Volume 7, Issue 26 (12-2016)                   jemr 2016, 7(26): 89-110 | Back to browse issues page


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Nazemi A, Azhdar R, Feshari M, Nouri S. Effect of Fare Changes on Commuters' Behavior: A Case Study of Tehran Subway. jemr 2016; 7 (26) :89-110
URL: http://jemr.khu.ac.ir/article-1-1473-en.html
1- Kharazmi University
2- Kharazmi University , reihan.azhdar@gmail.com
Abstract:   (6681 Views)

In this study, the effect of fare changes on commuters' motivation to change their travel time in the Tehran subway during peak hours was evaluated. A sample of 432 Tehran metro passengers who commuted between 6:30 and 9 am was studied, and their preferences were examined. The main question in this article is whether fare changes could affect passenger behavior. We evaluated fare changes and influencing factors using discrete choice models, including Probit regression models. The results indicated that commuters who received an allowance from their workplace were more willing to change their departure time. People with flexible schedules were not attracted to fare changes, as they perceived little benefits from this adjustment. The findings of this study suggest that increasing fares during the morning peak is not an effective measure. They indicate that people are more motivated when being rewarded rather than punished. Moreover, some commuters might decide to use a different mode of transportation for commuting instead of taking an earlier subway trip, which would have a negative implication for morning transportation.

Full-Text [PDF 1861 kb]   (1841 Downloads)    
Type of Study: Applicable | Subject: سایر
Received: 2016/08/23 | Accepted: 2017/01/17 | Published: 2017/03/1

References
1.  Andersson, J., & Ubøe, J. (2012). "Some aspects of random utility, extreme value theory and multinomial logit models". Stochastics An International Journal of Probability and Stochastic Processes, 84(2-3), 425-435. [DOI:10.1080/17442508.2011.619660]
2.  Bakens, J., Knockaert, J., & Verhoef, E. T. (2010, May). "Rewarding off-peak railway commuting: A choice experiment". In Proceedings of the World Conference on Transport Research, 2010 Lisbon.
3.  Cochran, W. (1977). "Sampling techniques". 3th edition. New York: John Wiley & Sons.
4.  Douglas, N. J., Henn, L., & Sloan, K. (2011). "Modelling the ability of fare to spread AM peak passenger loads using rooftops". In 34th Australasian Transport Research Forum.
5.  Giuliano, G., & Small, K. A. (1995). "Alternative strategies for coping with traffic congestion". Springer Berlin Heidelberg. pp. 199-225. [DOI:10.1007/978-3-642-79397-4_9]
6.  Henn, L., Douglas, N., & Sloan, K. (2011). "Surveying Sydney rail commuters' willingness to change travel time". In 34th Australasian Transport Research Forum.
7.  Jewell, N. P. (2003). "Statistics for epidemiology". CRC Press. 258-259.
8.  Jiang, C. S., Deng, Y. F., Hu, C., Ding, H., & Chow, W. K. (2009). "Crowding in platform staircases of a subway station in China during rush hours". Safety science, 47(7), 931-938. [DOI:10.1016/j.ssci.2008.10.003]
9.  Litman, T. (2007). "Evaluating rail transit benefits: A comment". Transport Policy, 14(1), 94-97. [DOI:10.1016/j.tranpol.2006.09.003]
10.  Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000). Stated choice methods: analysis and applications. Cambridge University Press. [DOI:10.1017/CBO9780511753831]
11.  Mahudin, N. D. M., Cox, T., & Griffiths, A. (2012). "Measuring rail passenger crowding: Scale development and psychometric properties". Transportation research part F: traffic psychology and behaviour, 15(1), 38-51. [DOI:10.1016/j.trf.2011.11.006]
12.  Mayeres, I., Ochelen, S., & Proost, S. (1996). "The marginal external costs of urban transport". Transportation Research Part D: Transport and Environment, 1(2), 111-130. [DOI:10.1016/S1361-9209(96)00006-5]
13.  McFadden, D. (1976). "The theory and practice of disaggregate demand forecasting for various modes of urban transportation".
14.  Meyer, M. D. (1999). "Demand management as an element of transportation policy: using carrots and sticks to influence travel behavior". Transportation Research Part A: Policy and Practice, 33(7), 575-599. [DOI:10.1016/S0965-8564(99)00008-7]
15.  Patterson, Z., Ewing, G., & Haider, M. (2005). "Gender-based analysis of work trip mode choice of commuters in suburban Montreal, Canada, with stated preference data". Transportation Research Record: Journal of the Transportation Research Board, (1924), 85-93. [DOI:10.3141/1924-11]
16.  Rantzien, V. H. A., & Rude, A. (2014). "Peak-load pricing in public transport: a case study of Stockholm". Journal of Transport Literature, 8(1), 52-94. [DOI:10.1590/S2238-10312014000100004]
17.  Seyedabrishami, H., Mamdoohi, A., & Fowri, H. (2014). "Investigating the role of congestion pricing and transit development in commuter's mode choice behavior; case study of Tehran's even-odd zone". The 13th International conference on traffic and transportation engineering.
18.  Sposato, R. G., Röderer, K., & Cervinka, R. (2012). "The influence of control and related variables on commuting stress". Transportation Research Part F: Traffic Psychology and Behaviour, 15(5), 581-587. [DOI:10.1016/j.trf.2012.05.003]
19.  Webb, M., Gaymer, S., & Stuchbery, P. (2010). "Opportunities for managing peak train travel demand: a Melbourne pilot study". In 33rd Australasian Transport Research Forum.
20.  Whelan, G., & Johnson, D. (2004). "Modelling the impact of alternative fare structures on train overcrowding". International journal of transport management, 2(1), 51-58. [DOI:10.1016/j.ijtm.2004.04.004]
21.  Yazdanpanah, H., Abedini, M., & Baratian, F. (2011). "The effect of various methods of work time management programs in reducing travel demand during morning peak hour in Tehran". The 11th International conference on traffic and transportation engineering.
22.  Zhang, Z., Fujii, H., & Managi, S. (2014). "How does commuting behavior change due to incentives? An empirical study of the Beijing Subway System". Transportation Research Part F: Traffic Psychology and Behaviour, 24, 17-26. [DOI:10.1016/j.trf.2014.02.009]

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