Location of Road Freight Transportation Logistics Hubs in Iran: A Network Analysis Approach

Document Type : Research Paper

Authors

1 Departmant of Financial Sciences, Management and Entrepreneurship, University of Kashan, Kashan, Iran

2 Departmant of Financial Sciences, Management and Entrepreneurship, kashan University, kashan, Iran

3 Departmant of Economic, Isfahan (khorasgan) Branch, Islamic Azad University, Isfahan, Iran

Abstract

Objective: The aim of this study is to identify optimal hubs in Iran’s road freight transport network using a network-analysis approach. The research seeks to reveal the actual structure of the country’s freight flows and provide a clustered network pattern by addressing the limitations of traditional hub-location methods, which often ignore both direct and indirect interactions among nodes.
Methods: For the network analysis, freight-flow data among the 31 provinces of Iran for the year 2023 were extracted, and a weighted matrix was constructed based on each province’s share of total outbound cargo. A threshold was then applied to remove low-importance links, and using computational network metrics in Gephi, the network structure, clusters, and selected hubs within each cluster were identified.
Results: The results indicate that Iran’s road transport network consists of four main clusters, each with a distinct freight-flow pattern. Analysis of centrality measures and clustering coefficients showed that Tehran, Hormozgan, Khuzestan, and Khorasan Razavi act as key network hubs, ranking highly in terms of flow intensity, brokerage roles, and network influence.
Conclusion: The findings demonstrate that network analysis provides a structural, flow-based framework for hub location and can compensate for the shortcomings of classical models and expert-judgment-based approaches. Since the identified hubs are located across different geographic clusters, implementing this structure could reduce transportation costs, enhance efficiency, and support logistics development policies.

