Research Article
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Year 2025, Volume: 9 Issue: 2, 230 - 240, 30.06.2025
https://doi.org/10.30939/ijastech..1639635

Abstract

References

  • [1] Bontekoning Y, Priemus H. Breakthrough innovations in in-termodal freight transport. Transportation Planning and Tech-nology. 2004;27(5):335-345. https://doi.org/10.1080/0308106042000273031
  • [2] Lättilä L, Henttu V, Hilmola, O P. Hinterland operations of sea ports do matter: Dry port usage effects on transportation costs and CO2 emissions. Transportation Research Part E: Logistics and Transportation Review. 2013; 55: 23-42. https://doi.org/10.1016/j.tre.2013.03.007
  • [3] Liedtke G, Murillo, D G C. Assessment of policy strategies to develop intermodal services: The case of inland terminals in Germany. Transport Policy. 2012; 24: 168-178. https://doi.org/10.1016/j.tranpol.2012.06.002
  • [4] Behrends S. The modal shift potential of intermodal line-trains rom a haulier's perspective: drivers and barriers in the mode choice rocess. World Review of Intermodal Transportation Research. 2015; 5(4): 369-386. https://doi.org/10.1504/WRITR.2015.076925
  • [5] Cryns, M., van Hassel, E., Vanelslander, T. Stakeholder iden-tification and mapping in peripheral European inland water-way ecosystems. Journal of Shipping and Trade. 2025; 10(1): 11. https://doi.org/10.1186/s41072-025-00201-7
  • [6] Fareed A G, De Felice F, Forcina A, Petrillo A. Role and ap-plications of advanced digital technologies in achieving sus-tainability in multimodal logistics operations: A systematic lit-erature review. Sustainable Futures. 2024; 100278. https://doi.org/10.1016/j.sftr.2024.100278
  • [7] Zečević S, Tadić S, Krstić M. Intermodal transport terminal location selection using a novel hybrid MCDM mod-el. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 2017; 25(06): 853-876. https://doi.org/10.1142/S0218488517500362
  • [8] Uyanik C, Tuzkaya G, Kalender Z T, Oguztimur S. An inte-grated DEMATEL–IF-TOPSIS methodology for logistics cen-ters’ location selection problem: an application for Istanbul Metropolitan area. Transport. 2020; 35(6): 548-556. https://doi.org/10.3846/transport.2020.12210
  • [9] Krstić M, Tadić S, Elia V, Massari S, Farooq, M U. Intermodal terminal subsystem technology selection using integrated fuzzy MCDM model. Sustainability. 2023; 15(4): 3427. https://doi.org/10.3390/su15043427
  • [10] Zadeh L A. Fuzzy sets. Information and control. 1965; 8(3): 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X
  • [11] Atanassov K T. Intuitionistic fuzzy sets, Fuzzy Sets and Sys-tems. 1986; 20 (1): 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3
  • [12] Cuong B C, Kreinovich V. Picture fuzzy sets. Journal of com-puter science and cybernetics. 2014; 30(4): 409-420. https://doi.org/10.15625/1813-9663/30/4/5032
  • [13] Garg H. Some picture fuzzy aggregation operators and their applications to multicriteria decision-making. Arabian Journal for Science and Engineering. 2017; 42(12): 5275-5290. https://doi.org/10.1007/s13369-017-2625-9
  • [14] Chiu R H, Lin L H, Ting S C. Evaluation of green port factors and performance: a fuzzy AHP analysis. Mathematical prob-lems in engineering. 2014; (1): 802976. https://doi.org/10.1155/2014/802976
  • [15] Kine H Z, Gebresenbet G, Tavasszy L, Ljungberg D. Digitali-zation and automation in intermodal freight transport and their potential application for low-income countries. Future Trans-portation. 2022; 2(1): 41-54. https://doi.org/10.3390/futuretransp2010003
  • [16] Muñuzuri J, Onieva L, Cortés P, Guadix J. Using IoT data and applications to improve port-based intermodal supply chains. Computers & Industrial Engineering. 2020; 139: 105668. https://doi.org/10.1016/j.cie.2019.01.042
  • [17] Asborno M I, Hernandez S, Yves M. GIS-based identification and visualization of multimodal freight transportation catch-ment areas. Transportation. 2021; 48(6): 2939-2968. https://doi.org/10.1007/s11116-020-10155-3
  • [18] Medić N, Anišić Z, Lalić B, Marjanović U, Brezocnik M. Hy-brid fuzzy multi-attribute decision making model for evalua-tion of advanced digital technologies in manufacturing: Indus-try 4.0 perspective. Advances in Production Engineering & Management. 2019; 14(4): 483-493. https://doi.org/10.14743/apem2019.4.343
  • [19] Kim J C, Laine T H, Åhlund C. Multimodal interaction sys-tems based on internet of things and augmented reality: A sys-tematic literature review. Applied Sciences. 2021; 11(4): 1738. https://doi.org/10.3390/app11041738
  • [20] Abdelaziz, S., Munawaroh, M. Mitigating Supply Chain Vul-nerabilities: A Bibliometric Analysis of Sustainable Logistics for Resilience and Risk Management with Perspectives on the Automotive Industry. International Journal of Automotive Science and Technology. 2024; 8(4): 544-588. https://doi.org/10.30939/ijastech..1554338

