, Volume 39, Issue 6, pp 1147–1171 | Cite as

Combining web and face-to-face in travel surveys: comparability challenges?

  • Caroline Bayart
  • Patrick BonnelEmail author


Response rates for household travel surveys are tending to fall, and it seems unlikely that this trend will be reversed in the future. In recent years, travel data collection methods have evolved in order to obtain reliable data that are sufficiently detailed to feed increasingly complex models, and in order to integrate new technologies into survey protocols (Internet, GPS…). Combining different media is an obvious low-cost way of improving data quality as it increases the overall response rate. But the question of the comparability of data over time and between different survey modes remains unresolved. This paper makes a comparative analysis between the travel behaviours of web-based survey respondents and respondents to a face-to-face interview. The data were obtained from the 2006 Lyon conurbation household travel survey. Our analysis shows that the Internet respondents reported fewer trips per day than the face-to-face respondents (3.00 vs. 4.04 daily trips), and that the differences between the two groups varied according to the travel mode and trip purpose. While part of this difference can be explained by socioeconomic disparities (the Internet respondents had a specific profile) we cannot exclude the possibility of under-reporting due to the web medium.


Household travel surveys Daily travel behaviour Survey modes Data comparability 


  1. The American Association for Public Opinion Research (AAPOR): Standard definitions: final dispositions of case codes and outcome rates for surveys, 7th edn. AAPOR. (2011). Accessed 26 Sep 2011
  2. Alsnih, R.: New technology and travel surveys: the way forward, Working Paper ITS-WP-04-11. Institute of Transport Studies, University of Sydney, Sydney (2004)Google Scholar
  3. Alsnih, R.: Characteristics of web-based surveys and applications in travel research, CD-Rom of the ISCTSC conference, August 2004, Costa Rica (2005)Google Scholar
  4. Ampt, E.S.: Response rates—do they matter? In: Bonnel, P., Chapleau, R., Lee-Gosselin, M., Raux, C. (eds.) Les enquêtes de déplacements urbains: mesurer le présent, simuler le futur, pp. 115–125. Programme Rhône-Alpes Recherches en Sciences Humaines, Lyon (1997)Google Scholar
  5. Armoogum, J., Axhausen, K., Hubert, J.-P., Madre, J.-L.: Immobility and mobility seen through trip-based versus time-use surveys. Transp. Rev. 28, 641–658 (2005)Google Scholar
  6. Atrostic, B.K., Burt, G.: Household non-response: what we have learned and a framework for the future, Statistical Policy working paper 28, pp. 153–180. Federal Committee on Statistical methodology, Office of Management and Budget, Washington DC (1999)Google Scholar
  7. Axhausen, K.W., Weis, C.: Predicting response rate: a natural experiment, survey practice, 3. (2010). Accessed 26 Sep 2011
  8. Bates, N.: Internet versus mail as a data collection methodology from a high coverage population. In: Proceedings of the annual meeting of the American Statistical Association, 5–9 Aug 2001Google Scholar
  9. Baudelle, G., Darris, G., Ollivro, J., Pihan, J.: Les conséquences d'un choix résidentiel périurbain sur la mobilité : pratiques et représentations des ménages. In: 3ème colloque du Groupe de Travail Mobilités spatiales et fluidité sociale (GT23) : Offre urbaine et expériences de la mobilité, Strasbourg, France, 20–22 March 2003Google Scholar
  10. Bayart, C., Bonnel, P.: Enquête web auprès des non-répondants de l’enquête ménages déplacements de Lyon 2005–2006, p. 256. Rapport pour le PREDIT, Laboratoire d’Economie des Transports, Lyon (2008)Google Scholar
  11. Bigot, R., Croutte, P.: La diffusion des technologies de l’information dans la société française, p. 210. CREDOC, Paris (2007)Google Scholar
  12. Bigot, R., Croutte, P.: La diffusion des technologies de l’information et de la communication dans la société française, CREDOC, Enquête (Conditions de vie et Aspirations des Français), Paris (2010)Google Scholar
  13. Bonnel, P.: Postal, telephone and face-to-face surveys: how comparable are they? In: Stopher, P.R., Jones, P.M. (eds.) Transport survey quality and innovation, pp. 215–237. Elsevier, London (2003)Google Scholar
