IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v41y2014i4p819-837.html
   My bibliography  Save this article

Tollroads are only part of the overall trip: the error of our ways in past willingness to pay studies

Author

Listed:
  • John Rose
  • David Hensher

Abstract

With rare exception, actual tollroad traffic in many countries has failed to reproduce forecast traffic levels, regardless of whether the assessment is made after an initial year of operation or as long as 10 years after opening. Pundits have offered many reasons for this divergence, including optimism bias, strategic misrepresentation, the promise to equity investors of early returns on investment, errors in land use forecasts, and specific assumptions underlying the traffic assignment models used to develop traffic forecasts. One such assumption is the selection of a behaviourally meaningful value of travel time savings (VTTS) for use in a generalised cost or generalised time user benefit expression that is the main behavioural feature of the traffic assignment (route choice) model. Numerous empirical studies using stated choice experiments have designed choice sets of alternatives as if users choose a tolled route or a free route under the (implied) assumption that the tolled route is tolled for the entire trip. Reality is often very different, with a high incidence of use of a non-tolled road leading into and connecting out of a tolled link. In this paper we recognise this feature of route choice and redesign the stated choice experiment to account for it. Furthermore, this study is a follow up to a previous study undertaken before a new toll road was in place, and it benefits from real exposure to the new toll road. We find that the VTTS is noticeably reduced, and if the VTTS is a significant contributing influence on errors on traffic forecasts, then the lower estimates make sense behaviourally. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • John Rose & David Hensher, 2014. "Tollroads are only part of the overall trip: the error of our ways in past willingness to pay studies," Transportation, Springer, vol. 41(4), pages 819-837, July.
  • Handle: RePEc:kap:transp:v:41:y:2014:i:4:p:819-837
    DOI: 10.1007/s11116-013-9494-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11116-013-9494-1
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-013-9494-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lindhjem, Henrik & Navrud, Ståle, 2011. "Using Internet in Stated Preference Surveys: A Review and Comparison of Survey Modes," International Review of Environmental and Resource Economics, now publishers, vol. 5(4), pages 309-351, September.
    2. Louviere, Jordan J. & Islam, Towhidul, 2008. "A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best-worst scaling," Journal of Business Research, Elsevier, vol. 61(9), pages 903-911, September.
    3. Brownstone, David & Ghosh, Arindam & Golob, Thomas F. & Kazimi, Camilla & Van Amelsfort, Dirk, 2003. "Drivers' willingness-to-pay to reduce travel time: evidence from the San Diego I-15 congestion pricing project," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(4), pages 373-387, May.
    4. Flynn, Terry N. & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2007. "Best-worst scaling: What it can do for health care research and how to do it," Journal of Health Economics, Elsevier, vol. 26(1), pages 171-189, January.
    5. Pat Auger & Timothy Devinney & Jordan Louviere, 2007. "Using Best–Worst Scaling Methodology to Investigate Consumer Ethical Beliefs Across Countries," Journal of Business Ethics, Springer, vol. 70(3), pages 299-326, February.
    6. Rose, John M. & Bliemer, Michiel C.J. & Hensher, David A. & Collins, Andrew T., 2008. "Designing efficient stated choice experiments in the presence of reference alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 395-406, May.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, September.
    8. John M. Rose & Michiel C. J. Bliemer, 2008. "Constructing Efficient Stated Choice Experimental Designs," Transport Reviews, Taylor & Francis Journals, vol. 29(5), pages 587-617, October.
    9. Hausman, Jerry A. & Ruud, Paul A., 1987. "Specifying and testing econometric models for rank-ordered data," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 83-104.
    10. Hess, Stephane & Rose, John M. & Hensher, David A., 2008. "Asymmetric preference formation in willingness to pay estimates in discrete choice models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 847-863, September.
    11. Flyvbjerg,Bent & Bruzelius,Nils & Rothengatter,Werner, 2003. "Megaprojects and Risk," Cambridge Books, Cambridge University Press, number 9780521009461, September.
    12. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-719, November.
    13. Krinsky, Itzhak & Robb, A Leslie, 1990. "On Approximating the Statistical Properties of Elasticities: A Correction," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 189-190, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Saxena, N. & Rashidi, T.H. & Dixit, V.V. & Waller, S.T., 2019. "Modelling the route choice behaviour under stop-&-go traffic for different car driver segments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 62-72.
    2. Tabasi, Maliheh & Rose, John M. & Pellegrini, Andrea & Hossein Rashidi, Taha, 2024. "An empirical investigation of the distribution of travellers’ willingness-to-pay: A comparison between a parametric and nonparametric approach," Transport Policy, Elsevier, vol. 146(C), pages 312-321.
