Risk identification and modeling for blockchain-enabled container shipping

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.

Citation

Nguyen, S., Chen, P.S.-L. and Du, Y. (2021), "Risk identification and modeling for blockchain-enabled container shipping", International Journal of Physical Distribution & Logistics Management, Vol. 51 No. 2, pp. 126-148. https://doi.org/10.1108/IJPDLM-01-2020-0036