Otonom deniz araçlarının ticari deniz taşımacılığında kullanımının donatanlar açısından değerlendirilmesi

Öz

Ticari deniz taşımacılığının gelişimine katkı sağlayan teknolojik değişimler işletmelerin maddi unsurlarının yanı sıra rekabet güçlerini de arttırmaktadır. Otonom deniz araçları teknolojisi ise son on yılda hızla gelişmektedir. Ancak, otonom deniz araçlarının ticari deniz taşımacılığı için uygulanabilirliği ve uygulama potansiyeli hala belirgin değildir. Bu araştırmanın temel amacı otonom deniz araçlarının ticari deniz taşımacılığında kullanımına etki eden kriterlerin önem ağırlıklarının donatanların bakış açısıyla değerlendirilmesidir. Bu amaç doğrultusunda otonom deniz araçlarının ticari deniz taşımacılığında kullanımını etkileyen kriterler literatür araştırması ile belirlenmiştir. Otonom deniz araçlarının ticari deniz taşımacılığında kullanımını etkileyen kriterlerin önem ağırlıklarının hesaplanmasında Sezgisel Bulanık SWARA (IF-SWARA) yönteminden yararlanılmıştır. Yapılan uygulamanın sonuçlarına göre otonom deniz araçlarının ticari deniz taşımacılığında kullanımını etkileyen en önemli kriterin 0,1913 önem ağırlığı ile İşletme Maliyetleri (ODA1) olduğu tespit edilmiştir.

Anahtar Kelimeler

• Otonom deniz araçları
• sezgisel bulanık çkkv
• ticari deniz taşımacılığı

Evaluation of the using autonomous marine vehicles in the commercial maritime transportation from the point of view shipowners

Öz

Technological changes contributing to development of the commercial maritime transport both affects the pecuniary elements of the enterprises and enhance the competitiveness. Technology of autonomous marine vehicles have been developing fastly in the last decade. But, the feasibility and application potential of the autonomous marine vehicles for commercial maritime transportation is not still clear. The main purpose of the research is to evaluate the criteria affecting the autonomous marine vehicles for using in the commercial maritime transportation point of view the shipowners. For the purpose, the criteria which affecting the autonomous marine vehicles for using in the commercial maritime transportation are determined with a literature search. Intuitionistic Fuzzy SWARA (IF-SWARA) method is utilized to importance weight of the criteria which affecting the autonomous marine vehicles for using in the commercial maritime transportation. According to the results of the application carried out, it was idetificationed that the most important criterion in regards to importance weight among the criteria which affecting the autonomous marine vehicles for using in the commercial maritime transportation was Operational Costs (ODA1) with 0.1913 importance weight.

Anahtar Kelimeler

• Autonomous marine vehicles
• intuitionistic fuzzy mcdm
• commercial maritime transportation

Kaynakça

1. Ahmed, Y.A., Theotokatos, G., Maslov, I., Wennersberg, L.A.L. & Nesheim, D.A. (2024). Regulatory and legal frameworks recommendations for short sea shipping maritime autonomous surface ships. Marine policy, 166, 1-17.
2. Atanassov, K.T. (1989). More on intuitionistic fuzzy sets. Fuzzy sets and systems, 33(1), 37-45.
3. Burmeister, H.C., Bruhn, W., Rodseth, O.J. & Porathe, T. (2014). Autonomous unmanned merchant vessel and its contribution towards the e-navigation implementation: The MUNIN perspective. International journal of e-navigation and maritime economy, 1, 1-13.
4. Chang, C.H., Lin, C.C., Yang, Z. & Kontovas, C. (2024). Evaluating the social acceptance of autonomous ferries: An observation from passengers’ boarding willingness. Transport policy, 159, 83-94.
5. Dantas, J.L.D. & Theotokatos, G. (2023). A framework for the economic-environmental feasibility assessment of short-sea shipping autonomous vessels. Ocean engineering, 279, 1-20.
6. Escorcia-Gutierrez, J., Gamarra, M., Beleno, K., Soto, C. & Mansour, R.F. (2022). Intelligent deep learning-enabled autonomous small ship detection and classification model. Computers and electrical engineering, 100, 1-13.
7. Fjortoft, K., Parvasi, S.P., Nesheim, D.A., Wennerberg, L.A.L., Morkrid, O.E. & Psaraftis, H.N. (2023). Assessing the resilience of sustainable autonomous shipping: New methodology, challenges, opportunities. Cleaner logistics and supply chain, 9, 1-16.
8. Fonseca, T., Lagdami, K. & Schröder-Hinrichs, J.U. (2021). Assessing innovation in transport: An application of the technology adoption (TechAdo) model to maritime autonomous surface ships (MASS), Transport policy, 114, 182-195.

