An interval-valued Pythagorean fuzzy set-based multi-criteria decision-making model for evaluating decarbonization criteria in maritime transport

Muhammed Turgut; İpek Gürsoy

doi:10.33714/masteb.1924939

An interval-valued Pythagorean fuzzy set-based multi-criteria decision-making model for evaluating decarbonization criteria in maritime transport

Abstract

Decarbonization in maritime transport has become an increasingly important strategic issue in response to growing environmental pressures, expanding regulatory obligations, and the sector’s need for transformation. This process, however, goes beyond technical innovation or the adoption of alternative fuels alone. It also requires a broader assessment of multiple factors such as infrastructure adequacy, energy management, emissions monitoring, operational feasibility, and institutional preparedness. The aim of this study is to identify the relative importance of the criteria affecting the decarbonization process in maritime transport through the Interval-Valued Pythagorean Fuzzy Analytic Hierarchy Process (IVPF-AHP) method. Based on the evaluations of five experts with relevant field knowledge, a multi criteria decision model was developed and the criteria were analyzed according to their order of priority. The findings show that decision makers assign the greatest importance to low carbon equipment, shore power, emissions measurement and reporting, fleet modernization, and energy monitoring and management systems. By contrast, social responsibility, training and awareness, and regulatory compliance received lower weights. The results indicate that decarbonization in maritime transport cannot be understood simply as a matter of seeking alternative technologies. Rather, it requires a comprehensive transformation approach that brings together feasible technical investments and measurable performance mechanisms. The study is expected to contribute to the literature by offering a holistic prioritization framework that takes uncertainty into account and by providing decision support for sector practitioners.

Keywords

Thanks

The authors would like to thank all individuals and institutions who contributed to the development of this study.

References

Akgül, E. F. (2024). Navigating decarbonization: Examining shipping companies’ fleet modernization strategies worldwide. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 16(1), 1-21. https://doi.org/10.18613/deudfd.1418186
Al Lawati, E. H., Singh, V. V., Pal, A., Gootam, S., Raj, P., & Munaqib, P. (2026). A multi-criteria decision model for enhancing green business and marketing strategies: insights from Pythagorean fuzzy-AHP. Management & Sustainability: An Arab Review, In press. https://doi.org/10.1108/MSAR-01-2025-0025
Atanassov, K. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87-96. https://doi.org/10.1016/S0165-0114(86)80034-3
Ayyildiz, E., & Taskin Gumus, A. (2021). Pythagorean fuzzy AHP based risk assessment methodology for hazardous material transportation: an application in Istanbul. Environmental Science and Pollution Research, 28(27), 35798-35810. https://doi.org/10.1007/s11356-021-13223-y
Balcombe, P., Brierley, J., Lewis, C., Skatvedt, L., Speirs, J., Hawkes, A., & Staffell, I. (2019). How to decarbonise international shipping: Options for fuels, technologies and policies. Energy Conversion and Management, 182, 72-88. https://doi.org/10.1016/j.enconman.2018.12.080
Bilgili, L. (2022). A discussion on alternative fuel criteria for maritime transport. Marine Science and Technology Bulletin, 11(3), 352-360. https://doi.org/10.33714/masteb.1145994
Bulak, M. E., Turan, H., Kozanoğlu, O., Taşkıran, A., Çiftçi, F. S., & Chebli, M. A. (2026). Enabling sustainable and technology‐driven health systems: A fuzzy quality function deployment approach for advancing healthcare 4.0. Sustainable Development, In press. https://doi.org/10.1002/sd.70739
Camargo-Díaz, C. P., Paipa-Sanabria, E., Zapata-Cortes, J. A., Aguirre-Restrepo, Y., & Quiñones-Bolaños, E. E. (2022). A review of economic incentives to promote decarbonization alternatives in maritime and inland waterway transport modes. Sustainability, 14(21), 14405. https://doi.org/10.3390/su142114405

