Transactions on Transport Sciences 2024, 15(1):17-27 | DOI: 10.5507/tots.2023.019

Transportation Mode Choice Behavior with Multinomial Logit Model: Work and School Trips

Yeshitila Denekea, Robel Destab*, Anteneh Afeworkb, János Tóthb
a. Department of Civil Engineering, Institute of Technology, Hawassa University. P.O.Box: 05, Hawassa, Ethiopia.
b. Department of Transport Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Muegyetem rkp. 3, H-1111 Budapest, Hungary.

This paper focuses on modeling transportation mode choice for commuting to work and school. The study employs a Multinomial Logit (MNL) model to examine how individuals choose their modes of transportation for work and school trips in Hawassa city. Additionally, the study aims to predict both the current and future distribution of transportation modes. To construct the model, surveys were distributed across the city's seven sub-cities, involving inspections of workplace and school travel. Primary data were collected through site visits to key transportation hubs, and travel cost data were obtained from the city's Road and Transportation Bureau. The data used for the MNL model describe the travel behaviors of employees and students, and these behaviors are integrated into the statistical analysis to formulate utility functions. The choice of transportation mode for a trip is treated as the dependent variable, while independent variables include factors like out-of-vehicle travel time, in-vehicle travel time, and travel cost. The model's validity and accuracy were assessed by examining the direction of parameter signs and comparing them to the fundamental properties of the MNL model. The study revealed that factors such as average monthly income, in-vehicle travel time, out-of-vehicle travel time, total travel cost, and comfort during the journey significantly influence individuals' choices of transportation modes. The results from the travel behavior forecast, which examines how employees choose their transportation modes, highlight the pressing need for implementing effective policy measures to incentivize the adoption of more sustainable transportation modes and promote a modal shift. Without such measures, employees are likely to increasingly favor motorcycles as their preferred mode of transportation, potentially exacerbating issues related to fuel consumption and congestion. It's evident that students tend to favor public transportation over motorcycles when selecting their mode of travel. The findings of this study offer valuable insights to decision-makers and transportation planners, shedding light on the critical factors influencing travel patterns, as well as providing estimates of existing and future market shares. These findings can serve as a foundation for crafting targeted policy adjustments to encourage sustainable transportation choices in a comprehensive manner.

Keywords: Mode choice; multinomial logit model; travel behaviour; utility function; work and school trips

Received: August 24, 2023; Revised: October 1, 2023; Accepted: October 4, 2023; Prepublished online: December 6, 2023; Published: April 1, 2024  Show citation

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Deneke, Y., Desta, R., Afework, A., & Tóth, J. (2024). Transportation Mode Choice Behavior with Multinomial Logit Model: Work and School Trips. Transactions on Transport Sciences15(1), 17-27. doi: 10.5507/tots.2023.019
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References