    3. Juan Gomez & Anestis Papanikolaou & José Manuel Vassallo, 2017. "Users’ perceptions and willingness to pay in interurban toll roads: identifying differences across regions from a nationwide survey in Spain," Transportation, Springer, vol. 44(3), pages 449-474, May.
    4. Andani, I Gusti Ayu & La Paix Puello, Lissy & Geurs, Karst, 2021. "Modelling effects of changes in travel time and costs of toll road usage on choices for residential location, route and travel mode across population segments in the Jakarta-Bandung region, Indonesia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 81-102.
    5. Hensher, David A. & Ho, Chinh Q. & Liu, Wen, 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, Elsevier, vol. 94(C), pages 604-621.
    6. Ricardo Ferreira Reis & Joaquim Miranda Sarmento, 2019. "“Cutting costs to the bone”: the Portuguese experience in renegotiating public private partnerships highways during the financial crisis," Transportation, Springer, vol. 46(1), pages 285-302, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Isler, Cassiano Augusto & Blumenfeld, Marcelo & Caldeira, Gabriel Pereira & Roberts, Clive, 2024. "Long-Distance railway mode choice in Brazil: Evidence from a discrete choice experiment," Research in Transportation Economics, Elsevier, vol. 104(C).
    2. Marti, Joachim, 2012. "A best–worst scaling survey of adolescents' level of concern for health and non-health consequences of smoking," Social Science & Medicine, Elsevier, vol. 75(1), pages 87-97.
    3. Scarpa, Riccardo & Notaro, Sandra & Raffaelli, Roberta & Louviere, Jordan, 2011. "Modelling attribute non-attendance in best-worst rank ordered choice data to estimate tourism benefits from Alpine pasture heritage," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115990, European Association of Agricultural Economists.
    4. Marco A. Palma, 2017. "Improving the prediction of ranking data," Empirical Economics, Springer, vol. 53(4), pages 1681-1710, December.
    5. Morten Mørkbak & Tove Christensen & Dorte Gyrd-Hansen, 2010. "Choke Price Bias in Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 45(4), pages 537-551, April.
    6. Scaccia, Luisa & Marcucci, Edoardo & Gatta, Valerio, 2023. "Prediction and confidence intervals of willingness-to-pay for mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 54-78.
    7. Muunda, Emmanuel & Mtimet, Nadhem & Schneider, Franziska & Wanyoike, Francis & Dominguez-Salas, Paula & Alonso, Silvia, 2021. "Could the new dairy policy affect milk allocation to infants in Kenya? A best-worst scaling approach," Food Policy, Elsevier, vol. 101(C).
    8. Wakamatsu, Mihoko & Shin, Kong Joo & Wilson, Clevo & Managi, Shunsuke, 2018. "Exploring a Gap between Australia and Japan in the Economic Valuation of Whale Conservation," Ecological Economics, Elsevier, vol. 146(C), pages 397-407.
    9. Simone Mueller & Larry Lockshin & Jordan Louviere, 2010. "What you see may not be what you get: Asking consumers what matters may not reflect what they choose," Marketing Letters, Springer, vol. 21(4), pages 335-350, December.
    10. Erdem, Seda & Rigby, Dan, 2011. "Using Best Worst Scaling To Investigate Perceptions Of Control & Concern Over Food And Non-Food Risks," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108790, Agricultural Economics Society.
    11. Denise Doiron & Hong Il Yoo, 2020. "Stated preferences over job characteristics: A panel study," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(1), pages 43-82, February.
    12. Hoyos, David, 2010. "The state of the art of environmental valuation with discrete choice experiments," Ecological Economics, Elsevier, vol. 69(8), pages 1595-1603, June.
    13. Feo-Valero, María & Arencibia, Ana Isabel & Román, Concepción, 2016. "Analyzing discrepancies between willingness to pay and willingness to accept for freight transport attributes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 151-164.
    14. Tavárez, Héctor & Álamo, Carmen & Cortés,Mildred, 2020. "Differentiated coffees and their potential markets in Puerto Rico: An economic valuation approach," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 20(02), December.
    15. Hess, Stephane & Hensher, David A., 2010. "Using conditioning on observed choices to retrieve individual-specific attribute processing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 781-790, July.
    16. Rodrigo J. Tapia & Gerard Jong & Ana M. Larranaga & Helena B. Bettella Cybis, 2021. "Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina," Networks and Spatial Economics, Springer, vol. 21(3), pages 581-608, September.
    17. Masiero, Lorenzo & Hensher, David A., 2010. "Analyzing loss aversion and diminishing sensitivity in a freight transport stated choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 349-358, June.
    18. T.N. Flynn & A.A.J. Marley, 2014. "Best-worst scaling: theory and methods," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 8, pages 178-201, Edward Elgar Publishing.
    19. Samare P. I. Huls & Emily Lancsar & Bas Donkers & Jemimah Ride, 2022. "Two for the price of one: If moving beyond traditional single‐best discrete choice experiments, should we use best‐worst, best‐best or ranking for preference elicitation?," Health Economics, John Wiley & Sons, Ltd., vol. 31(12), pages 2630-2647, December.
    20. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:transp:v:41:y:2014:i:4:p:819-837. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.