Choosing a servicing company’s strategy while interacting with freight owners at the road transport market
- Details
- Parent Category: 2021
- Category: Content №1 2021
- Created on 05 March 2021
- Last Updated on 05 March 2021
- Published on 30 November -0001
- Written by G.Nugymanova, M.Nurgaliyeva, Zh.Zhanbirov, V.Naumov, I.Taran
- Hits: 3455
Authors:
G.Nugymanova, orcid.org/0000-0001-6035-9590, Kazakh Academy of Transport and Communications, Almaty, Republic ofKazakhstan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
M.Nurgaliyeva, orcid.org/0000-0003-1860-5211, Kazakh Automobile and Road L.Goncharov Academy, Almaty, Republic ofKazakhstan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Zh.Zhanbirov, orcid.org/0000-0002-6444-0836, Central Asian University, Almaty, Republic ofKazakhstan, , e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
V.Naumov, orcid.org/0000-0001-9981-4108, Cracow University of Technology, Krakow, Poland, This email address is being protected from spambots. You need JavaScript enabled to view it.
I.Taran, orcid.org/0000-0002-3679-2519, Dnipro University of Technology, Dnipro, Ukraine, email: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2021, (1): 204 - 210
https://doi.org/10.33271/nvngu/2021-1/204
Abstract:
Purpose. To develop the methodology for choosing the strategies of freight forwarding companies in the situation of interaction with freight owners as customers of forwarding services.
Methodology. The game-theoretical approach is used to formalize the conflict situation between a freight forwarding company and a cargo owner. A set of services proposed by forwarders is used as the base in order to represent possible strategies of a forwarder as the vector of probabilities that the respective services are provided for a client. The strategies of the cargo owner are represented as a binary variable that shows whether the client uses the provided services or not. The payoff function for a forwarder is defined as the companys profit and the clients payoff function as fee paid for forwarding services. To determine the influence of the demand parameters on the forwarders optimal strategies, the demand for transport services is represented as a flow of requests characterized by two numeric parameters delivery distance and consignment weight.
Findings. The conducted experimental studies have shown that as a result of the use of the proposed methodology, the optimal strategy of a forwarding company can always be determined from the payoff matrix. The performed simulation experiment allowed us to state that in most cases the forwarders optimal strategy is mixed (the technological and commercial services should be provided with the given probability while servicing the flow of requests from freight owners).
Originality. The studies on the influence of the request flow parameters on the probabilities of choosing the elementary strategies are carried in the paper for the first time.
Practical value. The proposed methodology can be used as the basic tool for supporting decisions of freight forwarders while servicing the cargo owners at the market of road freight transportation.
Keywords: freight forwarding, game-theoretical approach, transport demand parameters, flow of requests
References.
1. Sabraliev, N., Abzhapbarova, A., Nugymanova, G., Taran,I., & Zhanbirov, Zh. (2019). Modern aspects of modeling of transport routes in Kazakhstan. News of the National Academy of sciences of the Republic Kazahstan, 2(434), 62-68. https://doi.org/10.32014/2019.2518-170X.39.
2. Sadkowski, A., Utegenova, A., Kolga, A.D., Gavrishev,S.E., Stolpovskikh, I., & Taran, I. (2019). Improving the efficiency of using dump trucks under conditions of career at open mining works. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (2), 36-42. https://doi.org/10.29202/nvngu/2019-2/8.
3. Ghannadpour, S.F., & Zandiyeh, F. (2020). A new game-theoretical multi-objective evolutionary approach for cash-in-transit vehicle routing problem with time windows (A Real-life Case). Applied Soft Computing Journal, (93), 106378. https://doi.org/10.1016/j.asoc.2020.106378.
4. Eren Akyol, D., & de Koster, R.B.M. (2018). Determining time windows in urban freight transport: A city cooperative approach. Transportation Research Part E: Logistics and Transportation Review, (118), 34-50. https://doi.org/10.1016/j.tre.2018.07.004.
