The consequences of container vessel collisions with quay cranes: a case study
Abstract
In the last few years several container terminals have faced accidents of collision between vessels and ship to shore (STS) gantry cranes, causing damage and losses to the port and terminal. The notion of port management should be designated to oversee the increasing amount of containers, particularly in the event of accidents or emergencies.
The primary research gap is that the majority of current literature predominantly depends on simulations, leading to a lack of empirical data. Accordingly, this article analyzes the impact and consequences of the collision involving an 8,000+ TEU container vessel and two Post-Panamax gantry cranes on container terminal operations, productivity and related financial costs and losses assigning empirical data. The study employs quantitative methods using port performance indicators (PPIs), which are well-established in maritime literature for measuring terminal efficiency, to quantify the impact of container ship STS gantry crane collisions at a container terminal. Pre- and post-incident PPIs show how the collision affected productivity, resource distribution, and service standards. Losses are assessed using financial indicators. The accident results revealed an increase in the Berth Occupancy Rate from 24% to 43%, a 40% rise in ship turnaround time, an increase in waiting time, a drop in the number of vessels, and a financial loss.
The research contributes in providing PPI-based empirical quantification of STS collision impacts based on PPI, facilitating better understanding of how vessel and STS incidents influence terminal production and performance using actual data. The study employs PPIs as measures of time, ship, STS, and financial loss to assess terminal disruption.
Received: 26 December 2025
Accepted: 25 January 2026
Published: 12 May 2026
Keywords
Full Text:
PDFReferences
Bovnegra, L., Pavlyshko, A., Nemchuk, O., Strelbitskyi, V. and Karabegovich, I. (2024). Experimental study of longevity in the metallic structure of boom for a portal crane of seaport. pp.432–439. doi:https://doi.org/10.1007/978-3-031-42778-7_40.
Caliskan, A. and Esmer, S. (2020). An assessment of port and shipping line relationships: the value of relationship marketing. Maritime Policy & Management, 47(2), pp.240–257. doi:https://doi.org/10.1080/03088839.2019.1690172.
Chang, Y.-T., Lee, S.-Y. and Tongzon, J.L. (2008). Port selection factors by shipping lines: Different perspectives between trunk liners and feeder service providers. Marine Policy, 32(6), pp.877–885. doi:https://doi.org/10.1016/j.marpol.2008.01.003.
Cheng, S., Liu, Q., Jin, H., Zhang, R., Ma, L. and Kwong, C.F. (2025). Collaborative optimization of truck scheduling in container terminals using graph theory and DDQN. Scientific Reports, 15(1), p.6950. doi:https://doi.org/10.1038/s41598-025-91140-7.
Chou, C.-C. (2010). AHP MODEL FOR THE CONTAINER PORT CHOICE IN THE MULTIPLE-PORTS REGION. Journal of Marine Science and Technology, 18(2). doi:https://doi.org/10.51400/2709-6998.2321.
Cui, H., Meng, Q. and Kuang, H. (2025). A trip-level multi-dimensional approach for the operational efficiency analysis of container vessel trips based on automatic identification system data. Maritime Policy & Management, 52(7), pp.1089–1111. doi:https://doi.org/10.1080/03088839.2024.2436080.
Cullinane, K. and Wang, T. (2010). The efficiency analysis of container port production using DEA panel data approaches. OR Spectrum, 32(3), pp.717–738. doi:https://doi.org/10.1007/s00291-010-0202-7.
Daryani, M.A., Omran, M.M. and Makui, A. (2020). A novel heuristic, based on a new robustness concept, for multi-objective project portfolio optimization. Computers & Industrial Engineering, 139, p.106187. doi:https://doi.org/10.1016/j.cie.2019.106187.
El-Refaei, A. and Idris, A.O. (2025). Towards a port demand management (PDM) system: An analytic hierarchy process (AHP)-based approach. Case Studies on Transport Policy, 19, p.101361. doi:https://doi.org/10.1016/j.cstp.2024.101361.
Gharehgozli, A.H., Roy, D. and de, M. (2014). Sea container terminals: New technologies, OR models, and emerging research areas. SSRN Electronic Journal. doi:https://doi.org/10.2139/ssrn.2469175.
