Subjective and Objective Analysis of Schedule Delaying Factors for Container Shipping Lines

Emerald - Tập 18 Số 4 - Trang 181-192 - 2020
Cheng-WeiLin, Wan-Chi JackieHsu, Hui-JuSu

Tóm tắt

The shipper selects a suitable shipping route and plans for a voyage in order to import and export cargo on the basis of published sailing schedules. The reliability of the sailing schedule will influence the shipper’s logistics expense, which means that the logistics costs will depend on the reliability of schedules published by container shipping companies. Therefore, it is important to consider factors which can cause delays would for container ships sailing on sea routes. The reliability of published sailing schedules can be affected by a number of different factors. This study adopts the multi-criteria decision making (MCDM) method to estimate the importance of the delaying factors in a sailing schedule. In addition, the consistent fuzzy preference relations (CFPR) method is applied to identify the subjective importance (weights) of the delaying factors. The entropy weight method combined with the actual performance of the container shipping company are both used when estimating the objective importance (weights) of the delaying factors. According to the analysis results, the criteria can be divided into four quadrants with different management implications, which indicate that instructions for chase strategy, sailing schedule control, fleet allocation, transship operation arrangement and planning for ports in routes are often ignored by container shipping companies. Container shipping companies should consider adjusting their operational strategies, which would greatly improve their operational performance.

Từ khóa


Tài liệu tham khảo

Abdul rahman, N. S. F., Othman, M. K., Sanusi, I. A., Arof, A. M., Ismail, A., 2019. Evaluation of delay factors on dry bulk cargo operation in Malaysia: A case study of Kemaman port. The Asian Journal of Shipping and Logistics 35, 127-137. 10.1016/j.ajsl.2019.09.001

Brooks, M. R., 1990. Ocean carrier selection criteria in a new environment. Logistics and Transportation Review 26, 339-355.

Chan, L. K., Wu, M. L., 2005. A systematic approach to quality function deployment with a full illustrative example. Omega 33, 119-139. 10.1016/j.omega.2004.03.010

Chao, R. J., Chen Y. H., 2009. Evaluation of the criteria and effectiveness of distance e-learning with consistent fuzzy preference relations. Expert Systems with Applications 36, 10657-10662. 10.1016/j.eswa.2009.02.047

Chen, J., Zhang, S., Li, S., Zhang, F., Zhu, Y., Huang, X., 2018. Identifying critical factors of oil spill in the tanker shipping industry worldwide. Journal of Cleaner Production 180, 1-10. 10.1016/j.jclepro.2017.12.238

Chen, J., Zhang, S., Xu, L., Wan, Z., Fei, Y., Zheng, T., 2019. Identification of key factors of ship detention under port state control. Marine Policy 102, 21-27. 10.1016/j.marpol.2018.12.020

Chung, C. C., Chiang, C. H., 2011. Critical factors in schedule reliability of container shipping carriers. Proceedings of World Multi-Conference on Systemics, Cybernetics and Informatics, Orlando, FL.

Ding, J. F., 2011. An integrated fuzzy TOPSIS method for ranking alternatives and its application. Journal of Marine Science and Technology 19, 341-352.

Herrera-Viedma, E., Herrera, F., Chiclana, F., Luque, M., 2004. Some issues on consistency of fuzzy preference relations. European Journal of Operational Research 154, 98-109. 10.1016/S0377-2217(02)00725-7

Hoffmann, P., 1985. Performance Indicators and Productivity. Port Management Textbook Containerization, Bremen, Germany.

Hsiao, S. W., Chou, J. R., 2006. A Gestalt-like perceptual measure for home page design using a fuzzy entropy approach. International Journal of Human-Computer Studies 64, 137-156. 10.1016/j.ijhcs.2005.05.005

Jee, D. H., Kang, K. J., 2000. A method for optimal material selection aided with decision making theory. Materials and Design 21, 199-206.

Kaliszewski, A., Kozłowski, A., Dąbrowski, J., Klimek, H., 2020. Key factors of container port competitiveness: A global shipping lines perspective. Marine Policy 117, 103896. 10.1016/j.marpol.2020.103896

Kristiansen, S., 2005. Maritime Transportation: Safety Management and Risk Analysis. Elsevier Butterworth-Heinemann, Oxford, UK.

