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Parametric Assessment of Hull Geometry Effects on the Coupled Dynamics of Semi-Submersible Floating Wind Turbines 2 2 This study presents a systematic investigation into the influence of geometric parameters and structural characteristics on the dynamic response of a semi-submersible platform supporting a floating wind turbine, with an emphasis on identifying stable performance regimes rather than determining a single optimal configuration. The analyses initiated with preliminary linear evaluations and were subsequently complemented by nonlinear time-domain simulations. A comparison of these approaches demonstrates that while the linear model is useful for identifying general response trends, it fails to fully capture oscillation amplitudes or the coupling intensity among degrees of freedom, particularly under hydrodynamic nonlinearities and mooring system effects. Consequently, a realistic assessment of system behavior necessitates nonlinear analysis. The investigation focused primarily on surge, heave, and pitch motions, as sway, roll, and yaw contributed minimally to the global response. Results indicate that the vertical and rotational motions of the platform are governed not only by the heave plate geometry but also by its interaction with the offset column arrangement. Variations in heave plate diameter and thickness, in conjunction with the geometric configuration of the offset columns, alter the dynamic response by modifying the added mass, hydrodynamic damping, and the relative positions of the centers of gravity and buoyancy. Within the examined range, heave plate diameters of 24–30 m and thicknesses equivalent to 7–10.5% of the offset column height produced more stable responses without shifting natural frequencies toward resonance. Specifically, a diameter of approximately 28.5 m and a thickness of around 8% yielded balanced surge, heave, and pitch responses. However, comparable performance across adjacent configurations suggests a robust design envelope rather than a single unique optimum. Overall, the findings highlight the utility of evaluating geometric parameters within an integrated framework to elucidate the relationships between platform geometry, hydrodynamic coefficients, and the coupled dynamic response. 1 19 2026/02/5 1404/11/16 2026/06/8 1405/3/18 Mohammad Javad Eslahi Mohammad Javad Eslahi Department of Civil Engineering, SRBIAU mj.eslahi@srbiau.ac.ir saeid kazemi saeid kazemi Department of Civil Engineering, SRBIAU Saeid.kazemi@srbiau.ac.ir Mojtaba Ezam Mojtaba Ezam Department of Physics Oceanography, SRBIAU ezam@srbiau.ac.ir madjid ghodsi hassanabad madjid ghodsi hassanabad Department of Mechanical Engineering, SRBIAU m.ghodsi@srbiau.ac.ir Floating offshore wind Turbines Coupled Dynamics Hull Form Effects Time-Domain Solution Method Response Amplitude Operation Withee, J. E., (2004). Fully coupled dynamic analysis of a floating wind turbine system (Doctoral dissertation, Monterey California. Naval Postgraduate School).##Wayman, E. N. (2006). Coupled Dynamic Modeling of Floating Wind Turbine Systems. Massachusetts Institute of Technology and National Renewable Energy Laboratory. ##https://doi.org/10.4043/18287-MS##Matha, D., Schlipf, M., Pereira, R., & Jonkman, J., (2011), June. Challenges in simulation of aerodynamics, hydrodynamics, and mooring-line dynamics of floating offshore wind turbines. In ISOPE International Ocean and Polar Engineering Conference. https://onepetro.org/ISOPEIOPEC/proceedings-abstract/ISOPE11/All-ISOPE11/12370.##Yang, Y., Bashir, M., Michailides, C., Li, C., & Wang, J., (2020). Development and application of an aero-hydro-servo-elastic coupling framework for analysis of floating offshore wind turbines. Renewable Energy, 161, 606-625. http://dx.doi.org/10.1016/j.renene.2020.07.134.##Xu, K., Gao, Z., & Moan, T., (2019). A study on fully nonlinear wave load effects on floating wind turbine. Journal of Fluids and Structures, 88, 216-240. ##https://doi.org/10.1016/j.jfluidstructs.2019.05.008##Li, H., & Bachynski-Polić, E. E., (2021). Validation and application of nonlinear hydrodynamics from CFD in an engineering model of a semi-submersible floating wind turbine. Marine Structures, 79, 103054. ##https://doi.org/10.1016/j.marstruc.2021.103054##Ferri, G., Marino, E., & Borri, C., (2020). Optimal dimensions of a semisubmersible floating platform for a 10 MW wind turbine. Energies, 13(12), 3092. ##https://doi.org/10.3390/en13123092##Sandua-Fernández, I., Vittori, F., Eguinoa, I., & Cheng, P. W., (2022), November. Impact of hydrodynamic drag coefficient uncertainty on 15 MW floating offshore wind turbine power and speed control. In Journal of Physics: Conference Series (Vol. 2362, No. 1). http://dx.doi.org/10.1088/1742-6596/2362/1/012037.##He, Y. P., Zhao, Y. S., Yang, X. Y., & Zhang, G. R., (2024). Coupled dynamic response analysis of multi-column floating offshore wind turbine with low center of gravity. Journal of Ocean Engineering and Science. http://dx.doi.org/10.1016/j.joes.2022.07.004.##Jonkman, J., & Musial, W., (2010). Offshore code comparison collaboration (OC3) for IEA Wind Task 23 offshore wind technology and deployment (No. NREL/TP-5000-48191). National Renewable Energy Lab (NREL).##Hansen, M., (2008). Aerodynamics of wind turbines. Routledge.##Hansen, M. H., Gaunaa, M., & Madsen, H. A., (2004). A Beddoes-Leishman type dynamic stall model in state-space and indicial formulations. Risø National Laboratory.##Journée, J. M. J., & Massie, W. W., (2001). Offshore Hydromechanics. Delft University of Technology.##Morison, J. R., Johnson, J. W., & Schaaf, S. A., (1950). The force exerted by surface waves on piles. Journal of Petroleum Technology, 2(05), 149-154. ##https://doi.org/10.2118/950149-G##MacCamy, R. C., & Fuchs, R. A., (1954). Wave forces on piles: a diffraction theory (No. 69). US Beach Erosion Board.##Hilber, H. M., Hughes, T. J. R., & Taylor, R. L. (1977). Improved numerical dissipation for time integration algorithms in structural dynamics. Earthquake Engineering & Structural Dynamics, 5(3), 283-292. ##https://doi.org/10.1002/eqe.4290050306##Simis AS, (2026). SIMIS (Version 4) [Computer software]. Simis AS, NTNU spin-off company, Leonardveien 3, NO-7790 Malm, Norway. https://www.simis.io/.##National Cartographic Center of Iran, (2026). Bathymetry Map of the Persian Gulf and Gulf of Oman [Map]. NCC, Tehran, Iran. https://en.ncc.gov.ir/.##GEBCO Compilation Group, (2023). GEBCO 2023 Grid. General Bathymetric Chart of the Oceans.##Javidaneh, A., (2023). Director General of National Cartographic Center of Iran (NCC). Retrieved from ncc.gov: https://en.ncc.gov.ir/Services.##Oceans, g. b., (2023). Gridded Bathymetry Data-Data & Products - Seabed. Retrieved from GEBCO: https://www.gebco.net.##Robertson, A., (2014). Definition of the semisubmersible floating system for phase II of OC4. NREL Technical Report, NREL/TP-5000-60601.##Chakrabarti, S. K., (1994). Offshore structure modeling (Vol. 9). World Scientific. https://www.researchgate.net/publication/238058967_Offshore_Code_Comparison_Collaboration_OC3_for_IEA_Wind_Task_23_Offshore_Wind_Technology_and_Deployment## ##

