Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/329703 
Year of Publication: 
2022
Citation: 
[Journal:] Asian Journal of Shipping and Logistics (AJSL) [ISSN:] 2352-4871 [Volume:] 38 [Issue:] 4 [Year:] 2022 [Pages:] 222-233
Publisher: 
Elsevier, Amsterdam
Abstract: 
Seaports are crucial in modern global supply chain networks and systems, exerting a significant impact on the ecological area's economy. Supply chain entities play a substantial integration role, and potential threats at seaports harm chain continuity. This study proposes a rough set-based genetic algorithm, to investigate the central tendency in seaport risk implied by supply chain threats through a questionnaire evaluation. We also employ the risk score to observe the level of clarity in terms of risk probability, showing that the lower the score an attribute obtains, the more likely it is that seaport risk implies supply chain disruption. We deploy 24 risk attributes, which threaten the proposed ten-dimensional factors, based on their risk scores. The results show that the lack of storage risk planning, low punctuality of delivery goods, shortage of port capacity, congestion in waterways, and the lack of distribution risk planning, are the "best five" of the seaport-fulcrum supply chain risk, in the context of Indonesian seaport firms. These identified risk attributes not only assist seaport managers to identify potential risk-associated deficiencies of supply chain disruption but also enhance their ability to determine resilience to manage supply chain problems.
Subjects: 
Central tendency analysis
Genetic algorithm
Risk assessment
Rough set theory
Seaport-fulcrum supply chain risk
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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