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2024 | z. 124 | 109--126
Tytuł artykułu

Assessing the synergetic effect of selecting the optimal structure of a logistics chain

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study tackles a critical challenge in logistics optimization: assessing the economic efficiency not only of individual entities within a logistics chain, but also the synergistic benefits that arise from their collaboration. We achieve this by proposing a methodology that evaluates the economic efficiency of interactions between participants in a logistics chain. This methodology goes beyond individual efficiency and delves into how the overall economic benefit is distributed among key stakeholders. These stakeholders include freight owners, who initiate the delivery process, forwarders who manage and optimize deliveries, carriers who physically transport goods, and freight terminals that facilitate cargo handling and storage. To ensure the methodology’s relevance to contemporary practices, we begin with a comprehensive review of recent advancements in delivery chain optimization research. We propose to measure the synergetic effect by considering delivery demand parameters, such as the weight of the consignment and the distance it needs to travel. To validate our methodology and gain practical insights, we conducted a series of experimental studies specifically tailored to the Kazakhstani transportation market. By analysing the share of the synergistic effect under varying delivery demand parameters, we were able to identify trends and patterns.
Wydawca

Rocznik
Tom
Strony
109--126
Opis fizyczny
Bibliogr. 35 poz.
Twórcy
  • Faculty of Civil Engineering, Cracow University of Technology, Warszawska 24 Street, 31-155 Kraków, Poland, vitalii.naumov@pk.edu.pl
autor
  • Department of Roads and Bridges, Rzeszow University of Technology, Powstańców Warszawy Ave. 12, 35-959 Rzeszów, Poland, i.taran@prz.edu.pl
  • Department of Aviation Transportation and Logistics, Academy of Civil Aviation, Akhmetov 44 Street, 050039 Almaty, Kazakhstan, zarinakonakbai8@gmail.com
Bibliografia
  • 1. Pani A., S. Mishra, P. Sahu. 2022. “Developing multi-vehicle freight trip generation models quantifying the relationship between logistics outsourcing and insourcing decisions”. Transportation Research Part E: Logistics and Transportation Review 159: 102632. DOI: https://doi.org/10.1016/j.tre.2022.102632.
  • 2. Li J., Y. Zheng, B. Dai, J. Yu. 2020. “Implications of matching and pricing strategies for multiple-delivery-points service in a freight O2O platform”. Transportation Research Part E: Logistics and Transportation Review 136: 101871. DOI: https://doi.org/10.1016/j.tre.2020.101871.
  • 3. Nugymanova G., M. Nurgaliyeva, Zh. Zhanbirov, V. Naumov, I. Taran. 2021. “Choosing a servicing company’s strategy while interacting with freight owners at the road transport market”. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 1: 204-210. DOI: https://doi.org/10.33271/nvngu/2021-1/204.
  • 4. Taheri F., A. Taft. 2024. “Reliable scheduling and routing in robust multiple cross-docking networks design”. Engineering Applications of Artificial Intelligence 128: 107466. DOI: https://doi.org/10.1016/j.engappai.2023.107466.
  • 5. Kogler C., P. Rauch. 2023. “Lead time and quality driven transport strategies for the wood supply chain”. Research in Transportation Business & Management 47: 100946. DOI: https://doi.org/10.1016/j.rtbm.2023.100946.
  • 6. Ramazan B., R. Mussaliyeva, Z. Bitileuova, V. Naumov, I. Taran. 2021. “Choosing the logistics chain structure for deliveries of bulk loads: case study of the Republic Kazakhstan”. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 3: 142-147. DOI: https://doi.org/10.33271/nvngu/2021-3/142.
  • 7. Tjandra S., S. Kraus, S. Ishmam, T. Grube, J. Linßen, J. May, D. Stolten. 2024. “Model-based analysis of future global transport demand”. Transportation Research Interdisciplinary Perspectives 23: 101016. DOI: https://doi.org/10.1016/j.trip.2024.101016.