Integrating Machine Learning with Oil Analysis for Predictive Maintenance of Ship Stern Tube Seals 2 2 Stern-tube bearing failures can immobilize vessels and discharge lubricants into the sea, yet traditional threshold-based oil monitoring often overlooks the earliest signs of wear. We have developed an AI-driven predictive-maintenance framework that combines routine oil-analysis data with machine-learning models to detect incipient faults. Using a labelled dataset of 437 samples (54.2 % normal, 40.3 % warning, 5.5 % abnormal), we trained Random Forest and CatBoost classifiers; the Random Forest achieved an overall accuracy of 85 %. Applying the ADASYN over sampler raised recall for the rare abnormal class from 0.42 to 0.73. SHAP analysis identified copper and lead (bearing wear) as well as sodium and boron (seal-water ingress and additive depletion) as the most influential predictors. In a field trial on an AHTS-DP1 vessel, the model flagged rising boron six months before a dry-dock inspection confirmed seal damage caused by fishing-net entanglement, enabling timely repair and averting a potential MARPOL violation. Compared with the operator’s existing rule-based alerts, the proposed system cut false alarms by 40 % while detecting subtle degradation earlier. These findings show that merging tribological expertise with data-driven analytics can markedly enhance stern-tube reliability and promote more sustainable ship operations. 20 30 2026/02/52025/05/13 1404/2/23 2026/06/82026/07/12 1405/4/21 Mohammad Ali Mohaghegh Mohammad Ali Mohaghegh Faculty of Mechanical Engineering, Sharif University of Technology, Tehran, Iran m.ali.mohaghegh@gmail.com Mehdi Behzad Mehdi Behzad Faculty of Mechanical Engineering, Sharif University of Technology, Tehran, Iran ایران m_behzad@sharif.edu Somaye Mohammadi Somaye Mohammadi Faculty of Mechanical Engineering, Sharif University of Technology, Tehran, Iran ایران somaye.mohammadi@sharif.edu Predictive maintenance Stern tube seals Oil analysis Machine learning SHAP values Li R.; Ouyang W.; Liu Q.; Jin Y.; Yang J. (2024). Dynamic bearing characteristics of the ship stern shaft-bearing system with wave impact. Ocean Engineering 297, pp. 119020.##Wodtke M.; Litwin W. (2020). Water-lubricated stern tube bearing - experimental and theoretical investigations of thermal effects. Tribology International 151, pp. 106608.##Lee J.; Jeong B.; An T.-H. (2019). Investigation on effective support point of single stern tube bearing for marine propulsion shaft alignment. Marine Structures 64, pp. 1-17.##Lin C.-G.; Zou M.-S.; Sima C.; Liu S.-X.; Jiang L.-W. (2019). Friction-induced vibration and noise of marine stern tube bearings considering perturbations of the stochastic rough surface. Tribology International 132, pp. 661-671.##Rossopoulos G. N.; Papadopoulos C. I.; Leontopoulos C. (2020). Tribological comparison of an optimum single and double-slope design of the stern tube bearing: case study for a marine vessel. Tribology International 148, pp. 106343.##Frost J.; Frycz M.; Kowalski J.; Wodtke M.; Litwin W. (2023). Environmentally acceptable lubricants (EAL) compared with a reference mineral oil as marine stern tube bearing lubricant - experimental and theoretical investigations. Tribology International 181, pp. 109001.##Rossopoulos G. N.; Pervelis I.; Skaltsas D.; Papadopoulos C. I.; Vlachos O.; Koutsoumpas G.; Leontopoulos C. (2025). Experimental characterization of the tribological and acoustic performance of different stern-tube bearing materials. Tribology International 191, pp. 110590.##Qin H.-L.; Zhou X.-C.; Zhao X.-Z.; Xing J.-T.; Yan Z.-M. (2015). A new rubber/UHMWPE alloy for water-lubricated stern bearings. Wear 332-333, pp. 257-261.##Zhang S.-D.; Long Z.-L.; Yang X.-Y. (2020). Reaction force of ship stern bearing in hull large deformation based on stochastic theory. International Journal of Naval Architecture and Ocean Engineering 12 (2), pp. 723-732.##Litwin W.; Dymarski C. (2016). Experimental research on water-lubricated marine stern tube bearings in conditions of improper lubrication and cooling causing rapid bush wear. Tribology International 95, pp. 449-455.##Fang S.; Mu L.; Jia S.; Liu K.; Liu D. (2022). Combining artificial intelligence and laboratory experiments to explore the behaviour of sunken and submerged oil: a typical oil drift and diffusion detection technology. Journal of Cleaner Production 338, pp. 133026.##American Bureau of Shipping (ABS); Germanischer Lloyd (GL). Rules and guidelines for ship classification. Classification Society Publications, n.d.##Dubai Dry Dock. (2024). AHTS-DP1 technical documents. Internal company documentation.## ##

Numerical Modeling of the Sedimentation in the Chabahar Bay Area under the Influence of Shahid Beheshti Port Development 2 2 Shahid Beheshti Port stands as a critical maritime infrastructure in Iran, serving as a pivotal transit hub for goods destined for Central Asia. This research aims to elucidate the sedimentation dynamics within Chabahar Bay, both before and following the expansion of the Shahid Beheshti Port. The study employed various modules of the MIKE21 hydrodynamic modeling suite to achieve this objective. The modeling results, comparing pre- and post-development scenarios of Shahid Beheshti Port, reveal that sediments circumnavigate the breakwater before entering the area between the Beheshti breakwater and Kalantari Port. The region north of Kalantari Port, characterized by the rocky Lipar coast and seabed, predominantly experiences erosion, with occasional sedimentation events. The coastal stretch extending from Tis Port to the beach area exhibits a complex interplay of depositional and erosional processes. Erosion rates in this sector are substantial, ranging from approximately 14,000 to 19,600 cubic meters annually. A desalination plant situated along the western coastline acts as a significant sediment trap, with pronounced accumulation on its eastern flank. Conversely, the western side of this structure is subject to erosion due to local current patterns. 31 41 2026/02/52025/05/132024/10/25 1403/8/4 2026/06/82026/07/122026/07/15 1405/4/24 Shahab Chakarzehi Shahab Chakarzehi Coastal Engineering Department Chabahar Maritime University, P.O. Box 99717-56499, Chabahar, Iran ایران shahab.chakarzehi@gmail.com Mehdi Rezapour Mehdi Rezapour Coastal Engineering Department Chabahar Maritime University, P.O. Box 99717-56499, Chabahar, Iran, E-mail: rezapour@cmu.ac.ir ایران rezapour@cmu.ac.ir Seyed Amin Hosseini Seyed Amin Hosseini Mechanical Engineering Department Chabahar Maritime University, P.O. Box 99717-56499, Chabahar, Iran, E-mail: amin.hosseini@cmu.ac.ir ایران amin.hoss@gmail.com Zahra Ranji Zahra Ranji Metocean Engineer, Van Oord, Rotterdam, Netherland zahra.ranji132@gmail.com Sedimentation Numerical Modeling Development Plan Chabahar Bay Wu, W., (2004), Depth-averaged two-dimensional numerical modeling of unsteady flow and nonuniform sediment transport in open channels, J Hydraul Eng, 130(10): p. 1013-1024.##Panigrahi, J.K., Ananth, P.N. and Umesh, P.A., (2009), Coastal morphological modeling to assess the dynamics of Arklow Bank, Ireland, Int J Sediment Res, 24(3): p. 299-314.##Xie, D., Gao, S., Wang, Z. and Pan, C., (2013), Numerical modeling of tidal currents, sediment transport and morphological evolution in Hangzhou Bay, China, Int J Sediment Res, 28(3): p. 316-328.##Sravanthi, N., Ramakrishnan, R., Rajawat, A.S. and Narayana, A.C., (2015), Application of numerical model in suspended sediment transport studies along the Central Kerala west coast of India, Aquat Procedia, 4: p. 109-116.##Hendriyono, W., Wibowo, M., Al Hakim, B. and Istiyanto, D.C., (2015), Modeling of sediment transport affecting the coastline changes due to infrastructures in Batang, Central Java, Procedia Earth Planet Sci, 14: p. 166-178.##Babu, M.T., Vethamony, P. and Desa, E., (2005), Modelling tide-driven currents and residual eddies in the Gulf of Kachchh and their seasonal variability: A marine environmental planning perspective, Ecol Model, 184(2-4): p. 299-312.##Zhang, C., Zheng, J.H., Wang, Y.G., Zhang, M.T., Jeng, D.S. and Zhang, J.S., (2011), A process-based model for sediment transport under various wave and current conditions, Int J Sediment Res, 26(4): p. 498-512.##Ganesh, R. and Gopaul, N., (2013), A predictive outlook of coastal erosion on a log-spiral bay (Trinidad) by wave and sediment transport modelling, J Coast Res, 65: p. 488-493.##DHI., MIKE 21 & MIKE 3 Flow Model FM.##Morianou, G.G., Kourgialas, N.N., Karatzas, G.P. and Nikolaidis, N.P., (2016), Hydraulic and sediment transport simulation of Koiliaris River using the MIKE 21C model, Procedia Eng, 162: p. 463-470.##Nardini, A. and Pavan, S., (2012), What river morphology after restoration? The methodology VALURI, Int J River Basin Manag, 10(1): p. 29-47.##Gholami, Z., (2022), Evaluation of longshore sediment transport rate in Imam Khomeini Port using three samples of meta-heuristics algorithm, Hydrophysics, 7(2): p. 39-49.##Kirby, R., (2011), Minimising harbour siltation: Findings of PIANC Working Group 43, Ocean Dyn, 61(2): p. 233-244.