Volume 29, Issue 2 (summer 2024)
JEPR 2024, 29(2): 170-96 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Shahangian R, Ghasemi N. (2024). Estimation of the willingness to pay for public transport improvements. JEPR. 29(2), 170-96. doi:10.61186/jpbud.29.2.75
URL: http://jpbud.ir/article-1-2290-en.html
URL: http://jpbud.ir/article-1-2290-en.html
1- Assistant Professor, Department of Economics and System, Ins titute for Management and Planning S tudies, Tehran, Iran. , r.shahangian@imps.ac.ir
2- Department of Economics and System, Institute for Management and Planning Studies, Tehran, Iran.
2- Department of Economics and System, Institute for Management and Planning Studies, Tehran, Iran.
Abstract: (519 Views)
This research examines people's willingness to pay (WTP) for improvements in public transportation as part of transportation demand management (TDM) policies. Proposed enhancements include reduced in-vehicle congestion, shorter access times for buses and metro services, increased bus reliability, and decreased travel times. An online stated preference (SP) survey was conducted to assess preferred transportation modes under hypothetical scenarios, and a nested logit model was applied to identify the factors influencing mode choice and to estimate WTP. The findings indicate that reduced congestion makes both buses and trains more attractive, while improved reliability significantly enhances bus appeal. Shortened access time positively impacts metro usage but has little effect on bus preference. Improved travel time for buses also emerges as an important factor. Additionally, the study reveals that people are willing to pay 1.4 times more for congestion improvements on the metro than for similar improvements on buses. Overall, these WTP values exceed current ticket prices, although the WTP for improved bus reliability is nearly equivalent to the current fare.
Keywords: Transportation Demand Management (TDM), Public Transport, Mode Choice, Discrete Choice, Willingness to Pay (WTP)
Type of Study: Research |
Subject:
General
Received: Jun 08 2024 | Accepted: Aug 26 2024 | ePublished: Jan 12 2025
Received: Jun 08 2024 | Accepted: Aug 26 2024 | ePublished: Jan 12 2025
References
1. Abbasi, M., Piccioni, C., Sarreshtehdari, A. and Lee, Y. J. (2022). Modeling travel mode choice under the effect of congestion pricing: The case study of Tehran. Advances in Transportation Studies, 56, pp. 89-106.
2. Bachok, S., and Ponrahono, Z. (2017). Modelling willingness to pay for improved public transport services: The challenges of non-response to stated preference hypothetical questions. Planning Malaysia, 15(1). [DOI:10.21837/pmjournal.v15.i6.250]
3. Baghestani. A., Tayarani, M., Mamdoohi, A. R., Habibian, M. and Gao. O. (2023). Travel demand management implications during the COVID-19 pandemic: The case study of Tehran. Sustainability, 15, 1209. [DOI:10.3390/su15021209]
4. Batarce, M., Muñoz, J. C., and Ortúzar, J. D. (2016). Valuing crowding in public transport: Implications for cost-benefit analysis. Transportation Research Part A, 91, pp. 358-378. [DOI:10.1016/j.tra.2016.06.025]
5. Bateman, I. J., and Willis, K. G. (eds) (2001). Valuing Environmental Preferences: Theory and Practice of the Contingent Valuation Method in the US, EU, and developing Countries, Oxford, pp. 645. [DOI:10.1093/0199248915.001.0001]
6. Bianco, M. J. (2000). Effective transportation demand management: Combining parking pricing, transit incentives, and transportation management in a commercial district of Portland, Oregon. Transportation Research Record, 1711(1), pp. 46-54. [DOI:10.3141/1711-07]
7. Breidert, C. (2006). Estimation of willingness-to-pay, theory, measurement, application, Deutscher Universitätsverlag Wiesbaden.
8. Breidert, C., Hahsler, M., and Reutterer, T. (2006). A review of methods for measuring willingness-to-pay. Innovative Marketing, 2(4), pp. 8-32.
9. Bwambale, A., Uzondu, C., Islam, M., Rahman, F., Batool, Z., Isolo Mukwaya, P., Wadud, Z. (2023). Willingness to pay for COVID-19 mitigation measures in public transport and paratransit in low-income countries. Transportation Research Part A, 167. [DOI:10.1016/j.tra.2022.103561] [PMID] []
10. Eboli, L. and Mazzulla, G. (2008). Willingness-to-pay of public transport users for improvement in service quality. European Transport, ISTIEE, Institute for the Study of Transport within the European Economic Integration, 38, pp. 107-118.
