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Transportation

, Volume 43, Issue 1, pp 1–23 | Cite as

Modelling bicycle use intention: the role of perceptions

  • Álvaro Fernández-Heredia
  • Sergio Jara-Díaz
  • Andrés Monzón
Article

Abstract

Users’ perceptions are identified as key elements to understand bicycle use, whose election cannot be explained with usual mobility variables and socio-economic characteristics. A hybrid model is proposed to model the intention of bicycle use; it combines a structural equations model that captures intentions and a choice model. The framework is applied to a case of a university campus in Madrid that is studying a new internal bike system. Results show that four latent variables (convenience, pro-bike, physical determinants and external restrictions) help explaining intention to use bike, representing a number of factors that are linked to individual perceptions.

Keywords

Bicycle use models Cyclist perceptions Hybrid models Latent variables 

Notes

Acknowledgments

Prof. Jara-Diaz acknowledges partial funding of Fondecyt, Chile, Grant 1120316, and the Institute for Complex Engineering Systems, grants ICM: P-05-004-F and CONICYT: FBO16. Alvaro Fernandez Heredia and Andres Monzon acknowledge partial funding of IDAE (Spanish Institute for Energy Efficiency), CRTM (Transport Authority of Madrid) and the Municipality of Madrid. We are grateful to the three unknown referees for their useful comments; remaining errors are, of course, our responsibility.

