The role of perceived satisfaction and the built environment on the frequency of cycle-commuting

Authors

  • Tomás Echiburú CEDEUS
  • Ricardo Hurtubia CEDEUS, ISCI
  • Juan Carlos Muñoz CEDEUS

DOI:

https://doi.org/10.5198/jtlu.2021.1826

Abstract

Understanding how several street attributes influence the frequency of cycle commuting is relevant for policymaking in urban planning. However, to better understand the impact of the built environment on people's choices, we must understand the subjective experience of individuals while cycling. This study examines the relationship between perceived satisfaction and the attributes of the built environment along the route.

Data was collected from a survey carried out within one district of Santiago’s central business district (N=2,545). It included socio-demographic information, origin-destination and route, travel behavior habits, and psychometric indicators. Two models were estimated. The first, a satisfaction latent variable model by mode, confirms previous findings in the literature, such as the correlation between cycling and a more enjoyable experience, while adding some new findings. For instance, satisfaction increases with distance and the number of trips per week. The second is a hybrid ordered logit model for cycle commuting frequency that includes satisfaction, through a structural equation, that shows this latent variable plays a significant role in travel behavior.

The presence of buses along the route decreases cycling satisfaction and frequency, while the trip length and the availability of cycle paths has the opposite effect for male and female cyclists. These results allow us to understand the main factors that deliver satisfaction to cyclists and therefore induce frequent cycle commuting. Overall, our study provides evidence of the need for policymakers to focus their strategies so as to effectively promote cycling among different types of commuters.

References

Abou-Zeid, M., Witter, R., Bierlaire, M., Kaufmann, V., & Ben-Akiva, M. (2012). Happiness and travel mode switching: Findings from a Swiss public transportation experiment. Transport Policy, 19(1), 93–104. https://doi.org/10.1016/j.tranpol.2011.09.009

Akar, G., & Clifton, K. J. (2009). Influence of individual perceptions and bicycle infrastructure on decision to bike. Transportation Research Record: Journal of the Transportation Research Board, 2140(1), 165–172. https://doi.org/10.3141/2140-18

Aldred, R., & Dales, J. (2017). Diversifying and normalizing cycling in London, UK: An exploratory study on the influence of infrastructure. Journal of Transport & Health, 4, 348–362. https://doi.org/10.1016/j.jth.2016.11.002

Bahamonde-Birke, F. J., Kunert, U., Link, H., & Ortúzar, J. de D. (2017). About attitudes and perceptions: Finding the proper way to consider latent variables in discrete choice models. Transportation, 44(3), 475–493. https://doi.org/10.1007/s11116-015-9663-5

Bierlaire, M. (2018a). Estimating choice models with latent variables with PandasBiogeme. Retrieved from http://infoscience.epfl.ch/record/264260

Bierlaire, M. (2018b). PandasBiogeme: A short introduction (Technical report TRANSP-OR 181219). Lausanne, Switzerland: Transport and Mobility Laboratory, ENAC, EPFL, Bioegeme.

Bollen, K. A. (2002). Latent variables in psychology and the social sciences. Annual Review of Psychology, 53(1), 605–634. https://doi.org/10.1146/annurev.psych.53.100901.135239

Borsboom, D., Mellenbergh, G. J., & van Heerden, J. (2003). The theoretical status of latent variables. Psychological Review, 110(2), 203–219. https://doi.org/10.1037/0033-295X.110.2.203

Broach, J., Dill, J., & Gliebe, J. (2012). Where do cyclists ride? A route choice model developed with revealed preference GPS data. Transportation Research Part A: Policy and Practice, 46(10), 1730–1740. https://doi.org/10.1016/j.tra.2012.07.005

Buehler, R., & Dill, J. (2015). Bikeway networks: A review of effects on cycling. Transport Reviews, 36, 9–27. https://doi.org/10.1080/01441647.2015.1069908

Buehler, R., & Pucher, J. (2011). Sustainable transport in Freiburg: Lessons from Germany’s environmental capital. International Journal of Sustainable Transportation, 5(1), 43–70. https://doi.org/10.1080/15568311003650531

Cervero, R., & Duncan, M. (2003). Walking, bicycling, and urban landscapes: Evidence from the San Francisco Bay Area. American Journal of Public Health, 93(9), 1478–1483. https://doi.org/10.2105/AJPH.93.9.1478

Cervero, R., Sarmiento, O. L., Jacoby, E., Gomez, L. F., & Neiman, A. (2009). Influences of built environments on walking and cycling: Lessons from Bogotá. International Journal of Sustainable Transportation, 3(4), 203–226. https://doi.org/10.1080/15568310802178314

