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Ilin, Igior
Kersten, Wolfgang
Jahn, Carlos
Weigell, Jürgen
Levina, Anastasia
Kalyazina, Sofia
Year of Publication: 
[Editor:] Jahn, Carlos [Editor:] Kersten, Wolfgang [Editor:] Ringle, Christian M. [Title:] Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 30 [ISBN:] 978-3-7531-2347-9 [Year:] 2020 [Pages:] 383-407
Purpose: The Arctic is of interest for many states and commercial organizations as it has a large undiscovered potential but very challenging climate and logistical conditions. Arctic maritime logistics need significant investments in infrastructure and is supposed to cause a minimal impact on the environment during port operations and cargo transit by creating efficient and safe supply chains. At the same time, ensuring the most efficient, reliable and safe functioning of supply chains is required. Methodology: The methodological basis of the paper is the analysis and structuring of existing publications on Arctic maritime logistics, a systematic review and formulation an applied system of relevant performance indicators related to Arctic supply chains (e.g. ice conditions, vessels and their parameters, the safe operation of floating production facilities and properties of ports). Findings: The result of this paper is a systematic overview of the current state of research on Arctic maritime logistics challenges and the influencing key performance indicators as well as approaches to assess the performance at all stages of the Arctic supply chain to facility and improve Arctic supply chains in the future. Originality: The originality of the study is defined by the scope of the review con-ducted. It is the first comprehensive overview over Arctic supply chains covering all relevant countries from a maritime logistics standpoint. The results of this paper create a solid foundation for further research in the area of developments of Arctic maritime logistics.
Industry 4.0
Supply Chain Management
City Logistics
Maritime Logistics
Data Science
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Conference Paper

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