  • 8. Taran I., A. Karsybayeva, V. Naumov, K. Murzabekova, M. Chazhabayeva. 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. DOI: https://doi.org/10.3390/su15054179.
  • 9. Barmuta K., N. Rusakova, A. Malkhasyan. 2022. “Improving the method of analyzing risks of the company’s logistics processes”. Transportation Research Procedia 63: 737-745. DOI: https://doi.org/10.1016/j.trpro.2022.06.069.
  • 10. Geyi D.G., Y. Yusuf, M.S. Menhat, T. Abubakar, N.J. Ogbuke. 2020. “Agile capabilities as necessary conditions for maximising sustainable supply chain performance: An empirical investigation”. International Journal of Production Economics 222: 107501. DOI: https://doi.org/10.1016/j.ijpe.2019.09.022.
  • 11. Suryawanshi P., P. Dutta. 2022. “Optimization models for supply chains under risk, uncertainty, and resilience: A state-of-the-art review and future research directions”. Transportation Research Part E: Logistics and Transportation Review 157: 102553. DOI: https://doi.org/10.1016/j.tre.2021.102553.
  • 12. Chen G., W. Cheung, S.-C. Chu, L. Xu. 2017. “Transshipment hub selection from a shipper’s and freight forwarder’s perspective”. Expert Systems with Applications 83: 396-404. DOI: https://doi.org/10.1016/j.eswa.2017.04.044.
  • 13. Köhler J., C. Brauer. 2023. “Transformation in freight transport: New analysis requirements and potential modelling approaches”. Transportation Research Procedia 72: 4420-4427. DOI: https://doi.org/10.1016/j.trpro.2023.11.303.
  • 14. Yang C., J. Bian, X. Guo, W. Jiang. 2024. “Logistics outsourcing strategy with online freight platforms”. Omega 125: 103042. DOI: https://doi.org/10.1016/j.omega.2024.103042.
  • 15. Bae H.-S. 2019. “The interaction effect of strategic information systems on performance of international freight forwarders: An analysis of gaps in performance”. The Asian Journal of Shipping and Logistics 35(2): 108-117. DOI: https://doi.org/10.1016/j.ajsl.2019.06.003.
  • 16. Wang Y., J. Sarkis. 2021. “Emerging digitalisation technologies in freight transport and logistics: Current trends and future directions”. Transportation Research Part E: Logistics and Transportation Review 148: 102291. DOI: https://doi.org/10.1016/j.tre.2021.102291.
  • 17. Kmiecik M. 2023. “ChatGPT in third-party logistics - The game-changer or a step into the unknown?” Journal of Open Innovation: Technology, Market, and Complexity 9(4): 100174. DOI: https://doi.org/10.1016/j.joitmc.2023.100174.
  • 18. Sharifi E., S.H. Amin, L. Fang. 2024. “Designing a sustainable, resilient, and responsive wheat supply chain under mixed uncertainty: A multi-objective approach”. Journal of Cleaner Production 434: 140076. DOI: https://doi.org/10.1016/j.jclepro.2023.140076.
  • 19. Pamucar D., M. Deveci, I. Gokasar, L. Martínez, M. Köppen. 2022. “Prioritizing transport planning strategies for freight companies towards zero carbon emission using ordinal priority approach”. Computers & Industrial Engineering 169: 108259. DOI: https://doi.org/10.1016/j.cie.2022.108259.
  • 20. Holguín-Veras J., L. Kalahasthi, S. Campbell, C.A. González-Calderón, X. Wang. 2021. “Freight mode choice: Results from a nationwide qualitative and quantitative research effort”. Transportation Research Part A: Policy and Practice 143: 78-120. DOI: https://doi.org/10.1016/j.tra.2020.11.016.
