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Risk identification and modeling for blockchain-enabled container shipping systems

Citation

Nguyen, S and Chen, PS-L and Du, Y, Risk identification and modeling for blockchain-enabled container shipping systems, International Journal of Physical Distribution and Logistics Management pp. 1-23. ISSN 0960-0035 (2020) [Refereed Article]

Copyright Statement

Copyright 2020, Emerald Publishing Limited

DOI: doi:10.1108/IJPDLM-01-2020-0036

Abstract

Purpose: Although being considered for adoption by stakeholders in container shipping, application of blockchain is hindered by different factors. This paper investigates the potential operational risks of blockchain-integrated container shipping systems as one of such barriers.

Design/methodology/approach: Literature review is employed as the method of risk identification. Scientific articles, special institutional reports and publications of blockchain solution providers were included in an inclusive qualitative analysis. A directed acyclic graph (DAG) was constructed and analyzed based on network topological metrics.

Findings: Twenty-eight potential risks and 47 connections were identified in three groups of initiative, transitional and sequel. The DAG analysis results reflect a relatively well-connected network of identified hazardous events (HEs), suggesting the pervasiveness of information risks and various multiple-event risk scenarios. The criticality of the connected systems' security and information accuracy are also indicated.

Originality/value: This paper indicates the changes of container shipping operational risk in the process of blockchain integration by using updated data. It creates awareness of the emerging risks, provides their insights and establishes the basis for further research.

Item Details

Item Type:Refereed Article
Keywords:blockchain, container shipping, risk identification, operational risk, directed acyclic graph, network analysis
Research Division:Commerce, Management, Tourism and Services
Research Group:Transportation, logistics and supply chains
Research Field:Maritime transportation and freight services
Objective Division:Transport
Objective Group:Water transport
Objective Field:International sea freight transport (excl. live animals, food products and liquefied gas)
UTAS Author:Nguyen, S (Mr Son Nguyen)
UTAS Author:Chen, PS-L (Associate Professor Peggy Chen)
UTAS Author:Du, Y (Dr Bill Du)
ID Code:140531
Year Published:2020
Web of Science® Times Cited:3
Deposited By:Maritime and Logistics Management
Deposited On:2020-08-25
Last Modified:2020-09-16
Downloads:0

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