Gothandapani, S.P. and Mohd (2021). Factors to determine quay crane lifecycle: Retrofit and replacement policy. IEOM Society International. doi:https://doi.org/10.46254/AN11.20210362.
Guy, E. and Urli, B. (2006). Port selection and multicriteria analysis: An application to the montreal-new york alternative. Maritime Economics & Logistics, 8(2), pp.169–186. doi:https://doi.org/10.1057/palgrave.mel.9100152.
Hendriks, M., Lefeber, E. and Udding, J.T. (2013). Simultaneous berth allocation and yard planning at tactical level. OR Spectrum, 35(2), pp.441–456. doi:https://doi.org/10.1007/s00291-012-0305-4.
Hu, H., Yang, X., Xiao, S. and Wang, F. (2023). Anti-conflict AGV path planning in automated container terminals based on multi-agent reinforcement learning. International Journal of Production Research, 61(1), pp.65–80. doi:https://doi.org/10.1080/00207543.2021.1998695.
Hwang, M.-J. and Huang, Y.-P. (2025). Exploring container port connectivity in Southeast Asia: An integrated assessment approach. The Asian Journal of Shipping and Logistics, 41(3), pp.139–152. doi:https://doi.org/10.1016/j.ajsl.2025.06.003.
Johnson, H. and Styhre, L. (2015). Increased energy efficiency in short sea shipping through decreased time in port. Transportation Research Part A: Policy and Practice, 71, pp.167–178. doi:https://doi.org/10.1016/j.tra.2014.11.008.
Kaizer, A., Smolarek, L., E. Ziajka and K. Krośnicka (2017). The analysis of container vessel service efficiency in the aspect of berth and handling equipment usage in polish ports. CRC Press, pp.249–254. doi:https://doi.org/10.1201/9781315099088-42.
Kalkschmied, K. and Stricker, P. (2026). Critical infrastructure, critical trade-offs: The growth effects of Chinese investments in European ports. Transportation Research Part A: Policy and Practice, 203, p.104704. doi:https://doi.org/10.1016/j.tra.2025.104704.
Kong, L. and Ji, M. (2024). Mathematical modeling and optimizing of yard layout in automated container terminals. Expert Systems with Applications, 258, p.125117. doi:https://doi.org/10.1016/j.eswa.2024.125117.
LI, C.-L. and VAIRAKTARAKIS, G.L. (2004). Loading and unloading operations in container terminals. IIE Transactions, 36(4), pp.287–297. doi:https://doi.org/10.1080/07408170490247340.
Li, S., Negenborn, R.R. and Lodewijks, G. (2017). Closed-loop coordination of inland vessels operations in large seaports using hybrid logic-based benders decomposition. Transportation Research Part E: Logistics and Transportation Review, 97, pp.1–21. doi:https://doi.org/10.1016/j.tre.2016.10.013.
Li, X., Peng, Y., Huang, J., Wang, W. and Song, X. (2021). Simulation study on terminal layout in automated container terminals from efficiency, economic and environment perspectives. Ocean & Coastal Management, 213, p.105882. doi:https://doi.org/10.1016/j.ocecoaman.2021.105882.
Magala, M. and Sammons, A. (2008). A new approach to port choice modelling. Maritime Economics & Logistics, 10(1-2), pp.9–34. doi:https://doi.org/10.1057/palgrave.mel.9100189.
Martin, J., Martin, S. and Pettit, S. (2015). Container ship size and the implications on port call workload. International Journal of Shipping and Transport Logistics, 7(5), p.553. doi:https://doi.org/10.1504/IJSTL.2015.072016.
Mennis, E., Platis, A., Ioannis Lagoudis and Nikitas Nikitakos (2008). Improving port container terminal efficiency with the use of markov theory. Maritime Economics & Logistics, 10(3), pp.243–257. doi:https://doi.org/10.1057/mel.2008.3.
Moya, J.M. and Valero, M.F. (2017). Port choice in container market: a literature review. Transport Reviews, 37(3), pp.300–321. doi:https://doi.org/10.1080/01441647.2016.1231233.