Lee, P. T. W., Lin, C. W., Chung, Y. S., 2014. Comparison analysis for subjective and objective weights of financial positions of container shipping companies. Maritime Policy and Management 41, 241-250. 10.1080/03088839.2013.839511

Lee, P. T. W., Lin, C. W., Shih, S. H., 2018. Financial performance evaluation of shipping companies using entropy and grey relation analysis. International Series in Operations Research and Management Science 260, 219-247. 10.1007/978-3-319-62338-2_9

Lee, S. W., Shin, S. H., Bae, H. S., 2020. Short sea shipping on the west coast of Korea: Keys to activating the shipping industry in preparation for Korea unification era. Journal of International Logistics and Trade 18, 91-105. 10.24006/jilt.2020.18.2.91

Li, Q., Meng, X.X., Liu, Y. B., Pang, L. F., 2019. Risk assessment of floor water inrush using entropy weight and variation coefficient model. Geotechnical and Geological Engineering 37, 1493-1501. 10.1007/s10706-018-0702-9

Li, X., Wang, K., Liu, L., Xin, J., Yang, H., Gao, C., 2011. Application of the entropy weight and TOPSIS method in safety evaluation of coal mines. Procedia Engineering 26, 2085-2091. 10.1016/j.proeng.2011.11.2410

Lin, H., Pan, T., Chen, S., 2020. Comprehensive evaluation of urban air quality using the relative entropy theory and improved TOPSIS method. Air Quality Atmosphere & Health. Available at: 10.1007/s11869-020-00930-7

Liu, F., Zhao, S., Weng, M., Liu, Y., 2017. Fire risk assessment for large-scale commercial buildings based on structure entropy weight method. Safety Science 94, 26-40. 10.1016/j.ssci.2016.12.009

Liu, L., Zhou, J., An, X., Zhang, Y. C., Yang, L., 2010. Using fuzzy theory and information entropy for water quality assessment in Three Gorges region, China. Expert Systems with Applications 37, 2517-2521. 10.1016/j.eswa.2009.08.004

Ma, J., Fan, Z. P., Huang, L. H., 1999. A subjective and objective integrated approach to determine attribute weights. European Journal of Operational Research 112, 397-404. 10.1016/S0377-2217(98)00141-6

McGinnis, M. A., 1979. Shipper attitudes toward freight transportation choice: A factor analytic study. International Journal of Physical Distribution and Materials Management 10, 25-34. 10.1108/eb014464

Murphy, P. R., Dalenberg, D. R., Daley, J. M., 1991. Analyzing International water transportation: The perspectives of large U.S. industrial corporations. Journal of Business Logistics 12, 169-189.

Notteboom, T. E., 2006. The time factor in liner Shipping Services. Maritime Economic and Logistics 8, 19-39. 10.1057/palgrave.mel.9100148

Pham, T. Y., Yeo, G. T., 2019. Evaluation of transshipment container terminals’ service quality in Vietnam: From the shipping companies’ perspective. Sustainability 11, 1503. 10.3390/su11051503

Plumlee, C. H., 1979. Port Performance Index. Public Works Consultants, Port Huenme, CA.

Seo, W., Ahn, S. B., 2019. A case study on logistics services preferences for supply chain entities in shandong province, China. Journal of International Logistics and Trade 17, 55-66. 10.24006/jilt.2019.17.2.003

Shannon, C. E., 1948. A mathematical theory of communication. The Bell System Technical Journal 27, 379-423.

Slack, B., 1985. Containerization, Inter-port competition, and port selection. Maritime Policy and Management 1, 293-303. 10.1080/03088838500000043

Suthiwartnarueput, K., Lee, P. T. W., Lin, C. W., Visamitanan, K., Yang, Z., 2020. A trial to generalise evaluation of key driving factors of port-city waterfront development. International Journal of Shipping and Transport Logistics 12, 174-196. 10.1504/IJSTL.2020.107228

Thomas, B. J., 1985. Operations Planning in Ports. University of Wales Institute of Science and Technology, Cardiff, UK.

Vernimmen, B., Dullaert, W., Engelen, S., 2007. Schedule unreliability in liner shipping: Origins and consequences for the hinterland supply chain. Maritime Economics and Logistics 9, 193-213. 10.1057/palgrave.mel.9100182

Wang, T. C., Chen, Y. H., 2007. Applying consistent fuzzy preference relations to partnership selection. Omega 35, 384-388. 10.1016/j.omega.2005.07.007

Weng, J., Yang, D., Chai, T., Fu, S., 2019. Investigation of occurrence likelihood of human errors in shipping operations. Ocean Engineering 182, 28-37. 10.1016/j.oceaneng.2019.04.083

Xu, X., 2004. A note on the subjective and objective integrated approach to determine attribute weights. European Journal of Operational Research 156, 530-532. 10.1016/S0377-2217(03)00146-2

Yang, C. C., Chang, Y. K., 2019. Crucial factors influencing international logistics operations for African landlocked countries: A case study of Burkina Faso. Maritime Policy and Management, 46, 939-956. 10.1080/03088839.2019.1606464

Zhang, Y., Yang, Z., Li, W., 2006. Analyses of urban ecosystem based on information entropy. Ecological Modeling 197, 1-12. 10.1016/j.ecolmodel.2006.02.032

Zou, Z. H., Yun, Y., Sun, J. N., 2006. Entropy method for determination of weight of evaluating in fuzzy synthetic evaluating for water quality assessment indicators. Journal of Environmental Science 18, 1020-1023. 10.1016/S1001-0742(06)60032-6

Thông tin
Thông tin xuất bản

Emerald

Tập 18 Số 4

181-192

Thông tin tác giả