Czermański, E., Pawłowska, B., Oniszczuk-Jastrząbek, A., & Cirella, G. T. (2020). Decarbonization of maritime transport: analysis of external costs. Frontiers in Energy Research, 8, 28. https://doi.org/10.3389/fenrg.2020.00028
Daniel, H., Trovão, J. P. F., & Williams, D. (2022). Shore power as a first step toward shipping decarbonization and related policy impact on a dry bulk cargo carrier. Etransportation, 11, 100150. https://doi.org/10.1016/j.etran.2021.100150
Di Vaio, A., Zaffar, A., Balsalobre-Lorente, D., & Garofalo, A. (2023). Decarbonization technology responsibility to gender equality in the shipping industry: A systematic literature review and new avenues ahead. Journal of Shipping and Trade, 8(1), 9. https://doi.org/10.1186/s41072-023-00140-1
Díaz-Secades, L. A. (2024). Enhancement of maritime sector decarbonization through the integration of fishing vessels into IMO energy efficiency measures. Journal of Marine Science and Engineering, 12(4), 663. https://doi.org/10.3390/jmse12040663
Erdebilli, B., Yilmaz, I., Aksoy, T., Hacıoglu, U., Yüksel, S., Dinçer, H. (2023). An interval-valued pythagorean fuzzy AHP and COPRAS hybrid methods for the supplier selection problem. International Journal of Computational Intelligence Systems, 16(1), 124. https://doi.org/10.1007/s44196-023-00297-4
Erdoğan, N. K., Onay, A., & Karamaşa, Ç. (2019). Measuring the performance of retailer firms listed in BIST under the balanced scorecard perspective by using interval valued Pythagorean Fuzzy AHP based Pythagorean Fuzzy TODIM methodology. Alphanumeric Journal, 7(2), 333-350. https://doi.org/10.17093/alphanumeric.451247
Gökler, S. H. (2025). Enhanced site selection for solar power plants utilizing the geographic information system and pythagorean fuzzy analytical hierarchy process method. Sustainable Energy, Grids and Networks, 44, 101929. https://doi.org/10.1016/j.segan.2025.101929
Grzelakowski, A. S., Herdzik, J., & Skiba, S. (2022). Maritime shipping decarbonization: Roadmap to meet zero-emission target in shipping as a link in the global supply chains. Energies, 15(17), 6150. https://doi.org/10.3390/en15176150
Gupta, S., Singh, R. K., Bag, S., & Mangla, S. K. (2026). Identification and prioritisation of strategies to mitigate the impact of greenwashing on sustainable supply chain management: an empirical research and a case study. International Journal of Logistics Research and Applications, In press. https://doi.org/10.1080/13675567.2026.2613901
Halim, R. A., Kirstein, L., Merk, O., & Martinez, L. M. (2018). Decarbonization pathways for international maritime transport: A model-based policy impact assessment. Sustainability, 10(7), 2243. https://doi.org/10.3390/su10072243
Hessevik, A. (2022). Green shipping networks as drivers of decarbonization in offshore shipping companies. Maritime Transport Research, 3, 100053. https://doi.org/10.1016/j.martra.2022.100053
Ibokette, A. I., Ogundare, T. O., Akindele, J. S., Anyebe, A. P., & Okeke, R. O. (2024). Decarbonization strategies in the US Maritime industry with a focus on overcoming regulatory and operational challenges in implementing zero-emission vessel technologies. International Journal of Innovative Science and Research Technology, 9(11), 131-162. https://doi.org/10.38124/ijisrt/IJISRT24NOV829
Jimenez, J. E. D., Blanco-Davis, E., Portela, R. M. D. L. C., Loughney, S., Wang, J., & Wilson, E. V. (2026). Training and competency gaps for shipping decarbonization in the era of disruptive technology: the case of Panama. Sustainability, 18(2), 958. https://doi.org/10.3390/su18020958
Kanberoğlu, B., Turan, E., & Kökkülünk, G. (2023). Decarbonization of maritime transportation: A case study for Turkish ship fleet. Journal of Marine Science and Application, 22(4), 716-727. https://doi.org/10.1007/s11804-023-00370-6
Kaya, C., Guo, H., Bolat, F., Yang, Z., Mutlu, Y. T., Zhou, D., Zincir B., Demirel H., & Başhan, V. (2026). Ship energy efficiency and maritime decarbonization: A comprehensive review of technologies, regulations and emerging solutions. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 240(2), 215-243. https://doi.org/10.1177/14750902261425082
Laskar, I. I., Dowlatabadi, H., & Giang, A. (2025). Expert assessments of maritime shipping decarbonization pathways by 2030 and 2050. Earth’s Future, 13(4), e2024EF005255. https://doi.org/10.1029/2024EF005255
Lind, M., Lehmacher, W., & Ward, R. (2023). Maritime decarbonization: Practical tools, case studies and decarbonization enablers. Springer. https://doi.org/10.1007/978-3-031-39936-7
