Providing a Model for Port-Hinterland Fright Mode Choice(Case Study: Imam Khomeini Port)

Document Type : Original Article

Authors
Alireza Mahpour 1
Amirhossein Jashnian 2
1 Assistant Professor, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran.
2 M.Sc., Grad., Islamic Azad University, Terhan, Iran.
10.22034/road.2023.379013.2127
Abstract
The design of the transportation network connecting land and sea and the identification of effective factors in this relationship is an important factor in improving the performance of the transportation system. In the meantime, identifying the effective factors in choosing the mode of transportation in the ports is of particular importance. After integrating the data discrete choice model for choosing land and rail transport modes has been produced. The findings show that the tendency to choose the mode of transportation between rail and road was dependent on the distance, the actual weight of the load and the total price of the load, that the distance and the actual weight of the load had a positive effect and the price of the total load had a negative effect on choosing the mode of transportation of grain from Imam Khomeini Port to It had domestic destinations, but for the purpose of data integration, only 22 destinations where the cargo of imported grain was transported by rail mode to the destination railway station were considered for road destinations. The comparison of the share of rail and road in the cargo exchange of these common destinations has shown that the share of rail was 56% and the share of road was 44% of the total exchange of grain, while considering all road destinations, the share of rail transport was 12% and the share of road transport was 88%.
Keywords
Mode Choice
Imam Khomeini Port
Freight Transportation
Grain Transportation
-گسکری، ریحانه و  عیدانی، مصطفی. ‌و اقبالی، علیرضا (1385). برآورد تابع تقاضای حمل‌و‌نقل ریلی در ایران. دو فصلنامه تحقیقات اقتصادی، شماره ۶۹، 48-40.
-صفارزاده، محمود و امینی، امیرعلی. (1385). حمل‌و‌نقل دریایی. جلد اول، چاپ اول. انتشارات اسرار دانش، تهران، ۶۶۴.
-صمیمی، امیر، رحیمی، احسان و امینی، حمیدرضا (1392). تحلیل ناهمفزون رفتار انتخاب وسیله در جابه‌جایی کالا به وسیله کامیون و قطار مطالعه موردی ایران. سیزدهمین کنفرانس بین المللی مهندسی حمل‌و‌نقل و ترافیک، تهران، معاونت و سازمان حمل‌و‌نقل و ترافیک.
- Nugroho, M. T., Whiteing, A., & de Jong, G. (2016). Port and inland mode choice from the exporters' and forwarders' perspectives: Case study Java, Indonesia. Research in Transportation Business & Management. 19, 73-82.
-Asadabadi, A., & Miller-Hooks, E. (2020). Maritime port network resiliency and reliability through co-opetition. Transportation Research Part E: Logistics and Transportation Review, 137, 101916.
-Gatta, V., Marcucci, E. (2016). Behavioural implications of non-linear effects on urban freight transport policies: The case of retailers and transport providers in Rome. Case Stud. Transp. Policy 4 (1), 22–28.
-Larranaga, A.M., Arellana, J., Senna, L.A. (2016). Encouraging intermodality: A stated preference analysis of freight mode choice in Rio Grande do Sul. Transport Res. Part A: Policy Practice.
-Mahpour, A., Amiri, A.M., Deldar, M., Saffarzadeh, M. and Nazifi, A., 2018. A heuristic method to determine traffic bottlenecks based on ant colony: a case study of Iran. Case Studies on Transport Policy, 6(4), pp.716-721.
-Mahpour, A., Asadi, M. and Baghestani, A., 2024. Are supply and demand the main key drivers of airport parking prices? The quantitative study. Journal of Air Transport Management, 114, p.102505.
-Mahpour, A., Farzin, I., Baghestani, A., Ashouri, S., Javadi, Z. and Asgari, L., 2023. Modeling the impact of logistic performance, economic features, and demographic factors of countries on the seaborne trade. The Asian Journal of Shipping and Logistics, 39(2), pp.60-66.
Mahpour, A.R., Amiri, A. and Ebrahimi, E.S., 2019. Do drivers have a good understanding of distraction by wrap advertisements? Investigating the impact of wrap advertisement on distraction-related driver's accidents. Advances in transportation studies, 48.
-Pan, J.-J., Bell, M.G.H., Cheung, K. F., Perera, S., Yu, H. (2019). Connectivity analysis of the global shipping network by eigenvalue decomposition. Marit. Policy Manag. 46, 957–966.
-Ravibabu, M. (2013). A nested logit model of mode choice for inland movement of export shipments: A case study of containerised export cargo from India. Research in Transportation Economics, 38(1), 91–100.
-Reis, V. (2014). Analysis of mode choice variables in short-distance intermodal freight transport using an agent-based model. Transportation Research Part A: Policy and Practice, 61, 100–120.
-Sahebi, S., Mirbaha, B., Mahpour, A. and Noruz Aliaei, M.H., 2015. Predicting pedestrian accidents in rural roads using ordered logit model. Quarterly Journal of Transportation Engineering, 6(3), pp.581-592
-Shen, S., Fowkes, T., Whiteing, T., & Johnson, D. (2009). Econometric modelling and forecasting of freight transport demand in Great Britain. In Proceedings of European Transport Conference, 5-7.
-Talley, W. K., (2013). Maritime transport chain choice by carriers, ports and shippers. International Journal of Production Economics, 142(2), 311–316.
-Tapia, R. J., dos Santos Senna, L. A., Larranaga, A. M., & Cybis, H. B. B. (2019). Joint mode and port choice for soy production in Buenos Aires province, Argentina. Transportation Research Part E: Logistics and Transportation Review, 121, 100-118.
-Tayarani Yousefabadi, A., Mahpour, A., Farzin, I. and Mohammadian Amiri, A., 2021. The Assessment of the Change in the Share of Public Transportation by Applying Transportation Demand Management Policies. AUT Journal of Civil Engineering, 5(2), pp.199-212.
-Viljoen, N.M., Joubert, J.W. )2016 .(The vulnerability of the global container shipping network to targeted link disruption. Phys. A Stat. Mech. its Appl. 462, 396–409.
-Wu, Y., Liu, J., & Peng, C. (2014). Analysis of port and inland transport mode selection. In 2014 11th International Conference on Service Systems and Service Management (ICSSSM),  1-6. IEEE.
-Xing, J., Zhong, M., (2017). A reactive container rerouting model for container flow recovery in a hub-and-spoke liner shipping network. Marit. Policy Manag. 44, 744–760.