References

  1. Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211 (1991)CrossRefGoogle Scholar
  2. Akar, G., Clifton, K.J.: The influence of individual perceptions and bicycle infrastructure on the decision to bike. Presented at the Transportation Research Board 88st Annual Meeting (2009)Google Scholar
  3. Allen-Munley, C., Daniel, J., Dhar, S.: Logistic model for rating urban bicycle route safety. Transp. Res. Rec. 1878, 107–115 (2004)CrossRefGoogle Scholar
  4. Alves, M.J.: Os perigos da segregação de tráfego no planeamento para bicicletas. Accessed at http://mariojalves.googlepages.com/problemas_segregacao_bicicleta (2006)
  5. Ashok, K., Dillon, W.R., Yuan, S.: Extending discrete choice models to incorporate attitudinal and other latent variables. J. Mark. Res. 39, 31–46 (2002)CrossRefGoogle Scholar
  6. Aultman-Hall, L.: The impact of work-related factors on levels of bicycle commuting. Presented at the Transportation Research Board 88st Annual Meeting, Washington D.C (2009)Google Scholar
  7. Baltes, M.: Factors influencing nondiscretionary work trips by bicycle determined from 1990 U.S. census metropolitan statistical area data. Transp. Res. Rec. 1538, 96–101 (1996)CrossRefGoogle Scholar
  8. Bamberg, S., Ajzen, I., Schmidt, P.: Choice of travel mode in the theory of planned behavior: The roles of past behavior, habit, and reasoned action. Basic Appl. Soc. Psychol. 25, 175–187 (2003). ISSN 0197-3533CrossRefGoogle Scholar
  9. Barnes, G., Krizek, K.: Estimating bicycling demand. Transp. Res. Rec. 1939, 45–51 (2005)CrossRefGoogle Scholar
  10. Ben-Akiva, M., Bolduc, D., Parki, J.: Discrete choice analysis of shipper’s preferences. In: Van de Voorde, E. (ed.) Recent Developments in Transport Modeling: Lessons for the Freight Sector. Elsevier, Oxford (2008)Google Scholar
  11. Ben-Akiva, M., McFadden, D., Train, K., Walker, J., Bhat, C., Bierlaire, M., Bolduc, D., Boersch-Supan, A., Brownstone, D., Bunch, D.S., Daly, A., De Palma, A., Gopinah, D., Karlstrom, A., Munizaga, M.A.: Hybrid choice models: progress and challenges. Mark. Lett. 13(3), 163–175 (2002)CrossRefGoogle Scholar
  12. Ben-Akiva, M., McFadden, D., Gärling, T., Gopinath, D., Walker, J., Bolduc, D., Bärsch-Supan, A., Delquil, P., Larichev, O., Morikawa, T., Polydoropoulou, A., Rao, V.: Extended framework for modeling choice behavior. Mark Lett 10, 187–203 (1999)CrossRefGoogle Scholar
  13. Bentler, P.M.: Multivariate analysis with latent variables. Annu. Rev. Psychol. 31, 419–456 (1980)CrossRefGoogle Scholar
  14. Bergström, A., Magnusson, R.: Potential of transferring car trips to bicycle during winter. Transp. Res. Part A 37, 649–666 (2003)Google Scholar
  15. Bolduc, D., Álvarez-Daziano, R.: On estimation of hybrid choice models. In: Hess, S., Daly, A. (eds.) In Choice Modelling: The State-of-the-Art and the State-of-Practice: Proceedings from the Inaugural International Choice Modelling Conference. Emerald Group Publishing (p. 259) (2010)Google Scholar
  16. Bolduc, D., Giroux, A.: The integrated choice and latent variable (ICLV) model: handout to accompany the estimation software. Département d’économique, Université Laval, Québec (2005)Google Scholar
  17. Bolduc, D., Ben-Akiva, M., Walker, J.L., Michaud, A.: Hybrid choice models with logit kernel: applicability to large scale models. In: Lee-Gosselin, M., Doherty, S. (eds.) Integrated Land-Use and Transportation Models: Behavioral Foundations, pp. 275–302. Elsevier, Oxford (2005)Google Scholar
  18. Bolduc, D., Boucher, N., Álvarez-Daziano, R.: Hybrid choice modeling of new technologies for car choice in Canada. Transp. Res. Rec. 2082, 63–71 (2008)CrossRefGoogle Scholar
  19. Burbidge, S.K., Goulias, K.G.: Active travel behavior. Transp. Lett. 1(2), 147–167 (2009)CrossRefGoogle Scholar
  20. Cao, X., Mokhtarian, P.L.: How do individuals adapt their personal travel? Objective and subjective influences on the consideration of travel-related strategies for San Francisco Bay Area commuters. Transp. Policy 12, 291–302 (2005)CrossRefGoogle Scholar