##Safaval, P.A., Neshaei, S.A., Heidarian, P., Khanmohammadi, M., Ghanbarpour, F., Azizi, Z., Behzadi, S. and Stefanakis, A., (2024), Studying the effect of Anzali port breakwaters on sedimentation in Anzali wetland using remote sensing, Environ Eng Res, 29(1).##Zeinali, S., Dehghani, M., Rastegar, M.A. and Mojarrad, M., (2017), Detecting shoreline changes in Chabahar Bay by processing satellite images, Sci Iran, 24(4): p. 1802-1809.##Soltanpour, M. and Dibajnia, M., (2015), Field measurements and 3D numerical modeling of hydrodynamics in Chabahar Bay, Iran, Int J Marit Technol, 3: p. 49-60.##Kulkarni, R.R., (2013), Numerical modelling of coastal erosion using MIKE21. Master's thesis, Institutt for bygg, anlegg og transport. http://hdl.handle.net/11250/232599##Badru, G.S., Odunuga, S.S., Omojola, A.S. and Oladipo, E.O., (2022), Numerical modelling of sediment transport in southwest coast of Nigeria: Implications for sustainable management of coastal erosion in the Bight of Benin, J Afr Earth Sci, 187: p. 104466.##Seenath, A., (2023), A new approach for handling complex morphologies in hybrid shoreline evolution models, Appl Ocean Res, 141: p. 103754.##Wibowo, M., Khoirunnisa, H., Wijayanti, R., Istiyanto, D.C. and Widagdo, A.B., (2024), Sediment transport modelling: Effect of the coastal reservoirs##Wu, W., (2004), Depth-averaged two-dimensional numerical modeling of unsteady flow and nonuniform sediment transport in open channels, J Hydraul Eng, 130(10): p. 1013-1024.##Panigrahi, J.K., Ananth, P.N. and Umesh, P.A., (2009), Coastal morphological modeling to assess the dynamics of Arklow Bank, Ireland, Int J Sediment Res, 24(3): p. 299-314.##Xie, D., Gao, S., Wang, Z. and Pan, C., (2013), Numerical modeling of tidal currents, sediment transport and morphological evolution in Hangzhou Bay, China, Int J Sediment Res, 28(3): p. 316-328.##Sravanthi, N., Ramakrishnan, R., Rajawat, A.S. and Narayana, A.C., (2015), Application of numerical model in suspended sediment transport studies along the Central Kerala west coast of India, Aquat Procedia, 4: p. 109-116.##Hendriyono, W., Wibowo, M., Al Hakim, B. and Istiyanto, D.C., (2015), Modeling of sediment transport affecting the coastline changes due to infrastructures in Batang, Central Java, Procedia Earth Planet Sci, 14: p. 166-178.##Babu, M.T., Vethamony, P. and Desa, E., (2005), Modelling tide-driven currents and residual eddies in the Gulf of Kachchh and their seasonal variability: A marine environmental planning perspective, Ecol Model, 184(2-4): p. 299-312.##Zhang, C., Zheng, J.H., Wang, Y.G., Zhang, M.T., Jeng, D.S. and Zhang, J.S., (2011), A process-based model for sediment transport under various wave and current conditions, Int J Sediment Res, 26(4): p. 498-512.##Ganesh, R. and Gopaul, N., (2013), A predictive outlook of coastal erosion on a log-spiral bay (Trinidad) by wave and sediment transport modelling, J Coast Res, 65: p. 488-493.##DHI., MIKE 21 & MIKE 3 Flow Model FM.##Morianou, G.G., Kourgialas, N.N., Karatzas, G.P. and Nikolaidis, N.P., (2016), Hydraulic and sediment transport simulation of Koiliaris River using the MIKE 21C model, Procedia Eng, 162: p. 463-470.##Nardini, A. and Pavan, S., (2012), What river morphology after restoration? The methodology VALURI, Int J River Basin Manag, 10(1): p. 29-47.##Gholami, Z., (2022), Evaluation of longshore sediment transport rate in Imam Khomeini Port using three samples of meta-heuristics algorithm, Hydrophysics, 7(2): p. 39-49.##Kirby, R., (2011), Minimising harbour siltation: Findings of PIANC Working Group 43, Ocean Dyn, 61(2): p. 233-244.##Safaval, P.A., Neshaei, S.A., Heidarian, P., Khanmohammadi, M., Ghanbarpour, F., Azizi, Z., Behzadi, S. and Stefanakis, A., (2024), Studying the effect of Anzali port breakwaters on sedimentation in Anzali wetland using remote sensing, Environ Eng Res, 29(1).##Zeinali, S., Dehghani, M., Rastegar, M.A. and Mojarrad, M., (2017), Detecting shoreline changes in Chabahar Bay by processing satellite images, Sci Iran, 24(4): p. 1802-1809.##Soltanpour, M. and Dibajnia, M., (2015), Field measurements and 3D numerical modeling of hydrodynamics in Chabahar Bay, Iran, Int J Marit Technol, 3: p. 49-60.##Kulkarni, R.R., (2013), Numerical modelling of coastal erosion using MIKE21. Master's thesis, Institutt for bygg, anlegg og transport. http://hdl.handle.net/11250/232599##Badru, G.S., Odunuga, S.S., Omojola, A.S. and Oladipo, E.O., (2022), Numerical modelling of sediment transport in southwest coast of Nigeria: Implications for sustainable management of coastal erosion in the Bight of Benin, J Afr Earth Sci, 187: p. 104466.##Seenath, A., (2023), A new approach for handling complex morphologies in hybrid shoreline evolution models, Appl Ocean Res, 141: p. 103754.##Wibowo, M., Khoirunnisa, H., Wijayanti, R., Istiyanto, D.C. and Widagdo, A.B., (2024), Sediment transport modelling: Effect of the coastal reservoirs## ##

Forecasting Stock Return Predictability of Maritime Shipping Companies: A Recursive Modelling Approach with Implications for Market-Risk Assessment 2 2 For maritime shipping companies, stock-return volatility and predictability are not only a finance question but also an indirect signal of the health of the industry’s investment cycle. Improving the accuracy of such forecasts, and quantifying the contribution of individual macroeconomic and commodity factors, therefore matters to both investors and maritime-industry stakeholders, yet remains a challenging task. This paper employs a recursive modelling approach that simulates investor behaviour to test whether macroeconomic and commodity variables help forecast the stock returns of tanker shipping companies. Methods: We follow the recursive approach of Pesaran and Timmermann (2000) and Pourkermani (2023a). A dedicated Matlab routine allows the model structure to change at every step and evaluates the out-of-sample forecasting performance of a set of eight macroeconomic and commodity regressors for five Maritime Company’s companies (Frontline, Knightsbridge Tankers, Nordic American Tankers, and Teekay Corporation) benchmarked against the S&P 500. Results: Contrary to part of the prior literature, we find that permutation-based, information-criterion-selected models do not outperform a fixed model that retains all regressors; the all-variable model consistently delivers the highest net-of-cost return. Conclusion: This paper contributes to the literature by (i) applying the recursive out-of-sample forecasting framework specifically to Maritime Company’s equities, (ii) explicitly accounting for transaction costs when evaluating switching strategies, and (iii) comparing statistical, Akaike, and Bayesian information criteria for model selection in this context. Research Limitation: The model uses historical macroeconomic and commodity data and does not incorporate maritime-specific operational variables such ::as char::ter rates or bunker fuel prices, which we identify as a direction for future research.   31 43 2026/02/52025/05/132024/10/252025/07/19 1404/4/28 2026/06/82026/07/122026/07/152026/08/2 1405/5/11 Kasra Pourkermani Kasra Pourkermani Khorramshahr University of Marine Science and Technology pourkermani@kmsu.ac.ir Recursive modelling Maritime Company Forecast Simulation Gujarati, D. N., & Porter, D. C. (2009). Basic econometrics. McGraw-hill.##Pesaran, M. H., & Timmermann, A. (1995). Predictability of stock returns: Robustness and economic significance. The Journal of Finance, 50(4), 1201-1228.##Welch, I., & Goyal, A. (2008). A comprehensive look at the empirical performance of equity premium prediction. The Review of Financial Studies, 21(4), 1455-1508. ##https://doi.org/10.1093/rfs/hhm014##Keim, D. B., & Stambaugh, R. F. (1986). Predicting returns in the stock and bond markets. Journal of financial Economics, 17(2), 357-390. ##https://doi.org/10.1016/0304-405X(86)90070-X##Campbell, J. Y. (1987). Stock returns and the term structure. Journal of financial economics, 18(2), 373-399. ##https://doi.org/10.1016/0304-405X(87)90045-6##Fama, E. F., & French, K. R. (1988). Dividend yields and expected stock returns. Journal of financial economics, 22(1), 3-25. ##https://doi.org/10.1016/0304-405X(88)90020-7##Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of financial economics, 25(1), 23-49. ##https://doi.org/10.1016/0304-405X(89)90095-0##Lettau, M., & Ludvigson, S. C. (2010). Measuring and modeling variation in the risk-return trade-off. Handbook of financial econometrics: Tools and techniques, 617-690.