  1. Ahmed, B. (2012). The traditional four steps transportation modeling using a simplified transport network: A case study of Dhaka City, Bangladesh. International Journal of Advanced Scientific Engineering and Technological Research, 1(1), 19-40. Go to original source...
  2. Aibinu, A. A., & Jagboro, G. O. (2002). The effects of construction delays on project delivery in Nigerian construction industry. International journal of project management, 20(8), 593-599. Go to original source...
  3. Ali, N. F. M., Sadullah, A. F. M., Majeed, A. P., Razman, M. A. M., Zakaria, M. A., & Nasir, A. F. A. (2021). Travel Mode Choice Modeling: Predictive Efficacy between Machine Learning Models and Discrete Choice Model. The Open Transportation Journal, 15(1). Go to original source...
  4. Al-Salih, W. Q., & Esztergár-Kiss, D. (2021). Linking mode choice with travel behavior by using logit model based on utility function. Sustainability, 13(8), 4332. Go to original source...
  5. Ben-Akiva, M. E., & Lerman, S. R. (1985). Discrete choice analysis: theory and application to travel demand, 9.
  6. Bull, A., & CEPAL, N. (2003). Traffic Congestion: The Problem and how to Deal with it. ECLAC.
  7. Carriel, V., Lufin, M., & Pérez-Trujillo, M. (2022). Do workers negative self-select when they commute? Evidence for the Chilean case of long-distance commuting. The Annals of regional science, 69(1), 255-279. Go to original source...
  8. Cendales, B., Llamazares, F. J., & Useche, S. A. (2023). Are subjective outcomes a "missing link" between driving stress and risky driving behaviors of commuters? Assessing the case of a LMIC. Safety Science, 158, 105996. Go to original source...
  9. Chavis, C., & Gayah, V. V. (2017). Development of a mode choice model for general purpose flexible-route transit systems. Transportation Research Record, 2650(1), 133-141. Go to original source...
  10. Cheng, L., Chen, X., De Vos, J., Lai, X., & Witlox, F. (2019). Applying a random forest method approach to model travel mode choice behavior. Travel behaviour and society, 14, 1-10. Go to original source...
  11. De Vos, J., Singleton, P. A., & Gärling, T. (2022). From attitude to satisfaction: introducing the travel mode choice cycle. Transport Reviews, 42(2), 204-221. Go to original source...
  12. Domencich, T. A., & McFadden, D. (1975). Urban travel demand-a behavioral analysis (No. Monograph).
  13. Eom, J. K., Lee, K. S., Ko, S., & Lee, J. (2022). Exploring Travel Mode Preference of External Trips for Smart City Transportation Planning: Sejong, Korea. Sustainability, 14(2), 630. Go to original source...
  14. Essam, A., & Sadi, A. (2013). Factors affecting mode choice of work trips in developing cities-Gaza as a case study. Journal of Transportation Technologies, 2013.
  15. Gebre, G., & Quezon, E. T. (2021). Modeling public transport users' trip production in Hawassa city, Ethiopia. Journal of Civil Engineering, Science and Technology, 12(2), 75-90. Go to original source...
  16. Harbering, M., & Schlüter, J. (2020). Determinants of transport mode choice in metropolitan areas the case of the metropolitan area of the Valley of Mexico. Journal of Transport Geography, 87, 102766. Go to original source...
  17. Hasnine, M. S., & Nurul Habib, K. (2021). Tour-based mode choice modelling as the core of an activity-based travel demand modelling framework: a review of state-of-the-art. Transport Reviews, 41(1), 5-26. Go to original source...
  18. Hensher, D. A., & Johnson, L. W. (2018). Applied discrete-choice modelling. Routledge.
  19. Khan, O. A., Kruger, J., & Trivedi, T. (2007). Developing passenger mode choice models for Brisbane to reflect observed travel behaviour from the South East Queensland Travel Survey. In 30th Australasian Transport Research Forum.
  20. Koppelman, F. S., & Bhat, C. (2006). A self instructing course in mode choice modeling: multinomial and nested logit models.
  21. Lewis, F., Butler, A., & Gilbert, L. (2011). A unified approach to model selection using the likelihood ratio test. Methods in ecology and evolution, 2(2), 155-162. Go to original source...
  22. Lim, E. C., & Alum, J. (1995). Construction productivity: issues encountered by contractors in Singapore. International journal of project management, 13(1), 51-58. Go to original source...
  23. Limtanakool, N., Dijst, M., & Schwanen, T. (2006). The influence of socioeconomic characteristics, land use and travel time considerations on mode choice for medium-and longer-distance trips. Journal of transport geography, 14(5), 327-341. Go to original source...
  24. Mayo, F. L., Maglasang, R. S., Moridpour, S., & Taboada, E. B. (2022). Impact of transport policies to commuter safety in urban cities of a developing country: A sustainability and system perspective. Case studies on transport policy, 10(4), 2138-2152. Go to original source...
  25. Mengistu, E.H. & Teklu, B. (2015). Logit model for school and work trip mode choice on railway route corridor. MSc thesis, Addis Ababa University, Ethiopia.
  26. Müller, S., Tscharaktschiew, S., & Haase, K. (2008). Travel-to-school mode choice modelling and patterns of school choice in urban areas. Journal of transport Geography, 16(5), 342-357. Go to original source...
  27. Nair, G. S., Dias, F. F., Ruiz-Juri, N., Kuhr, J., & Bhat, C. R. (2018). Travel Modeling in an Era of Connected and Automated Transportation Systems: An Investigation in the Dallas-Fort Worth Area (No. D-STOP/2016/143).
  28. Olsson, A. L. L. (2003). Factors that influence choice of travel mode in major urban areas. The Attractiveness of Park & Ride.
  29. Ortúzar, J.D. and Willumsen, L.G. (2011) Modelling Transport. 4th Edition, Wiley, Hoboken. Go to original source...
  30. Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R. (1996). A simulation study of the number of events per variable in logistic regression analysis. Journal of clinical epidemiology, 49(12), 1373-1379. Go to original source...
  31. Richards, M. J., & Zill, J. C. (2019, October). Modelling mode choice with machine learning algorithms. In Australasian Transport Research Forum (ATRF), 41st, 2019, Canberra, ACT, Australia.
  32. Rodrigue, J. P. (2020). The geography of transport systems. 5th ed., Langara College, pp. 83-321. Go to original source...
  33. Saxena, N., Rashidi, T. H., & Auld, J. (2019). Studying the tastes effecting mode choice behavior of travelers under transit service disruptions. Travel behaviour and society, 17, 86-95. Go to original source...
  34. Sekhar, C. (2014). Mode Choice Analysis: The Data, the Models and Future Ahead. International Journal for Traffic & Transport Engineering, 4(3). Go to original source...
  35. Shang, B., & Zhang, X. N. (2013). Study of travel mode choice behavior based on nested Logit model. In Applied Mechanics and Materials, 253, 1345-1350. Go to original source...
  36. ©inko, S., Rupnik, B., Prah, K., & Kramberger, T. (2021). Spatial modelling of the transport mode choice: Application on the Vienna transport network. Transport, 36(5), 386-394. Go to original source...
  37. Suaa, A. J. Q., Chuaa, H. N., Khoob, H. L., Lowa, Y. C., Leea, A. S. H., & Ismailc, M. A. (2022). User Mode Choice Behavior in Public Transportation: A Systematic Literature Review. Jurnal Kejuruteraan, 34(1), 11-28. Go to original source...
  38. Takahashi, T. (2019). Transportation mode choice and spatial structure of a city.
  39. Tskeris, T., & Tsekeris, C. (2011). Demand forecasting in transport: Overview and modeling advances. Economic research-Ekonomska istraľivanja, 24(1), 82-94. Go to original source...
  40. Tuan, V. A. (2015). Mode choice behavior and modal shift to public transport in developing countries-the case of Hanoi city. Journal of the Eastern Asia Society for Transportation Studies, 11, 473-487.
  41. Tushara, T., Rajalakshmi, P., & Bino, I. K. (2013). Mode choice modelling for work trips in Calicut City. International Journal of Innovative Technology and Exploring Engineering (IJITEE).
  42. Tyrinopoulos, Y., & Antoniou, C. (2013). Factors affecting modal choice in urban mobility. European Transport Research Review, 5(1), 27-39. Go to original source...

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