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Stakeholder mapping and disruption scenarios with application to resilience of a container port

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  • Almutairi, Ayedh
  • Collier, Zachary A.
  • Hendrickson, Daniel
  • Palma-Oliveira, José M.
  • Polmateer, Thomas L.
  • Lambert, James H.

Abstract

Port infrastructure and port operations are highly impacted by disruptive scenarios that stem from several different types of causes, including adverse weather events, economic crises, traffic congestion, and spikes in demand, among others. Port intermodal transportation systems are characterized by high complexity and uncertainty since they serve and impact multiple groups of stakeholders, including exporters, importers, operators, organizations, port workers, port authorities, residents, and others. The influences of the disruptive scenarios combined with the influences of possible conflicting interests among groups of stakeholders make significant impacts to port operations and planning programs. The innovation of this study is that it integrates two existing approaches to resilience analytics addressing the influences of scenarios and stakeholders to priorities: a stakeholder classification approach called stakeholder mapping, and an approach known as scenario-based preferences modeling. The framework that is developed in this paper finds the joint influences of disruptive scenarios and groups of stakeholders to disrupt the importance ranking of initiatives. The results emphasize that the most disruptive scenario to the multiple groups of stakeholders is s1, Traffic Congestion, the least disruptive scenario is s3, High Operation Cost, and the most robust and highly prioritized initiative is x18, Constructing the CIMT marine terminal.

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  • Almutairi, Ayedh & Collier, Zachary A. & Hendrickson, Daniel & Palma-Oliveira, José M. & Polmateer, Thomas L. & Lambert, James H., 2019. "Stakeholder mapping and disruption scenarios with application to resilience of a container port," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 219-232.
    • Handle: RePEc:eee:reensy:v:182:y:2019:i:c:p:219-232
    DOI: 10.1016/j.ress.2018.10.010
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    References listed on IDEAS

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    13. Jordi Gallego-Ayala & Dinis Juízo, 2014. "Integrating Stakeholders’ Preferences into Water Resources Management Planning in the Incomati River Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 527-540, January.
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    Cited by:

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    2. Al-Mutairi, Ayedh & AlKheder, Sharaf & Alzwayid, Shaikhah & Talib, Dalal & Heji, Mariam Bn & Lambert, James H., 2022. "Scenario-based preferences modeling to investigate port initiatives resilience," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    3. Zhen, Lu & Lin, Shumin & Zhou, Chenhao, 2022. "Green port oriented resilience improvement for traffic-power coupled networks," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    4. Li, Shan & Haralambides, Hercules & Zeng, Qingcheng, 2022. "Economic forces shaping the evolution of integrated port systems - The case of the container port system of China's Pearl River Delta," Research in Transportation Economics, Elsevier, vol. 94(C).
    5. Dui, Hongyan & Zheng, Xiaoqian & Wu, Shaomin, 2021. "Resilience analysis of maritime transportation systems based on importance measures," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    6. Li, Junjun & Yu, Anqi & Xu, Bowei, 2022. "Risk propagation and evolution analysis of multi-level handlings at automated terminals based on double-layer dynamic network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    7. Hossain, Niamat Ullah Ibne & Nur, Farjana & Hosseini, Seyedmohsen & Jaradat, Raed & Marufuzzaman, Mohammad & Puryear, Stephen M., 2019. "A Bayesian network based approach for modeling and assessing resilience: A case study of a full service deep water port," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 378-396.
    8. Hassler, Madison L. & Andrews, Daniel J. & Ezell, Barry C. & Polmateer, Thomas L. & Lambert, James H., 2020. "Multi-perspective scenario-based preferences in enterprise risk analysis of public safety wireless broadband network," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    9. Panahi, Roozbeh & Ng, Adolf K.Y. & Pang, Jiayi, 2020. "Climate change adaptation in the port industry: A complex of lingering research gaps and uncertainties," Transport Policy, Elsevier, vol. 95(C), pages 10-29.
    10. HOSSAIN, Niamat Ullah Ibne & Amrani, Safae El & Jaradat, Raed & Marufuzzaman, Mohammad & Buchanan, Randy & Rinaudo, Christina & Hamilton, Michael, 2020. "Modeling and assessing interdependencies between critical infrastructures using Bayesian network: A case study of inland waterway port and surrounding supply chain network," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    11. Park, Jaehun & Lee, Byung Kwon, 2020. "Liner-dedicated manageability estimation for port operational reliability," Reliability Engineering and System Safety, Elsevier, vol. 198(C).

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