Knowledge Economy Studies

Identification and Prioritization of Industry 4.0 Technologies in Maritime Industries Using Best-Worst Method (BWM)

Document Type : Original Article

Authors

Hamid Ameri 1
Vahid Ameri 2
Mojtaba Abbaspour 3

1 M.A. in Marine Engineering, Malek Ashtar University of Technology, Shahin Shahr, Iran.

2 M.A. Student in Marketing Management, Faculty of Management and Accounting, Farabi College, Tehran University, Qom, Iran.

3 Assistant Professor, Department of Maritime Economics and Management, Khorramshahr University of Marine Science and Technology, Khorramshahr, Iran

https://doi.org/10.22034/kes.2025.2056235.1049
Abstract
The Fourth Industrial Revolution (Industry 4.0) has provided significant opportunities to improve performance and productivity in maritime industries through emerging technologies. However, the multiplicity and diversity of these technologies have turned their selection and prioritization into a fundamental challenge for decision-makers. This research study aims to identify and prioritize key Industry 4.0 technologies in maritime industries. Through conducting a systematic literature review and interviews with 15 industry experts, 59 applications within 12 key technologies were identified. Then, using the Best-Worst Method (BWM) of multi-criteria decision-making, the relative importance of technologies and their applications were determined. The results showed that Digital Twin Systems with a weight of 20.02 is the most important technology, followed by Robotics and Automation with a weight of 16.11, and Artificial Intelligence (AI) and Machine Learning with a weight of 12.08. Among the applications, operation optimization through scenario testing, autonomous vehicle guidance in port areas, and staff training with virtual models obtained the highest priorities. By providing a systematic framework for technology prioritization, this research can assist decision-makers in maritime industry to allocate optimal resources and reduce investment risks.

Keywords

Artificial Intelligence
Digital Twin Systems
Fourth Industrial Revolution
Maritime Industries
Robotics and Automation

Subjects

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Knowledge Economy Studies
Volume 2, Issue 1
April 2025
Pages 157-174

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