Keywords

References

References
Attar, A., Irawan, C. A., Akbari, A. A., Zhong, S., & Luis, M. (2024). Multi‑disruption resilient hub location–allocation network design for less‑than‑truckload logistics. Transportation Research Part A: Policy and Practice, 190, 104260. https://doi.org/10.1016/j.tra.2024.104260 
Bai, Z., Wang, H., & Yang, K. (2025). Optimizing metro‑based logistics hub locations for sustainable urban freight distribution. Sustainability, 17(10), 4735. https://doi.org/10.3390/su17104735 
Barabási, A.-L. (2016). Network science. Cambridge University Press. https://doi.org/10.1017/CBO9781107298019
Baruah, P., & Sarma, T. R. (2024). Optimizing dry port locations using hub and spoke network design – A conceptual framework for inland water ports in Assam. Educational Administration: Theory and Practice, 30(1), 3510–3517. https://doi.org/10.53555/kuey.v30i1.7317
Campbell, J. F., & O’Kelly, M. E. (2012). Twenty‑five years of hub location research. Transportation Science, 46(2), 153–169. https://doi.org/10.1287/trsc.1120.0410
Čupić, A., & Teodorović, D. (2014). A multi‑objective approach to the parcel express service delivery problem. Journal of Advanced Transportation, 48(7), 701–720. https://doi.org/10.1002/atr.1218
Deguchi, T., Takahashi, K., Takayasu, H., & Takayasu, M. (2014). Hubs and authorities in the world trade network using a weighted HITS algorithm. PLoS ONE, 9(7), e100338. https://doi.org/10.1371/journal.pone.0100338
Dueñas, M., & Fagiolo, G. (2013). Modeling the international‑trade network: A gravity approach. Journal of Economic Interaction and Coordination, 8(1), 155–178. https://doi.org/10.1007/s11403‑013‑0108-y 
Espejo, I., Marín, A., Muñoz‑Ocaña, J. M., & Rodríguez‑Chía, A. M. (2023). A new formulation and branch‑and‑cut method for single‑allocation hub location problems. Computers & Operations Research, 155, 106241. https://doi.org/10.1016/j.cor.2023.106241
Fabry, J., Zapletal, F., & Machacova, T. (2024). Location selection for logistics centre using PROMETHEE method. Acta Logistica, 11(3), 409–419. https://doi.org/10.22306/al.v11i3.526
Gao, M., & Dong, M. (2013). Analysis of logistics center location‑selecting based on GIS—Take Li County as an example. Advanced Materials Research, 569, 804–807. https://doi.org/10.4028/www.scientific.net/AMR.569.804
Gocer, F., & Sener, N. (2022). Spherical fuzzy extension of AHP‑ARAS methods integrated with modified k‑means clustering for logistics hub location problem. Expert Systems, 39(2), e12886. https://doi.org/10.1111/exsy.12886
Guo, F., Wang, Z., Huang, Z., & Ma, X. (2024). Robust optimization of micro hub network and mixed service strategy for a multidepot location‑routing problem. Computers & Industrial Engineering, 190, 110070. https://doi.org/10.1016/j.cie.2024.110070
Haseli, G., Yazdani, M., Shaayesteh, M. T., & Hajiaghaei‑Keshteli, M. (2025). Logistic hub location problem under fuzzy Extended Z‑numbers to consider the uncertainty and reliable group decision‑making. Applied Soft Computing, 171, 112751. https://doi.org/10.1016/j.asoc.2025.112751
Ishfaq, R., & Sox, C. R. (2011). Hub location–allocation in intermodal logistic networks. European Journal of Operational Research, 210(2), 213–230. https://doi.org/10.1016/j.ejor.2010.09.017  
Jackson, M. O. (2008). Social and economic networks. Princeton University Press. https://doi.org/10.1515/9781400834203
Jane, Kimberly. (2025). Branding Oman's Logistics Hub for the Sustainability-Conscious Global Market: An Entrepreneurial Approach. Industrial Engineering, 190, 110.
Khairunissa, M., & Lee, H. (2022). Hybrid metaheuristic‑based spatial modeling and analysis of logistics distribution center. ISPRS International Journal of Geo‑Information, 11(1), 5. https://doi.org/10.3390/ijgi11010005
Lin, J. R., Yang, T. H., & Chang, Y. C. (2013). A hub location inventory model for bicycle sharing system design: Formulation and solution. Computers & Industrial Engineering, 65(1), 77–86. https://doi.org/10.1016/j.cie.2011.12.006
 Lium, A.-G., Crainic, T. G., & Wallace, S. W. (2009). A study of demand stochasticity in service network design. Transportation Science, 43(2), 144–157. https://doi.org/10.1287/trsc.1090.0265
Lopes, M. C., de Andrade, C. E., de Queiroz, T. A., Resende, M. G. C., & Miyazawa, F. K. (2016). Heuristics for a hub location‑routing problem. Networks, 68(1), 54–90. https://doi.org/10.1002/net.21685
Mata, A. S. D. (2020). Complex networks: A mini‑review. Brazilian Journal of Physics, 50(5), 658–672. https://doi.org/10.1007/s13538-020-00772-9
Naganawa, H., Hirata, E., Firdausiyah, N., & Thompson, R. G. (2024). Logistics hub and route optimization in the Physical Internet paradigm. Logistics, 8(2), 37. https://doi.org/10.3390/logistics8020037
Newman, M. (2010). Networks: An introduction. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199206650.001.0001
O’Kelly, M. E. (1986). The location of interacting hub facilities. Transportation Science, 20(2), 92–106. https://doi.org/10.1287/trsc.20.2.92
O’Kelly, M. E. (1992). A clustering approach to the planar hub location problem. Annals of Operations Research, 40(1), 339–353. https://doi.org/10.1007/BF02060486
Oh, C., Kim, H., & Chun, Y. (2025). An efficient approach for solving hub location problems using network autocorrelation structures. Annals of the American Association of Geographers, 115(6), 1263–1285. https://doi.org/10.1080/24694452.2025.2482105
Rahman, M. A., Basheer, M. A., Khalid, Z., Tahir, M., & Uppal, M. (2025). Logistics hub location optimization: A k-means and p-median model hybrid approach using road network distances. Transportation Research Procedia, 84, 219–226. https://doi.org/10.1016/j.trpro.2025.03.066
Smith, Hussein. (2025). Eco-Entrepreneurial Marketing in Logistics: Oman's Strategy for Branding a Sustainable Logistics Hub, Logistics, 8(2), 35.
Vieira, C. L. D. S., & Luna, M. M. M. (2016). Models and methods for logistics hub location: A review towards transportation networks design. Pesquisa Operacional, 36, 375–397. https://doi.org/10.1590/0101-7438.2016.036.02.0375
Wu, Y., Qureshi, A. G., & Yamada, T. (2022). Adaptive large neighborhood decomposition search algorithm for multi-allocation hub location routing problem. European Journal of Operational Research, 302(3), 1113–1127. https://doi.org/10.1016/j.ejor.2022.02.002
Xie, F., Wang, T., & Xu, H. (2025). Research on the location of cross-border logistics hub for the Belt and Road Initiative. Transportation Research Record: Journal of the Transportation Research Board. https://doi.org/10.1177/03611981251333711
Zabihi, A., & Gharakhani, M. (2018). A literature survey of HUB location problems and methods with emphasis on the marine transportations. Uncertain Supply Chain Management, 6 (1), 91-116. 
Zhang, X., Liu, C., Peng, Y., & Zhou, J. (2025). Two-phase optimization approach to international multimodal hub location: The case of China under the Belt and Road Initiative. International Journal of Systems Science: Operations & Logistics, 12(1), 2474090. https://doi.org/10.1080/23302674.2024.2474090
Zhang, X., Lu, J., & Peng, Y. (2021). Hybrid MCDM model for location of logistics hub: A case in China under the Belt and Road Initiative. IEEE Access, 9, 41227–41245. https://doi.org/10.1109/ACCESS.2021.3065100
 
 
 
 
 
 
 
 
Management Science and Information Technology
Volume 2, Issue 3
September 2025
Pages 269-284

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