Journal of Finance and Economics
ISSN (Print): 2328-7284 ISSN (Online): 2328-7276 Website: https://www.sciepub.com/journal/jfe Editor-in-chief: Suman Banerjee
Open Access
Journal Browser
Go
Journal of Finance and Economics. 2024, 12(2), 29-38
DOI: 10.12691/jfe-12-2-2
Open AccessArticle

Major Factors Affecting Shanghai Shipping Freight Rates during the Covid-19 Pandemic: Inspecting and Ranking by Grey Relational Analysis

Hsiang-Hsi Liu1, , Fu-Hsiang Kuo2 and Guan-Ting Liu3

1Graduate Institute of International Business, National Taipei University, New Taipei City, Taiwan

2Department of Finance, National Yunlin University of Science and Technology, Yunlin County, Taiwan

3Department of Shipping and Transportation Management, National Taiwan Ocean University, Taiwan

Pub. Date: March 24, 2024

Cite this paper:
Hsiang-Hsi Liu, Fu-Hsiang Kuo and Guan-Ting Liu. Major Factors Affecting Shanghai Shipping Freight Rates during the Covid-19 Pandemic: Inspecting and Ranking by Grey Relational Analysis. Journal of Finance and Economics. 2024; 12(2):29-38. doi: 10.12691/jfe-12-2-2

Abstract

This study aims to GRA (Grey relational analysis) method to analyze the factors that affect Shanghai shipping rates(∆SCFI) and which factors will play a key role under the impact of COVID-19 epidemic outbreak. GRA method can analyze the weight relationship between factors and their attributes to explore the factors that affect the shipping rates. We find that the change rate of the main route's on-time rates of receiving and dispatching scheduled services (∆OTRADSCI) affects the change rate of Shanghai shipping freight rates the strongest, followed by the change rate of the main route's on-time arrival and departure service rates (∆OTRRSRCI) and the change rate of China export container freight rates (∆CCF). Subsequently, the change rate of China international seafarer salary (∆CISSI), the change rate of China senior seafarer salary (∆CSSSI) and the change rate of China ordinary seafarer salary (∆COSSI) gave the strong influence to the Shanghai shipping freight rates. While, the change rate of Shanghai port container handling volumes (or throughput) (∆SPCV) gave the least effect to the Shanghai shipping freight rates during the COVID-19 pandemic in 2019-2020. It is hoped that these findings can help policy makers in making decisions on port management/operations and future port development.

Keywords:
COVID-19 epidemic Shipping freight rates Grey relational analysis (GRA)

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  Fang, J., Collins, A., Yao, S., 2021. On the global COVID-19 pandemic and China’s FDI. Journal of Asian Economics, 74, 101300.
 
[2]  Nguyen, L. T. M., Dinh, P. H., 2021. Ex-ante risk management and financial stability during the COVID-19 pandemic: a study of Vietnamese firms. China Finance Review International, 11(3), 349-371.
 
[3]  Michail, N. A., Melas, K. D., 2020. Shipping markets in turmoil: An analysis of the Covid-19 outbreak and its implications. Transportation Research Interdisciplinary Perspectives, 7, 100178.
 
[4]  Huang, J. T., Liao, Y. S., 2003. Optimization of machining parameters of wire-EDM based on grey relational and statistical analyses. International Journal of Production Research, 41(8), 1707-1720.
 
[5]  Robinson, R., 2002. Ports as elements in value-driven chain systems: the new paradigm. Maritime Policy & Management, 29(3), 241-255.
 
[6]  Meersman, H., Van de Voorde, E., Vanelslander, T., 2012. Port congestion and implications to maritime logistics. In Maritime Logistics. Emerald Group Publishing Limited.
 
[7]  Davies, P., Kieran, M., 2015. Port congestion and drayage efficiency, paper presented at the METRANS international urban freight conference. Long Beach, CA.
 
[8]  Loh, H. S., Thai, V. V., 2015. Cost consequences of a port-related supply chain disruption. The Asian Journal of Shipping and Logistics, 31(3), 319-340.
 
[9]  Christopher, M., Peck, H., Towill, D., 2006. A taxonomy for selecting global supply chain strategies. The International Journal of Logistics Management, 17(2), 277-287.
 
[10]  Cullinane, K., 1992. A short-term adaptive forecasting model for BIFFEX speculation: a Box-Jenkins approach. Maritime Policy & Management, 19(2), 91-114.
 
[11]  Kavussanos, M. G., 1996a. Comparisons of volatility in the dry-cargo ship sector. Spot versus time-charters, and smaller versus larger vessels. Journal of Transportation Economics and Policy, 30(1), 67-82.
 
