Assessment Of The Efficiency Of A Freight Forwarding Company When Choosing A Rational Vehicle Model
DOI:
https://doi.org/10.32515/2664-262X.2026.13(44).442-450Keywords:
forwarding services, trucks, interaction, rational modelAbstract
It is necessary to develop a comprehensive approach that will include the collection and analysis of technical and operational characteristics of various car models, calculation of operating costs, formation of a multi-criteria selection model, and assessment of the sensitivity of results to changes in demand parameters.
To improve the efficiency of the TEK operation, it is proposed to consider interaction with a regular carrier who has seven vehicles with different characteristics, as well as customers who submit applications for the delivery of goods in international traffic in the direction of European countries. The TEK operation process will be evaluated by specific profit. The parameters of the outflow on specific profit: the volume of the cargo consignment, the distance of cargo transportation, the interval of receiving the order. According to the results of the regression analysis of the obtained values of the evaluation indicator, linear regression models were built to determine the specific profit of the TEK. The statistical analysis of the parameter values allowed us to establish that the values of the cargo batch volume and the distance of cargo transportation are distributed according to the normal distribution law of random variables, and the interval of receiving the order is distributed according to the exponential distribution law. To achieve maximum measurement accuracy with a minimum number of studies and maintain statistical reliability of the results, a full-factorial experimental design was developed for three input parameters, which consists of eight series of experiments.
It was established that when the values of the cargo consignment volume increase by more than 9.45 tons, the specific profit of the TEK becomes positive for all car models at the maximum level of the transportation distance. And at the maximum volume of the cargo consignment, the specific profit becomes positive at a distance of more than 990 kilometers for all car models. The maximum specific profit of the TEK will be obtained when using the MAN TGM car model - 19.86 UAH/tkm at the maximum values of the cargo consignment volume and the distance of cargo transportation.
References
Список літератури
1. Wu R., Li M. Optimization of shipping freight forwarding services considering consumer rebates under the impact of carbon tax policy. Ocean & Coastal Management. 2024. Vol. 258, Р. 107361. DOI:10.1016/j.ocecoaman.2024.107361
2. Лебідь Є. М. Заходи з оптимізації бізнес-процесів транспортно-експедиторських підприємств при організації міжнародних перевезень різних видів вантажів. Інтелектуальні транспортні технології: тези доповідей 6-ї міжнародної науково-технічної конференції (м. Харків, 24-26 листопада 2025 р.). Харків: УкрДУЗТ, 2025. С. 179–182.
3. Global freight rises but shows signs of weakness in US : веб-сайт. URL: https://www.reuters.com/markets/commodities/global-freight-rises-shows-signs-weakness-us-2024-06-27 (дата звернення: 12.01.2026).
4. Global freight forwarding marketsize & forecasting 2023-2028 : веб-сайт. URL: https://ti-insight.com/wp-content/uploads/2024/07/GFF-Market-Size-Forecasting-2023-2028-WP.pdf (дата звернення: 12.01.2026).
5. Naumov V., Kholeva O. Studying Demand for Freight Forwarding Services in Ukraine on the Base of Logistics Portals Data. Procedia Engineering. 2017. Vol. 187, P. 317-323. DOI:10.1016/j.proeng.2017.04.381
6. Dobrovolskiy O., Dobrovolska A., Kuznetsova E. Management Of Logistics Service Processes In Freight Forwarding Activities. Modern Science. 2025. URL: https://www.researchgate.net/publication/394391860_MANAGEMENT_OF_LOGISTICS_SERVICE_PROCESSES_IN_FREIGHT_FORWARDING_ACTIVITIES (Last accessed: 13.01.2026).
7. Wang L., Wang Y., Li N. A deep reinforcement learning approach for robust dynamic Bayesian network-based systemic risk analysis in freight forwarding. Reliability Engineering & System Safety. 2026.Vol. 271, Р. 112190. DOI:10.1016/j.ress.2026.112190
8. Aulin V., Lyashuk O., Pavlenko O., Velykodnyi D., Hrynkiv A., Lysenko S., Holub D., Vovk Y., Dzyura V., Sokol M. Realization of the logistic approach in theinternational cargo delivery system. Communications - Scientific Letters of the University of Zilina. 2019. Vol. 21(2), P. 3-12.
9. Логістика постачання транспортних і виробничих підприємств, фірм, компаній: навч. посіб. / В. В. Аулін та ін. – Кропивницький: Лисенко В. Ф., 2022. 325 с.
