Skip to main content

Understanding Commuter Information Needs and Desires in Public Transport: A Comparative Analysis of Stated and Revealed Preferences

  • Conference paper
  • First Online:
HCI in Mobility, Transport, and Automotive Systems (HCII 2024)

Abstract

This paper explores commuters’ stated- and revealed preference information needs and desires in public transport through a multi-method study. A survey with 286 participants uncovers stated preferences, while a diary study with 31 participants provides insight into the revealed preferences. Key findings include a comprehensive overview of travellers’ information needs and desires, offering insights to improve current traveller information systems. Moreover, the results show differences between real-time information needs and those recalled from memory. During disruptions, important information includes information about the duration, cause of disruption, consequences for the journey and alternatives, while information about potential disruptions, schedule, journey planning and interchanges are important for journeys without disruptions. Another important finding was the significant difference between the needs and desires during a regular and disrupted journey.

A. van Kasteren and M. Vredenborg—The two authors contributed equally to this paper.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    https://www.nspanel.nl/.

  2. 2.

    Cochran’s Q was selected due to the paired nature of the data.

  3. 3.

    This test was performed as the assumption of independence was violated.

  4. 4.

    www.panelclix.nl.

  5. 5.

    Categories were based on previous results.

  6. 6.

    This test was selected due to the repeated observations in the data.

  7. 7.

    Based on a Cochran’s Q [11] analysis.

References

  1. Adele, S., Tréfond-Alexandre, S., Dionisio, C., Hoyau, P.A.: Exploring the behavior of suburban train users in the event of disruptions. Transport. Res. F: Traffic Psychol. Behav. 65, 344–362 (2019)

    Article  Google Scholar 

  2. Armougum, A., Gaston-Bellegarde, A., Joie-La Marle, C., Piolino, P.: Physiological investigation of cognitive load in real-life train travelers during information processing. Appl. Ergon. 89, 103180 (2020)

    Article  Google Scholar 

  3. Bannert, M.: Managing cognitive load-recent trends in cognitive load theory. Learn. Instr. 12(1), 139–146 (2002)

    Article  Google Scholar 

  4. Bartram, D.: Comprehending spatial information: the relative efficiency of different methods of presenting information about bus routes. J. Appl. Psychol. 65(1), 103 (1980)

    Article  Google Scholar 

  5. Berggren, U., Brundell-Freij, K., Svensson, H., Wretstrand, A.: Effects from usage of pre-trip information and passenger scheduling strategies on waiting times in public transport: an empirical survey based on a dedicated smartphone application. Public Transport 13, 503–531 (2021)

    Article  Google Scholar 

  6. Brakewood, C., Watkins, K.: A literature review of the passenger benefits of real-time transit information. Transp. Rev. 39(3), 327–356 (2019)

    Article  Google Scholar 

  7. Cats, O., Koutsopoulos, H.N., Burghout, W., Toledo, T.: Effect of real-time transit information on dynamic path choice of passengers. Transp. Res. Rec. 2217(1), 46–54 (2011)

    Article  Google Scholar 

  8. Centraal Bureau voor de Statistiek: Hoeveel reisden inwoners van nederland van en naar het werk? (2021). https://www.cbs.nl/nl-nl/visualisaties/verkeer-en-vervoer/personen/van-en-naar-werk

  9. Centraal Bureau voor de Statistiek: Hoeveel wordt er met het openbaar vervoer gereisd? (2021). https://www.cbs.nl/nl-nl/visualisaties/verkeer-en-vervoer/personen/openbaar-vervoer

  10. Chen, L., Qi, L.: A diary study of understanding contextual information needs during leisure traveling. In: Proceedings of the Third Symposium on Information Interaction in Context, pp. 265–270 (2010)

    Google Scholar 

  11. Cochran, W.G.: The comparison of percentages in matched samples. Biometrika 37(3/4), 256–266 (1950)

    Article  MathSciNet  Google Scholar 

  12. Costa, P.T., Jr., Terracciano, A., McCrae, R.R.: Gender differences in personality traits across cultures: robust and surprising findings. J. Pers. Soc. Psychol. 81(2), 322 (2001)

    Article  Google Scholar 

  13. Cramér, H.: Mathematical Methods of Statistics, vol. 26. Princeton University Press (1999)

    Google Scholar 

  14. Dunn, O.J.: Multiple comparisons among means. J. Am. Stat. Assoc. 56(293), 52–64 (1961)

    Article  MathSciNet  Google Scholar 

  15. Farag, S., Lyons, G.: To use or not to use? an empirical study of pre-trip public transport information for business and leisure trips and comparison with car travel. Transp. Policy 20, 82–92 (2012)

    Article  Google Scholar 

  16. Government of the Netherlands: Sustainable public transport

    Google Scholar 

  17. Habib, M.A., Anik, M.A.H.: Impacts of covid-19 on transport modes and mobility behavior: analysis of public discourse in twitter. Transp. Res. Rec. (2021)

    Google Scholar 

  18. van Hagen, M., van Oort, N.: Improving railway passengers experience: two perspectives. J. Traffic Transp. Eng. 7(3), 2328-2142 (2019)

    Google Scholar 

  19. Hörold, S., Mayas, C., Krömker, H.: Identifying the information needs of users in public transport. Adv. Hum. Aspects Road Rail Transp. 1(2012), 331–340 (2012)

