International Journal of Transportation Engineering

International Journal of Transportation Engineering

What Drives Students to Use Shuttle Services? Exploring Preferences and Behavior

Document Type : Research Paper

Authors
Amirhossein Baghestani
Sahand Heshami
Maryam Delkhak
Alireza Mahpour
Faculty of Civil, Water, and Environmental Engineering, Shahid Beheshti University, Tehran, Iran
10.22119/ijte.2025.532608.1701
Abstract
Shuttle services have become an increasingly popular mode of transportation, particularly in areas where direct access to public transit is lacking. This study focuses on the utilization of shuttle services at Abbaspoor University in Tehran, Iran, and aims to identify the key determinants of students' willingness to use these services. A stated preference survey was conducted to gather data on student preferences, with the questionnaire divided into three sections: socio-economic information, travel behavior, and stated preference scenarios. The survey results were analyzed using a binary logit model to assess the impact of various factors on the adoption of shuttle service. Findings indicate that shuttle services are instrumental in reducing reliance on private vehicles and alleviating traffic congestion. The binary logit model results show that students who commute by metro are 33% more likely to use the shuttle, while car ownership decreases the probability of shuttle adoption by 9%. Moreover, increasing shuttle headways significantly reduces the likelihood of use: from –0.11 at 15 minutes to –0.42 at 60 minutes, underscoring the critical role of service frequency. The model achieved a prediction accuracy of 71% with a McFadden’s ρ² of 0.225, indicating a satisfactory fit.  The study provides valuable insights for the design and implementation of shuttle services in university settings, particularly in developing countries with limited public transportation infrastructure. The results underscore the importance of strategically located shuttle stops and highlight the role of shuttle services in enhancing accessibility, equity, and sustainability within the broader transportation ecosystem.
Keywords
Shuttle Services
University Campus
Stated Preference Scenario
Binary Logit
- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
 
- Arif Khan, M., Patel, R. K., Kermanshachi, S., Rosenberger, J. M., Hladik, G., Etminani-Ghasrodashti, R., Pamidimukkala, A., & Foss, A. (2023). Understanding Students’ Satisfaction with University Transportation. International Conference on Transportation and Development 2023, 522–532.
 
- Azzali, S., & Sabour, E. A. (2018). A framework for improving sustainable mobility in higher education campuses: The case study of Qatar University. Case Studies on Transport Policy, 6(4), 603–612.
 
- Baghestani, A., Heshami, S., & Mahpour, A. (2024). Analyzing The Online Taxi Usage in Educational Trips within the Central Business District of Tehran City.
 
- Baghestani, A., Heshami, S., & Mahpour, A. (2025a). A Decision Tree Approach for Modal Shift from Online Taxi to Private Car During the COVID-19 Pandemic. Iranian Journal of Science and Technology, Transactions of Civil Engineering.
 
https://doi.org/10.1007/s40996-025-01906-2
 
- Baghestani, A., Heshami, S., & Mahpour, A. (2025b). The impact of pandemic experiences on future similar situations: analysis of latent variables and trip purposes in ride-hailing choice. Transportation Planning and Technology, 1–20.
 
- Baghestani, A., Heshami, S., Mahpour, A., Sadeghitabar, S., & Borhani, R. (2025). Behavioral intentions towards ride-hailing services during the Pandemic: Using the health belief model and the moderating role of health norms and age. Journal of Transport & Health, 44, 102153.
https://doi.org/https://doi.org/10.1016/j.jth.2025.102153
 
- Baghestani, A., Najafabadi, S., Salem, A., Jiang, Z., Tayarani, M., & Gao, O. (2023). An application of the Node–Place model to explore the land Use–Transport development dynamics of the I-287 corridor. Urban Science, 7(1), 21.
 
- Balsas, C. J. L. (2003). Sustainable transportation planning on college campuses. Transport Policy, 10(1), 35–49.
 
- Berrebi, S. J., Joshi, S., & Watkins, K. E. (2021). On bus ridership and frequency. Transportation Research Part A: Policy and Practice, 148, 140–154.
 
- Bland, J. R., & Cook, A. C. (2019). Random effects probit and logit: understanding predictions and marginal effects. Applied Economics Letters, 26(2), 116–123.
 
- Cao, Y., & Wang, J. (2016). The key contributing factors of customized shuttle bus in rush hour: A case study in Harbin city. Procedia Engineering, 137, 478–486.
 
- Cattaneo, M., Malighetti, P., Morlotti, C., & Paleari, S. (2018). Students’ mobility attitudes and sustainable transport mode choice. International Journal of Sustainability in Higher Education, 19(5), 942–962.
 
- Charbatzadeh, F., Chipulu, M., Marshall, A., & Ojiako, U. (2016). Determinants of satisfaction with campus transportation services: Implications for service quality. Journal of Transport and Supply Chain Management, 10(1), 1–14.
 
- Chen, C.-F. (2019). Factors affecting the decision to use autonomous shuttle services: Evidence from a scooter-dominant urban context. Transportation Research Part F: Traffic Psychology and Behaviour, 67, 195–204.
 
- Cramer, J. S. (1999). Predictive performance of the binary logit model in unbalanced samples. Journal of the Royal Statistical Society Series D: The Statistician, 48(1).
https://doi.org/10.1111/1467-9884.00173
 
- Currie, G., & Loader, C. (2010). Bus network planning for transfers and the network effect in Melbourne, Australia. Transportation Research Record, 2145(1), 8–17.
 
