Open Access Repository

Risk identification and modeling for blockchain-enabled container shipping systems

Nguyen, S, Chen, PS-L ORCID: 0000-0002-1513-4365 and Du, Y ORCID: 0000-0001-7540-493X 2020 , 'Risk identification and modeling for blockchain-enabled container shipping systems' , International Journal of Physical Distribution and Logistics Management , pp. 1-23 , doi: 10.1108/IJPDLM-01-2020-0036.

Full text not available from this repository.

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 Type: Article
Authors/Creators:Nguyen, S and Chen, PS-L and Du, Y
Keywords: blockchain, container shipping, risk identification, operational risk, directed acyclic graph, network analysis
Journal or Publication Title: International Journal of Physical Distribution and Logistics Management
Publisher: Emerald Publishing Limited
ISSN: 0960-0035
DOI / ID Number: 10.1108/IJPDLM-01-2020-0036
Copyright Information:

Copyright © 2020, Emerald Publishing Limited

Related URLs:
Item Statistics: View statistics for this item

Actions (login required)

Item Control Page Item Control Page
TOP