Lovričić, L., Skender, H. P., & Zaninović, P. A. (2022). Going green: The effects of decarbonization on container-shipping companies’ competitiveness. In Sustainable logistics (pp. 265-284). Productivity Press.
McKenney, T. A. (2024, August). The impact of maritime decarbonization on ship design: State-of-the-Art Report. In Proceedings of the 15th International Marine Design Conference (IMDC-2024), the Netherlands. p.907. https://doi.org/10.59490/imdc.2024.907
Misran, M. F. R., Roslin, E. N., & Nur, N. M. (2020). AHP-consensus judgement on transitional decision-making: With a discussion on the relation towards open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 6(3), 63. https://doi.org/10.3390/joitmc6030063
Nisiforou, O., Shakou, L. M., Magou, A., & Charalambides, A. G. (2022). A roadmap towards the decarbonization of shipping: A participatory approach in Cyprus. Sustainability, 14(4), 2185. https://doi.org/10.3390/su14042185
Notteboom, T., Pallis, A., & Rodrigue, J. P. (2022). Port economics, management and policy. Routledge.
Özyörük, B., Taşdemir, B. D., Kumcu, S., & Karacaer, B. (2025). Comparative analysis of internal hospital supply chain management performance with PFAHP and PFTOPSIS methods. Journal of the Faculty of Engineering and Architecture of Gazi University, 40(4), 2839-2849. https://10.17341/gazimmfd.1739731
Palaz, H., & Kovancı, A. (2008). Türk deniz kuvvetleri denizaltilarinin seçilimin AHP ile değerlendirilmesi [Evaluate the selection of Turkish navy submarines by using AHP]. Journal of Aeronautics and Space Technologies, 3(3), 53-60.
Psaraftis, H. N. (2019). Decarbonization of maritime transport: to be or not to be?. Maritime Economics & Logistics, 21(3), 353-371. https://doi.org/10.1057/s41278-018-0098-8
Psaraftis, H. N., & Kontsovas, C. A. (2020). Decarbonization of maritime transport: Is there light at the end of the tunnel?. Sustainability, 13(1), 237. https://doi.org/10.3390/su13010237
Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. McGraw-Hill.
Sahin, A. U. (2024). IMO 2023 revised emission reduction strategy and regulatory challenges of maritime decarbonization. European Journal of Commercial Contract Law, 16(1), 25-33. https://doi.org/10.7590/187714624X17132716463900
Sung, I., Zografakis, H., & Nielsen, P. (2022). Multi-lateral ocean voyage optimization for cargo vessels as a decarbonization method. Transportation Research Part D: Transport and Environment, 110, 103407. https://doi.org/10.1016/j.trd.2022.103407
Tan, E. C., Harris, K., Tifft, S. M., Steward, D., Kinchin, C., & Thompson, T. N. (2022). Adoption of biofuels for marine shipping decarbonization: A long‐term price and scalability assessment. Biofuels, Bioproducts and Biorefining, 16(4), 942-961. https://doi.org/10.1002/bbb.2350
Wan, Z., El Makhloufi, A., Chen, Y., & Tang, J. (2018). Decarbonizing the international shipping industry: Solutions and policy recommendations. Marine Pollution Bulletin, 126, 428-435. https://doi.org/10.1016/j.marpolbul.2017.11.064
Wang, J., Lee, K., Fu, X., & Yan, R. (2026). Data-driven decarbonization in the maritime industry: An integrative analytical review. Communications in Transportation Research, 6(1), 9640002. https://doi.org/10.26599/COMMTR.2026.9640002
Xiao, G., Pan, L., & Lai, F. (2025). Application, opportunities, and challenges of digital technologies in the decarbonizing shipping industry: A bibliometric analysis. Frontiers in Marine Science, 12, 1523267. https://doi.org/10.3389/fmars.2025.1523267
Xu, L., & Chen, Y. (2025). Overview of sustainable maritime transport optimization and operations. Sustainability, 17(14), 6460. https://doi.org/10.3390/su17146460
Yager, R. R. (2013). Pythagorean fuzzy subsets. In 2013 joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS) (pp. 57-61). IEEE. https://doi.org/10.1109/IFSA-NAFIPS.2013.6608375
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information Sciences, 8(3), 199-249. https://doi.org/10.1016/0020-0255(75)90036-5
Zanobetti, F., Pio, G., Jafarzadeh, S., Ortiz, M. M., & Cozzani, V. (2023). Decarbonization of maritime transport: Sustainability assessment of alternative power systems. Journal of Cleaner Production, 417, 137989. https://doi.org/10.1016/j.jclepro.2023.137989
Zincir, B., İnal, Ö. B., Dere, Ç., & Deniz, C. (2022). An overview on the readiness level of the Turkish maritime industry for decarbonization in shipping. Marine Science and Technology Bulletin, 11(1), 63-75. https://doi.org/10.33714/masteb.1061972

Details

Primary Language

English

Subjects

Maritime Business Administration, Maritime Transportation and Freight Services

Journal Section

Research Article

Authors

Muhammed Turgut ^*
0000-0002-0868-7041
Türkiye

İpek Gürsoy
0000-0002-6409-7177
Türkiye

Early Pub Date

September 1, 2026

Publication Date

-

Submission Date

April 7, 2026

Acceptance Date

July 28, 2026

Published in Issue

Year 2026 Number: Advanced Online Publication

DOI

https://doi.org/10.33714/masteb.1924939

IZ

https://izlik.org/JA37BS89XS

Cite

RIS / Bibtex

APA

Turgut, M., & Gürsoy, İ. (2026). An interval-valued Pythagorean fuzzy set-based multi-criteria decision-making model for evaluating decarbonization criteria in maritime transport. Marine Science and Technology Bulletin, Advanced Online Publication, 172-185. https://doi.org/10.33714/masteb.1924939

AMA

1.Turgut M, Gürsoy İ. An interval-valued Pythagorean fuzzy set-based multi-criteria decision-making model for evaluating decarbonization criteria in maritime transport. Mar. Sci. Tech. Bull. 2026;(Advanced Online Publication):172-185. doi:10.33714/masteb.1924939

Chicago

Turgut, Muhammed, and İpek Gürsoy. 2026. “An Interval-Valued Pythagorean Fuzzy Set-Based Multi-Criteria Decision-Making Model for Evaluating Decarbonization Criteria in Maritime Transport”. Marine Science and Technology Bulletin, no. Advanced Online Publication: 172-85. https://doi.org/10.33714/masteb.1924939.

EndNote

Turgut M, Gürsoy İ (September 1, 2026) An interval-valued Pythagorean fuzzy set-based multi-criteria decision-making model for evaluating decarbonization criteria in maritime transport. Marine Science and Technology Bulletin Advanced Online Publication 172–185.

IEEE

[1]M. Turgut and İ. Gürsoy, “An interval-valued Pythagorean fuzzy set-based multi-criteria decision-making model for evaluating decarbonization criteria in maritime transport”, Mar. Sci. Tech. Bull., no. Advanced Online Publication, pp. 172–185, Sept. 2026, doi: 10.33714/masteb.1924939.

ISNAD

Turgut, Muhammed - Gürsoy, İpek. “An Interval-Valued Pythagorean Fuzzy Set-Based Multi-Criteria Decision-Making Model for Evaluating Decarbonization Criteria in Maritime Transport”. Marine Science and Technology Bulletin. Advanced Online Publication (September 1, 2026): 172-185. https://doi.org/10.33714/masteb.1924939.

JAMA

1.Turgut M, Gürsoy İ. An interval-valued Pythagorean fuzzy set-based multi-criteria decision-making model for evaluating decarbonization criteria in maritime transport. Mar. Sci. Tech. Bull. 2026;:172–185.

MLA

Turgut, Muhammed, and İpek Gürsoy. “An Interval-Valued Pythagorean Fuzzy Set-Based Multi-Criteria Decision-Making Model for Evaluating Decarbonization Criteria in Maritime Transport”. Marine Science and Technology Bulletin, no. Advanced Online Publication, Sept. 2026, pp. 172-85, doi:10.33714/masteb.1924939.

Vancouver

1.Muhammed Turgut, İpek Gürsoy. An interval-valued Pythagorean fuzzy set-based multi-criteria decision-making model for evaluating decarbonization criteria in maritime transport. Mar. Sci. Tech. Bull. 2026 Sep. 1;(Advanced Online Publication):172-85. doi:10.33714/masteb.1924939