- Etminani-Ghasrodashti, R., Paydar, M., & Hamidi, S. (2018). University-related travel behavior: Young adults’ decision-making in Iran. Sustainable Cities and Society, 43, 495–508.
https://doi.org/10.1016/j.scs.2018.09.011
 
- Farzin, I., Mamdoohi, A. R., Abbasi, M., Baghestani, A., & Ciari, F. (2024). Determinants behind the acceptance of autonomous vehicles in mandatory and optional trips. Proceedings of the Institution of Civil Engineers-Engineering Sustainability, 177(3), 174–184.
 
- Gbadamosi, B. (2023a). Challenges and Prospect of Operating University Campus Shuttle Services in Lagos State University. Available at SSRN 4541109.
 
- Gbadamosi, B. (2023b). Challenges and Prospect of Operating University Campus Shuttle Services in Lagos State University. Available at SSRN 4541109.
 
- Heath, Y., & Gifford, R. (2002). Extending the theory of planned behavior: Predicting the use of public transportation 1. Journal of Applied Social Psychology, 32(10), 2154–2189.
 
- Hensher, D. A., Rose, J. M., & Greene, W. H. (2015). Applied choice analysis. In Applied Choice Analysis.
https://doi.org/10.1007/9781316136232
 
- Javid, M. A., & Al-Kasbi, G. H. (2021). Factors affecting students’ intentions to use a university bus: Importance of travel attitudes and service quality attributes. Journal of Engineering Research, 9(4B).
 
- Kanafani, A., & Wang, R. (2010). Measuring multimodal transport level of service.
 
- Kazemeini, A., & Kermanshah, A. (2023). Promoting Sustainable Transport in Developing Countries: A Case Study of University Students in Tehran. Future Transportation, 3(3), 858–877.
 
- Kutty, A. A., Al-Jurf, N., Naser, A. F., Kucukvar, M., Ayad, H., Al-Obadi, M., Abdella, G. M., Bulak, M. E., & Elkharaz, J. M. (2021). Optimizing university campus shuttle bus congestion focusing on system effectiveness and reliability: A combined modeling based-routing approach. Proceedings of the International Conference on Industrial Engineering and Operations Management, 5–8.
- Li, Z., & Hensher, D. A. (2013). Crowding in public transport: a review of objective and subjective measures. Journal of Public Transportation, 16(2), 107–134.
 
- Limanond, T., Butsingkorn, T., & Chermkhunthod, C. (2011). Travel behavior of university students who live on campus: A case study of a rural university in Asia. Transport Policy, 18(1), 163–171.
 
- Losada Rojas, L. L., Gkritza, K. “Nadia,” & Pyrialakou, V. D. (2018). Assessing the First and Last Mile Problem for Intercity Passenger Rail Service. ASME/IEEE Joint Rail Conference, 50978, V001T05A002.
 
- Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000a). Stated choice methods: analysis and applications. Cambridge university press.
 
- Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000b). Stated choice methods: analysis and applications. Cambridge university press.
 
- Mahpour, A., Baghestani, A., & Mamdoohi, A. (2023). An exploration of heterogeneity in Latent Psychological Variables on Travelers’ destination choice. Decision Analytics Journal, 6.
https://doi.org/10.1016/j.dajour.2023.100179
 
- Maljaee, S. S., & Sameni, M. K. (2022). Investigating factors affecting university students’ use of subway before and after COVID-19 outbreak: A case study in Tehran. Journal of Transport Geography, 105, 103461.
 
- Nadimi, N., Zamzam, A., & Litman, T. (2023). University Bus Services: Responding to Students’ Travel Demands? Sustainability, 15(11), 8921.
 
- Puan, O. C., Hassan, Y. A. H., Mashros, N., Idham, M. K., Hassan, N. A., Warid, M. N. M., & Hainin, M. R. (2019). Transportation mode choice binary logit model: A case study for Johor Bahru city. IOP Conference Series: Materials Science and Engineering, 527(1).
https://doi.org/10.1088/1757-899X/527/1/012066
 
- Rich, J. (2024). Let’s walk! The fallacy of urban first-and last-mile public transport. Transportation, 1–23.
 
- Rossi, R. J. (2018). Mathematical statistics: an introduction to likelihood based inference. John Wiley & Sons.
 
- Shiftan, Y., Vary, D., & Geyer, D. (2006). Demand for park shuttle services––a stated-preference approach. Journal of Transport Geography, 14(1), 52–59.
 
- Shu, P., Sun, Y., Xie, B., Xu, S. X., & Xu, G. (2021). Data-driven shuttle service design for sustainable last mile transportation. Advanced Engineering Informatics, 49, 101344.
 
- Train, K. E. (2009). Discrete choice methods with simulation. Cambridge university press.
 
- Van der Hurk, E., Koutsopoulos, H. N., Wilson, N., Kroon, L. G., & Maróti, G. (2016). Shuttle planning for link closures in urban public transport networks. Transportation Science, 50(3), 947–965.
 
- Whalen, K. E., Páez, A., & Carrasco, J. A. (2013). Mode choice of university students commuting to school and the role of active travel. Journal of Transport Geography, 31, 132–142.
 
- Yim, Y. B., & Ceder, A. A. (2006). Smart feeder/shuttle bus service: consumer research and design. Journal of Public Transportation, 9(1), 97–121.
 
- Zhao, J., & Dessouky, M. (2008). Service capacity design problems for mobility allowance shuttle transit systems. Transportation Research Part B: Methodological, 42(2), 135–146.
 
- Zhao, Z., Fang, M., Tang, L., Yang, X., Kan, Z., & Li, Q. (2022). The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution. International Journal of Environmental Research and Public Health, 19(22), 15128.
 
- Zhou, J. (2014). From better understandings to proactive actions: Housing location and commuting mode choices among university students. Transport Policy, 33, 166–175.
International Journal of Transportation Engineering
Volume 13, Issue 3 - Serial Number 51
Winter 2026
Pages 2277-2290