A study on interstate freight mode choice between trucks and trains used to transport oil products: a case study of Iraq

• Autorzy: Noor Hussein M. , Asmael Noor M.

Identyfikatory

DOI

10.20858/tp.2023.18.3.03

• Języki publikacji: EN

Abstrakty

EN

Freight mode choice is an important stage in shipping demand modeling. Transporting oil products using trucks between cities has several issues, including increased risk of accidents, higher transportation costs, environmental impact, and traffic congestion. Due to the absence of local studies, in addition to the few global studies that deal with freight mode selection used to transport oil derivatives between cities, the aim of the study is to develop transport mode choice models for trucks and trains transporting oil products between the interstate capital of Baghdad and the government of Basra for export. The revealed preference survey was used for 277 goods transport data collected with the help of personal interviews, questionnaires, and government institutions. The collected data were processed using two statistical approaches: binary logistic regression and Firth logistic regression. The study’s findings assist decision-makers in selecting sustainable modes of transport.

Słowa kluczowe

EN

freight transport; freight mode choice; binary logistic regression; firth logistic regression; complete separation; truck; train; Iraq

PL

transport towarowy; wybór rodzaju transportu towarowego; binarna regresja logistyczna; piąta regresja logistyczna; całkowita separacja; ciężarówka; pociąg; Irak

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Transport Problems
• Rocznik: 2023
• Tom: T. 18, z. 3
• Strony: 29--40
• Opis fizyczny: Bibliogr. 27 poz.

Twórcy

autor

Noor Hussein M.

• Mustansiriyah University, College of Engineering, Highway and Transportation Department; Palastine St. Baghdad, Iraq

• https://orcid.org/0009-0001-1445-5589

autor

Asmael Noor M.

• Mustansiriyah University, College of Engineering, Highway and Transportation Department; Palastine St. Baghdad, Iraq

• https://orcid.org/0000-0002-8871-7983

Bibliografia

• 1. Holguín-Veras, J. & Jaller, M. & Sánchez-Díaz, I. & Wojtowicz, J. & Campbell, S. & Levinson, H. & Tavasszy, L. NCHRP Report 739/NCFRP Report 19: freight trip generation and land use. Washington DC: Transportation Research Board of the National Academies. 2012.
• 2. Wang, Y. & Ding, C. & Liu, C. & Xie, B. An analysis of Interstate freight mode choice between truck and rail: A case study of Maryland, United States. Procedia-Social and Behavioral Sciences. 2013. Vol. 96. P. 1239-1249.
• 3. National Academies of Sciences, Engineering, and Medicine. Impacts of Public Policy on the Freight Transportation System. 2011.
• 4. Gourdin, K. Global logistics management: a competitive advantage for the 21st century. Wiley- Blackwell. 2006.
• 5. Akay, D. Uluslararası lojistikte taşıma modu seçimini etkileyen faktörler Türkiye uygulaması ve bir model önerisi. Master Thesis. Karatay University, Social Science Institute. 2016. [In Turkish: A model suggestı̇ on and applı̇ catı̇ on of Turkey affectı̇ ng models to transportatı̇ on models selectı̇ ons mode ı̇ n ı̇ nternatı̇ onal logı̇ stı̇ cs].
• 6. Gim, T.H.T. & Ko, J. Maximum likelihood and firth logistic regression of the pedestrian route choice. International regional science review. 2017. Vol. 40. No. 6. P. 616-637.
• 7. Samimi, A. & Kawamura, K. & Mohammadian, A. A disaggregate analysis of rail-truck mode choice behaviors for freight shipments. Amirkabir Journal of Civil Engineering. 2011. Vol. 50(3). P. 159-162.
• 8. Liu, H. & Zhang, R. & Jian, W. & Zhang, S. Effects of Distance and Reliability on Value of Time in Intercity Freight Transportation: An Adaptive Experiment in China. Transportation Research Record. 2022. Vol. 2677(2). P. 115-128.
• 9. Tavasszy, L. & van de Kaa, G. & Liu, W. Importance of freight mode choice criteria: An MCDA approach. Journal of Supply Chain Management Science. 2020. Vol. 1. Nos. 1-2. P. 27-44. 10.De Souza, F.L.U. & Larranaga, A.M. & Palma, D. & Pitombo, C.S. Modeling travel mode choice and characterizing freight transport in a Brazilian context. Transportation Letters. 2022. Vol. 14(9). P. 983-996.
• 11.Ansu, V. & Anjaneyulu, M.V.L.R. The optimum strategy for mode choice modelling of interregional fish transport considering shippers’ heterogeneity. Archives of Transport. 2022. Vol. 64(4). P. 7-26.
• 12. Firdausiyah, N. & Chrisdiani, D.P. Freight shipper’s mode choice preference for sustainable inland transportation. In: IOP Conference Series: Earth and Environmental Science. IOP Publishing. 2021. No. 012004.
• 13. Siridhara, S. & Paonoi, W. & Meeyai, S. & Ratanavaraha, V. Container transport mode choice analysis with a binary logit model case study: Northeastern Thailand. Engineering and Applied Science Research. 2019. Vol. 46(3). P. 256-266.
• 14. Field, A. Discovering statistics using SPSS (Third edition). London and New York: Sage. 2009. 274 p.
• 15. Allison, P.D. Convergence failures in logistic regression. In: SAS Global Forum. 2008. 11 p.
• 17. Energy, B.P. Statistical Review of World Energy globally consistent data on world energy markets and authoritative publications in the field of energy. BP Energy Outlook. 2021. Vol. 70. P. 8-20.
• 18. State Oil Marketing Organization. SOMO 2021.
• 19. NOP. 2023. Map of Iraq and surrounding countries with international borders, the national capital Baghdad, governorate capitals, major cities, main roads, railroads, and major airports. Available at: https://www.nationsonline.org/oneworld/map/iraq_map.htm.
• 20. Puan, O.C. & Hassan, Y.A.H. & Mashros, N. & Idham, M.K. & Hassan, N.A. & Warid, M.N.M. & Hainin, M.R. Transportation mode choice binary logit model: A case study for Johor Bahru city. In: IOP conference series: Materials science and engineering. IOP Publishing. 2019. No. 012066.
• 21. Roess, R.P. & McShane, W.R. & Prassas, E.S. Traffic Engineering (3rd edition) Upper Saddle River, N.J: Prentice Hall. 1998.
• 22. Tseng, Y.Y. & Knockaert, J. & Verhoef, E.T. A revealed-preference study of behavioural impacts of real-time traffic information. Transportation Research Part C: Emerging Technologies. 2013. Vol. 30. P. 196-209.
• 23. Koppelman, F.S. & Bhat, C. A self instructing course in mode choice modeling: multinomial and nested logit models. Prepared for U.S. Department of Transportation Federal Transit Administration. 2006.
• 24. Ben-Akiva, M. & Boccara, B. Discrete choice models with latent choice sets. International journal of Research in Marketing. 1995. Vol. 12. No. 1. P. 9-24.
• 25. Ben-Akiva, M. & Bierlaire, M. Discrete choice methods and their applications to short term travel decisions. Handbook of transportation science. 1999. P. 5-33.
• 26. Firth, D. Bias reduction of maximum likelihood estimates. Biometrika. 1995. Vol. 82. No. 3. P. 667-667.
• 27. Heinze, G. & Schemper, M. A solution to the problem of separation in logistic regression. Statistics in medicine. 2002. Vol. 21. No. 16. P. 2409-2419.