    Google Scholar 

  20. Huang, Z., Loo, B.P., Axhausen, K.W.: Travel behaviour changes under work-from-home (WFH) arrangements during covid-19. Travel Behav. Soc. 30, 202–211 (2023)

    Article  Google Scholar 

  21. Ibraeva, A., de Sousa, J.F.: Marketing of public transport and public transport information provision. Procedia Soc. Behav. Sci. 162, 121–128 (2014)

    Article  Google Scholar 

  22. Jevinger, Å., Johansson, E., Persson, J.A., Holmberg, J.: Context-aware travel support during unplanned public transport disturbances. In: VEHITS 2023–9th International Conference on Vehicle Technology and Intelligent Transport Systems, vol. 1, pp. 160–170. SCITEPRESS (2023)

    Google Scholar 

  23. Ku, D.G., Um, J.S., Byon, Y.J., Kim, J.Y., Lee, S.J.: Changes in passengers’ travel behavior due to covid-19. Sustainability 13(14), 7974 (2021)

    Article  Google Scholar 

  24. Leng, N., Corman, F.: The role of information availability to passengers in public transport disruptions: an agent-based simulation approach. Transpo. Res. Part A Policy Pract. 133, 214–236 (2020)

    Article  Google Scholar 

  25. Mantel, N.: Chi-square tests with one degree of freedom; extensions of the mantel-haenszel procedure. J. Am. Stat. Assoc. 58(303), 690–700 (1963)

    MathSciNet  Google Scholar 

  26. McNemar, Q.: Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika 12(2), 153–157 (1947)

    Article  Google Scholar 

  27. Mulley, C., Clifton, G.T., Balbontin, C., Ma, L.: Information for travelling: awareness and usage of the various sources of information available to PT users in NSW. Transp. Res. Part A Policy Pract. 101, 111–132 (2017)

    Article  Google Scholar 

  28. de Palma, A., Vosough, S., Liao, F.: An overview of effects of covid-19 on mobility and lifestyle: 18 months since the outbreak. Transp. Res. Part A Policy Pract. (2022)

    Google Scholar 

  29. Papangelis, K., Velaga, N.R., Ashmore, F., Sripada, S., Nelson, J.D., Beecroft, M.: Exploring the rural passenger experience, information needs and decision making during public transport disruption. Res. Transp. Bus. Manag. 18, 57–69 (2016)

    Google Scholar 

  30. Pearson, K.: On the criterion that a given system of deviations given system of deviations of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philos. Mag. Ser. 5, 157–175 (1900)

    Article  Google Scholar 

  31. Pearson, K.: X. on the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. London Edinburgh Dublin Philos. Mag. J. Sci. 50(302), 157–175 (1900)

    Google Scholar 

  32. QSR International Pty.: Nvivo 20 (2023). https://www.qsrinternational.com/nvivo-qualitative-data-analysis-software/home

  33. Romero, C., Zamorano, C., Monzón, A.: Exploring the role of public transport information sources on perceived service quality in suburban rail. Travel Behav. Soc. 33, 100642 (2023)

    Article  Google Scholar 

  34. Rosenthal, R., Cooper, H., Hedges, L., et al.: Parametric measures of effect size. In: The Handbook of Research Synthesis, vol. 621, no. 2, pp. 231–244 (1994)

    Google Scholar 

  35. Tang, L., Ho, C.Q., Hensher, D.A., Zhang, X.: Investigating traveller’s overall information needs: What, when and how much is required by urban residents. Travel Behav. Soc. 28, 155–169 (2022)

    Article  Google Scholar 

  36. Un, P., Adelé, S., Vallet, F., Burkhardt, J.M.: How does my train line run? Elicitation of six information-seeking profiles of regular suburban train users. Sustainability 14(5), 2665 (2022)

    Article  Google Scholar 

  37. Van Lierop, D., Badami, M.G., El-Geneidy, A.M.: What influences satisfaction and loyalty in public transport? A review of the literature. Transp. Rev. 38(1), 52–72 (2018)

    Article  Google Scholar 

  38. Vianello, M., Schnabel, K., Sriram, N., Nosek, B.: Gender differences in implicit and explicit personality traits. Personality Individ. Differ. 55(8), 994–999 (2013)

    Article  Google Scholar 

  39. Wilcoxon, F.: Individual comparisons by ranking methods. In: Kotz, S., Johnson, N.L. (eds.) Breakthroughs in Statistics: Methodology and Distribution, pp. 196–202. Springer, New York (1992). https://doi.org/10.1007/978-1-4612-4380-9_16

    Chapter  Google Scholar 

  40. Yeboah, G., Cottrill, C.D., Nelson, J.D., Corsar, D., Markovic, M., Edwards, P.: Understanding factors influencing public transport passengers’ pre-travel information-seeking behaviour. Public Transport 11, 135–158 (2019)

    Article  Google Scholar 

Download references

Acknowledgements

We thank the participants for their time and effort. This work was partially funded by the Dutch Railways.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anouk van Kasteren .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

van Kasteren, A., Vredenborg, M., Masthoff, J. (2024). Understanding Commuter Information Needs and Desires in Public Transport: A Comparative Analysis of Stated and Revealed Preferences. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2024. Lecture Notes in Computer Science, vol 14733. Springer, Cham. https://doi.org/10.1007/978-3-031-60480-5_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-60480-5_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-60479-9

  • Online ISBN: 978-3-031-60480-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics