Selecting the Most Economical Ship Type for the Marine Business Investor: A Hybrid Approach with PSI-PIPRECIA-COCOSO Methods

Authors

DOI:

https://doi.org/10.5281/zenodo.14630805

Abstract

The demand for maritime transportation is rapidly increasing with the increase in trade between countries. Turkey's increasing import and export figures enable the country to buy and send more products. This increase has caused a significant increase in the number of ship purchases by maritime companies operating in Turkey. However, this situation indicates that there are deficiencies in choosing the most appropriate ship type for the investments to be made by ship operator investors. The ship selection process is of critical importance for investors to minimize their costs and increase the profitability of their investments. In this study, a hybrid approach was developed using F.PSI-PIPRECIA-CoCoSo methods in choosing the most economical ship type for maritime companies operating in maritime transportation. The research analyzes this data by collecting data through surveys on different ship types and the criteria effective in their selection. The findings show that criteria such as operating costs, environmental impact, income potential and efficiency are at the forefront among ship types. Within the framework of the findings obtained, ships used for energy purposes were determined as the best ship type to invest in. LPG tankers came in second and oil tankers came in third. As a result, this study presents a methodology that will assist maritime transportation investors in selecting the most economically suitable ship type and shows similarities and differences with studies in literature. The developed hybrid method draws attention with its applicability and effectiveness in decision-making processes and functions as a tool to support investors' strategic decisions.

References

Arıcan, OH, & Kara, EGE (2022). Determination of chemical tanker selection criteria for shipping companies. Mersin University Journal of Maritime and Logistics Research, 4 (2), 209-233. https://doi.org/10.54410/denlojad.1194715

Arıcan, OH, & Kara, EGE (2024). Selection model of chemical tanker ships for cargo types using fuzzy AHP and fuzzy TOPSIS. Regional Studies in Marine Science, 103724. https://doi.org/10.1016/j.rsma.2024.103724

Arıcan, OH (2023). Determination of Deadweight Tonnage Range in Chemical Tankers Based on Time-Term Chartering. International Journal of Management and Administration, 7(14), 195-213. https://doi.org/10.29064/ijma.1320254

Đalić, I., Stević, Ž., Karamasa, C., & Puška, A. (2020). A novel integrated fuzzy PIPRECIA–interval rough SAW model: Green supplier selection. Decision Making: Applications in Management and Engineering, 3(1), 126-145. https://doi.org/10.31181/dmame2003114d

De Assis, GS, Da Silva, RGA, Júnior, ELP, Dos Santos, M., Gomes, CFS, & Da Silva, MPRL (2024, January). Use of the PSI-CoCoSo method in the evaluation of imagers for use in helicopters of the military police of the state of Rio de Janeiro. In 2024 5th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI) (pp. 451-459). IEEE.

De Sousa, FDA, Pereira, EL, Gomes, CFS, dos Santos, M., & da Silva, MPRL (2024, January). Application of the PSI-CoCoSo hybrid method in the choice of light fleet supplier for a logistics distribution center. In 2024 5th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI) (pp. 357-365). IEEE.

Fan, L., & Luo, M. (2013). Analyzing ship investment behavior in liner shipping. Maritime Policy & Management, 40 (6), 511-533. https://doi.org/10.1080/03088839.2013.776183

Grubišić, I., Begović, E., & Krilić, T. (2000). Multi-criteria ship selection procedure. In International Design Conference-Design 2000 (pp. 649-654).