  • 21. You G. 2022. “Sustainable vehicle routing problem on real-time roads: the restrictive inheritance-based heuristic algorithm”. Sustainable Cities and Society 79: 103682. DOI: https://doi.org/10.1016/j.scs.2022.103682.
  • 22. Ma M., F. Zhang, W. Liu, V. Dixit. 2023. “On urban co-modality: Non-cooperative and cooperative games among freight forwarder, carrier and transit operator”. Transportation Research Part C: Emerging Technologies 153: 104234. DOI: https://doi.org/10.1016/j.trc.2023.104234.
  • 23. Cavallaro F., S. Nocera. 2023. “Flexible-route integrated passenger-freight transport in rural areas”. Transportation Research Part A: Policy and Practice 169: 103604. DOI: https://doi.org/10.1016/j.tra.2023.103604.
  • 24. Rześny-Cieplińska J. 2023. “Overview of the practices in the integration of passenger mobility and freight deliveries in urban areas”. Case Studies on Transport Policy 14: 101106. DOI: https://doi.org/10.1016/j.cstp.2023.101106.
  • 25. Ben Rabia M., A. Bellabdaoui. 2023. “Collaborative intuitionistic fuzzy-AHP to evaluate simulation-based analytics for freight transport”. Expert Systems with Applications 225: 120116. DOI: https://doi.org/10.1016/j.eswa.2023.120116.
  • 26. Lim K.G., N. Nomikos, N. Yap. 2019. “Understanding the fundamentals of freight markets volatility”. Transportation Research Part E: Logistics and Transportation Review 130: 1-15. DOI: https://doi.org/10.1016/j.tre.2019.08.003.
  • 27. Comi A., M.M. Schiraldi, B. Buttarazzi. 2018. “Smart urban freight transport: tools for planning and optimising delivery operations”. Simulation Modelling Practice and Theory 88: 48-61. DOI: https://doi.org/10.1016/j.simpat.2018.08.006.
  • 28. Kim H.-C., A. Nicholson, D. Kusumastuti. 2017. “Analysing freight shippers’ mode choice preference heterogeneity using latent class modelling”. Transportation Research Procedia 25: 1109-1125. DOI: https://doi.org/10.1016/j.trpro.2017.05.123.
  • 29. Angelelli E., C. Archetti, L. Peirano. 2020. “A matheuristic for the air transportation freight forwarder service problem”. Computers’ Operations Research 123: 105002. DOI: https://doi.org/10.1016/j.cor.2020.105002.
  • 30. Silva E., A.G. Ramos, A. Moura. 2024. “Pallets delivery: Two matheuristics for combined loading and routing”. Expert Systems with Applications 243: 122893. DOI: https://doi.org/10.1016/j.eswa.2023.122893.
  • 31. Yuan Y., J. Zhou, H. Li, X. Li. 2023. “A two-stage optimization model for road-rail transshipment procurement and truckload synergetic routing”. Advanced Engineering Informatics 56: 101956. DOI: https://doi.org/10.1016/j.aei.2023.101956.
  • 32. Adler N., A. Brudner, S. Proost. 2021. “A review of transport market modeling using game-theoretic principles”. European Journal of Operational Research 291(3): 808-829. DOI: https://doi.org/10.1016/j.ejor.2020.11.020.
  • 33. Feo M., R. Espino, L. García. 2011. “A stated preference analysis of Spanish freight forwarders modal choice on the south-west Europe Motorway of the Sea”. Transport Policy 18(1): 60-67. DOI: https://doi.org/10.1016/j.tranpol.2010.05.009.
  • 34. Naumov V. 2020. “Substantiating the logistics chain structure while servicing the flow of requests for road transport deliveries”. Sustainability 12(4): 1635. DOI: https://doi.org/10.3390/su12041635.
  • 35. GitHub. „Library for simulations of delivery processes”. Available at: https://github.com/naumovvs/delivery-chain-simulation.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-004880d1-2225-4073-b96d-6d6febb13680
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