IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v193y2025ics1366554524004526.html

Towards advanced decision-making support for shipping safety: A functional connectivity analysis

Author

Listed:
  • Fan, Shiqi
  • Fairclough, Stephen
  • Khalique, Abdul
  • Bury, Alan
  • Yang, Zaili

Abstract

Decision making (DM) is essential and proven to be a natural and inherent part of the success of transport systems, particularly given the fast growth of autonomous systems in transport. It is critical but remains challenging to understand and predict DM performance in transport, because operators’ mental states have not been effectively considered in complex DM processes such as ship anti-collision operations. This paper proposes an advanced decision support methodology that pioneers the incorporation of objective neurophysiological and subjective data to analyse functional connectivity in the brain and predict DM performance in ship navigation. Experiments were conducted using a functional Near-Infrared Spectroscopy (fNIRS) technology to explore the functional connectivity of two groups (low workload and high workload) and predict their DM performance in a ship collision avoidance situation. It brings brain science into transport engineering and the results generate new contributions to the existing knowledge, including (1) the establishment of a methodology to detect different workload levels in safety–critical transport systems using psychophysiological measurement; (2) analysis of brain’s functional connectivity of different groups of decision makers (e.g., seafarers) with high and low workload tasks; (3) an advanced methodology to assess human reliability in complex scenarios and predict operational behaviours; (4) pioneering a human-centred approach to predict DM performance and demonstrate its feasibility in shipping. From a practical perspective, stakeholders can utilise the findings of this study to rationally evaluate human performance in transport system operations, aiding in operator qualification and certification processes. Furthermore, it is critical for adaptive automation regarding DM support in safety–critical systems.