Pan, W., Chen, M., Lin, B., Wang, Y., Zhao, X., He, X. and Ye, J. (2025). Large-scale storage location assignment via hierarchical reinforcement learning: A rank and assign approach. IEEE Transactions on Knowledge and Data Engineering, 37(11), pp.6506–6520. doi:https://doi.org/10.1109/TKDE.2025.3609173.
Park, B.-I. and Min, H. (2011). The selection of transshipment ports using a hybrid data envelopment analysis/analytic hierarchy process. Journal of Transportation Management, 22(1), pp.47–64. doi:https://doi.org/10.22237/jotm/1301616240.
Parola, F., Pallis, A.A., Marcello Risitano and Ferretti, M. (2018). Marketing strategies of Port Authorities: A multi-dimensional theorisation. Transportation Research Part A: Policy and Practice, 111, pp.199–212. doi:https://doi.org/10.1016/j.tra.2018.03.012.
Rodrigue, J.-P. (2025). A systemic analysis of container terminal layouts. Journal of Shipping and Trade, 10(1), p.4. doi:https://doi.org/10.1186/s41072-025-00194-3.
Schuler, M. (2024). Caught on camera: Containership YM WITNESS takes out cranes at turkish port. [online] Available at: https://gcaptain.com/caught-on-camera-containership-ym-witness-takes-out-cranes-at-turkish-port/.
Seatrade Maritime (2024). Cargo ship collides with crane at port of Keelung. [online] Available at: https://www.seatrade-maritime.com/accidents/cargo-ship-collides-with-crane-at-port-of-keelung.
Siddaramaiah, D.G., Karnoji, D.S. and Gurudev, V. (2021). Factors affecting the vessel turnaround time in a seaport. HYDRO 2020 INTERNATIONAL, NIT Rourkela.
Stehmeyer, E.H., Canivan, G.J. and Camp, W.M. (2016). In situ dynamic pile testing to realize wharf renovation savings. American Society of Civil Engineers, pp.577–586. doi:https://doi.org/10.1061/9780784479902.058.
Steven, A.B. and Corsi, T.M. (2012). Choosing a port: An analysis of containerized imports into the US. Transportation Research Part E: Logistics and Transportation Review, 48(4), pp.881–895. doi:https://doi.org/10.1016/j.tre.2012.02.003.
Sunaryo and Hamka, M.A. (2017). Safety risks assessment on container terminal using hazard identification and risk assessment and fault tree analysis methods. Procedia Engineering, 194, pp.307–314. doi:https://doi.org/10.1016/j.proeng.2017.08.150.
Talley, W.K. and Ng, M. (2013). Maritime transport chain choice by carriers, ports and shippers. International Journal of Production Economics, 142(2), pp.311–316. doi:https://doi.org/10.1016/j.ijpe.2012.11.013.
Tran, N.K., Hercules Haralambides, Notteboom, T. and Cullinane, K. (2025). The costs of maritime supply chain disruptions: The case of the Suez Canal blockage by the ‘Ever Given’ megaship. International Journal of Production Economics, 279, p.109464. doi:https://doi.org/10.1016/j.ijpe.2024.109464.
Tran, Q.H., Huh, J., Nguyen, V.B., Kang, C., Ahn, J.-H. and Park, I.-J. (2018). Sensitivity analysis for ship-to-shore container crane design. Applied Sciences, 8(9), p.1667. doi:https://doi.org/10.3390/app8091667.
Transportation Safety Board of Canada (TSB) (2020). Marine transportation safety investigation report M19P0020 - transportation safety board of canada. [online] Available at: https://www.tsb.gc.ca/eng/rapports-reports/marine/2019/m19p0020/m19p0020.html.
UNCTAD (2019). Review of maritime transport 2019. UN. doi:https://doi.org/10.18356/17932789-en.
UNCTAD (2021). Review of maritime transport 2020. United Nations. doi:https://doi.org/10.18356/9789210052719.
UNCTAD (2022). Review of maritime transport. United Nations. doi:https://doi.org/10.18356/9789210021470.
UNCTAD (2024). Review of maritime transport 2024. United Nations. doi:https://doi.org/10.18356/9789211065923.
UNCTAD (2025). Review of maritime transport 2025. United Nations. doi:https://doi.org/10.18356/9789211591774.