9. Inkinen, T., Helminen, R. & Saarikoski, J. (2021). Technological trajectories and scenarios in seaport digitalization. Research in transportation business & management, 41, 1-11.
10. Ivanova, A., Butsanets, A., Breskich, V. & Zhilkina, T. (2021). Autonomous shipping Means: the main areas of patenting research and development results. Transportation research procedia, 54, 793-801.
11. Janmethakulwat, A. & Thanasopon, B. (2024). Digital technology adoption and institutionalization in Thai maritime industry: An exploratory study of the Thai shipowners. The Asian journal of shipping and logistics, 40(3), 157-166.
12. Jovanovic, I., Vladimir, N., Percic, M. & Korican, M. (2022). The feasibility of autonomous low-emission ro-ro passenger shipping in the Adriatic Sea. Ocean engineering, 247, 1-12.
13. Karetnikov, V.V., Butsanets, A.A. & Danilov, O.O. (2023). Features of the development of a navigation safety system for unmanned port tugs based on the risk assessment method. Transportation research procedia, 68, 357-362.
14. Kersuliene, V., Zavadskas, E. K. & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of business economics and management, 11(2), 243-258.
15. Kim, M., Joung, T.H., Jeong, B. & Park, H.S. (2020). Autonomous shipping and its impact on regulations, technologies, and industries. Journal of international maritime safety, environmental affairs, and shipping, 4(2), 17-25.
16. Klein, M. & Wojtkiewicz, M.S. (2023). Digitalization of small ports as a step in achieving sustainable goals. Procedia computer science, 225, 3381-3387.
17. Kooij, C., Kana, A.A. & Hekkenberg, R.G. (2021). A task-based analysis of the economic viability of low-manned and unmanned cargo ship concepts. Ocean engineering, 242, 1-11.
18. Kurt, I. & Aymelek, M. (2024). Operational adaptation of ports with maritime autonomous surface ships. Transport policy, 145, 1-10.
19. Li, H. & Yang, Z. (2023). Incorporation of AIS data-based machine learning into unsupervised route planning for maritime autonomous surface ships. Transportation research part e: Logistics and transportation review, 176, 1-32.
20. Liu, C. (2018). Supplier selection evaluation of shipbuilding enterprises based on entropy weight and multi-attribute decision making. Proceedings of the fifth international forum on decision sciences, 255-268.
21. Liu, J., Law, A.W.K. & Duru, O. (2021). Abatement of atmospheric pollutant emissions with autonomous shipping in maritime transportation using bayesian probabilistic forecasting. Atmospheric environment, 261, 1-10.
22. Makkonen, H., Davies, S.N., Saarni, J. & Huikkola, T. (2022). A contextual account of digital servitization through autonomous solutions: Aligning a digital servitization process and a maritime service ecosystem transformation to autonomous shipping. Industrial marketing management, 102, 546-563.
23. Munim, Z.H. (2019). Autonomous ships: a review, innovative applications and future maritime business models. Supply chain forum: An international journal, 20(4), 266–279.
24. Munim, Z.H., Notteboom, T., Haralambides, H. & Schoyen, H. (2025). Key determinants for the commercial feasibility of maritime autonomous surface ships (MASS). Marine policy, 172, 1-13.
25. Munim, Z.H., Saha, R., Schoyen, H., Ng, A.K.Y & Notteboom, T.E. (2022). Autonomous ships for container shipping in the Arctic routes. Journal of marine science and technology, 27, 320-334.
26. MUNIN (2016). About Munin-Maritime Unmanned Navigation through Intelligence in Networks. Erişim: 25 Aralık, 2024, http://www.unmanned-ship.org/munin/ about/.
27. Sar, A.B. (2023). Considerations on assistance and rescue at sea in the light of the increasing autonomy in shipping. Marine policy, 153, 1-11.
28. Shahbakhsh, M., Emad, G.R. & Cahoon, S. (2021). Industrial revolutions and transition of the maritime industry: The case of seafarer’s role in autonomous shipping. The Asian journal of shipping and logistics, 38(1), 10-18.
29. Tijan, E., Jovic, M., Aksentijevic, S. & Pucihar, A. (2021). Digital transformation in the maritime transport sector. Technological forecasting and social change, 170, 1-15.
30. Wu, B., Yip, T.L., Yan, X. & Soares, C.G. (2022). Review of techniques and challenges of human and organizational factors analysis in maritime transportation. Reliability engineering & system safety, 219, 1-12.
31. Xing, W. & Zhu, L. (2023). Exploring legal gaps and barriers to the use of unmanned merchant ships in China. Marine policy, 153, 1-12.
32. Xing, W. (2024). Contemplating maritime autonomous surface ships (MASS) under the international law on ship-source pollution. Marine pollution bulletin, 207, 1-15.
33. Xu, G.L., Wan, S.P. & Xie, X.L. (2015). A selection method based on MAGDM with interval-valued intuitionistic fuzzy sets. Mathematical problems in engineering, 2015, 1-13.
34. Xu, Z. (2007). Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making. Control and decision, 22(2), 215-219.
35. Yalman, S. C., Tıkız, İ., & Bamyacı, M. (2023). Deniz taşımacılığında dönüm noktası: Otonom gemilerin geleceği. Denizcilik araştırmaları dergisi: Amfora, 2(3), 32-39.
36. Zhang, M., Zhang, D., Yao, H. & Zhang, K. (2020). A probabilistic model of human error assessment for autonomous cargo ships focusing on human-autonomy collaboration. Safety science, 130, 1-12.
37. Ziquan, X., Jiaqi, Y., Naseem, M.H., Zuquan, X. & Xueheng, L. (2021). Supplier selection of shipbuilding enterprises based on intuitionistic fuzzy multicriteria decision. Mathematical problems in engineering, 2021, 1-11. Zis, T.P.V., Psaraftis, H.N. & Vilanova, M.R. (2023). Design and application of a key performance indicator (KPI) framework for autonomous shipping in Europe. Maritime transport research, 5, 1-17.