOMIC RISK FACTORS IN THE OPERATION OF OIL–CHEMICAL TANKER FLEETS IN SOUTHERN VIETNAMESE ENTERPRISES
Nội dung chính của bài viết
Tóm tắt
This study aims to identify and assess the relative importance of economic risk factors in the operation of oil–chemical tanker fleets in Southern Vietnam using the Analytic Network Process (ANP). The analysis is based on empirical data collected from enterprises engaged in maritime oil and chemical transportation services. Seven key economic risk factors are considered in this research: (1) Commercial pressure on the shipmaster, (2) Wage fluctuations, (3) Payment risk, (4) Variations in the costs of fuel, materials, and spare parts, (5) Risks of uncollected freight charges and demurrage fees, (6) Errors in voyage cost planning, and (7) Extended voyage duration leading to increased costs and reduced number of voyages.
The results reveal that “Extended voyage duration leading to increased costs and reduced number of voyages” is the most influential factor within the economic risk group. This finding indicates that this factor plays a particularly critical role in the management and operation of oil–chemical tanker fleets in Southern Vietnam, as it significantly affects all three key objectives: profitability, transport quality, and maritime safety.
Từ khóa
Economic risk, oil–chemical tanker fleet, ANP, risk assessment, risk identification
Chi tiết bài viết
Tài liệu tham khảo
[2] Ngô, Q. H., & Nguyễn, Q. T. (1998). Risk management. Hanoi: Education Publishing House.
[3] Ngô, Q. H., Võ, T. P., & Trần, A. M. (2020). Enterprise risk management. Ho Chi Minh City: University of Economics Ho Chi Minh City.
[4] Nguyễn, V. S. (2012). Risk management for maritime transport enterprises. Journal of Maritime Science, 31, 59.
[5] Đinh, G. H., & Nguyễn, T. N. L. (n.d.). Proposal of a risk assessment model for ship chartering in the Middle East. Transport Journal.
[6] Shipping risks – risky ships: Thoughts on the approach to market forecasting for tankers. (1995). Fuel and Energy Abstracts, 36(5), 328. https://doi.org/10.1016/0140-6701(95)96336-B
[7] Santos, A. M. P., & Soares, C. G. (2024). Cost optimization of shuttle tanker offloading operations. Ocean Engineering, 301, 117378. https://doi.org/10.1016/j.oceaneng.2024.117378
[8] Kavussanos, M. G., & Dimitrakopoulos, D. N. (2011). Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets. International Review of Financial Analysis, 20(5), 258–268. https://doi.org/10.1016/j.irfa.2011.05.007
[9] Ajith, P. J., Totakura, B. R., Gupta, R., & Kulshrestha, N. (2023). Volatility in tanker freight markets. Case Studies on Transport Policy, 12, 100993. https://doi.org/10.1016/j.cstp.2023.100993
[10] Bai, X., & Lam, J. S. L. (2021). Freight rate co-movement and risk spillovers in the product tanker shipping market: A copula analysis. Transportation Research Part E: Logistics and Transportation Review, 149, 102315. https://doi.org/10.1016/j.tre.2021.102315
[11] Siddiqui, A. W., & Verma, M. (2017). A conditional value-at-risk based methodology to intermediate-term planning of crude oil tanker fleet. Computers & Industrial Engineering, 113, 405–418. https://doi.org/10.1016/j.cie.2017.09.021
[12] Celik, M., Cebi, S., Kahraman, C., & Er, I. D. (2009). An integrated fuzzy QFD model proposal on routing of shipping investment decisions in the crude oil tanker market. Expert Systems with Applications, 36(3), 6227–6235. https://doi.org/10.1016/j.eswa.2008.07.031
[13] Talley, W. K. (1999). Determinants of the property damage costs of tanker accidents. Transportation Research Part D: Transport and Environment, 4(6), 413–426. https://doi.org/10.1016/S1361-9209(99)00020-6
[14] Durukan, O., Akyuz, E., Destanoğlu, O., Arslanoglu, Y., & Sezer, Ş. İ. (2024). Quantitative HAZOP and D–S evidence theory–fault tree analysis approach to predict fire and explosion risk in inert gas systems on board tanker ships. Ocean Engineering, 308, 118274. https://doi.org/10.1016/j.oceaneng.2024.118274
[15] Koza, D. F., Ropke, S., & Molas, A. B. (2017). The liquefied natural gas infrastructure and tanker fleet sizing problem. Transportation Research Part E: Logistics and Transportation Review, 99, 96–114. https://doi.org/10.1016/j.tre.2017.01.003
[16] Saaty, T. L. (1996). Decision making with dependence and feedback: The Analytic Network Process. Pittsburgh, PA: RWS Publications.
[17] Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, priority setting, resource allocation. New York: McGraw-Hill.
[18] Saaty, T. L. (2010). Mathematical principles of decision making: Principia mathematica decernendi. Generalization of the Analytic Hierarchy Process to neural firing and synthesis. Pittsburgh, PA: RWS Publications.
[19] Hatch, M. J. (1997). Organization theory: Modern, symbolic, and postmodern perspectives. Oxford: Oxford University Press.
[20] Mu, E., & Cooper, O. (2022). A contingency approach to multi-criteria decision-making: A search for validity through rigor and relevance. In Y. I. Topcu, Ş. Onsel Ekici, O. Kabak, E. Aktas, & O. Ozaydın (Eds.), International series in operations research & management science (pp. 499–525). Cham: Springer. https://doi.org/10.1007/978-3-030-91851-4_19
[21] Bell, G., Bromley, P., & Bryson, J. (1998). Spinning a complex web: Links between strategic decision-making context, content, process, and outcome. In V. Papadakis & P. Barwise (Eds.), Strategic decisions. Boston, MA: Kluwer Academic.