  21. Carré, J.R.: Mobilité urbaine et déplacements non motorisés. Institut National de Recherche sur les transports et leur Sécurité, Francia (1999)Google Scholar
  22. Carter, D.L., Hunter, W.W., Zegeer, C.V., Stewart, J.R., Huang, H.F.: Bicyclist intersection safety index. Transp. Res. Rec. 2031, 18 (2007)CrossRefGoogle Scholar
  23. Cervero, R., Duncan, M.: Walking, bicycling, and urban landscapes: evidence From the San Francisco Bay Area. Am. J. Public Health 93, 1478–1483 (2003)CrossRefGoogle Scholar
  24. Correia, G., Abreu e Silva, J., Viegas, J.: Using latent variables for measuring carpooling propensity. Presented at the World Conference on Transport Research, 2010. Lisbon (2010)Google Scholar
  25. Cour Lund, B.: Driver behaviour towards circulating cyclists at roundabouts A vehicle simulator study with concurrent collection of eye movements. Presented at the Transportation Research Board 88st Annual Meeting, Washington D.C (2009)Google Scholar
  26. Danya, Y., Sihan, C., Yuelong, S., Yi, Z., Li, L.: A New CA Model for Simulating Behaviors of Conflicts in Vehicle-Bicycle Laminar Flow. Presented at the Transportation Research Board 88st Annual Meeting, Washington D.C (2009)Google Scholar
  27. Daziano, R.A., Bolduc, D.: Incorporating pro-environmental preferences towards green automobile technologies through a Bayesian hybrid choice model. Transp. A 9(1), 74–106 (2013)Google Scholar
  28. Dill, J.: Travel Behavior and Attitudes: New Urbanist Vs. Traditional Suburban Neighborhoods. Presented at the Transportation Research Board 82st Annual Meeting, Washington D.C (2003)Google Scholar
  29. Dill, J., Voros, K.: Factors affecting bicycling demand: initial survey findings from the Portland, Oregon, Region. Transp. Res. Rec. 2031, 9–17 (2007)CrossRefGoogle Scholar
  30. Di Ciommo, F., Monzón, A., Fernandez-Heredia, A.: Improving the analysis of road pricing acceptability surveys by using hybrid models. Transp. Res. Part A 49, 302–316 (2013)Google Scholar
  31. Duarte, A., Garcia, C., Limao, S., Polydoropoulou, A. (2009). Experienced and expected happiness in transport mode decision making process. Presented at the Transportation Research Board Annual Meeting 2009, Washington D.CGoogle Scholar
  32. Eash, R.: Destination and mode choice models for nonmotorized travel. Transp. Res. Rec. 1674, 1–8 (1999)CrossRefGoogle Scholar
  33. Elrod, T.: A factor-analytic probit model for representing the market structure in panel data. J. Mark. Res. 32, 1 (1995)CrossRefGoogle Scholar
  34. Emond, C.R., Tang, W., Handy, S.L.: Explaining gender difference in bicycling behavior. Presented at the Transportation Research Board 88st Annual Meeting, Washington D.C (2009)Google Scholar
  35. Faghri, A., Egyháziová, E.: Development of a computer simulation model of mixed motor vehicle and bicycle traffic on an urban road network. Transp. Res. Rec. 1674, 86–93 (1999)CrossRefGoogle Scholar
  36. Fernández-Heredia, A., Monzon, A., Jara-Díaz, S.: Understanding cyclists’ perceptions, keys for a successful bicycle promotion. Transp. Res. Part A 63, 1–11 (2014)Google Scholar
  37. Fleischer, A., Tchetchik, A., Toledo, T.: The impact of fear of flying on travelers’ flight choice choice model with latent variables. J. Travel Res. 51(5), 653–663 (2012)CrossRefGoogle Scholar
  38. Garrard, J., Rose, G., Lo, S.K.: Promoting transportation cycling for women: the role of bicycle infrastructure. Prev. Med. 46, 55–59 (2008)CrossRefGoogle Scholar
  39. Golob, T.F.: Joint models of attitudes and behavior in evaluation of the San Diego I-15 congestion pricing project. Transp. Res. Part A 35, 495–514 (2001)Google Scholar
  40. Golob, T.F.: Structural equation modeling for travel behavior research. Transp. Res. Part B 37, 1–25 (2003)CrossRefGoogle Scholar