10. Taran I., Karsybayeva A., Naumov V., Murzabekova K., Chazhabayeva M. Fuzzy-logic approach to estimating the fleet efficiency of a road transport company: a case study of agricultural products deliveries in Kazakhstan. Sustainability. 2023. Vol. 15, no. 5, P. 4179. DOI:10.3390/su15054179
11. Medvediev I., Muzylyov D., Montewka J. A model for agribusiness supply chain risk management using fuzzy logic. Case study: Grain route from Ukraine to Poland. Transportation Research Part E: Logistics and Transportation Review. 2024. Vol. 190, P. 103691. DOI:10.1016/j.tre.2024.103691
12. Taran I., Kairatkyzy G., Pavlenko O., Nefyodov V., Muzylyov D. Determining the optimal service area of a logistics center: a quantitative approach. Transport Problems. 2025. Vol. 20(3), P. 5-18. DOI:10.20858/tp.2025.20.3.01
References
1. Wu, R., & Li, M. (2024). Optimization of shipping freight forwarding services considering consumer rebates under the impact of carbon tax policy. Ocean & Coastal Management, 258, 107361. https://doi.org/10.1016/j.ocecoaman.2024.107361
2. Lebid E. M. Measures to optimize business processes of freight forwarding companies when organizing international transportation of various types of cargo. Intelektualʹni transportni tekhnolohiyi: tezy dopovidey 6-yi mizhnarodnoyi naukovo-tekhnichnoyi konferentsiyi (рр. 179-182). Kharkiv: UkrDUZT [in Ukrainian].
3. Global freight rises but shows signs of weakness in US. https://www.reuters.com/markets/commodities/global-freight-rises-shows-signs-weakness-us-2024-06-27
4. Global freight forwarding marketsize & forecasting 2023-2028. https://ti-insight.com/wp-content/uploads/2024/07/GFF-Market-Size-Forecasting-2023-2028-WP.pdf
5. Naumov, V., & Kholeva, O. (2017). Studying Demand for Freight Forwarding Services in Ukraine on the Base of Logistics Portals Data. Procedia Engineering, 187, 317–323. https://doi.org/10.1016/j.proeng.2017.04.381
6. Dobrovolskiy, O., Dobrovolska, A., & Kuznetsova, E. (2025). MANAGEMENT OF LOGISTICS SERVICE PROCESSES IN FREIGHT FORWARDING ACTIVITIES. Modern Science. https://doi.org/10.62204/2336-498x-2025-2-14
7. Wang, L., Wang, Y., & Li, N. (2026). A deep reinforcement learning approach for robust dynamic Bayesian network-based systemic risk analysis in freight forwarding. Reliability Engineering & System Safety, 271, 112190. https://doi.org/10.1016/j.ress.2026.112190
8. Aulin, V., Lyashuk, O., Pavlenko, O., Velykodnyi, D., Hrynkiv, A., Lysenko, S., Holub, D., Vovk, Y., Dzyura, V., & Sokol, M. (2019). Realization of the Logistic Approach in the International Cargo Delivery System. Communications - Scientific letters of the University of Zilina, 21(2), 3–12. https://doi.org/10.26552/com.c.2019.2.3-12
9. Aulin, V. et al. (2022). Logistics of supply of transport and manufacturing enterprises, firms, companies. Kropyvnytskyi: Lysenko V. F. [in Ukrainian].
10. Taran, I., Karsybayeva, A., Naumov, V., Murzabekova, K., & Chazhabayeva, M. (2023). Fuzzy-Logic Approach to Estimating the Fleet Efficiency of a Road Transport Company: A Case Study of Agricultural Products Deliveries in Kazakhstan. Sustainability, 15(5), 4179. https://doi.org/10.3390/su15054179
11. Medvediev, I., Muzylyov, D., & Montewka, J. (2024). A model for agribusiness supply chain risk management using fuzzy logic. Case study: Grain route from Ukraine to Poland. Transportation Research Part E: Logistics and Transportation Review, 190, 103691. https://doi.org/10.1016/j.tre.2024.103691
12. Taran, I., Kairatkyzy, G., Pavlenko, O., Nefyodov, V. & Muzylyov, D. (2025). Determining the optimal service area of a logistics center: a quantitative approach. Transport Problems, 20(3), 5-18. https://doi.org/10.20858/tp.2025.20.3.01
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