Prioritization of Digital Technology Applications in Intermodal Freight Transport using CRITIC-based Picture Fuzzy TOPSIS Method

Year 2025, Volume: 9 Issue: 2, 230 - 240, 30.06.2025
https://doi.org/10.30939/ijastech..1639635

Abstract

Recent advancements in digitalization have transformed the logistics sector by introducing in-novative solutions that enhance efficiency, sustainability, and decision-making. In intermodal freight transport, the adoption of digital technologies offers significant potential to optimize operations, reduce costs, and improve environmental performance. However, prioritizing these technologies is crucial for ensuring strategic investments and maximizing their impact. This study proposes a hybrid multi-criteria decision-making (MCDM) framework that integrates Cri-teria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) within a Picture Fuzzy environment to evaluate and rank digital technology applications in intermodal freight transport. The findings indicate that “Artificial Intelligence (AI) for Optimization” is the most critical digital technology, followed by “Cloud Computing and Big Data Analytics” and “Internet of Things (IoT) for Asset Tracking”. Additionally, Operational Efficiency and Economic Efficiency emerged as the most influential evaluation criteria for digital adoption. To validate the reliability and consistency of the proposed methodology, a sensitivity analysis was conducted by modifying the weight values of the criteria, with robustness tested across 15 different scenarios. The results provide logistics managers with a structured approach for selecting and implementing the most impactful digital technologies to improve efficiency, cost-effectiveness, and supply chain resilience. Furthermore, the study offers insights for the automotive industry to integrate smart vehicle technologies and AI-driven solutions, increasing connectivity, automation, and sustainability in intermodal logis-tics. Future research can extend this framework by incorporating additional MCDM methods and real-world case studies to further refine digital transformation strategies in freight transport.

References

  • [1] Bontekoning Y, Priemus H. Breakthrough innovations in in-termodal freight transport. Transportation Planning and Tech-nology. 2004;27(5):335-345. https://doi.org/10.1080/0308106042000273031
  • [2] Lättilä L, Henttu V, Hilmola, O P. Hinterland operations of sea ports do matter: Dry port usage effects on transportation costs and CO2 emissions. Transportation Research Part E: Logistics and Transportation Review. 2013; 55: 23-42. https://doi.org/10.1016/j.tre.2013.03.007
  • [3] Liedtke G, Murillo, D G C. Assessment of policy strategies to develop intermodal services: The case of inland terminals in Germany. Transport Policy. 2012; 24: 168-178. https://doi.org/10.1016/j.tranpol.2012.06.002
  • [4] Behrends S. The modal shift potential of intermodal line-trains rom a haulier's perspective: drivers and barriers in the mode choice rocess. World Review of Intermodal Transportation Research. 2015; 5(4): 369-386. https://doi.org/10.1504/WRITR.2015.076925
  • [5] Cryns, M., van Hassel, E., Vanelslander, T. Stakeholder iden-tification and mapping in peripheral European inland water-way ecosystems. Journal of Shipping and Trade. 2025; 10(1): 11. https://doi.org/10.1186/s41072-025-00201-7
  • [6] Fareed A G, De Felice F, Forcina A, Petrillo A. Role and ap-plications of advanced digital technologies in achieving sus-tainability in multimodal logistics operations: A systematic lit-erature review. Sustainable Futures. 2024; 100278. https://doi.org/10.1016/j.sftr.2024.100278
  • [7] Zečević S, Tadić S, Krstić M. Intermodal transport terminal location selection using a novel hybrid MCDM mod-el. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 2017; 25(06): 853-876. https://doi.org/10.1142/S0218488517500362
  • [8] Uyanik C, Tuzkaya G, Kalender Z T, Oguztimur S. An inte-grated DEMATEL–IF-TOPSIS methodology for logistics cen-ters’ location selection problem: an application for Istanbul Metropolitan area. Transport. 2020; 35(6): 548-556. https://doi.org/10.3846/transport.2020.12210
  • [9] Krstić M, Tadić S, Elia V, Massari S, Farooq, M U. Intermodal terminal subsystem technology selection using integrated fuzzy MCDM model. Sustainability. 2023; 15(4): 3427. https://doi.org/10.3390/su15043427
  • [10] Zadeh L A. Fuzzy sets. Information and control. 1965; 8(3): 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X
  • [11] Atanassov K T. Intuitionistic fuzzy sets, Fuzzy Sets and Sys-tems. 1986; 20 (1): 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3
  • [12] Cuong B C, Kreinovich V. Picture fuzzy sets. Journal of com-puter science and cybernetics. 2014; 30(4): 409-420. https://doi.org/10.15625/1813-9663/30/4/5032
  • [13] Garg H. Some picture fuzzy aggregation operators and their applications to multicriteria decision-making. Arabian Journal for Science and Engineering. 2017; 42(12): 5275-5290. https://doi.org/10.1007/s13369-017-2625-9
  • [14] Chiu R H, Lin L H, Ting S C. Evaluation of green port factors and performance: a fuzzy AHP analysis. Mathematical prob-lems in engineering. 2014; (1): 802976. https://doi.org/10.1155/2014/802976
  • [15] Kine H Z, Gebresenbet G, Tavasszy L, Ljungberg D. Digitali-zation and automation in intermodal freight transport and their potential application for low-income countries. Future Trans-portation. 2022; 2(1): 41-54. https://doi.org/10.3390/futuretransp2010003
  • [16] Muñuzuri J, Onieva L, Cortés P, Guadix J. Using IoT data and applications to improve port-based intermodal supply chains. Computers & Industrial Engineering. 2020; 139: 105668. https://doi.org/10.1016/j.cie.2019.01.042
  • [17] Asborno M I, Hernandez S, Yves M. GIS-based identification and visualization of multimodal freight transportation catch-ment areas. Transportation. 2021; 48(6): 2939-2968. https://doi.org/10.1007/s11116-020-10155-3
  • [18] Medić N, Anišić Z, Lalić B, Marjanović U, Brezocnik M. Hy-brid fuzzy multi-attribute decision making model for evalua-tion of advanced digital technologies in manufacturing: Indus-try 4.0 perspective. Advances in Production Engineering & Management. 2019; 14(4): 483-493. https://doi.org/10.14743/apem2019.4.343
  • [19] Kim J C, Laine T H, Åhlund C. Multimodal interaction sys-tems based on internet of things and augmented reality: A sys-tematic literature review. Applied Sciences. 2021; 11(4): 1738. https://doi.org/10.3390/app11041738
  • [20] Abdelaziz, S., Munawaroh, M. Mitigating Supply Chain Vul-nerabilities: A Bibliometric Analysis of Sustainable Logistics for Resilience and Risk Management with Perspectives on the Automotive Industry. International Journal of Automotive Science and Technology. 2024; 8(4): 544-588. https://doi.org/10.30939/ijastech..1554338
There are 20 citations in total.