##Rapach, D., & Zhou, G. (2013). Forecasting stock returns. In Handbook of economic forecasting (Vol. 2, pp. 328-383). Elsevier.##Paye, B. S., & Timmermann, A. (2006). Instability of return prediction models. Journal of Empirical Finance, 13(3), 274-315. ##https://doi.org/10.1016/j.jempfin.2005.11.001##Rapach, D. E., & Wohar, M. E. (2006). Structural breaks and predictive regression models of aggregate US stock returns. Journal of Financial Econometrics, 4(2), 238-274. https://doi.org/ 10. 1093/jjfinec/nbj008.##https://doi.org/10.1093/jjfinec/nbj008##Pourkermani, K. (2023). Time Charter or Trip Charter? An Assessment of Market Efficiency in Shipping Market. Transactions on Maritime Science, 12(01). doi: 10.7225/toms.v12.n01.010.##Henkel, S. J., Martin, J. S., & Nardari, F. (2011). Time-varying short-horizon predictability. Journal of financial economics, 99(3), 560-580. ##https://doi.org/10.1016/j.jfineco.2010.09.008##Dangl, T., & Halling, M. (2012). Predictive regressions with time-varying coefficients. Journal of Financial Economics, 106(1), 157-181. ##https://doi.org/10.1016/j.jfineco.2012.04.003##Johannes, M., Korteweg, A., & Polson, N. (2014). Sequential learning, predictability, and optimal portfolio returns. The Journal of Finance, 69(2), 611-644. https://doi.org /10.1111 /jofi.12121.##Rapach, D. E., Strauss, J. K., & Zhou, G. (2010). Out-of-sample equity premium prediction: Combination forecasts and links to the real economy. The Review of Financial Studies, 23(2), 821-862. ##https://doi.org/10.1093/rfs/hhp063##Chen, B., & Hong, Y. (2012). Testing for smooth structural changes in time series models via nonparametric regression. Econometrica, 80(3), 1157-1183.##Kelly, B., & Pruitt, S. (2013). Market expectations in the cross‐section of present values. The Journal of Finance, 68(5), 1721-1756. ##https://doi.org/10.1111/jofi.12060##Pettenuzzo, D., Timmermann, A., & Valkanov, R. (2014). Forecasting stock returns under economic constraints. Journal of Financial Economics, 114(3), 517-553. ##https://doi.org/10.1016/j.jfineco.2014.07.015##Pesaran, M. H., & Timmermann, A. (2000). A recursive modelling approach to predicting UK stock returns. The Economic Journal, 110(460), 159-191. ##https://doi.org/10.1111/1468-0297.00495##Pourkermani, K. (2023). Modeling the symmetric relation between Baltic Exchange indexes. Maritime Business Review, 8(3), 225-237.##Zhao, Y., Gong, X., Zhang, W., & Xu, W. (2025). Stock return forecasting based on the proxy variables of category factors: Y. Zhao et al. Financial Innovation, 11(1), 110.##Grammenos, C. T., & Arkoulis, A. G. (2002). Macroeconomic factors and international shipping stock returns. Maritime Economics & Logistics, 4(1), 81-99.##Wang, G. W. Y., Woo, S.-H., & Mileski, J. (2014). The relative efficiency and financial risk assessment of shipping companies. Maritime Policy & Management, 41(7), 651-666.##Mohanty, S. K., Aadland, R., Westgaard, S., Frydenberg, S., Lillienskiold, H., & Kristensen, C. (2021). Modelling stock returns and risk management in the shipping industry. Journal of Risk and Financial Management, 14(4), 190. ##https://doi.org/10.3390/jrfm14040171##Melas, K. D., & Michail, N. A. (2024). Can commodity prices predict stock market returns? The case of dry bulk shipping companies. Journal of Shipping and Trade, 9(1), 14.##Kamal, M. R., Chowdhury, M. A. F., & Hosain, M. M. (2021). Stock market reactions of maritime shipping industry in the time of COVID-19 pandemic crisis: An empirical investigation. Maritime Policy & Management, 49(8), 1184-1200.## ##

Arrangement and Stowage of AUVs on Military Mother Submarines 2 2 One of the key features of the next-generation (sixth-generation) military submarines is their capability to carry, launch, and recover AUVs (Autonomous Underwater Vehicles). These AUVs will be responsible for defending the submarine, monitoring and listening to the surrounding environment. This is crucial because, in the future, AUVs are expected to pose the most significant threat to submarines. Heavy and few torpedoes are not effective for dealing with small and numerous AUVs. Therefore, the internal layout of future military submarines should be modified to enable the widespread use of AUVs. The two significant distinctions between AUVs and torpedo launchers are that, firstly, AUVs must be recoverable and not disposable, and secondly, AUVs must be deployed in large numbers simultaneously. As a result, their launchers will be different. In this article, 13 methods are proposed for the deployment of AUVs, and the advantages and disadvantages of each method are also listed. Also, due to the requirement for special launchers for AUVs, the sixth-generation submarines will feature double-hull or combined hull designs, whereas most military submarines in this century have been predominantly single-hull. The article also examines the issue of "ocean transparency," which poses the greatest threat to future submarines.   44 60 2026/02/52025/05/132024/10/252025/07/192025/10/6 1404/7/14 2026/06/82026/07/122026/07/152026/08/22026/08/5 1405/5/14 Farzad Eskandari Farzad Eskandari Marine Industries Organization, Tehran, Iran ایران f.eskandari9@gmail.com Mohammad Moonesun Mohammad Moonesun Faculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran ایران m.moonesun@gmail.com Ataollah Gharechae Ataollah Gharechae Chabahar Maritime University, Maritime Engineering College, Chabahar, Iran ایران a.gharehchahi@gmail.com AUV Naval Submarine Mother Submarine Future Submarine Double Hull Submarine. Moonesun, M., Korol, Y., 2017. Naval submarine body form design and hydrodynamics. LAP LAMBERT Academic Publishing.##Bell, C., 2000. The Royal Navy, Seapower and Strategy between the Wars. Springer.##DoD, U., 2016. Annual Report to Congress [on] Military and Security Developments Involving the People's Republic of China 2016. DoD, Washington DC, 25.##Eskandari, F., Moonesun, M., Adjami, M., 2023. Transparency of the Oceans, a Threat to the Future of Nuclear Submarines. Journal Of Marine Engineering 19 (40), 43-62.##le Poole, J., Duchateau, E., van Oers, B., Hopman, H., Kana, A.A., 2022. WARGEAR: 'Real time' generation of detailed layout plans of surface warships during early stage design. Ocean Engineering 250, 110815.##Linton Brooks, A., 2015. Strategic Stability and Submarine Operations: Lessons from the Cold War, Confidence-Building and Maritime Strategic Stability in the Asia-Pacific, Carnegie-Tsinghua Center, Beijing, China. https://carnegieendowment.org/files/Speaker_Remarks%20-%20Ambassador%20Linton%20Brooks.pdf##Mahoney, R.W., 2009. The Royal Air Force, Combined Operations Doctrine and the Raid on Dieppe, 19 August 1942. University of Birmingham.##Asadi Asrami, E., Moonesun, M., 2023. Numerical and experimental investigation of the hydrodynamic lift and drag coefficients of a solar-powered AUV in near-surface mode. International Journal of Maritime Technology, IJMT Vol.10/No.19/Spring & Summer, pp: 1-26.##Moonesun, M., Charmdooz, P., 2006. General Arrangement and Architectural Aspects in Midget Submarines. 4th International Conference Underwater Sys. Tech.: Theory Appl.: Defence Technology Asia (DTA) 2006 - Singapore.##Moonesun, M., Ardeshiri, S., Asgari Jezi, A., 2023. Investigation of naval submarine dynamic equilibrium, balancing, and reverse speed considering control considerations. Journal Of Marine Engineering 19 (39), 113-138.##Pawling, R., Andrews, D., 2011. A Submarine Concept design-The Submarine as an UXV Mothership. International Conference Warship 2011: Naval Submarines and UUVs.##Pearce, P., Friedenthal, S., 2013. A practical approach for modelling submarine subsystem architecture in SysML. 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Journal Of Marine Engineering 19 (38), 106-124.##Stewart, M.S., Pavlos, J., 2006. A means to networked persistent undersea surveillance, Technology Symposium, pp. 1-38.##Sutton, H.I., 2020. France's Submarine Game Changer: The New Suffren-class. Naval News. https://www.navalnews.com/event-news/euronaval-2020/2020/10/frances-submarine-game-changer-the-new-suffren-class/##Zwolak, K., Wigley, R., Bohan, A., Zarayskaya, Y., Bazhenova, E., Dorshow, W., Sumiyoshi, M., Sattiabaruth, S., Roperez, J., Proctor, A., 2020. The autonomous underwater vehicle integrated with the unmanned surface vessel mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE. Remote Sensing 12 (8), 1344.## ##