Kana, A.A. (2017). Forecasting design and decision paths in ship design using the ship-centric Markov decision process model. Ocean Engineering, 137, 328-337. https://doi.org/10.1016/j.oceaneng.2017.04.012

Lucas, F.F., dos Santos, M., Gomes, CFS, de Araújo Costa, AP, de Oliveira Braga, G., da Costa, LMA, & de Araújo Costa, V.P. (2024). Valuation of real estate investment trusts using the PSI-CoCoSo multicriteria method. Procedia Computer Science, 242, 881-887. https://doi.org/10.1016/j.procs.2024.08.264

Mahendra, G.S., & Wiradika, INI (2024). System pendukung keputusan pemilihan daya tarik wisata favorit menggunakan PIPRECIA-CoCoSo dengan implementationasi Python. Teknomatika, 14 (01), 1-12. https://doi.org/10.61423/teknomatika.v14i01.630

Marineinsight, (2024). A Guide to Types of Ships. Retrieved from https://www.marineinsight.com/guidelines/a-guide-to-types-of-ships/

Qiao, X., Yang, Y., Pang, K. W., Jin, Y., & Wang, S. (2024). Ship selection and inspection scheduling in inland waterway transport. Mathematics, 12 (15). . https://doi.org/10.3390/math12152327

Popović, M. (2021). An MCDM approach for personnel selection using the CoCoSo method. Journal of Process Management and New Technologies, 9 (3-4), 78-88. https://doi.org/10.5937/jpmnt9-34876

Sener, Z. (2016). Evaluating ship selection criteria for maritime transportation. Journal of Advanced Management Science, 4 (4).

Setiawansyah, S., & Saputra, V. H. (2023). Kombinasi Pembobotan PIPRECIA-S dan Methode SAW dalam Pemilihan Ketua Organisasi Sekolah. Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM), 2(1), 32-40. https://doi.org/10.58602/jima-ilkom.v2i1.16

Sulistiani, H., Palupiningsih, P., Hamidy, F., Sari, P.L., & Khairunnisa, Y. (2023, November). Employee Performance Evaluation Using Multi-Attribute Utility Theory (MAUT) with PIPRECIA-S Weighting: A Case Study in Educational Institution. In 2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS) (pp. 369-373). IEEE.

Xie, X., Xu, D. L., Yang, J. B., Wang, J., Ren, J., & Yu, S. (2008). Ship selection using a multiple-criteria synthesis approach. Journal of Marine Science and Technology, 13, 50-62.

Uluta, A., Balo, F., Sua, L., Karabasevic, D., Stanujkic, D., & Popovic, G. (2021). Selection of insulation materials with PSI-CRITIC based CoCoSo method. Revista de la Construcción, 20 (2). https://doi.org/10.7764/rdlc.20.2.382

Ulutaş, A., Popovic, G., Radanov, P., Stanujkic, D., & Karabasevic, D. (2021). A new hybrid fuzzy PSI-PIPRECIA-CoCoSo MCDM based approach to solving the transportation company selection problem. Technological and Economic Development of Economy, 27 (5), 1227-1249. https://doi.org/10.3846/tede.2021.15058

Yan, R., Wang, S., & Peng, C. (2021). An artificial intelligence model considering data imbalance for ship selection in port state control based on detention probabilities. Journal of Computational Science, 48, 101257. https://doi.org/10.1016/j.jocs.2020.101257

Yan, R., Wang, S., & Peng, C. (2022). Ship selection in port state control: Status and perspectives. Maritime Policy & Management, 49 (4), 600-615. https://doi.org/10.1080/03088839.2021.1889067

Yan, R., Wu, S., Jin, Y., Cao, J., & Wang, S. (2022). Efficient and explainable ship selection planning in port state control. Transportation Research Part C: Emerging Technologies, 145, 103924. https://doi.org/10.1016/j.trc.2022.103924

Zhong-zhen, YANG, & Jun, ZHAO (2013). Ship selection of container transport based on trade goods fluctuation. Journal of Transportation Systems Engineering and Information Technology, 13 (5), 93

Downloads

Published

2024-12-31

How to Cite

Arıcan, O. H. (2024). Selecting the Most Economical Ship Type for the Marine Business Investor: A Hybrid Approach with PSI-PIPRECIA-COCOSO Methods. International Journal of Contemporary Economics and Administrative Sciences, 14(2), 833–853. https://doi.org/10.5281/zenodo.14630805