Details

Primary Language English
Subjects Automotive Engineering (Other)
Journal Section Articles
Authors

Gözde Bakioğlu 0000-0003-3754-2631

Publication Date June 30, 2025
Submission Date February 14, 2025
Acceptance Date May 10, 2025
Published in Issue Year 2025 Volume: 9 Issue: 2

Cite

APA Bakioğlu, G. (2025). Prioritization of Digital Technology Applications in Intermodal Freight Transport using CRITIC-based Picture Fuzzy TOPSIS Method. International Journal of Automotive Science And Technology, 9(2), 230-240. https://doi.org/10.30939/ijastech..1639635
AMA Bakioğlu G. Prioritization of Digital Technology Applications in Intermodal Freight Transport using CRITIC-based Picture Fuzzy TOPSIS Method. IJASTECH. June 2025;9(2):230-240. doi:10.30939/ijastech.1639635
Chicago Bakioğlu, Gözde. “Prioritization of Digital Technology Applications in Intermodal Freight Transport Using CRITIC-Based Picture Fuzzy TOPSIS Method”. International Journal of Automotive Science And Technology 9, no. 2 (June 2025): 230-40. https://doi.org/10.30939/ijastech. 1639635.
EndNote Bakioğlu G (June 1, 2025) Prioritization of Digital Technology Applications in Intermodal Freight Transport using CRITIC-based Picture Fuzzy TOPSIS Method. International Journal of Automotive Science And Technology 9 2 230–240.
IEEE G. Bakioğlu, “Prioritization of Digital Technology Applications in Intermodal Freight Transport using CRITIC-based Picture Fuzzy TOPSIS Method”, IJASTECH, vol. 9, no. 2, pp. 230–240, 2025, doi: 10.30939/ijastech..1639635.
ISNAD Bakioğlu, Gözde. “Prioritization of Digital Technology Applications in Intermodal Freight Transport Using CRITIC-Based Picture Fuzzy TOPSIS Method”. International Journal of Automotive Science And Technology 9/2 (June 2025), 230-240. https://doi.org/10.30939/ijastech. 1639635.
JAMA Bakioğlu G. Prioritization of Digital Technology Applications in Intermodal Freight Transport using CRITIC-based Picture Fuzzy TOPSIS Method. IJASTECH. 2025;9:230–240.
MLA Bakioğlu, Gözde. “Prioritization of Digital Technology Applications in Intermodal Freight Transport Using CRITIC-Based Picture Fuzzy TOPSIS Method”. International Journal of Automotive Science And Technology, vol. 9, no. 2, 2025, pp. 230-4, doi:10.30939/ijastech. 1639635.
Vancouver Bakioğlu G. Prioritization of Digital Technology Applications in Intermodal Freight Transport using CRITIC-based Picture Fuzzy TOPSIS Method. IJASTECH. 2025;9(2):230-4.


International Journal of Automotive Science and Technology (IJASTECH) is published by Society of Automotive Engineers Turkey

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