Vis, I.F.A., Koster, R. de, Roodbergen, K.J. and Peeters, L.W.P. (2001). Determination of the number of automated guided vehicles required at a semi-automated container terminal. Journal of the Operational Research Society, 52(4), pp.409–417. doi:https://doi.org/10.1057/palgrave.jors.2601094.
Walters, J. (2024). STS crane damage and business interruption. [online] Available at: https://www.waves-group.co.uk/general-news/sts-crane-damage-and-business-interruption-a-ports-critical-challenge/.
World Bank Group (2024). Regional disruptions drive changes in global container port performance ranking. [online] Available at: https://www.worldbank.org/en/news/press-release/2024/06/01/regional-disruptions-drive-changes-in-global-container-port-performance-ranking.
Yang, D., Liao, S., Lun, Y.H.V. and Bai, X. (2023). Towards sustainable port management: Data-driven global container ports turnover rate assessment. Transportation Research Part E: Logistics and Transportation Review, 175, p.103169. doi:https://doi.org/10.1016/j.tre.2023.103169.
Yang, Y., Sun, S., Wu, Y., Feng, J., Lu, W., Wu, L. and Octavian Postolache (2025). Integrating multi-equipment scheduling with accurate AGV path planning for U-shaped automated container terminals. Computers & Industrial Engineering, 209, p.111427. doi:https://doi.org/10.1016/j.cie.2025.111427.
Yin, R.K. (2024). Case study research and applications design and methods. In CERN Document Server. [online] Available at: https://cds.cern.ch/record/2634179.
Zaerpour, N., Gharehgozli, A. and Koster, R.D. (2019). Vertical expansion: A solution for future container terminals. Transportation Science, 53(5), pp.1235–1251. doi:https://doi.org/10.1287/trsc.2018.0884.
Zhang, J., Luo, M. and Yang, D. (2025). Are efficient ports for port operators also those for shipping companies? A meta-frontier analysis of global top 80 container ports. Ocean & Coastal Management, 263, p.107616. doi:https://doi.org/10.1016/j.ocecoaman.2025.107616.
Zhang, J., Xin, X., Liao, Z., Dubey, R., Nguyen, T.T., Li, N. and Yang, Z. (2025). Analysis of the ripple effects of disruptions on multimodal container terminals operations: a System Dynamics approach. Transportation Research Part E: Logistics and Transportation Review, 202, p.104264. doi:https://doi.org/10.1016/j.tre.2025.104264.
Zhang, Y. and Siu, J. (2015). Estimating the economic losses of port disruption due to extreme wind events. Ocean & Coastal Management, 116, pp.300–310. doi:https://doi.org/10.1016/j.ocecoaman.2015.08.009.
Zhang, Y., Wei, K., Shen, Z., Bai, X., Lu, X. and Soares, C.G. (2020). Economic impact of typhoon-induced wind disasters on port operations: A case study of ports in China. International Journal of Disaster Risk Reduction, 50, p.101719. doi:https://doi.org/10.1016/j.ijdrr.2020.101719.
Zhao, B., Chen, W.-N., Wei, F.-F., Liu, X., Pei, Q. and Zhang, J. (2024). PEGA: A privacy-preserving genetic algorithm for combinatorial optimization. IEEE Transactions on Cybernetics, 54(6), pp.3638–3651. doi:https://doi.org/10.1109/TCYB.2023.3346863.
Zhong, H., Lin, Y., Yip, T.L., Cai, W. and Gu, Y. (2020). A novel oil port risk and efficiency performance measured by using AIS data and maritime open data: The case of Guangzhou, China. Ocean Engineering, 216, p.107859. doi:https://doi.org/10.1016/j.oceaneng.2020.107859.
DOI: https://dx.doi.org/10.21622/MRT.2026.05.1.1873
Refbacks
- There are currently no refbacks.
Copyright (c) 2026 Hossameldin Bakr Abdelsalam
Maritime Research and Technology
E-ISSN: 2812-5622
P-ISSN: 2812-5614
Published by:
Academy Publishing Center (APC)
Arab Academy for Science, Technology and Maritime Transport (AASTMT)
Alexandria, Egypt
