Exploring the key enablers of robotic process automation in the maritime industry

Basit Öğe Kaydı
dc.authorid0000-0001-9323-5025
dc.contributor.authorKarakas, Serkan
dc.date.accessioned2026-04-04T18:55:38Z
dc.date.available2026-04-04T18:55:38Z
dc.date.issued2025
dc.departmentİstanbul Bilgi Üniversitesi
dc.description.abstractThe term autonomy in the maritime industry has become increasingly popular thanks to the availability of new technologies, such as artificial intelligence, advanced IoT sensors, and satellite communication systems. However, the widespread adoption of fully autonomous ships requires overcoming serious technological, legal, and social challenges. Implementing robotic process automation (RPA), or software robots, represents a cost-effective and minimally invasive solution and allows automating processes without significant modifications to existing IT infrastructure. However, theoretical research on the enablers of RPA remains limited, particularly concerning its application in commercial vessels. To address this gap, this study adopts the Technology-Organisation-Environment (TOE) framework and employs the fuzzy DEMATEL methodology to identify the critical factors that facilitate the adoption of shipboard RPA. Empirical insights are derived from the involvement of nine highly qualified experts. The findings show that software robots can possess the capability to enhance shipboard processes, providing a viable solution at a time when the widespread use of full automation remains infeasible. Furthermore, our findings provide important insights for policymakers regarding the way software robots can improve the shipboard ecosystem, onboard quality standards, and regulatory compliance with maritime practices. This research contributes by examining both the theoretical and practical dimensions of robotic process automation in shipboard applications-an area that, as said, has received limited scholarly attention.
dc.description.sponsorshipIstanbul Bilgi University
dc.description.sponsorshipThis study was supported by Istanbul Bilgi University. Dr. Karahan Kaya is acknowledged for accepting this work for a first review to improve overall research quality. The author sincerely thanks the editors and reviewers of MEL for the time devoted and their valuable feedback. Constructive comments have been addressed, resulting in improved clarity, accuracy, and overall quality of the manuscript. Appreciation is extended for their guidance and consideration. The data that support the findings of this study are available from the author upon reasonable request.
dc.identifier.doi10.1057/s41278-025-00330-7
dc.identifier.doi10.1057/s41278-025-00330-7
dc.identifier.issn1479-2931
dc.identifier.issn1479-294X
dc.identifier.scopus2-s2.0-105013747850
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1057/s41278-025-00330-7
dc.identifier.urihttps://hdl.handle.net/11411/10502
dc.identifier.wosWOS:001555481700001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPalgrave Macmillan Ltd
dc.relation.ispartofMaritime Economics & Logistics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260402
dc.snmzKA_Scopus_20260402
dc.subjectDigitalisation
dc.subjectFuzzy Dematel
dc.subjectMaritime Industry
dc.subjectRpa
dc.subjectSoftware Robots
dc.subjectToe
dc.titleExploring the key enablers of robotic process automation in the maritime industry
dc.typeArticle

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