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Operational risk identification of maritime surface autonomous ship: A network analysis approach

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  • Li, Xue
  • Oh, Poong
  • Zhou, Yusheng
  • Yuen, Kum Fai

Abstract

Maritime autonomous surface ships (MASS) have gained increasing attention from both academia and industry. The safety of MASS is a critical concern of maritime stakeholders. Accordingly, the identification and understanding of related risks have become important for the improvement of their autonomy levels and safe operations. With this perspective, this research aims to identify potential operational risks of MASS and examine their intertwined causal relationships using network modeling. A directed network is established based on the identity that shoulders a specific operational function and causal relationships drawing from academic and gray literature. The single-risk and multiple-risk identification are realized via network modeling. Moreover, network metrics, including the density, betweenness centrality, and reachability, are measured, and the community structure among potential risks is examined. This research contributes to the existing literature by providing an integrative approach to operational risk analysis and an improved understanding of the potential risks in MASS operations. The results shed light on the architecture of potential operational risks, providing managerial implications for MASS risk control and safe operations.

Suggested Citation

  • Li, Xue & Oh, Poong & Zhou, Yusheng & Yuen, Kum Fai, 2023. "Operational risk identification of maritime surface autonomous ship: A network analysis approach," Transport Policy, Elsevier, vol. 130(C), pages 1-14.
    • Handle: RePEc:eee:trapol:v:130:y:2023:i:c:p:1-14
    DOI: 10.1016/j.tranpol.2022.10.012
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    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Hadi Ghaderi, 2019. "Autonomous technologies in short sea shipping: trends, feasibility and implications," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 152-173, January.
    3. Wróbel, Krzysztof & Montewka, Jakub & Kujala, Pentti, 2018. "Towards the development of a system-theoretic model for safety assessment of autonomous merchant vessels," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 209-224.
    4. Fang, Chao & Marle, Franck & Zio, Enrico & Bocquet, Jean-Claude, 2012. "Network theory-based analysis of risk interactions in large engineering projects," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 1-10.
    5. Utne, Ingrid Bouwer & Rokseth, Børge & Sørensen, Asgeir J. & Vinnem, Jan Erik, 2020. "Towards supervisory risk control of autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    6. de Vos, Jiri & Hekkenberg, Robert G. & Valdez Banda, Osiris A., 2021. "The Impact of Autonomous Ships on Safety at Sea – A Statistical Analysis," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    7. Eriksen, Stig & Utne, Ingrid Bouwer & Lützen, Marie, 2021. "An RCM approach for assessing reliability challenges and maintenance needs of unmanned cargo ships," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    8. Shuyi Pu & Jasmine Siu Lee Lam, 2021. "Blockchain adoptions in the maritime industry: a conceptual framework," Maritime Policy & Management, Taylor & Francis Journals, vol. 48(6), pages 777-794, August.
    9. Valdez Banda, Osiris A. & Kannos, Sirpa & Goerlandt, Floris & van Gelder, Pieter H.A.J.M. & Bergström, Martin & Kujala, Pentti, 2019. "A systemic hazard analysis and management process for the concept design phase of an autonomous vessel," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    10. Chang, Chia-Hsun & Kontovas, Christos & Yu, Qing & Yang, Zaili, 2021. "Risk assessment of the operations of maritime autonomous surface ships," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    11. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
    12. Thieme, Christoph A. & Mosleh, Ali & Utne, Ingrid B. & Hegde, Jeevith, 2020. "Incorporating software failure in risk analysis––Part 2: Risk modeling process and case study," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
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