Barriers to blockchain adoption in the seaport industry: A fuzzy DEMATEL analysis

Peng Guan, Lincoln C. Wood, Jason X. Wang, Linh N.K. Duong

Research output: Contribution to journalArticlepeer-review

Abstract

Blockchain technology, marked as a disruptive force across various sectors, including seaport logistics, faces challenges and obstacles that impede its effective adoption. We aim to empirically identify the significant barriers impeding blockchain adoption in the seaport industry and elucidate the interconnected relationships between these impediments. Utilizing the Fuzzy DecisionMaking Trial and Evaluation Laboratory Analysis (Fuzzy DEMATEL) technique, we quantify the cause-and-effect relationships between various barriers to blockchain adoption. Structured interviews involving 18 experts were conducted, collecting both qualitative interview data and quantitative data. The nature of ports and the maritime industry did not seem to be accurately reflected in the literature about blockchain adoption, presenting several new findings in this study. Four primary obstacles were identified: 1) Lack of management support and commitment. 2) Issues in supply chain collaboration, communication and coordination. 3) Resistance from and lack of involvement of external stakeholders. 4) The high cost. Furthermore, cost was reaffirmed as a significant factor influencing blockchain adoption. We enhance existing literature by revealing the interdependencies among identified barriers and offers insights for policymakers and industry practitioners. We aim to foster successful blockchain integration in the seaport industry, improving its sustainability performance. During this research, it has been acknowledged by the business sector that the effective employment of business process reengineering (BPR) and the strategic implementation of blockchain technology are crucial strategies to surmount the obstacles that have impeded the extensive integration of blockchain within port operations.

Original languageEnglish
Pages (from-to)20995-21031
Number of pages37
JournalMathematical Biosciences and Engineering
Volume20
Issue number12
Early online date23 Nov 2023
DOIs
Publication statusPublished - 1 Dec 2023

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