An Integrated MCDM Framework for Risk Assessment of Commercial Fishing Vessel Subsystems: Resolving Methodological Ambiguities in Maritime Safety 2 2 Commercial fishing vessels account for 44% of global seafarer fatalities despite comprising only 2.3% of the merchant fleet, with equipment failure contributing to 31% of fatal incidents. The FMEA method critically underperforms in this context due to implicit equal weighting, non-unique Risk Priority Number (RPN) mapping, and subjective weight assignment. This study validates an integrated CRITIC-CODAS-FMEA framework, building on our prior application to composite Lenj hulls, by extending robust proof across navigation, refrigeration, and propulsion subsystems of fishing Lenj. Almost all failure modes are analyzed using expert elicitation (n=12 marine specialists). The CRITIC method derives objective weights by quantifying contrast intensity and inter-criterion conflict in S/O/D ratings, while the CODAS method employed Euclidean and Taxicab distances to resolve ranking ambiguities in the weighted space. The framework achieves 100% resolution of identical RPN clusters and elevates 89% of high-severity modes (S≥9) into top-10 rankings versus 60% for conventional FMEA. It demonstrated superior alignment with expert consensus (Spearman ρ=0.87 vs. 0.62) and 92% expert agreement versus 56% for RPN-based prioritization. This framework transforms risk assessment into a context-aware decision tool, objectively capturing marine operational realities to significantly enhance crew safety for the 34.3 million fishers operating worldwide. 61 80 2026/02/52025/05/132024/10/252025/07/192025/10/62026/05/22 1405/3/1 2026/06/82026/07/122026/07/152026/08/22026/08/52026/09/2 1405/6/11 Esmaeil Shafizadeh Esmaeil Shafizadeh Department of Maritime Engineering, Amirkabir University of Technology ایران e.shafizadeh@aut.ac.ir S. Hossein Mousavizadegan S. Hossein Mousavizadegan Department of Maritime Engineering, Amirkabir University of Technology ایران hmousavi@aut.ac.ir Maritime Safety FMEA CRITIC CODAS Multi-Criteria Decision Making (MCDM) Fishing Lenj. [1] F. Wang et al., “Identification of Risk Influential Factors for Fishing Vessel Accidents Using Claims Data from Fishery Mutual Insurance Association,” Sustainability, vol. 15, no. 18, p. 13427, Sep. 2023, doi: 10.3390/su151813427.##[2] S.-H. Kim, S.-H. Lee, K.-J. Ryu, and Y.-W. Lee, “Analysis of Accidents of Fishing Vessels Caused by Human Elements in Korean Sea Area,” J. Mar. Sci. Eng., vol. 12, no. 9, p. 1564, Sep. 2024, doi: 10.3390/jmse12091564.##[3] V. Domeh, F. Obeng, F. Khan, N. Bose, and E. Sanli, “A novel methodology to develop risk-based maintenance strategies for fishing vessels,” Ocean Eng., vol. 253, p. 111281, Jun. 2022, doi: 10.1016/j.oceaneng.2022.111281.##[4] G. Vizentin and D. Vukelić, “Marine environment induced failure of FRP composites used in maritime transport,” Eng. Fail. Anal., vol. 137, p. 106258, 2022, doi: 10.1016/j.engfailanal.2022.106258.##[5] Z. Han, J. Jang, J. R. G. Souppez, and H. Seo, “Comparison of structural design and future trends in composite hulls : A regulatory review,” Int. J. Nav. Archit. Ocean Eng., vol. 15, no. March, p. 100558, 2023, doi: 10.1016/j.ijnaoe.2023.100558.##[6] Z. Zhang, H. Zhu, and H. Liang, “Blockchain-Based Cold Chain Traceability with NR-PBFT and IoV-IMS for Marine Fishery Vessels,” J. Mar. Sci. Eng., vol. 12, no. 8, p. 1371, Aug. 2024, doi: 10.3390/jmse12081371.##[7] F. Obeng, D. Domeh, F. Khan, N. Bose, and E. Sanli, “An operational risk management approach for small fishing vessel,” Reliab. Eng. Syst. Saf., vol. 247, p. 110104, 2024, doi: https://doi.org/10.1016/j.ress.2024.110104.##[8] H. Wang, N. Chen, B. Wu, and C. Guedes Soares, “Human and organizational factors analysis of collision accidents between merchant ships and fishing vessels based on HFACS-BN model,” Reliab. Eng. Syst. Saf., vol. 249, p. 110201, 2024, doi: https://doi.org/10.1016/j.ress.2024.110201.##[9] X. Li, Z. Han, M. Yazdi, and G. Chen, “A CRITIC-VIKOR based robust approach to support risk management of subsea pipelines,” Appl. Ocean Res., vol. 124, p. 103187, 2022, doi:https://doi.org/10.1016/j.apor.2022.103187.##[10] S. G. Wang and R. Z. Wang, “Recent developments of refrigeration technology in fishing vessels,” Renew. Energy, vol. 30, pp. 589–600, 2005, doi: 10.1016/j.renene.2004.03.020.##[11] V. Anes and A. Abreu, “A Hybrid FMEA-ROC-CoCoSo Approach for Improved Risk Assessment and Reduced Complexity in Failure Mode Prioritization,” Algorithms 2024, Vol. 17, Page 585, vol. 17, no. 12, p. 585, Dec. 2024, doi: 10.3390/A17120585.##[12] E. Akdamar, G. Elidolu, M. Gögebakan, and B. O. Ceylan, “Entropy-based borda extended weighted expert FMEA approach: Comparison with classical and fuzzy FMEA on a ship system,” Appl. Soft Comput., vol. 188, p. 114424, Feb. 2026, doi: 10.1016/J.ASOC.2025.114424.##[13] V. Karanović, B. O. Ceylan, and M. Jocanović, “Reliable ships: A fuzzy FMEA based risk analysis on four-ram type hydraulic steering system,” Ocean Eng., vol. 314, p. 119758, 2024, doi: https://doi.org/10.1016/j.oceaneng.2024.119758.##[14] A. Laakso, M. Chaal, and O. A. Valdez Banda, “A risk assessment of an autonomous navigation system for a maritime autonomous surface ship,” J. Mar. Eng. Technol., vol. 24, no. 4, pp. 253–269, Jul. 2025, doi: 10.1080/20464177.2025.2460268.##[15] H. Li, H. Díaz, and C. Guedes Soares, “A failure analysis of floating offshore wind turbines using AHP-FMEA methodology,” Ocean Eng., vol. 234, p. 109261, 2021, doi: https://doi.org/10.1016/j.oceaneng.2021.109261.##[16] S. I. Sezer, “An extended failure mode and effects analysis (FMEA) combining cloud model, AHP and TOPSIS for cargo discharge operation failure,” Ocean Eng., vol. 356, p. 125334, 2026, doi: https://doi.org/10.1016/j.oceaneng.2026.125334.##[17] Q. Fu, Y. Sun, and L. Wang, “Risk Assessment of Import Cold Chain Logistics Based on Entropy Weight Matter Element Extension Model: A Case Study of Shanghai, China,” Int. J. Environ. Res. Public Heal. 2022, Vol. 19, Page 16892, vol. 19, no. 24, p. 16892, Dec. 2022, doi: 10.3390/IJERPH192416892.##[18] Z. Zhang, Y. Sun, L. Sun, Y. Guo, and J. Kang, “Research on the failure modes of autonomous navigation equipment based on the improved expert evaluation method,” Ocean Eng., vol. 300, p. 117375, May 2024, doi: 10.1016/J.OCEANENG.2024.117375.##[19] A. R. Krishnan, M. M. Kasim, R. Hamid, and M. F. Ghazali, “A Modified CRITIC Method to Estimate the Objective Weights of Decision Criteria,” Symmetry (Basel)., vol. 13, no. 6, p. 973, May 2021, doi: 10.3390/sym13060973.##[20] A. Pillay and J. Wang, “Modified failure mode and effects analysis using approximate reasoning,” Reliab. Eng. Syst. Saf., vol. 79, no. 1, pp. 69–85, Jan. 2003, doi: 10.1016/S0951-8320(02)00179-5.##[21] G. Jin, Q. Meng, and W. Feng, “Optimization of Logistics System with Fuzzy FMEA-AHP Methodology,” Process. 2022, Vol. 10, Page 1973, vol. 10, no. 10, p. 1973, Sep. 2022, doi: 10.3390/PR10101973.##[22] J. H. Zhu, Z. S. Chen, B. Shuai, W. Pedrycz, K. S. Chin, and L. Martínez, “Failure mode and effect analysis: A three-way decision approach,” Eng. Appl. Artif. Intell., vol. 106, p. 104505, Nov. 2021, doi: 10.1016/J.ENGAPPAI.2021.104505.##[23] J. Roy, S. Das, S. Kar, and D. Pamučar, “An Extension of the CODAS Approach Using Interval-Valued Intuitionistic Fuzzy Set for Sustainable Material Selection in Construction Projects with Incomplete Weight Information,” Symmetry 2019, Vol. 11, Page 393, vol. 11, no. 3, p. 393, Mar. 2019, doi: 10.3390/SYM11030393.