  41. Green, P.: Hybrid models for conjoint analysis: an expository review. J. Mark. Res. 21, 155–169 (1984)CrossRefGoogle Scholar
  42. Greene, W.H.: Econometric Analysis. Pearson, New Jersey (1990)Google Scholar
  43. Harris, C., Glaser, D.: Gender differences in risk assessment: why do women take fewer risks than men? Judgem. Decis. Making 1, 48–63 (2006)Google Scholar
  44. Harris, K.M., Keane, M.P.: A model of health plan choice: inferring preferences and perceptions from a combination of revealed preference and attitudinal data. J. Econom. 89(1), 131–157 (1998)CrossRefGoogle Scholar
  45. Heath, Y., Gifford, R.: Extending the theory of planned behavior: predicting the use of public transportation. J. Appl. Soc. Psychol. 32, 2154–2189 (2006)CrossRefGoogle Scholar
  46. Heinen, E., Maat, K., Wee, B.: The role of attitudes toward characteristics of bicycle commuting on the choice to cycle to work over various distances. Transp. Res. Part D 16(2), 102–109 (2010a)CrossRefGoogle Scholar
  47. Heinen, E., van Wee, B., Maat, K.: Commuting by bicycle: an overview of the literature. Transp. Rev. 30, 59–96 (2010b)CrossRefGoogle Scholar
  48. Hopkinson, P., Wardman, M.: Evaluating the demand for new cycle facilities. Transp. Policy 3, 241–249 (1996)CrossRefGoogle Scholar
  49. Hunt, J., Abraham, J.: Influences on bicycle use. Transportation 34, 453–470 (2007)CrossRefGoogle Scholar
  50. Hyodo, T., Suzuki, N., Takahashi, K.: Modeling of bicycle route and destination choice behavior for bicycle road network plan. behavior. Presented at the Transportation Research Board 79st Annual Meeting, Washington D.C (2000)Google Scholar
  51. Jöreskog, K.G.: A general method for estimating a linear structural equation system. In: Goldberguer, A.S., Duncan, O.D. (eds.) Structural Models in the Social Sciences. Academic Press, New York (1973)Google Scholar
  52. Karash, K.H., Coogan, M.A, Adler, T., Cluett, C., Shaheen, S.A., Azjen, I., Simon, M.: Understanding how individuals make travel and location decisions: Implications for Public Transportation Behaviour. Presented at the Transportation Research Board 87st Annual Meeting, Washington D.C (2008)Google Scholar
  53. Keesling, J.W.: Maximum Likelihood Approaches to Causal Analysis. Ph.D. Dissertation, University of Chicago (1972)Google Scholar
  54. Kemperman, A., Timmermans, H.: Influences of the built environment on walking and cycling of latent segments of the aging population. Behaviour. Presented at the Transportation Research Board 88st Annual Meeting, Washington D.C (2009)Google Scholar
  55. Koppelman, F.S., Hauser, J.R.: Destination choice behaviour for non-grocery-shopping trips. Transp. Res. Rec. 673, 157–165 (1978)Google Scholar
  56. Krizek, K.J., Johnson, P.J., Tilahun, N.: Gender differents in bicyling behavoir and facility preferences. In: Rosenbloom, S. (ed.) National Research Council (U.S.). Research on Women’s Issues in Transportation, pp. 31–40. Transportation Research Board, Washington D.C (2005)Google Scholar
  57. Landis, B.W., Vattikuti, V., Brannick, M.: Real-time human perceptions: toward a bicycle level of service. Transp. Res. Rec. 1578, 119–126 (1997)CrossRefGoogle Scholar
  58. Lapietra, M. (2007) Transport Surveys. Guidelines. PhD Dissertation. Department of Hydraulics, Transport and Civil Infrastructures. Politecnico di TorinoGoogle Scholar
  59. McCahil, C., & Garrick, N. W.: The applicability of space syntax to bicycle facility planning. Trans. Res. Rec. J. Trans. Res. Board. 2074(1), 46–51 (2008)Google Scholar
  60. McClintock, H., Cleary, J.: Cycle facilities and cyclists’ safety. Transp. Policy 3, 67–77 (1996)CrossRefGoogle Scholar
  61. Mokhtarian, P.L., Cao, X.: Examining the impacts of residential self-selection on travel behavior: A focus on methodologies. Transp. Res. Part B 42, 204–228 (2008)CrossRefGoogle Scholar
  62. Molino, J.A., Emo, A.K.: Pedestrian and bicyclist exposure to risk: a methodology for estimation in an urban environment. Transp. Res. Rec. 2140(1), 145–156 (2009)CrossRefGoogle Scholar
  63. Moudon, A.V., Lee, C., Cheadle, A.D., Collier, C.W., Johnson, D., Schmid, T.L., Weather, R.D.: Cycling and the built environment, a US perspective. Transp. Res. Part D 10, 245–261 (2005)CrossRefGoogle Scholar
  64. Nankervis, M.: The effect of weather and climate on bicycle commuting. Transp. Res. Part A 33, 417–431 (1999)CrossRefGoogle Scholar
  65. Natarajan, S., Demetsky, M.J.: Selection and evaluation of bicycle and pedestrian safety projects. Presented at the Transportation Research Board 88st Annual Meeting, Washington D.C (2009)Google Scholar
  66. Nkurunziza, A., Maarseveen M., Zuidgeest, M.: Cycling potencial demand and travel behaviour change in Dar-es-Salaam. Tanzania. Habitat Int. 36(1), 78–84 (2010)CrossRefGoogle Scholar
  67. Noland, R.B., Kunreuther, H.: Short-run and long-run policies for increasing bicycle transportation for daily commuter trips. Transp. Policy 2, 67–79 (1995)CrossRefGoogle Scholar
  68. Noland, R., Quddus, M.: Analysis of Pedestrian and Bicycle Casualties with Regional Panel Data. Transp. Res. Rec. 1897, 28–33 (2004)CrossRefGoogle Scholar
  69. OECD: National policies to promote cycling. Organisation for Economic Cooperation and Development, European Conference of the Ministers of Transport, Paris, France (2004)Google Scholar
  70. Ortúzar, J.D., Willumsen, L.G.: Modelling Transport. Wiley, West Sussex (1990)Google Scholar
  71. Ortúzar, J.D., Iacobelli, A., Valeze, C.: Estimating demand for a cycle-way network. Transp. Res. Part A 34, 353–373 (2000)Google Scholar
  72. Parkin, J., Wardman, M., Page, M.: Estimation of the determinants of bicycle mode share for the journey to work using census data. Transportation 35, 93–109 (2008)CrossRefGoogle Scholar
  73. Petritsch, T.A., Landis, B.W., Huang, H.F., Challa, S.: Sidepath safety model bicycle sidepath design factors affecting crash rates. Transp. Res. Rec. 1982, 194–201 (2006)CrossRefGoogle Scholar
  74. Petritsch, T.A., Landis, B.W., McLeod, P.S., Huang, H.F., Scott, D.: Energy Savings Resulting from the Provision of Bicycle Facilities. Behaviour. Presented at the Transportation Research Board 87st Annual Meeting, Washington D.C (2008)Google Scholar
  75. Pinjari, A., Eluru, N., Bhat, C., Pendyala, R., Spissu, E.: Joint model of choice of residential neighborhood and bicycle ownership: accounting for self-selection and unobserved heterogeneity. Transp. Res. Rec. 2082, 17–26 (2008)CrossRefGoogle Scholar
  76. Prashker, J.N.: Scaling perceptions of reliability of urban travel modes using indscal and factor analysis methods. Transp. Res. Part A 13, 203–212 (1979)CrossRefGoogle Scholar
  77. Pucher, J., Buehler, R.: Making cycling irresistible: lessons from The Netherlands, Denmark and Germany. Transp. Rev. 28, 495–528 (2008)CrossRefGoogle Scholar
  78. Pucher, J., Dill, J., Handy, S.: Infrastructure, programs, and policies to increase bicycling: an international review. Prev. Med. 50, 106–125 (2010)CrossRefGoogle Scholar
  79. Pucher, J., Buehler, T.J., Seinen, M.: Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies. Transp. Res. A 45(6), 451–475 (2011)Google Scholar
  80. Rietveld, P.: The accessibility of railway stations: the role of the bicycle in The Netherlands. Transp. Res. Part D 5, 71–75 (2000)CrossRefGoogle Scholar
  81. Rietveld, P., Daniel, V.: Determinants of bicycle use: do municipal policies matter? Transp. Res. Part A 38, 531–550 (2004)Google Scholar
  82. Raveau, S., Álvarez-Daziano, R., Yáñez, M., Bolduc, D., Ortúzar, J.D.: Sequential and simultaneous estimation of hybrid discrete choice models. Transp. Res. Rec. 2156, 131–139 (2010)CrossRefGoogle Scholar
  83. Rondinella, G., Fernandez-Heredia, A., Monzón, A. (2012). Analysis of Perceptions of Utilitarian Cycling by Level of User Experience. Presented at the Transportation Research Board 91st Annual Meeting, Washington D.C.Google Scholar
  84. Saelens, B.E., Sallis, J.F., Frank, L.D.: Environmental correlates of walking and cycling: findings from the transportation, urban design, and planning literatures. Ann. Behav. Med. 25, 80 (2003)CrossRefGoogle Scholar
  85. Schossberg, M., Brehm, C.: Participatory GIS and active transportation: collecting data and creating change. Transp. Res. Rec. 2105(1), 83–91 (2009)CrossRefGoogle Scholar
  86. Sener, I.N., Eluru, N., Bhat, C.R.: An Analysis of Bicyclists and Bicycling Characteristics: Who, Why, and How Much are they Bicycling? Behavior. Presented at the Transportation Research Board 88st Annual Meeting, Washington D.C (2009) Google Scholar
  87. Shiva Nagendra, S.M., Khare, M.: Principal component analysis of urban traffic characteristics and meteorological data. Transp. Res. Part D 8, 285–297 (2003)CrossRefGoogle Scholar
  88. Stinson, M., Bhat, C.: Commuter bicyclist route choice: analysis using a stated preference survey. Transp. Res. Rec. 1828, 107–115 (2003)CrossRefGoogle Scholar
  89. Taylor, D., Mahmassani, H.: Analysis of stated preferences for intermodal bicycle-transit interfaces. Transp. Res. Rec. 1556, 86–95 (1996)CrossRefGoogle Scholar
  90. Teich, T.L. (2009) Adapting planning process and tools to the promotion of cycling in a medium-sized, developing city. Presented at the Transportation Research Board 88st Annual Meeting, Washington D.CGoogle Scholar
  91. Thomas, T., Jaarsma, C.F., Tutert, S.I.A. (2009) Temporal variations of bicycle demand in the Netherlands: The influence of weather on cycling. Presented at the Transportation Research Board 88st Annual Meeting, Washington D.CGoogle Scholar
  92. Titze, S., Stronegger, W.J., Janschitz, S., Oja, P.: Association of built-environment, social-environment and personal factors with bicycling as a mode of transportation among Austrian city dwellers. Prev. Med. 47, 252–259 (2008)CrossRefGoogle Scholar
  93. Vredin Johansson, M., Heldt, T., Johansson, P.: The effects of attitudes and personality traits on mode choice. Transp. Res. Part A 40, 507–525 (2006)Google Scholar
  94. Walker, J.L.: Extended Discrete Choice Model: Integrated Framework, Flexible Error Structures and Latent Variables. Ph.D. Dissertation, Massachusetts Institute of Technology (2001) Google Scholar
  95. Walker, J.L., Ben-Akiva, M.: Generalized random utility model. Math. Soc. Sci. 43, 303–343 (2002)CrossRefGoogle Scholar
  96. Wardman, M., Tight, M., Page, M.: Factors influencing the propensity to cycle to work. Transp. Res. Part A 41(4), 339–350 (2007)Google Scholar
  97. Wiley, D.E.: The identification problem for structural equation models with unmeasured variables. In: Goldberguer, A.S., Duncan, O.D. (eds.) Structural Models in the Social Sciences. Academic Press, New York (1973)Google Scholar
  98. Xing, Y., Handy, S.L., Buehler, T.J.: Factors Associated with Bicycle Ownership and Use: A Study of 6 Small U.S. Cities Behavior. Presented at the Transportation Research Board 87st Annual Meeting, Washington D.C (2008)Google Scholar
  99. Yáñez, M.F., Raveau, S., Ortúzar, J.D.: Inclusion of latent variables in mixed logit models: modelling and forecasting. Transp. Res. Part A 44, 744–753 (2010)Google Scholar
  100. Zahran, S., Brody, S.D., Maghelal, P., Prelog, A., Lacy, M.: Cycling and walking: explaining the spatial distribution of healthy modes of transportation in the united states. Transp. Res. Part D 13, 462–470 (2008)CrossRefGoogle Scholar

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Authors and Affiliations

  • Álvaro Fernández-Heredia
    • 1
  • Sergio Jara-Díaz
    • 2
  • Andrés Monzón
    • 3
  1. 1.Civil Engineering DepartmentUniversidad Europea Calle Tajo s/nVillaviciosa de OdónSpain
  2. 2.Transport Systems DivisionUniversidad de ChileSantiagoChile
  3. 3.Transport DepartmentUniversidad Politecnica de MadridMadridSpain

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