IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v230y2016i3p323-333.html
   My bibliography  Save this article

Safety assessment for inland waterway transportation with an extended fuzzy TOPSIS

Author

Listed:
  • Kezhong Liu
  • Jinfen Zhang
  • Xinping Yan
  • Yiliu Liu
  • Di Zhang
  • Weidong Hu

Abstract

Maritime safety has been one of the top concerns for inland waterway transportation, and safety assessment based on historic accident data is one of the most effective ways to evaluate navigation risk and take steps to enhance safety. Maritime safety is usually affected by many cost/benefit indicators, and it can be treated as multi-criteria decision making problem. An extended technique for order preference by similarity to ideal solution is proposed in this article at first. The model not only facilitates the comparison between fuzzy numbers with the same expected value but also makes it possible for the fuzzy number with lower expected value but higher reliability to outperform that with higher expected value but lower reliability. A variance matrix is adapted to measure the degree of uncertainty of an alternative. The proposed method is then applied to an inland waterway transportation safety assessment, which is regarded as a multi-criteria decision making. The results indicate that the safety situation has been improved a lot over the last 21 years with some local fluctuations, and an evident improvement can be seen from the year of 2003. In addition, the extended model is proved to provide more flexibility for the ranking of alternatives with similar expected values.

Suggested Citation

  • Kezhong Liu & Jinfen Zhang & Xinping Yan & Yiliu Liu & Di Zhang & Weidong Hu, 2016. "Safety assessment for inland waterway transportation with an extended fuzzy TOPSIS," Journal of Risk and Reliability, , vol. 230(3), pages 323-333, June.
  • Handle: RePEc:sae:risrel:v:230:y:2016:i:3:p:323-333
    DOI: 10.1177/1748006X16631869
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X16631869
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X16631869?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
    ---><---

    References listed on IDEAS

    as
    1. Cheng, Ching-Hsue & Lin, Yin, 2002. "Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 174-186, October.
    2. Zhang, D. & Yan, X.P. & Yang, Z.L. & Wall, A. & Wang, J., 2013. "Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 93-105.
    Full references (including those not matched with items on IDEAS)

    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. Wu, Bing & Yip, Tsz Leung & Yan, Xinping & Guedes Soares, C., 2022. "Review of techniques and challenges of human and organizational factors analysis in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    2. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.
    3. Di Zhang & Xinping Yan & Zaili Yang & Jin Wang, 2014. "An accident data–based approach for congestion risk assessment of inland waterways: A Yangtze River case," Journal of Risk and Reliability, , vol. 228(2), pages 176-188, April.
    4. Yuan-Wei Du & Wen Zhou, 2019. "DSmT-Based Group DEMATEL Method with Reaching Consensus," Group Decision and Negotiation, Springer, vol. 28(6), pages 1201-1230, December.
    5. Lung-Hsin Lin & Kung-Jeng Wang, 2022. "Talent Retention of New Generations for Sustainable Employment Relationships in Work 4.0 Era—Assessment by Fuzzy Delphi Method," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    6. Büyüközkan, Gülçin & Ruan, Da, 2008. "Evaluation of software development projects using a fuzzy multi-criteria decision approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 77(5), pages 464-475.
    7. Li, Huanhuan & Çelik, Cihad & Bashir, Musa & Zou, Lu & Yang, Zaili, 2024. "Incorporation of a global perspective into data-driven analysis of maritime collision accident risk," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    8. Daniel Reißmann & Daniela Thrän & Alberto Bezama, 2018. "Key Development Factors of Hydrothermal Processes in Germany by 2030: A Fuzzy Logic Analysis," Energies, MDPI, vol. 11(12), pages 1-20, December.
    9. Shin-Liang Chan & Wann-Ming Wey & Pin-Huai Chang, 2014. "Establishing Disaster Resilience Indicators for Tan-sui River Basin in Taiwan," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 115(1), pages 387-418, January.
    10. Shakhawat Chowdhury & Muhammad Al-Zahrani, 2014. "Fuzzy synthetic evaluation of treated wastewater reuse for agriculture," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 16(3), pages 521-538, June.
    11. Wang, Shuaian & Yan, Ran & Qu, Xiaobo, 2019. "Development of a non-parametric classifier: Effective identification, algorithm, and applications in port state control for maritime transportation," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 129-157.
    12. Guizhen Zhang & Vinh V. Thai & Adrian Wing‐Keung Law & Kum Fai Yuen & Hui Shan Loh & Qingji Zhou, 2020. "Quantitative Risk Assessment of Seafarers’ Nonfatal Injuries Due to Occupational Accidents Based on Bayesian Network Modeling," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 8-23, January.
    13. Cai, Mingyou & Zhang, Jinfen & Zhang, Di & Yuan, Xiaoli & Soares, C. Guedes, 2021. "Collision risk analysis on ferry ships in Jiangsu Section of the Yangtze River based on AIS data," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    14. Li, Huanhuan & Ren, Xujie & Yang, Zaili, 2023. "Data-driven Bayesian network for risk analysis of global maritime accidents," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    15. Wang, Likun & Yang, Zaili, 2018. "Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 277-289.
    16. Seng Boon Lim & Jalaluddin Abdul Malek & Md Farabi Yussoff Md Yussoff & Tan Yigitcanlar, 2021. "Understanding and Acceptance of Smart City Policies: Practitioners’ Perspectives on the Malaysian Smart City Framework," Sustainability, MDPI, vol. 13(17), pages 1-31, August.
    17. Fan, Shiqi & Blanco-Davis, Eduardo & Yang, Zaili & Zhang, Jinfen & Yan, Xinping, 2020. "Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    18. Molin Sun & Zhongyi Zheng & Longhui Gang, 2018. "Uncertainty Analysis of the Estimated Risk in Formal Safety Assessment," Sustainability, MDPI, vol. 10(2), pages 1-16, January.
    19. Lu, Cheng & Aritua, Bernard & de Leijer, Harrie & van Liere, Richard & Lee, Paul Tae-Woo, 2023. "Exploring causes of growth in China's inland waterway transport, 1978–2018: Documentary analysis approach," Transport Policy, Elsevier, vol. 136(C), pages 47-58.
    20. Bernetti, Iacopo & Ciampi, Christian & Fagarazzi, Claudio & Sacchelli, Sandro, 2011. "The evaluation of forest crop damages due to climate change. An application of Dempster-Shafer method," Journal of Forest Economics, Elsevier, vol. 17(3), pages 285-297, August.

    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:sae:risrel:v:230:y:2016:i:3:p:323-333. 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: SAGE Publications (email available below). General contact details of provider: .

    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.