##[24] S. H. Gurmani, S. Zhang, F. A. Awwad, and E. A. A. Ismail, “Combinative distance-based assessment method using linguistic T-spherical fuzzy aggregation operators and its application to multi-attribute group decision-making,” Eng. Appl. Artif. Intell., vol. 133, p. 108165, Jul. 2024, doi: 10.1016/J.ENGAPPAI.2024.108165.##[25] M. Keshavarz Ghorabaee, E. K. Zavadskas, Z. Turskis, and J. 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Prioritizing Cargo-Handling Quality Levers for B2B Customer Continuance Intention in Container Ports: An Importance-Performance and Relative-Importance Approach 2 2 Although research on port service quality has consistently shown that operational quality influences customer-related outcomes, it provides comparatively limited guidance on which cargo-handling dimensions should be preserved, accelerated or improved first. This study develops a priority-based assessment of cargo-handling operational quality by examining how operational speed, accuracy and error reduction, operational safety, and equipment availability and readiness should be ranked in relation to the continuance intention of organizational customers in a container-port setting. A cross-sectional survey was conducted among representatives of organizational customers directly involved in container loading and unloading activities at Imam Khomeini Port, yielding 110 valid responses. The analytical framework combined dimension-level multiple regression, Pratt-based relative-importance decomposition, importance–performance analysis and an action-priority score that integrated each dimension’s contribution to explained variance with its remaining performance gap. The findings showed that the four cargo-handling dimensions jointly explained 59.5% of the variance in B2B customer continuance intention. Operational speed recorded the largest standardized regression coefficient (β = 0.32) and the highest relative-importance share (35.4%), followed by equipment availability and readiness (β = 0.29; relative-importance share = 29.2%). When relative importance was considered alongside the remaining performance gaps, operational speed retained the highest action priority, followed by equipment readiness, operational safety, and accuracy and error reduction. Notably, although accuracy and error reduction received the lowest perceived performance score, its comparatively weaker contribution to continuance intention prevented it from emerging as the most urgent improvement priority. By moving beyond the question of whether cargo-handling quality affects customer continuance intention, this study demonstrates how individual operational dimensions can be translated into a defensible and practically meaningful sequence of managerial priorities. The proposed framework distinguishes statistical importance, perceived performance and improvement urgency, thereby providing port managers with a transparent basis for allocating limited operational resources while extending port service-quality research toward a more actionable and outcome-oriented approach to prioritization. 81 98 2026/02/52025/05/132024/10/252025/07/192025/10/62026/05/222026/05/18 1405/2/28 2026/06/82026/07/122026/07/152026/08/22026/08/52026/09/22026/09/5 1405/6/14 Mohammad Soltani Shirazi Mohammad Soltani Shirazi Master of Science (M.Sc.), Department of Maritime Business Management, SR.C., Islamic Azad University, Tehran, Iran ایران m.asadian@gmail.com Mohammad Asadian Ghahfarokhi Mohammad Asadian Ghahfarokhi Assistant professor, Department of Marine Industries, SR.C., Islamic Azad University, Tehran, Iran ایران asadian@srbiau.ac.ir Seyed Reza Samaei Seyed Reza Samaei Assistant professor, Department of Marine Industries, SR.C., Islamic Azad University, Tehran, Iran ایران samaei@srbiau.ac.ir Container ports Cargo-handling operational quality B2B customer continuance intention Importance–performance analysis Relative-importance analysis Equipment readiness operational reliability Maritime logistics. 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A paradox association in the context of port operations', The Asian Journal of Shipping and Logistics, 36(4), pp. 157-168. doi: 10.1016/j.ajsl.2020.02.001.##Nikolaou, P. and Dimitriou, L. (2021) 'Lessons to be learned from top-50 global container port terminals efficiencies: A multi-period DEA-Tobit approach', Maritime Transport Research, 2, article 100032. doi: 10.1016/j.martra.2021.100032.##Nanyam, V.P.S.N. and Jha, K.N. (2022) 'Operational performance model for Indian container terminals using qualitative comparative analysis', The Asian Journal of Shipping and Logistics, 38(4), pp. 197-206. doi: 10.1016/j.ajsl.2022.08.001.##Zhou, L. and Suh, W. (2024) 'A comprehensive study on static and dynamic operational efficiency in major Korean container terminals amid the smart port development context', Sustainability, 16(13), article 5288. doi: 10.3390/su16135288.##Mathias, T.N., Inutsuka, H., Shinoda, T. and Sugimura, Y. (2024) 'Operational performance evaluation of a container terminal using data mining and simulation', Asian Transport Studies, 10, article 100127. doi: 10.1016/j.eastsj.2024.100127.##Danladi, C., Tuck, S., Tziogkidis, P., Tang, L. and Okorie, C. (2024) 'Efficiency analysis and benchmarking of container ports operating in lower-middle-income countries: A DEA approach', Journal of Shipping and Trade, 9, article 7. doi: 10.1186/s41072-024-00163-2.##Kazmi, S.M., Rocha, E.M. and Brochado, Â.F. (2025) 'Evaluation of seaport equipment performance using multi-directional efficiency analysis for sustainable logistics operations: A case from Portugal', Research in Transportation Business & Management, 62, article 101442. doi: 10.1016/j.rtbm.2025.101442.##Rosca, E., Rusca, F., Carlan, V., Stefanov, O., Dinu, O. and Rusca, A. (2025) 'Assessing the influence of equipment reliability over the activity inside maritime container terminals through discrete-event simulation', Systems, 13(3), article 213. doi: 10.3390/systems13030213.##Pak, J.Y., Thai, V.V. and Yeo, G.-T. (2015) 'Fuzzy MCDM approach for evaluating intangible resources affecting port service quality', The Asian Journal of Shipping and Logistics, 31(4), pp. 459-468. doi: 10.1016/j.ajsl.2016.01.004.##Hsu, W.-K.K., Yu, H.-F. and Huang, S.-H.S. (2015) 'Evaluating the service requirements of dedicated container terminals: A revised IPA model with fuzzy AHP', Maritime Policy & Management, 42(8), pp. 789-805. doi: 10.1080/03088839.2015.1043750.##Sayareh, J., Iranshahi, S. and Golfakhrabadi, N. (2016) 'Service quality evaluation and ranking of container terminal operators', The Asian Journal of Shipping and Logistics, 32(4), pp. 203-212. doi: 10.1016/j.ajsl.2016.12.003.##Hemalatha, S., Dumpala, L. and Balakrishna, B. (2018) 'Service quality evaluation and ranking of container terminal operators through hybrid multi-criteria decision-making methods', The Asian Journal of Shipping and Logistics, 34(2), pp. 137-144. doi: 10.1016/j.ajsl.2018.06.010.##Nguyen, T.Q., Ngo, L.T.T., Huynh, N.T., Quoc, T.L. and Hoang, L.V. (2022) 'Assessing port service quality: An application of the extension fuzzy AHP and importance-performance analysis', PLOS ONE, 17(2), article e0264590. doi: 10.1371/journal.pone.0264590.##Min, H. and Park, B.-I. (2023) 'Examining port selection factors in Sub-Saharan Africa using the modified importance-performance analysis', Maritime Economics & Logistics, 25(4), pp. 755-777. doi: 10.1057/s41278-023-00270-0.##Pham, T.Y., Truong, N.C., Nguyen, P.H. and Kim, H.-S. (2024) 'The fuzzy MCDM for container terminal choice in Vietnam from shipping lines' perspective based on cumulative prospect theory', The Asian Journal of Shipping and Logistics, 40(3), pp. 147-156. doi: 10.1016/j.ajsl.2024.06.003.##Pham, T.Y. and Yeo, G.-T. (2019) 'Evaluation of transshipment container terminals' service quality in Vietnam: From the shipping companies' perspective', Sustainability, 11(5), article 1503. doi: 10.3390/su11051503.##Kaliszewski, A., Kozłowski, A., Dąbrowski, J. and Klimek, H. (2020) 'Key factors of container port competitiveness: A global shipping lines perspective', Marine Policy, 117, article 103896. doi: 10.1016/j.marpol.2020.103896.