Author
Listed:
- Mahmut Mollaoglu
(Department of Maritime Business Administration, Maritime Faculty, Zonguldak Bülent Ecevit University, Zonguldak 67300, Türkiye)
- Bukra Doganer
(Department of Logistics Management, Applied Sciences Faculty, Ankara University, Ankara 06590, Türkiye)
- Hakan Demirel
(Department of Marine Engineering, Maritime Faculty, İstanbul Technical University, Istanbul 34940, Türkiye
Maritime Clean Energy Research Laboratory (MarCERLab), İstanbul Technical University, Istanbul 34940, Türkiye)
- Abit Balin
(School of Transportation and Logistics, Istanbul University, Istanbul 34940, Türkiye)
- Emre Akyuz
(Department of Maritime Transportation and Management Engineering, Istanbul Technical University, Istanbul 34940, Türkiye
Industrial Data Analytics and Decision Support Systems Center, Azerbaijan State University of Economics, Baku 1001, Azerbaijan)
Abstract
The rapid diffusion of industry 4.0 technologies has substantially transformed the maritime transportation sectors by enabling data-driven operations, enhanced connectivity, and more intelligent decision-making processes. Digital technologies such as the Internet of Things (IoT), simulation systems, and advanced data analytics are increasingly reshaping operational structures in maritime logistics, positioning technological transformation as a strategic priority for firms. However, the weighting and prioritization of components emerging with industry 4.0 technologies remain an underexplored area in the literature. The primary motivation of this study is to determine the weights of these industry 4.0 components using the Bayesian Best Worst Method (BWM) and to reveal their corresponding credal ranking levels. In this context, the present study aims to evaluate and prioritize the critical industry 4.0 components influencing technological transformation processes using the Bayesian BWM. Bayesian BWM is preferred over alternative Multi Criteria Decision Making (MCDM) approaches due to its ability to explicitly model uncertainty within a probabilistic framework, generate more consistent weighting results, and flexibly incorporate decision-makers’ judgments. The findings reveal that safety and security (0.2945) constitute the most influential main component, underscoring the necessity of robust digital infrastructures and reliable systems within highly digitalized operational environments. Among the sub-components, data privacy (0.1301) demonstrates the highest global weight, highlighting the growing importance of safeguarding sensitive information in data-intensive digital systems. The results further indicate that autonomous operation and coordination play significant roles in facilitating efficient digital operations, particularly through real-time equipment monitoring and IoT-based operational visibility. Moreover, sustainability (0.1968) emerges as the second most important component, suggesting that organizations increasingly assess technological investments not only in terms of operational efficiency but also with respect to long-term resilience. Within this dimension, continuous training (0.0614) is identified as the most influential component, indicating that the success of digital transformation depends not only on technological infrastructure but also on the development of human capabilities. With the increasing digitalization of the maritime industry, protection against cyber threats has become essential for ensuring operational continuity and safeguarding data integrity. In this regard, adopting proactive cybersecurity strategies and continuously monitoring and updating systems are of critical importance. In the digital transformation of maritime transportation, integrating sustainability considerations is essential to ensure long-term operational efficiency and environmental responsibility. These practical implications are particularly relevant for policymakers, port authorities, and shipping companies seeking to enhance both digital capabilities and sustainable performance.
Suggested Citation
Mahmut Mollaoglu & Bukra Doganer & Hakan Demirel & Abit Balin & Emre Akyuz, 2026.
"Industry 4.0 in the Sustainable Maritime Sector: A Componential Evaluation with Bayesian BWM,"
Sustainability, MDPI, vol. 18(8), pages 1-26, April.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:8:p:4078-:d:1924041
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