11. Halvorsen, A., Koutsopoulos, H. N., Lau, S., Au, T., and Zhao, J. (2016). Reducing subway crowding: Analysis of an off-peak discount experiment in Hong Kong. Transportation Research Record, 2544, pp. 38-46. [DOI:10.3141/2544-05]
12. Han, N. A., and Burris, M. W. (2018). The potential impact of incentives on managed lane travel. Journal of Transportation Technologies, 8 (4). [DOI:10.4236/jtts.2018.84014]
13. Hanna, N., and Dodge, H. R. (1997). Pricing: policies and procedures. Macmillan International Higher Education.
14. Jedidi, K., and Jagpal, S. (2009). Willingness to pay: Measurement and managerial implications. In Rao, V. R. (Eds.), Handbook of pricing research in marketing, Edward Elgar Publishing. [DOI:10.4337/9781848447448.00010]
15. Kroes, E., Kouwenhoven, M., Debrincat, L., and Pauget, N. (2014). Value of crowding on public transport in Île-de-France, France. Transportation Research Record, 2417, pp. 37-45. [DOI:10.3141/2417-05]
16. Lee, L. Y., and Cheah, Y. K. (2014). Willingness-to-pay for monorail services: Case study in Penang, Malaysia. Pertanika Journal of Social Sciences & Humanities, 22(1), 165-179. [https://www.researchgate.net/publication/285998835_Willingness-to-pay_for_monorail_services_Case_stu]
17. Li, Z., and Hensher, D. A. (2011). Crowding and public transport: A review of willingness to pay evidence and its relevance in project appraisal. Transport Policy, 18 (6), pp. 880-887. [DOI:10.1016/j.tranpol.2011.06.003]
18. McFadden, D. (1979). Quantitive Methods for Analysing Travel Behaviour of Individuals: Some Recent Development. In D. A. Hensher & P. R. Stopher (Eds), Behavioural Travel Modelling, Routledge.
19. McFadden, D. (1986). The choice theory approach to market research. Marketing Science, 5(4), pp. 275-297. [DOI:10.1287/mksc.5.4.275]
20. Meyer, M. D. (1999). Demand management as an element of transportation policy: Using carrots and sticks to influence travel behavior. Transportation Research Part A, 33 (7-8), pp. 575-599. [DOI:10.1016/S0965-8564(99)00008-7]
21. Piatkowski, D. P., Marshall, W. E., and Krizek K.J. (2019). Carrots versus sticks: Assessing intervention effectiveness and implementation challenges for active transport. Journal of Planning Education and Research, 39(1). pp. 50-64. [DOI:10.1177/0739456X17715306]
22. Pujiati, A., Nihayah, D. M., Bowo, P. A., and Prastiwi, F. S. (2019). Willingness to pay for improving the quality of public transportation. Jurnal Ekonomi dan Kebijakan, 12(2), pp. 365-381. [DOI:10.15294/jejak.v12i2.20302]
23. Shahangian, R. S., Kermanshah, M. and Mokhtarian, P. L. (2012). Gender differences in response to policies targeting commute to automobile-restricted central business district: Stated preference study of mode choice in Tehran, Iran. Transportation Research Record, 2320, pp. 80-89. [DOI:10.3141/2320-10]
24. Tan, R., and Lin, B. (2019). Public perception of new energy vehicles: Evidence from willingness to pay for new energy bus fares in China. Energy policy, 130, pp. 347-354. [DOI:10.1016/j.enpol.2019.04.010]
25. Tirachini, A., Hurtubia, R., Dekker, T., and Daziano, R. A. (2017). Estimation of crowding discomfort in public transport: Results from Santiago de Chile. Transportation Research Part A, 103, pp. 311-326. [DOI:10.1016/j.tra.2017.06.008]
26. Varian, H. R. (1992). Microeconomic Analysis, Viva Norton., New York.
27. Vasudevan, V., and Lunani, K. (2017). Willingness to pay for improvement in service quality of public transit system. In: Tandon, M., Ghosh, P. (eds) Mobility Engineering, Springer, Singapore. [DOI:10.1007/978-981-10-3099-4_9] []
28. Venkatachalam, L. (2004). The contingent valuation method: A review. Environmental Impact Assessment Review, 24(1), pp. 89-124. [DOI:10.1016/S0195-9255(03)00138-0]
29. Victoria Transport Policy Institute (2024, May). Why Manage Transportation Demand? [https://www.vtpi.org/tdm/tdm51.htm]
30. Wicki, M., Huber, R. A., and Bernauer, M. (2020). Can policy-packaging increase public support for costly policies? Insights from a choice experiment on policies against vehicle emissions. Journal of Public Policy, 4, pp. 599 - 625. [DOI:10.1017/S0143814X19000205]
31. Worku, G. B. (2013). Demand for improved public transport services in the UAE: A Contingent valuation study in Dubai. International Journal of Business and Management, 8(10), pp. 108- 125. [DOI:10.5539/ijbm.v8n10p108]
32. Zahabi, S. A. H., Miranda-Moreno, L. F., Patterson, Z., and Varla, P. (2012). Valuating the effects of land use and strategies for parking and transit supply on mode choice of downtown commuters. Journal of Transport and Land Use, 5(2), pp. 103-119. [DOI:10.5198/jtlu.v5i2.260]
| Rights and permissions | |
.jpg) |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