  14. Bonnel, P., Armoogum, J.: National transport surveys—what can we learn from international comparisons? In: European transport conference, Strasbourg (2005)Google Scholar
  15. Bonnel, P., Le Nir, M.: The quality of survey data: telephone versus face-to-face interviews. Transportation 25, 147–167 (1998)CrossRefGoogle Scholar
  16. Brög, W., Meyburg, A.H.: Influence of survey methods on the results of representative travel surveys. Transp. Res. A 17, 149–156 (1983)CrossRefGoogle Scholar
  17. CERTU: L’enquête ménages déplacements (standard Certu), p. 204. CERTU, Lyon (2008)Google Scholar
  18. Christensen, L.: Busy people are hard to reach. CD-Rom of the ISCTSC conference, Costa Rica (2004)Google Scholar
  19. Cobanoglu, C., Warde, B., Moreo, P.J.: A comparison of mail, fax and web-based survey methods. Int. J. Mark. Res. 43, 441–452 (2001)Google Scholar
  20. Couper, M.P.: Web surveys: a review of issues and approaches. Public Opin. Quart. 65, 230–253 (2000)CrossRefGoogle Scholar
  21. Crawford, S., Mc Cabe, S., Couper, M.P., Boyd, C.: From mail to web: improving response rates and data collection efficiencies. In: International conference on improving surveys, Copenhagen, 25–28 Aug 2002Google Scholar
  22. De Leeuw, E.: Data quality in mail, telephone and face to face surveys, p. 182. TT Publikaties Amsterdam, Vrije Universiteit, Amsterdam (1992)Google Scholar
  23. Deville, J.-C., Särndal, C.-E., Sautory, O.: Generalized raking procedures in survey sampling. J. Am. Stat. Assoc. 88(423), 1013–1020 (1993)CrossRefGoogle Scholar
  24. Dillman, D.A., Bowker, D.K.: The web questionnaire challenge to survey methodologists. In: Reips, U.D., Bosnjak, M. (eds.) Dimensions of internet science, pp. 159–178. Pabst Science Publishers, Lengerich (2001)Google Scholar
  25. Dillman, A., Phelps, G., Tortora, R., Swift, K., Kohrell, J., Berck, J., Messer, B.L.: Response rate and measurement differences in mixed-mode surveys using mail, telephone, interactive voice response (IVR) and the internet. Soc. Sci. Res. 38, 1–18 (2009)CrossRefGoogle Scholar
  26. Ettema, D., Swanen, T., Timmermans, H.: The effect of location, mobility and socio-demographic factors on task and time allocation of households. Transportation 34(1), 89–105 (2007)CrossRefGoogle Scholar
  27. Fan, W., Yan, Z.: Factors affecting response rates of the web survey: a systematic review. Comput. Hum. Behav. 26, 132–139 (2010)CrossRefGoogle Scholar
  28. Gunn, H.: Web-based surveys: changing the survey process, first monday, 7(12) (2002)Google Scholar
  29. Hourriez, J.M., Olier, L.: Niveau de vie et taille du ménage: estimations d’une échelle d’équivalence. Économie et statistique. 308/309/310, 65–94 (1997)Google Scholar
  30. Hubert, J.P., Toint, P.: La mobilité quotidienne des Belges, p. 164. Presses Universitaires de Namur, Namur (2003)Google Scholar
  31. Jones, P.M., Dix, M.C., Clarke, M.I., Heggie, I.G.: Understanding travel behavior, p. 241. Oxford studies of Transport, Gower (1980)Google Scholar
  32. Lozar, K.M., Vehovar, V.: Do mail and web surveys provide same results? In: Ferligoj, A., Mrvar, A. (eds.) Development in social science methodology, pp. 149–169. FDV, Ljubljana (2002)Google Scholar
  33. Lozar, M.K., Vehovar, V.: Mode effect in web surveys. In: Proceedings of the survey research methods, American Statistical Association (2002b)Google Scholar
  34. Manfreda, K.M., Bosnjak, M., Berzelak, J., Haas, I., Vehovar, V.: Web surveys versus other survey modes. Int. J. Mark. Res. 50, 79–104 (2008)Google Scholar
  35. Madre, J.-L., Axhausen, K., Brög, W.: Immobility in travel diary surveys. Transportation 34(1), 107–128 (2007)CrossRefGoogle Scholar
  36. Madre, J.-L., Axhausen, K., Gascon, M.-O.: Immobility: a microdata analysis. In: 10th IATBR conference, Lucerne (2003)Google Scholar
  37. Mohammadian, A.K., Bekhor, S.: Travel behavior of special population groups. Transportation 35(5), 579–583 (2008)CrossRefGoogle Scholar
  38. Mokhtarian, P.L., Chen, C.: TTB or not TTB, that is the question: a review and analysis of the empirical literature on travel time (and money) budgets. Transp. Res. A Policy Pract. 38(9–10), 643–675 (2004)CrossRefGoogle Scholar