Cui, Y., Mishra, S., & Welch, T. F. (2014). Land use effects on bicycle ridership: A framework for state planning agencies. Journal of Transport Geography, 41, 220–228. https://doi.org/10.1016/j.jtrangeo.2014.10.004

Damant-Sirois, G., & El-Geneidy, A. M. (2015). Who cycles more? Determining cycling frequency through a segmentation approach in Montreal, Canada. Transportation Research Part A: Policy and Practice, 77, 113–125. https://doi.org/10.1016/j.tra.2015.03.028

de Hartog, J. J., Boogaard, H., Nijland, H., & Hoek, G. (2010). Do the health benefits of cycling outweigh the risks? Environmental Health Perspectives, 118(8), 1109–1116. https://doi.org/10.1289/ehp.0901747

De Vos, J. (2019). Satisfaction-induced travel behavior. Transportation Research Part F: Traffic Psychology and Behavior, 63,12–21. https://doi.org/10.1016/j.trf.2019.03.001

De Vos, J., Schwanen, T., Van Acker, V., & Witlox, F. (2019). Do satisfying walking and cycling trips result in more future trips with active travel modes? An exploratory study. International Journal of Sustainable Transportation, 13(3), 180–196. https://doi.org/10.1080/15568318.2018.1456580

Dickinson, J. E., Kingham, S., Copsey, S., & Hougie, D. J. P. (2003). Employer travel plans, cycling and gender: Will travel plan measures improve the outlook for cycling to work in the UK? Transportation Research Part D: Transport and Environment, 8(1), 53–67. https://doi.org/10.1016/S1361-9209(02)00018-4

Dill, J., & McNeil, N. (2013). Four types of cyclists? Examination of typology for better understanding of bicycling behavior and potential. Transportation Research Record: Journal of the Transportation Research Board, 2387(1), 129–138. https://doi.org/10.3141/2387-15

Dill, J., & Voros, K. (2007). Factors affecting bicycling demand: Initial survey findings from the Portland region. Retrieved from https://doi.org/10.3141/2031-02

Ettema, D., Gärling, T., Eriksson, L., Friman, M., Olsson, L. E., & Fujii, S. (2011). Satisfaction with travel and subjective well-being: Development and test of a measurement tool. Transportation Research Part F: Traffic Psychology and Behavior, 14(3), 167–175. https://doi.org/10.1016/j.trf.2010.11.002

Fernández-Heredia, Á., Monzón, A., & Jara-Díaz, S. (2014). Understanding cyclists’ perceptions, keys for a successful bicycle promotion. Transportation Research Part A: Policy and Practice, 63, 1–11. https://doi.org/10.1016/j.tra.2014.02.013

Fuentes, L., & Pezoa, M. (2018). Nuevas geografías urbanas en Santiago de Chile 1992—2012. Entre la explosión y la implosión de lo metropolitano. Revista de Geografía Norte Grande, 70, 131–151. https://doi.org/10.4067/S0718-34022018000200131

Gatersleben, B., & Appleton, K. M. (2007). Contemplating cycling to work: Attitudes and perceptions in different stages of change. Transportation Research Part A: Policy and Practice, 41(4), 302–312. https://doi.org/10.1016/j.tra.2006.09.002

Gatersleben, B., & Uzzell, D. (2007). Affective appraisals of the daily commute: Comparing perceptions of drivers, cyclists, walkers, and users of public transport. Environment and Behavior, 39(3), 416–431. https://doi.org/10.1177/0013916506294032

Golob, T. F. (2003). Structural equation modeling for travel behavior research. Transportation Research Part B: Methodological, 37(1), 1–25. https://doi.org/10.1016/S0191-2615(01)00046-7

Guevara, C. A., Tirachini, A., Hurtubia, R., & Dekker, T. (2020). Correcting for endogeneity due to omitted crowding in public transport choice using the multiple indicator solution (MIS) method. Transportation Research Part A: Policy and Practice, 137, 472–484. https://doi.org/10.1016/j.tra.2018.10.030

Gutiérrez, M., Hurtubia, R., & Ortúzar, J. de D. (2020). The role of habit and the built environment in the willingness to commute by bicycle. Travel Behavior and Society, 20, 62–73. https://doi.org/10.1016/j.tbs.2020.02.007

Handy, S. L., & Xing, Y. (2011). Factors correlated with bicycle commuting: A study in six small U.S. cities. International Journal of Sustainable Transportation, 5(2), 91–110. https://doi.org/10.1080/15568310903514789

Heinen, E., Maat, K., & van Wee, B. (2013). The effect of work-related factors on the bicycle commute mode choice in the Netherlands. Transportation, 40(1), 23–43. https://doi.org/10.1007/s11116-012-9399-4

Heinen, E., van Wee, B., & Maat, K. (2009). Commuting by bicycle: An overview of the literature. Transport Reviews, 30, 59–96. https://doi.org/10.1080/01441640903187001

Hunt, J. D., & Abraham, J. E. (2007). Influences on bicycle use. Transportation, 34(4), 453–470. https://doi.org/10.1007/s11116-006-9109-1

Krizek, K. J., Barnes, G., & Thompson, K. (2009). Analyzing the effect of bicycle facilities on commute mode share over time. Journal of Urban Planning and Development, 135(2), 66–73. https://doi.org/10.1061/(ASCE)0733-9488(2009)135:2(66)

Lowry, M. B., Furth, P., & Hadden-Loh, T. (2016). Prioritizing new bicycle facilities to improve low-stress network connectivity. Transportation Research Part A: Policy and Practice, 86, 124–140. https://doi.org/10.1016/j.tra.2016.02.003

Ma, L., & Dill, J. (2015). Associations between the objective and perceived built environment and bicycling for transportation. Journal of Transport & Health, 2(2), 248–255. https://doi.org/10.1016/j.jth.2015.03.002

Macmillan, A., Connor, J., Witten, K., Kearns, R., Rees, D., & Woodward, A. (2014). The societal costs and benefits of commuter bicycling: Simulating the effects of specific policies using system dynamics modeling. Environmental Health Perspectives, 122(4), 335–344. https://doi.org/10.1289/ehp.1307250

Martínez, M. A., Leiva, A. M., Petermann, F., Garrido, A., Díaz, X., Álvarez, C. … & Celis, C. (2018). Factores asociados a sedentarismo en Chile: Evidencia de la Encuesta Nacional de Salud 2009-2010. Revista Médica de Chile, 146(1), 22–31. https://doi.org/10.4067/s0034-98872018000100022

MIDESO. (2017). Encuesta CASEN. Ministerio de Desarrollo Social, Chile. Retrieved from: http://observatorio.ministeriodesarrollosocial.gob.cl/casen-multidimensional/casen/casen_2017.php

Morris, E. A., & Guerra, E. (2015). Mood and mode: Does how we travel affect how we feel? Transportation, 42(1), 25–43. https://doi.org/10.1007/s11116-014-9521-x

Moudon, A. V., Lee, C., Cheadle, A. D., Collier, C. W., Johnson, D., Schmid, T. L., & Weather, R. D. (2005). Cycling and the built environment, a US perspective. Transportation Research Part D: Transport and Environment, 10(3), 245–261. https://doi.org/10.1016/j.trd.2005.04.001

Muñoz, B., Monzon, A., & López, E. (2016a). Transition to a cyclable city: Latent variables affecting bicycle commuting. Transportation Research Part A: Policy and Practice, 84, 4–17. https://doi.org/10.1016/j.tra.2015.10.006

Muñoz, B., Monzon, A., & Daziano, R. A. (2016b). The increasing role of latent variables in modelling bicycle mode choice. Transport Reviews, 36(6), 737–771. https://doi.org/10.1080/01441647.2016.1162874

Noland, R. B., & Kunreuther, H. (1995). Short-run and long-run policies for increasing bicycle transportation for daily commuter trips. Transport Policy, 2(1), 67–79. https://doi.org/10.1016/0967-070X(95)93248-W

Ogilvie, D., Egan, M., Hamilton, V., & Petticrew, M. (2004). Promoting walking and cycling as an alternative to using cars: Systematic review. BMJ, 329(7469), 763. https://doi.org/10.1136/bmj.38216.714560.55

Oja, P., Titze, S., Bauman, A., de Geus, B., Krenn, P., Reger-Nash, B., & Kohlberger, T. (2011). Health benefits of cycling: A systematic review: Cycling and health. Scandinavian Journal of Medicine & Science in Sports, 21(4), 496–509. https://doi.org/10.1111/j.1600-0838.2011.01299.x

Oliva, I., Galilea, P., & Hurtubia, R. (2017). Identifying cycling-inducing neighborhoods: A latent class approach. International Journal of Sustainable Transportation, 12, 701–713. https://doi.org/10.1080/15568318.2018.1431822

Olsson, L. E., Gärling, T., Ettema, D., Friman, M., & Fujii, S. (2013). Happiness and satisfaction with work commute. Social Indicators Research, 111(1), 255–263.

Ortúzar, J. de D., Iacobelli, A., & Valeze, C. (2000). Estimating demand for a cycle-way network. Transportation Research Part A: Policy and Practice, 34(5), 353–373. https://doi.org/10.1016/S0965-8564(99)00040-3

Palma, D., Ortúzar, J. de D., Rizzi, L. I., Guevara, C. A., Casaubon, G., & Ma, H. (2016). Modelling choice when price is a cue for quality: A case study with Chinese consumers. Journal of Choice Modelling, 19, 24–39. https://doi.org/10.1016/j.jocm.2016.06.002

Pritchard, R. (2018). Revealed preference methods for studying bicycle route choice—A systematic review. International Journal of Environmental Research and Public Health, 15(3), 470. https://doi.org/10.3390/ijerph15030470

Pucher, J., Buehler, R., & Seinen, M. (2011). Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies. Transportation Research Part A: Policy and Practice, 45(6), 451–475. https://doi.org/10.1016/j.tra.2011.03.001

Rissel, C., Crane, M., Wen, L. M., Greaves, S., & Standen, C. (2016). Satisfaction with transport and enjoyment of the commute by commuting mode in inner Sydney: Satisfaction and enjoyment by commute mode. Health Promotion Journal of Australia, 27(1), 80–83. https://doi.org/10.1071/HE15044

Rossetti, T., Guevara, C. A., Galilea, P., & Hurtubia, R. (2018). Modeling safety as a perceptual latent variable to assess cycling infrastructure. Transportation Research Part A: Policy and Practice, 111, 252–265. https://doi.org/10.1016/j.tra.2018.03.019

Rossetti, T., Saud, V., & Hurtubia, R. (2019). I want to ride it where I like: Measuring design preferences in cycling infrastructure. Transportation, 46(3), 697–718. https://doi.org/10.1007/s11116-017-9830-y

Sallis, J. F., Conway, T. L., Dillon, L. I., Frank, L. D., Adams, M. A., Cain, K. L., & Saelens, B. E. (2013). Environmental and demographic correlates of bicycling. Preventive Medicine, 57(5), 456–460. https://doi.org/10.1016/j.ypmed.2013.06.014

SECTRA. (2013). Análisis del comportamiento de la demanda de infraestructura especializada para bicicletas. Ministerio de Transporte y Telecomunicaciones, Santiago. Retrieved from http://www.sectra.gob.cl/biblioteca/detalle1.asp?mfn=3121

SECTRA. (2015). Encuesta Origen Destino de Santiago 2012. Ministerio de Transporte y Telecomunicaciones, Santiago. Retrieved from http://www.sectra.gob.cl/biblioteca/biblioteca.asp

Stinson, M. A., & Bhat, C. R. (2003). Commuter bicyclist route choice: Analysis using a stated preference survey. Transportation Research Record: Journal of the Transportation Research Board, 1828(1), 107–115. https://doi.org/10.3141/1828-13

Stinson, M. A., & Bhat, C. R. (2004). Frequency of bicycle commuting: Internet-based survey analysis. Transportation Research Record: Journal of the Transportation Research Board, 1878(1), 122–130. https://doi.org/10.3141/1878-15

Stinson, M. A., & Bhat, C. R. (2005). A comparison of the route preferences of experienced and inexperienced bicycle commuters (No. 05-1434).

Walker, J., & Ben-Akiva, M. (2002). Generalized random utility model. Mathematical Social Sciences, 43(3), 303–343. https://doi.org/10.1016/S0165-4896(02)00023-9

Wang, H., Palm, M., Chen, C., Vogt, R., & Wang, Y. (2016). Does bicycle network level of traffic stress (LTS) explain bicycle travel behavior? Mixed results from an Oregon case study. Journal of Transport Geography, 57, 8–18. https://doi.org/10.1016/j.jtrangeo.2016.08.016

Wardman, M., Tight, M., & Page, M. (2007). Factors influencing the propensity to cycle to work. Transportation Research Part A: Policy and Practice, 41(4), 339–350. https://doi.org/10.1016/j.tra.2006.09.011

Willis, D. P., Manaugh, K., & El-Geneidy, A. (2013). Uniquely satisfied: Exploring cyclist satisfaction. Transportation Research Part F: Traffic Psychology and Behavior, 18, 136–147. https://doi.org/10.1016/j.trf.2012.12.004

Ye, R., & Titheridge, H. (2017). Satisfaction with the commute: The role of travel mode choice, built environment and attitudes. Transportation Research Part D: Transport and Environment, 52, 535–547. https://doi.org/10.1016/j.trd.2016.06.011

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2021-02-01

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Echiburú, T., Hurtubia, R., & Muñoz, J. C. (2021). The role of perceived satisfaction and the built environment on the frequency of cycle-commuting. Journal of Transport and Land Use, 14(1), 171–196. https://doi.org/10.5198/jtlu.2021.1826

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