##Munim, Z.H., Hasan, K.R., Schramm, H.-J. and Tusher, H.M. (2022) 'A port attractiveness assessment framework: Chittagong Port's attractiveness from the users' perspective', Case Studies on Transport Policy, 10(1), pp. 463-471. doi: 10.1016/j.cstp.2022.01.007.##Tijan, E., Jović, M., Žgaljić, D. and Aksentijević, S. (2022) 'Factors affecting container seaport competitiveness: Case study on Port of Rijeka', Journal of Marine Science and Engineering, 10(10), article 1346. doi: 10.3390/jmse10101346.##Nguyen, S., Chen, P.S.-L., Du, Y. and Thai, V.V. (2021) 'An operational risk analysis model for container shipping systems considering uncertainty quantification', Reliability Engineering & System Safety, 209, article 107362. doi: 10.1016/j.ress.2020.107362.##Tseng, P.-H. and Pilcher, N. (2023) 'A safety assessment model for handling dangerous goods in port operations: The key role of detection capability', Journal of Marine Science and Engineering, 11(9), article 1704. doi: 10.3390/jmse11091704.##Wang, S., Yin, J. and Khan, R.U. (2023) 'Dynamic safety assessment and enhancement of port operational infrastructure systems during the COVID-19 era', Journal of Marine Science and Engineering, 11(5), article 1008. doi: 10.3390/jmse11051008.##Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1996) 'The Behavioral Consequences of Service Quality', Journal of Marketing, 60(2), pp. 31-46. doi: 10.1177/002224299606000203.##Bhattacherjee, A. (2001) 'Understanding information systems continuance: An expectation-confirmation model', MIS Quarterly, 25(3), pp. 351-370. doi: 10.2307/3250921.##Lawshe, C.H. (1975) 'A quantitative approach to content validity', Personnel Psychology, 28(4), pp. 563-575. doi: 10.1111/j.1744-6570. 1975.tb01393. x.##Polit, D.F. and Beck, C.T. (2006) 'The content validity index: Are you sure you know what's being reported? Critique and recommendations', Research in Nursing & Health, 29(5), pp. 489-497. doi: 10.1002/nur.20147.##Nunnally, J.C. (1978) Psychometric Theory, 2nd edn. New York: McGraw-Hill.##Fornell, C. and Larcker, D.F. (1981) 'Evaluating structural equation models with unobservable variables and measurement error', Journal of Marketing Research, 18(1), pp. 39-50. doi: 10.1177/002224378101800104.##Henseler, J., Ringle, C.M. and Sarstedt, M. (2015) 'A new criterion for assessing discriminant validity in variance-based structural equation modeling', Journal of the Academy of Marketing Science, 43, pp. 115-135. doi: 10.1007/s11747-014-0403-8.##Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2014) Multivariate Data Analysis, 7th edn. Harlow: Pearson Education Limited.##Tabachnick, B.G. and Fidell, L.S. (2019) Using Multivariate Statistics, 7th edn. Pearson.##Martilla, J.A. and James, J.C. (1977) 'Importance-Performance Analysis', Journal of Marketing, 41(1), pp. 77-79. doi: 10.1177/002224297704100112.##Kano, N., Seraku, N., Takahashi, F. and Tsuji, S. (1984) 'Attractive quality and must-be quality', Journal of the Japanese Society for Quality Control, 14(2), pp. 147-156. doi: 10.20684/quality.14.2_147.##Matzler, K., Bailom, F., Hinterhuber, H.H., Renzl, B. and Pichler, J. (2004) 'The asymmetric relationship between attribute-level performance and overall customer satisfaction: A reconsideration of the importance-performance analysis', Industrial Marketing Management, 33(4), pp. 271-277. doi: 10.1016/S0019-8501(03)00055-5.##Yeo, G.-T., Thai, V.V. and Roh, S.-Y. (2015) 'An analysis of port service quality and customer satisfaction: The case of Korean container ports', The Asian Journal of Shipping and Logistics, 31(4), pp. 437-447. doi: 10.1016/j.ajsl.2016.01.002.##Thai, V.V. (2016) 'The impact of port service quality on customer satisfaction: The case of Singapore', Maritime Economics & Logistics, 18(4), pp. 458-475. doi: 10.1057/mel.2015.19.##Le, D.N., Nguyen, H.T. and Truong, P.H. (2020) 'Port logistics service quality and customer satisfaction: Empirical evidence from Vietnam', The Asian Journal of Shipping and Logistics, 36(2), pp. 89-103. doi: 10.1016/j.ajsl.2019.10.003.##Sakyi, D. (2020) 'A comparative analysis of service quality among ECOWAS seaports', Transportation Research Interdisciplinary Perspectives, 6, article 100152. doi: 10.1016/j.trip.2020.100152.##Sakyi, D., Appiah, C.K., Ayesu, E.K., Immurana, M. and Baidoo, S.T. (2020) 'A terminal level analysis of service quality at Nigerian seaports', Journal of Shipping and Trade, 5, article 17. doi: 10.1186/s41072-020-00069-9.##Phan, T.M., Thai, V.V. and Vu, T.P. (2021) 'Port service quality (PSQ) and customer satisfaction: An exploratory study of container ports in Vietnam', Maritime Business Review, 6(1), pp. 72-94. doi: 10.1108/MABR-01-2020-0003.##Mwendapole, M.J. and Jin, Z. (2021) 'Evaluation of seaport service quality in Tanzania: From the Dar es Salaam Seaport perspective', Sustainability, 13(18), article 10076. doi: 10.3390/su131810076.##Abdul Rahman, N.S.F., Balasa, A.P., Othman, M.K. and Alemu, A.E. (2024) 'Port service quality assessment using a ROPMIS modeling: Seaports scenario in a Gulf country', Maritime Business Review, 9(1), pp. 17-34. doi: 10.1108/MABR-03-2023-0027.##Alsalfiti, A. and Notteboom, T. (2025) 'The impact of port service quality on customer satisfaction: The case of clearing and forwarding agents in Kuwait Shuwaikh Port', Maritime Business Review, 10(1), pp. 76-103. doi: 10.1108/MABR-04-2024-0030.##Chang, C.-H. and Thai, V.V. (2016) 'Do port security quality and service quality influence customer satisfaction and loyalty?', Maritime Policy & Management, 43(6), pp. 720-736. doi: 10.1080/03088839.2016.1151086.##Roh, S., Haddoud, M.Y., Onjewu, A.-K.E., Jang, H. and Thai, V.V. (2025) 'Revisiting the impact of container port service quality on customer satisfaction: A configuration approach', Transport Policy, 162, pp. 221-231. doi: 10.1016/j.tranpol.2024.12.008.##Zhou, L. and Suh, W. (2025) 'A study on port service quality, customer satisfaction, customer loyalty, and referral intention: Focusing on Korean container terminals amid smart port development', Systems, 13(6), article 486. doi: 10.3390/systems13060486.##Hirata, E. (2019) 'Service characteristics and customer satisfaction in the container liner shipping industry', The Asian Journal of Shipping and Logistics, 35(1), pp. 24-29. doi: 10.1016/j.ajsl.2019.03.004.##Chao, S.-L., Yu, M.-M. and Wei, S.-Y. (2024) 'Ascertaining the impact of e-service quality on e-loyalty for the e-commerce platform of liner shipping companies', Transportation Research Part E: Logistics and Transportation Review, 184, article 103491. doi: 10.1016/j.tre.2024.103491.##Utama, D.R., Hamsal, M., Rahim, R.K. and Furinto, A. (2024) 'The effect of digital adoption and service quality on business sustainability through strategic alliances at port terminals in Indonesia', The Asian Journal of Shipping and Logistics, 40(1), pp. 11-21. doi: 10.1016/j.ajsl.2023.12.001.##Molavi, A., Lim, G.J. and Race, B. (2020) 'A framework for building a smart port and smart port index', International Journal of Sustainable Transportation, 14(9), pp. 686-700. doi: 10.1080/15568318.2019.1610919.##Pham, T.Y. (2023) 'A smart port development: Systematic literature and bibliometric analysis', The Asian Journal of Shipping and Logistics, 39(3), pp. 57-62. doi: 10.1016/j.ajsl.2023.06.005.##Paraskevas, A., Madas, M., Zeimpekis, V. and Fouskas, K. (2024) 'Smart ports in Industry 4.0: A systematic literature review', Logistics, 8(1), article 28. doi: 10.3390/logistics8010028.##Vrakas, G., Chan, C. and Thai, V.V. (2021) 'The effects of evolving port technology and process optimisation on operational performance: The case study of an Australian container terminal operator', The Asian Journal of Shipping and Logistics, 37(4), pp. 281-290. doi: 10.1016/j.ajsl.2020.04.001.##Yen, B.T.H., Huang, M.-J., Lai, H.-J., Cho, H.-H. and Huang, Y.-L. (2023) 'How smart port design influences port efficiency-A DEA-Tobit approach', Research in Transportation Business & Management, 46, article 100862. doi: 10.1016/j.rtbm.2022.100862.##Hsu, C.-T., Chou, M.-T. and Ding, J.-F. (2023) 'Key factors for the success of smart ports during the post-pandemic era', Ocean & Coastal Management, 233, article 106455. doi: 10.1016/j.ocecoaman.2022.106455.