  39. Mokhtarian, P.L., Salomon, I., Handy, S.L.: The impacts of ICT on leisure activities and travel: a conceptual exploration. Transportation 33, 263–289 (2006)CrossRefGoogle Scholar
  40. Morris, J., Adler, T.: Mixed mode survey. In: Stopher, P.R., Jones, P.M. (eds.) Transport survey quality and innovation, pp. 239–252. Pergamon, Oxford (2003)Google Scholar
  41. Mullahy, J.: Specifiaction and testing of some modified count data models. J. Econom. 33, 341–365 (1986)CrossRefGoogle Scholar
  42. Murakami, E.: Survey methods, transportation research circular. In: National household travel survey conference, FHWA, pp. 23–26 (2004)Google Scholar
  43. Richardon, A.J.: Behavioural mechanisms of non-response in mailback travel surveys, p. 18. 79th Transportation Research Board, Washington DC (2000)Google Scholar
  44. Richardon, A.J., Ampt, E.S.: The Victoria integrated travel, activities and land-use toolkit, VITAL working paper VWP93/1. Transport Research Centre, University of Melbourne, Melbourne (1993)Google Scholar
  45. Rietveld, P.: Rounding of arrival and departure times in travel surveys: an interpretation in terms of scheduled activities. J. Transp. Stat. 5, 71–82 (2002)Google Scholar
  46. Sautory, O.: Redressement d’un échantillon par calage sur marges, Document de travail de la DSDS n°F9310, p. 51. INSEE, Paris (1993)Google Scholar
  47. Schonlau, M., Fricker, R.D., Elliott, M.N.: Conducting research surveys via e-mail and the web. Rand Documents, Santa Monica (2001)Google Scholar
  48. Shashaani, L.: Socioeconomic status, parents’ sex-role stereotypes, and the gender gap in computing. J. Res. Comput. Educ. 26(4), 433–451 (1994)Google Scholar
  49. Stopher, P.R.: A review of separate and joint strategies for the use of data on revealed and stated choices. Transportation 25, 187–205 (1998)CrossRefGoogle Scholar
  50. Stopher, P.R., Fitzgerald, C., Xu, M.: Assessing the accuracy of the Sydney household travel survey with GPS. Transportation 34, 723–741 (2007)CrossRefGoogle Scholar
  51. Stopher, P.R.: The travel survey toolkit: where to from here? In: Bonnel, P., Lee Gosselin, M., Zmud, J., Madre, J.-L. (eds.) Transport survey methods, keeping up with a changing world, pp. 15–46. Emerald, Bradford (2009)Google Scholar
  52. Wang, D., Law, F.Y.T.: Impacts of information and communication technologies (ICT) on time use and travel behaviour: a structural equations analysis. Transportation 34, 513–527 (2007)CrossRefGoogle Scholar
  53. Weis, C., Frei, A., Axhausen, K.W., Haupt, T., Fell, B.: A comparative study of web- and paper-based travel behaviour surveys. Paper presented at the European Transport Conference, Noordwijkerhout (2008)Google Scholar
  54. Wolf, J., Lechl, M., Thompson, M., Arce, C.: Trip rate analysis in GPS-enhanced personal travel surveys. In: Stopher, P.R., Jones, P.M. (eds.) Transport survey quality and innovation, pp. 483–498. Elsevier, London (2003)Google Scholar
  55. Wright, D.L., Aquilino, W.S., Supple, A.J.: A comparison of computer assisted and paper-and-pencil self-administered questionnaires in a drug use survey. Public Opin. Quart. 62(3), 331–353 (1998)CrossRefGoogle Scholar
  56. Yun, G.M., Trumbo, C.W.: Comparative response to a survey executed by post, e-mail & web form. J. Comput. Mediat. Commun. 6 (2000)Google Scholar
  57. Zahavi, Y.: The ‘UMOT’ project, report prepared for the U.S. department of transportation and the ministry of transport of Federal Republic Of Germany, p. 267 (1979)Google Scholar
  58. Zmud, J.: Designing instruments to improve response: keeping the horse before the cart. In: Stopher, P.R., Jones, P.M. (eds.) Transport survey quality and innovation, pp. 89–108. Elsevier, Pergamon (2003)Google Scholar

Copyright information

© Springer Science+Business Media, LLC. 2012

Authors and Affiliations

  1. 1.Laboratoire de Sciences Actuarielle et FinancièreUniversité Lyon 1—Article rédigé au Laboratoire d’Économie des TransportsLyonFrance
  2. 2.Laboratoire d’Economie des TransportUniversité de Lyon (ENTPE, CNRS, Université Lumière Lyon)Vaulx en Velin CedexFrance

Personalised recommendations