[12]  Kavussanos, M. G., 1996b. Price risk modelling of different size vessels in the tanker industry using autoregressive conditional heteroskedastic (ARCH) models. Logistics and Transportation Review, 32(2), 161-176.
 
[13]  Kavussanos, M. G., Alizadeh-M, A. H., 2001. Seasonality patterns in dry bulk shipping spot and time charter freight rates. Transportation Research Part E: Logistics and Transportation Review, 37(6), 443-467.
 
[14]  Kavussanos, M. G., Alizadeh-M, A. H., 2002. Seasonality patterns in tanker spot freight rate markets. Economic Modelling, 19(5), 747-782.
 
[15]  Kavussanos, M. G., Visvikis, I. D., 2004. Market interactions in returns and volatilities between spot and forward shipping freight markets. Journal of Banking and Finance, 28(8), 2015-2049.
 
[16]  Poulsen, R. T., Sampson, H., 2020. A swift turnaround? Abating shipping greenhouse gas emissions via port call optimization. Transportation Research. Part D: Transport & Environment, 86, 102460.
 
[17]  Mańkowska, M., Pluciński, M., Kotowska, I., Filina-Dawidowicz, L., 2021. Seaports during the COVID-19 pandemic: the terminal operators’ tactical responses to disruptions in Maritime supply chains. Energies, 14(14), 4339.
 
[18]  Lin, A. J., Chang, H. Y. Hung, B., 2022. Identifying key financial, environmental, and social, governance (ESG), bond, and COVID-19 factors affecting global shipping companies-a hybrid multiple-criteria decision-making method. Sustainability, 14(9), 5148.
 
[19]  Zhou, X., Dai, L., Jing, D., Hu, H., Wang, Y., 2022. Estimating the economic loss of a seaport due to the impact of COVID-19. Regional Studies in Marine Science, 52, 102258.
 
[20]  Huang, L., Lasserre, F., Pic, P., Chiu, Y. Y., 2020. Opening up the Chinese shipping market 1988–2018: The perspective of Chinese shipping companies facing foreign competition. Asian Transport Studies, 6, 100004.
 
[21]  Deng, J. L. 1982. Control problems of grey theory system. System & Control Letters, 1(5), 288.
 
[22]  Deng, J. L., 2000. Grey System: Theory and Applications, Taipei. TW: Gao Books Limited.
 
[23]  Liu, H. H., Guo, F. H., 2019. An approach to explore the factors affecting operational efficiency of school management from teaching through digital mobile e-Learning: DEA and Grey Relational Analysis. Advances in Management & Applied Economics, 9(6), 111-126.
 
[24]  Deng, J. L., 1989. Introduction to grey theory system. The Systems Journal of Grey System, 8(1), 1-24.
 
[25]  Mehregan, M. R., Jamporazmey, M., Hosseinzadeh, M., Kazemi, A. 2012. An integrated approach of critical success factors (CSFs) and grey relational analysis for ranking KM systems. Procedia-Social and Behavioral Sciences, 41, 402-409.
 
[26]  Jiang, B., Li, J., Gong, C., 2018. Maritime shipping and export trade on “Maritime Silk Road”. The Asian Journal of Shipping and Logistics, 34(2), 83-90.
 
[27]  Jeon, J. (2019). A Study on the Causal Relationship between Shipping Freight Rates. Journal of Convergence for Information Technology, 9(12), 47-53.
 
[28]  Shi, H. J., 2015. Research on the correlation between China's export container composite freight index and Shanghai export container composite freight index. [Unpublished master’s thesis]. Evergreen University. https://hdl.handle.net/11296/eg6eca.
 
[29]  Yin, X. F., Khoo, L. P., Chen, C. H., 2011. A distributed agent system for port planning and scheduling. Advanced Engineering Informatics, 25(3), 403-412.
 
[30]  Chen, J., Abdullah, M. G., 2019. Research and analysis of international shipping market freight index. In 19th COTA International Conference of Transportation Professionals (pp. 34-42).
 
[31]  Lušić, Z., Bakota, M., Čorić, M., Skoko, I., 2019. Seafarer market-challenges for the future. Transactions on Maritime Science, 8(1), 62-74.
 
[32]  Zhao, Z., 2021. Recruiting and managing labor for the global shipping industry in China. In the World of the Seafarer: Qualitative Accounts of Working in the Global Shipping Industry (pp. 23-35). Springer.
 
[33]  Ruiz-Primo, M. A., Shavelson, R. J. Mitchell, M. (1996). Student guide for Shavelson statistical reasoning for the behavioral sciences. Allyn & Bacon.
 
[34]  Taylor, R., 1990. Interpretation of the correlation coefficient: a basic review. Journal of diagnostic medical sonography, 6(1), 35-39.