IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v52y2025i2d10.1007_s11116-023-10435-8.html
   My bibliography  Save this article

Does response lag affect travelers’ stated preference? Evidence from a real-time stated adaptation survey

Author

Listed:
  • Keishi Fujiwara

    (Hiroshima University)

  • Varun Varghese

    (Hiroshima University)

  • Makoto Chikaraishi

    (Hiroshima University)

  • Takuya Maruyama

    (Kumamoto University)

  • Akimasa Fujiwara

    (Hiroshima University)

Abstract

Stated preference (SP) surveys typically ask respondents to make a choice under a hypothetical situation. However, the choice context is often unrealistic, leading to errors and biases in the response. To overcome this, revealed preference (RP) data has been used to create a more realistic choice context for generating SP questions. For instance, in stated adaptation (SA) surveys, users are asked to answer SP questions based on a specific RP context they actually experienced. One challenge in SA surveys is that it is difficult for the respondents to precisely recall the RP context, especially when there is a longer time gap between RP behavior and SP response (response lag). However, no empirical studies have been conducted to test how elicited preferences vary in response to changes in the response lag. This study empirically examines the impact of response lag on SP responses using real-time SA survey data collected from Kumamoto and Hiroshima, Japan. To accomplish this, we developed a survey tool that enables respondents to answer SP questions in real time, i.e., immediately after their RP behavior. The empirical results confirmed that systematic bias increases with an increase in response lag. Additionally, the results showed that the greater the response lag, the more respondents tended to focus on the SP attributes rather than the RP attributes. These findings indicate that the timing of responses is an important survey design parameter when conducting an SA survey.

Suggested Citation

  • Keishi Fujiwara & Varun Varghese & Makoto Chikaraishi & Takuya Maruyama & Akimasa Fujiwara, 2025. "Does response lag affect travelers’ stated preference? Evidence from a real-time stated adaptation survey," Transportation, Springer, vol. 52(2), pages 693-713, April.
  • Handle: RePEc:kap:transp:v:52:y:2025:i:2:d:10.1007_s11116-023-10435-8
    DOI: 10.1007/s11116-023-10435-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-023-10435-8
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-023-10435-8?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. 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.
    2. Fifer, Simon & Rose, John & Greaves, Stephen, 2014. "Hypothetical bias in Stated Choice Experiments: Is it a problem? And if so, how do we deal with it?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 164-177.
    3. Tobias Börger, 2016. "Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(2), pages 389-413, October.
    4. Arentze, Theo & Borgers, Aloys & Timmermans, Harry & DelMistro, Romano, 2003. "Transport stated choice responses: effects of task complexity, presentation format and literacy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(3), pages 229-244, May.
    5. Kosuke Imai & David A. van Dyk, 2004. "Causal Inference With General Treatment Regimes: Generalizing the Propensity Score," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 854-866, January.
    6. John Rose & Iain Black, 2006. "Means matter, but variance matter too: Decomposing response latency influences on variance heterogeneity in stated preference experiments," Marketing Letters, Springer, vol. 17(4), pages 295-310, December.
    7. Mickael Bech & Trine Kjaer & Jørgen Lauridsen, 2011. "Does the number of choice sets matter? Results from a web survey applying a discrete choice experiment," Health Economics, John Wiley & Sons, Ltd., vol. 20(3), pages 273-286, March.
    8. Danaf, Mazen & Atasoy, Bilge & de Azevedo, Carlos Lima & Ding-Mastera, Jing & Abou-Zeid, Maya & Cox, Nathaniel & Zhao, Fang & Ben-Akiva, Moshe, 2019. "Context-aware stated preferences with smartphone-based travel surveys," Journal of choice modelling, Elsevier, vol. 31(C), pages 35-50.
    Full references (including those not matched with items on IDEAS)