##Sahraoui, A., Tran, N.K., Tliche, Y., Kacem, A. and Taghipour, A. (2023) 'Examining ICT innovation for sustainable terminal operations in developing countries: A case study of the Port of Radès in Tunisia', Sustainability, 15(11), article 9123. doi: 10.3390/su15119123.##Wu, S. and Yang, Z. (2024) 'Impact of port integration on port service quality in the context of shipping alliance', Transport Economics and Management, 2, pp. 331-347. doi: 10.1016/j.team.2024.09.009.##Munim, Z.H. (2020) 'Does higher technical efficiency induce a higher service level? A paradox association in the context of port operations', The Asian Journal of Shipping and Logistics, 36(4), pp. 157-168. doi: 10.1016/j.ajsl.2020.02.001.##Nikolaou, P. and Dimitriou, L. (2021) 'Lessons to be learned from top-50 global container port terminals efficiencies: A multi-period DEA-Tobit approach', Maritime Transport Research, 2, article 100032. doi: 10.1016/j.martra.2021.100032.##Nanyam, V.P.S.N. and Jha, K.N. (2022) 'Operational performance model for Indian container terminals using qualitative comparative analysis', The Asian Journal of Shipping and Logistics, 38(4), pp. 197-206. doi: 10.1016/j.ajsl.2022.08.001.##Zhou, L. and Suh, W. (2024) 'A comprehensive study on static and dynamic operational efficiency in major Korean container terminals amid the smart port development context', Sustainability, 16(13), article 5288. doi: 10.3390/su16135288.##Mathias, T.N., Inutsuka, H., Shinoda, T. and Sugimura, Y. (2024) 'Operational performance evaluation of a container terminal using data mining and simulation', Asian Transport Studies, 10, article 100127. doi: 10.1016/j.eastsj.2024.100127.##Danladi, C., Tuck, S., Tziogkidis, P., Tang, L. and Okorie, C. (2024) 'Efficiency analysis and benchmarking of container ports operating in lower-middle-income countries: A DEA approach', Journal of Shipping and Trade, 9, article 7. doi: 10.1186/s41072-024-00163-2.##Kazmi, S.M., Rocha, E.M. and Brochado, Â.F. (2025) 'Evaluation of seaport equipment performance using multi-directional efficiency analysis for sustainable logistics operations: A case from Portugal', Research in Transportation Business & Management, 62, article 101442. doi: 10.1016/j.rtbm.2025.101442.##Rosca, E., Rusca, F., Carlan, V., Stefanov, O., Dinu, O. and Rusca, A. (2025) 'Assessing the influence of equipment reliability over the activity inside maritime container terminals through discrete-event simulation', Systems, 13(3), article 213. doi: 10.3390/systems13030213.##Pak, J.Y., Thai, V.V. and Yeo, G.-T. (2015) 'Fuzzy MCDM approach for evaluating intangible resources affecting port service quality', The Asian Journal of Shipping and Logistics, 31(4), pp. 459-468. doi: 10.1016/j.ajsl.2016.01.004.##Hsu, W.-K.K., Yu, H.-F. and Huang, S.-H.S. (2015) 'Evaluating the service requirements of dedicated container terminals: A revised IPA model with fuzzy AHP', Maritime Policy & Management, 42(8), pp. 789-805. doi: 10.1080/03088839.2015.1043750.##Sayareh, J., Iranshahi, S. and Golfakhrabadi, N. (2016) 'Service quality evaluation and ranking of container terminal operators', The Asian Journal of Shipping and Logistics, 32(4), pp. 203-212. doi: 10.1016/j.ajsl.2016.12.003.##Hemalatha, S., Dumpala, L. and Balakrishna, B. (2018) 'Service quality evaluation and ranking of container terminal operators through hybrid multi-criteria decision-making methods', The Asian Journal of Shipping and Logistics, 34(2), pp. 137-144. doi: 10.1016/j.ajsl.2018.06.010.##Nguyen, T.Q., Ngo, L.T.T., Huynh, N.T., Quoc, T.L. and Hoang, L.V. (2022) 'Assessing port service quality: An application of the extension fuzzy AHP and importance-performance analysis', PLOS ONE, 17(2), article e0264590. doi: 10.1371/journal.pone.0264590.##Min, H. and Park, B.-I. (2023) 'Examining port selection factors in Sub-Saharan Africa using the modified importance-performance analysis', Maritime Economics & Logistics, 25(4), pp. 755-777. doi: 10.1057/s41278-023-00270-0.##Pham, T.Y., Truong, N.C., Nguyen, P.H. and Kim, H.-S. (2024) 'The fuzzy MCDM for container terminal choice in Vietnam from shipping lines' perspective based on cumulative prospect theory', The Asian Journal of Shipping and Logistics, 40(3), pp. 147-156. doi: 10.1016/j.ajsl.2024.06.003.##Pham, T.Y. and Yeo, G.-T. (2019) 'Evaluation of transshipment container terminals' service quality in Vietnam: From the shipping companies' perspective', Sustainability, 11(5), article 1503. doi: 10.3390/su11051503.##Kaliszewski, A., Kozłowski, A., Dąbrowski, J. and Klimek, H. (2020) 'Key factors of container port competitiveness: A global shipping lines perspective', Marine Policy, 117, article 103896. doi: 10.1016/j.marpol.2020.103896.##Munim, Z.H., Hasan, K.R., Schramm, H.-J. and Tusher, H.M. (2022) 'A port attractiveness assessment framework: Chittagong Port's attractiveness from the users' perspective', Case Studies on Transport Policy, 10(1), pp. 463-471. doi: 10.1016/j.cstp.2022.01.007.##Tijan, E., Jović, M., Žgaljić, D. and Aksentijević, S. (2022) 'Factors affecting container seaport competitiveness: Case study on Port of Rijeka', Journal of Marine Science and Engineering, 10(10), article 1346. doi: 10.3390/jmse10101346.##Nguyen, S., Chen, P.S.-L., Du, Y. and Thai, V.V. (2021) 'An operational risk analysis model for container shipping systems considering uncertainty quantification', Reliability Engineering & System Safety, 209, article 107362. doi: 10.1016/j.ress.2020.107362.##Tseng, P.-H. and Pilcher, N. (2023) 'A safety assessment model for handling dangerous goods in port operations: The key role of detection capability', Journal of Marine Science and Engineering, 11(9), article 1704. doi: 10.3390/jmse11091704.##Wang, S., Yin, J. and Khan, R.U. (2023) 'Dynamic safety assessment and enhancement of port operational infrastructure systems during the COVID-19 era', Journal of Marine Science and Engineering, 11(5), article 1008. doi: 10.3390/jmse11051008.##Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1996) 'The Behavioral Consequences of Service Quality', Journal of Marketing, 60(2), pp. 31-46. doi: 10.1177/002224299606000203.##Bhattacherjee, A. (2001) 'Understanding information systems continuance: An expectation-confirmation model', MIS Quarterly, 25(3), pp. 351-370. doi: 10.2307/3250921.##Lawshe, C.H. (1975) 'A quantitative approach to content validity', Personnel Psychology, 28(4), pp. 563-575. doi: 10.1111/j.1744-6570. 1975.tb01393. x.##Polit, D.F. and Beck, C.T. (2006) 'The content validity index: Are you sure you know what's being reported? Critique and recommendations', Research in Nursing & Health, 29(5), pp. 489-497. doi: 10.1002/nur.20147.##Nunnally, J.C. (1978) Psychometric Theory, 2nd edn. New York: McGraw-Hill.##Fornell, C. and Larcker, D.F. (1981) 'Evaluating structural equation models with unobservable variables and measurement error', Journal of Marketing Research, 18(1), pp. 39-50. doi: 10.1177/002224378101800104.##Henseler, J., Ringle, C.M. and Sarstedt, M. (2015) 'A new criterion for assessing discriminant validity in variance-based structural equation modeling', Journal of the Academy of Marketing Science, 43, pp. 115-135. doi: 10.1007/s11747-014-0403-8.##Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2014) Multivariate Data Analysis, 7th edn. Harlow: Pearson Education Limited.##Tabachnick, B.G. and Fidell, L.S. (2019) Using Multivariate Statistics, 7th edn. Pearson.##Martilla, J.A. and James, J.C. (1977) 'Importance-Performance Analysis', Journal of Marketing, 41(1), pp. 77-79. doi: 10.1177/002224297704100112.##Kano, N., Seraku, N., Takahashi, F. and Tsuji, S. (1984) 'Attractive quality and must-be quality', Journal of the Japanese Society for Quality Control, 14(2), pp. 147-156. doi: 10.20684/quality.14.2_147.##Matzler, K., Bailom, F., Hinterhuber, H.H., Renzl, B. and Pichler, J. (2004) 'The asymmetric relationship between attribute-level performance and overall customer satisfaction: A reconsideration of the importance-performance analysis', Industrial Marketing Management, 33(4), pp. 271-277. doi: 10.1016/S0019-8501(03)00055-5.## ##