Suggested Citation

  • Fan, Shiqi & Fairclough, Stephen & Khalique, Abdul & Bury, Alan & Yang, Zaili, 2025. "Towards advanced decision-making support for shipping safety: A functional connectivity analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:transe:v:193:y:2025:i:c:s1366554524004526
    DOI: 10.1016/j.tre.2024.103861
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554524004526
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2024.103861?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Hogenboom, Sandra & Parhizkar, Tarannom & Vinnem, Jan Erik, 2021. "Temporal decision-making factors in risk analyses of dynamic positioning operations," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    2. Vladimir Jakovljevic & Mališa Zizovic & Dragan Pamucar & Željko Stević & Miloljub Albijanic, 2021. "Evaluation of Human Resources in Transportation Companies Using Multi-Criteria Model for Ranking Alternatives by Defining Relations between Ideal and Anti-Ideal Alternative (RADERIA)," Mathematics, MDPI, vol. 9(9), pages 1-25, April.
    3. Vivek Vijayakumar & Fabio Sgarbossa & W. Patrick Neumann & Ahmad Sobhani, 2022. "Framework for incorporating human factors into production and logistics systems," International Journal of Production Research, Taylor & Francis Journals, vol. 60(2), pages 402-419, January.
    4. Bai, Congcong & Jin, Sheng & Jing, Jun & Yang, Chengcheng & Yao, Wenbin & Rong, Donglei & Alagbé, Jérémie Adjé, 2024. "A multimodal data-driven approach for driving risk assessment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).
    5. Al Hajj Hassan, Lama & Mahmassani, Hani S. & Chen, Ying, 2020. "Reinforcement learning framework for freight demand forecasting to support operational planning decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    6. Atashfeshan, Nooshin & Saidi-Mehrabad, Mohammad & Razavi, Hamideh, 2021. "A novel dynamic function allocation method in human-machine systems focusing on trigger mechanism and allocation strategy," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    7. Tseremoglou, Iordanis & Bombelli, Alessandro & Santos, Bruno F., 2022. "A combined forecasting and packing model for air cargo loading: A risk-averse framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    8. Moktadir, Md. Abdul & Ren, Jingzheng, 2024. "Towards green logistics: An innovative decision support model for zero-emission transportation modes development," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).
    9. Kayisoglu, Gizem & Gunes, Bunyamin & Besikci, Elif Bal, 2022. "SLIM based methodology for human error probability calculation of bunker spills in maritime operations," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    10. Xu, Ren-Hong & Lai, Yung-Cheng & Huang, Kwei-Long, 2021. "Decision support models for annual catenary maintenance task identification and assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    11. Eskandarzadeh, Saman & Fahimnia, Behnam & Hoberg, Kai, 2023. "Adherence to standard operating procedures for improving data quality: An empirical analysis in the postal service industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 176(C).
    12. Zheng, Shiyuan & Jiang, Changmin, 2024. "Consortium blockchain in Shipping: Impacts on industry and social welfare," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    13. Fan, Shiqi & Yang, Zaili, 2023. "Towards objective human performance measurement for maritime safety: A new psychophysiological data-driven machine learning method," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    14. Christian Hendriksen, 2023. "Artificial intelligence for supply chain management: Disruptive innovation or innovative disruption?," Journal of Supply Chain Management, Institute for Supply Management, vol. 59(3), pages 65-76, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qiao, Runtao & Fan, Shiqi, 2026. "Human-machine interaction for maritime transport using a data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 267(PB).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhou, Fuli & Zhang, Chenchen & Tiwari, Sunil & Huang, Xingjun & Basu, Preetam, 2026. "Can Gen-AI promote community group buying? A tripartite evolutionary game analysis," International Journal of Production Economics, Elsevier, vol. 291(C).
    2. Bergsma, Ritsaart & de Ruijt, Corné & Bhulai, Sandjai, 2025. "A systematic review of machine learning approaches in inventory control optimization," Operations Research Perspectives, Elsevier, vol. 15(C).
    3. Fan, Shiqi & Shi, Kun & Weng, Jinxian & Yang, Zaili, 2025. "Letting losses be lessons: Human-machine cooperation in maritime transport," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    4. Qiao, Runtao & Fan, Shiqi, 2026. "Human-machine interaction for maritime transport using a data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 267(PB).
    5. BOWERS Dominique & MATLALA Ntswaki & BERHADIEN Moegamat & UMETOR Henry & GONGXEKA Thabo, 2024. "Sustainable Supply Chain Management And Disruptive Theory: A Bibliometric Review," Management of Sustainable Development, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 16(1), pages 11-23, June.
    6. Zhao, Xian & Wang, Xinlei & Dai, Ying & Qiu, Qingan, 2024. "Joint optimization of loading, mission abort and rescue site selection policies for UAV," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    7. Garg, Vipul & Gabaldon, Janeth & Niranjan, Suman & Hawkins, Timothy G., 2025. "Impact of strategic performance measures on performance: The role of artificial intelligence and machine learning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 198(C).
    8. Bai, Shizhen & Zhou, Jiamin & Han, Chunjia & Yang, Mu & Wang, Chen & Gupta, Brij B., 2026. "From information to operations: Exploring the impact of integrated AI-HI on information diffusion and users' willingness in humanitarian aid," Technological Forecasting and Social Change, Elsevier, vol. 224(C).
    9. Gursel, Ezgi & Madadi, Mahboubeh & Coble, Jamie Baalis & Agarwal, Vivek & Yadav, Vaibhav & Boring, Ronald L. & Khojandi, Anahita, 2025. "The role of AI in detecting and mitigating human errors in safety-critical industries: A review," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    10. Lu, Bo & Fan, Lijie & Perera, Sandun C. & Wang, Jian-Jun, 2025. "Does antitrust immunity matter for complementary shipping alliances? Competition and welfare analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 198(C).
    11. Vechgama, Wasin & Park, Jinkyun & Kim, Yochan & Wetchagarun, Saensuk & Pechrak, Anantachai & Pornroongruengchok, Weerawat & Silva, Kampanart, 2025. "Suggestion of specific performance shaping factor update for the human reliability analysis framework of the TRIGA research reactor," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    12. Maryam Roosta & Masoud Javadpoor & Maryam Ebadi, 2025. "Implementing urban cooling: a framework of strategies for improving heat resiliency of urban spaces in hot and arid climate zone of Iran," Climatic Change, Springer, vol. 178(10), pages 1-25, October.
    13. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).
    14. Bouaziz, Nourddine & Bettayeb, Belgacem & Sahnoun, M’hammed & Yassine, Adnan, 2024. "Incorporating uncertain human behavior in production scheduling for enhanced productivity in Industry 5.0 context," International Journal of Production Economics, Elsevier, vol. 274(C).
    15. Ning Li & Yingchao Xu & Yunfei Xie, 2025. "How Digital Transformation Intensity Enables Persistent Green Innovation? An Empirical Study of Chinese A-Share Listed Firms," SAGE Open, , vol. 15(3), pages 21582440251, August.
    16. Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Chen, Yan & Song, Dongdong & Zhi, Danyue & Wang, Yiyun & Gao, Ziyou, 2023. "Estimating intercity heavy truck mobility flows using the deep gravity framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    17. Qiao, Yidan & Gao, Xinwei & Ma, Lin & Chen, Dengkai, 2024. "Dynamic human error risk assessment of group decision-making in extreme cooperative scenario," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    18. Feng, Xinhang & Gai, Wenmei, 2026. "Extended reality technology applied to emergency evacuation research, training and on-site guidance: Analysis and future research," Reliability Engineering and System Safety, Elsevier, vol. 268(C).
    19. Podrecca, Matteo & Culot, Giovanna & Tavassoli, Sam & Orzes, Guido, 2024. "Artificial intelligence for climate change: a patent analysis in the manufacturing sector," Papers in Innovation Studies 2024/12, Lund University, CIRCLE - Centre for Innovation Research.
    20. Yujing Chen & Jiao Mo & Bin Yang, 2025. "Freight Rate Decisions in Shipping Logistics Service Supply Chains Considering Blockchain Adoption Risk Preferences," Mathematics, MDPI, vol. 13(15), pages 1-31, July.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:193:y:2025:i:c:s1366554524004526. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.