Volume List  / Volume 10 (4)



DOI: 10.7708/ijtte.2020.10(4).09

10 / 4 / 508-518 Pages


Rajorshi Sen Gupta - Department of Economics, BITS Pilani KK Birla Goa Campus, India -

Mohammed Anjal - Department of Economics, BITS Pilani KK Birla Goa Campus, India & Department of Computer Science, BITS Pilani KK Birla Goa Campus, India -


Toll road projects in India have been facing the problem of overestimated revenue forecasts. Given the importance of toll road users’ value of time (VOT) and consequently willingness to pay (WTP) on expected toll revenue, there is dearth of information regarding VOT of toll road users in India. This paper addresses this important gap in literature by providing a methodology to estimate VOT in the absence of primary survey data. Using 74 origin-destination pairs involving a toll road and an alternative non-tolled road, a unique database was prepared to estimate travel time saved (TTS) and VOT of seven different user categories of vehicles. Each of the seven user categories are found to be characterized by different VOT. The user heterogeneity in terms of VOT is an important finding which needs to be accounted for while conducting revenue estimates and economic feasibility analysis of proposed toll roads. Moreover, point estimates of VOT have limited application in conducting toll road feasibility analysis. Using stochastic TTS data, it is found that VOT of different user categories follow LogNormal distribution(s). The estimated projections on VOT can prove to be useful in improving the toll revenue forecasting in the context of India. The methodology can also be applied to other developing countries in the absence of primary data on VOT and WTP of potential toll road users.

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The authors are grateful to Vasu Mohan Gupta for providing excellent support during the data collection phase of this project.


Athira, I. C.; Muneera, C. P.; Krishnamurthy, K.; Anjaneyulu, M. V. L. R. 2016. Estimation of Value of Travel Time for Work Trips, Transportation Research Procedia 17: 116 – 23.


Bagui, S.K.; Ghosh, A. 2012. Traffic and Revenue Forecast at Risk for a BOT Road Project, KSCE Journal of Civil Engineering 16(6): 905-912.


Bain, R. 2009. Error and optimism bias in toll road traffic forecasts, Transportation 36(5): 469-482.


Ben-Akiva, M.; Bolduc, D.; Bradley, M. 1993. Estimation of travel choice models with randomly distributed value of time, Transportation Research Record, 1413: 88-97.


Boyer, K.D. 1997. Principles of Transportation Economics. Addison-Wesley Publishing Company. 416 p.


Brownstone, D.; Small, K. A. 2005. Valuing time and reliability: assessing the evidence from road pricing demonstrations, Transportation Research Part A: Policy and Practice 39(4): 279-93.


Gupta, R.S; Vadali, S.R. 2008. Stochastic Dominance Approach to evaluate Optimism Bias in Truck-Toll Forecasts, Transportation Research Record 2066(1): 98–105.


Hensher, D.A. 2001. Measurement of the Valuation of Travel Time Savings, Journal of Transport Economics and Policy 35(1): 71-98.


Hensher, D.A.; Goodwin, P. 2004. Using values of travel time savings for toll roads: avoiding some common errors, Transport Policy 11(2): 171-81.


Hensher, D.A.; Ho, C.Q.; Liu, W. 2016. How much is too much for tolled road users: Toll saturation and the implications for car commuting value of travel time savings?, Transportation Research Part A: Policy and Practice 94: 604-621.


IIDC. 2015. The Purvanchal Expressway Project: Traffic, Toll and Financial Studies. IIDC Ltd. Available from Internet: http://upeida.in.


IRC. 2009. Manual on Economic Evaluation of Highway Projects in India, IRC Special Publication SP-30, Indian Road Congress. 351 p.


Iyer, K.C.; Sagheer, M. 2011. A real options based traffic risk mitigation model for build-operate-transfer highway projects in India, Construction Management and Economics 29(8): 771–779.


Kawamura, K. 2003. Perceived Benefits of Congestion Pricing for Trucks, Transportation Research Record 1833(1): 59–65.


Ku, S; An, H.K. 2020. Revenue Risk Evaluation for PPP Road Infrastructure, International Journal for Traffic and Transport Engineering 10(2): 187-198.


MORTH. 2020. Ministry of Road Transport and Highways. Available from Internet: https://morth.nic.in/road-transport.


NCHRP. 2006. Synthesis 364: Estimating Toll Road Demand and Revenue, A Synthesis of Highway Practice. Transportation Research Board, Washington, D.C. 105 p.


NHAI. 2020. Available from Internet: http://tis.nhai.gov.in. Seetharaman, G. 2012. Untolled woe. Business Today. Available from Internet: https://www.businesstoday.in.


Singh, L.B.; Kalidindi, S.N. 2006. Traffic Revenue Risk Management through Annuity Model of PPP, International Journal of Project Management 24(7): 605-613.


Small, K.A. 2012. Valuation of travel time, Economics of Transportation 1(1-2): 2–14.


Toledo, T.; Sharif, S. 2019. The effect of information on drivers’ toll lane choices and travel times expectations, Transportation Research Part F: Traffic Psychology and Behaviour 62: 149-59.


Yang, H.; Tang, W. H.; Cheung, W. M.; Meng, Q. 2002. Profitability and Welfare Gain of Private Toll Roads in a Network with Heterogeneous Users, Transportation Research, Part A: Policy and Practice 36(6): 537–554.