5. Guo, J., Xie, Z., & Li, Q. (2020). Stackelberg Game Model of Railway Freight Pricing Based on Option Theory. Discrete Dynamics in Nature and Society, (2020), 6436729. https://doi.org/10.1155/2020/6436729.
6. Naumov, V., & Kholeva, O. (2017). Forming the strategies of sustainable development of freight forwarders at transportation market. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (3), 129-134.
7. Reis, V. (2019). A disaggregated freight transport market model based on agents and fuzzy logic. Transportmetrica B, 7(1), 363-385. https://doi.org/10.1080/21680566.2017.1421108.
8. Kellner, F., & Schneiderbauer, M. (2019). Further insights into the allocation of greenhouse gas emissions to shipments in road freight transportation: The pollution routing game. European Journal of Operational Research, 278(1), 296-313. https://doi.org/10.1016/j.ejor.2019.04.007.
9. Asadabadi, A., & Miller-Hooks, E. (2018). Co-opetition in enhancing global port network resiliency: A multi-leader, common-follower game theoretic approach. Transportation Research Part B: Methodological, (108), 281-298. https://doi.org/10.1016/j.trb.2018.01.004.
10. Algaba, E., Fragnelli, V., Llorca, N., & Snchez-Soriano,J. (2019). Horizontal cooperation in a multimodal public transport system: The profit allocation problem. European Journal of Operational Research, 275(2), 659-665. https://doi.org/10.1016/j.ejor.2018.11.050.
11. Luo, J., Kuang, H., Feng, T., & Song, D. (2019). Research on the co-opetition between high speed rail and civil aviation based on two stage game model. System Engineering Theory and Practice, 39(1), 150-164. https://doi.org/10.12011/1000-6788-2018-0154-15.
12. Liu, D., Yan, P., Deng, Z., Wang, Y., & Kaisar, E.I. (2020). Collaborative intermodal freight transport network design and vehicle arrangement with applications in the oil and gas drilling equipment industry. Transportmetrica A: Transport Science, 16(3), 1574-1603. https://doi.org/10.1080/23249935.2020.1758235.
13. Chen, H., Lam, J.S.L., & Liu, N. (2018). Strategic investment in enhancing port-hinterland container transportation network resilience: A network game theory approach. Transportation Research Part B: Methodological, (111), 83-112. https://doi.org/10.1016/j.trb.2018.03.004.
14. Naumov, V. (2012). Definition of the optimal strategies of transportation market participators. Transport Problems, 7(1), 43-52.
15. Dimitriou, L. (2021). Optimal competitive pricing in European port container terminals: A game-theoretical framework. Transportation Research Interdisciplinary Perspectives, (9), 100287. https://doi.org/10.1016/j.trip.2020.100287.
16. Zhang, L., Long, R., Huang, Z., Li, W., & Wei, J. (2020). Evolutionary game analysis on the implementation of subsidy policy for sustainable transportation development. Journal of Cleaner Production, (267), 122159. https://doi.org/10.1016/j.jclepro.2020.122159.
17. Miguel, F., Frutos, M., Tohme, F., & Babey, M.M. (2020). A decision support tool for urban freight transport planning based on a multi-objective evolutionary algorithm. IEEE Access, (7), 156707-156721. https://doi.org/10.1109/ACCESS.2019.2949948.
18. Yi, Z., Xiang, C., Li, L., & Jiang, H. (2020). Evolutionary game analysis and simulation with system dynamics for behavioral strategies of participants in crowd logistics. Transportation Letters, 1-15. https://doi.org/10.1080/19427867.2020.1783609.
19. Shankar, R., Choudhary, D., & Jharkharia, S. (2018). An integrated risk assessment model: A case of sustainable freight transportation systems. Transportation Research Part D: Transport and Environment, (63), 662-676. https://doi.org/10.1016/j.trd.2018.07.003.
20. Owen, G. (2013). Game Theory. Emerald Group Publishing, ISBN Print: 9781781905074, ISBN Electronic: 9781781905081.
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