Shipping inspections, detentions, and incidents: an empirical analysis of risk dimensions
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DOI: 10.1080/03088839.2019.1647362
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Cited by:
- Knapp, S. & van de Velden, M., 2021. "Exploration of machine learning algorithms for maritime risk applications," Econometric Institute Research Papers 2021-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Antão, P. & Sun, S. & Teixeira, A.P. & Guedes Soares, C., 2023. "Quantitative assessment of ship collision risk influencing factors from worldwide accident and fleet data," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Yan, Ran & Wang, Shuaian & Zhen, Lu, 2023. "An extended smart “predict, and optimize” (SPO) framework based on similar sets for ship inspection planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
- Yan, Ran & Wang, Shuaian & Fagerholt, Kjetil, 2020. "A semi-“smart predict then optimize” (semi-SPO) method for efficient ship inspection," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 100-125.
- Knapp, S. & Franses, Ph.H.B.F. & B. Whitby (Bruce), 2020. "Measuring the effect of perceived corruption on detention and incident risk – an empirical analysis," Econometric Institute Research Papers EI 2020-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Yan, Ran & Liu, Yan & Wang, Shuaian, 2024. "A data-driven optimization approach to improving maritime transport efficiency," Transportation Research Part B: Methodological, Elsevier, vol. 180(C).
- Yan, Ran & Wang, Shuaian & Cao, Jiannong & Sun, Defeng, 2021. "Shipping Domain Knowledge Informed Prediction and Optimization in Port State Control," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 52-78.
- Filom, Siyavash & Amiri, Amir M. & Razavi, Saiedeh, 2022. "Applications of machine learning methods in port operations – A systematic literature review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
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