    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. Fraser, Iain & Balcombe, Kelvin & Williams, Louis & McSorley, Eugene, 2021. "Preference stability in discrete choice experiments. Some evidence using eye-tracking," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 94(C).
    2. Tobias Börger & Oliver Frör & Sören Weiß, 2017. "The relationship between perceived difficulty and randomness in discrete choice experiments: Investigating reasons for and consequences of difficulty," Discussion Papers in Environment and Development Economics 2017-03, University of St. Andrews, School of Geography and Sustainable Development.
    3. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    4. Fifer, Simon & Rose, John M., 2016. "Can you ever be certain? Reducing hypothetical bias in stated choice experiments via respondent reported choice certaintyAuthor-Name: Beck, Matthew J," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 149-167.
    5. Tobias Börger & Joseph Cook, 2016. "Giving respondents “time to think” reduces response randomness in repeated discrete choice tasks," Discussion Papers in Environment and Development Economics 2016-13, University of St. Andrews, School of Geography and Sustainable Development.
    6. Chavez, Daniel E. & Palma, Marco A. & Nayga, Rodolfo M. & Mjelde, James W., 2020. "Product availability in discrete choice experiments with private goods," Journal of choice modelling, Elsevier, vol. 36(C).
    7. Chèze, Benoît & David, Maia & Martinet, Vincent, 2020. "Understanding farmers' reluctance to reduce pesticide use: A choice experiment," Ecological Economics, Elsevier, vol. 167(C).
    8. Tobias Börger, 2016. "Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(2), pages 389-413, October.
    9. Danaf, Mazen & Atasoy, Bilge & de Azevedo, Carlos Lima & Ding-Mastera, Jing & Abou-Zeid, Maya & Cox, Nathaniel & Zhao, Fang & Ben-Akiva, Moshe, 2019. "Context-aware stated preferences with smartphone-based travel surveys," Journal of choice modelling, Elsevier, vol. 31(C), pages 35-50.
    10. Jang, Sunghoon & Rasouli, Soora & Timmermans, Harry, 2022. "The effect of task complexity on stated choice processes: The moderating role of cognitive ability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    11. Komarek, Timothy M. & Lupi, Frank & Kaplowitz, Michael D., 2011. "Valuing energy policy attributes for environmental management: Choice experiment evidence from a research institution," Energy Policy, Elsevier, vol. 39(9), pages 5105-5115, September.
    12. Hess, Stephane & Stathopoulos, Amanda, 2013. "Linking response quality to survey engagement: A combined random scale and latent variable approach," Journal of choice modelling, Elsevier, vol. 7(C), pages 1-12.
    13. Thijs Dekker & Paul Koster & Roy Brouwer, 2014. "Changing with the Tide: Semiparametric Estimation of Preference Dynamics," Land Economics, University of Wisconsin Press, vol. 90(4), pages 717-745.
    14. Jürgen Meyerhoff & Malte Oehlmann & Priska Weller, 2015. "The Influence of Design Dimensions on Stated Choices in an Environmental Context," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 61(3), pages 385-407, July.
    15. Tirachini, Alejandro & Hurtubia, Ricardo & Dekker, Thijs & Daziano, Ricardo A., 2017. "Estimation of crowding discomfort in public transport: Results from Santiago de Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 311-326.
    16. Haghani, Milad & Sarvi, Majid, 2018. "Hypothetical bias and decision-rule effect in modelling discrete directional choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 361-388.
    17. Matthews, Yvonne & Scarpa, Riccardo & Marsh, Dan, 2017. "Using virtual environments to improve the realism of choice experiments: A case study about coastal erosion management," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 193-208.
    18. Nicolas Krucien & Jonathan Sicsic & Mandy Ryan, 2019. "For better or worse? Investigating the validity of best–worst discrete choice experiments in health," Health Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 572-586, April.
    19. Hess, Stephane & Rose, John M., 2009. "Allowing for intra-respondent variations in coefficients estimated on repeated choice data," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 708-719, July.
    20. Johnson, F. Reed & Ozdemir, Semra & Phillips, Kathryn A., 2010. "Effects of simplifying choice tasks on estimates of taste heterogeneity in stated-choice surveys," Social Science & Medicine, Elsevier, vol. 70(2), pages 183-190, January.

    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:52:y:2025:i:2:d:10.1007_s11116-023-10435-8. 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.