Journal of Transport and Land Use

Satisfaction with travel, ideal commuting, and accessibility to employment

John P. Pritchard

Faculty of Architecture & Town Planning, Technion Israel Institute of Technology

https://orcid.org/0000-0001-8546-4872

Karst Geurs

University of Twente

Diego B. Tomasiello

Escola Politecnica, Universidade de São Paulo

Anne Slovic

Faculdade de Saúde Pública, Universidade de São Paulo

Adelaide Nardocci

Faculdade de Saúde Pública, Universidade de São Paulo

Prashant Kumar

Global Centre for Clean Air Research (GCARE), Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey

Mariana Giannotti

Escola Politecnica, Universidade de São Paulo

Alex Hagen-Zanker

Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey

DOI: https://doi.org/10.5198/jtlu.2021.1835

Keywords: Potential Accessiblity, Satisfaction, Commuting, São Paulo, London, Randstad

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Abstract

This paper explores relationships between commuting times, job accessibility, and commuting satisfaction based on a large-scale survey applied in the Greater London Area (GLA), the municipality of São Paulo (MSP) and the Dutch Randstad (NLR). Potential accessibility to jobs is estimated under 3 different scenarios: reported actual commuting times (ACT), ideal commuting times (ICT), and maximum willingness to commute (MCT). In addition, binary logistic regression models, estimated using generalized linear modeling (GLM), are performed to assess the impact of these temporal preferences on the likelihood of being satisfied with commuting. As expected, ideal and maximum commuting preferences strongly impact the volume and spatial distribution of the measured accessibility to jobs. In the selected case studies, estimated ICT-based job accessibility significantly decreases total measured accessibility (60 to 100 percent), with those living in the lowest accessibility zones impacted most. Furthermore, although specific results varied between regions, the overall findings show an association between ACT and satisfaction. Likewise, commuting mode is found to be a strong predictor of travel satisfaction. Those actively traveling in all three metropolitan regions tend to be more satisfied with their commutes. Potential job accessibility is found to be only weakly associated with travel satisfaction.

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References

Brand, V., Kumar, P., Damascena, A. S., Pritchard, J. P., Geurs, K., & Andrade, M. d. F. (2019). Impact of route choice and period of the day on cyclists’ exposure to black carbon in London, Rotterdam and São Paulo. Journal of Transport Geography, 76, 153–165. https://doi.10.1016/j.jtrangeo.2019.03.007

Cerin, E., Leslie, E., du Toit, L., Owen, N., & Frank, L. D. (2007). Destinations that matter: Associations with walking for transport. Health & Place, 13(3), 713–724. https://doi.10.1016/ j.healthplace.2006.11.002

Chaloux, N., Boisjoly, G., Grisé, E., El-Geneidy, A., & Levinson, D. (2019). I only get some satisfaction: Introducing satisfaction into measures of accessibility. Transportation Research Part F: Traffic Psychology and Behavior, 62, 833–843. https://doi.10.1016/j.trf.2019.03.008

Chatterjee, K., Chng, S., Clark, B., Davis, A., De Vos, J., Ettema, D., … Reardon, L. (2020). Commuting and wellbeing: A critical overview of the literature with implications for policy and future research. Transport Reviews, 40(1), 5–34. https://doi.10.1080/01441647.2019.1649317

Choo, S., Collantes, G. O., & Mokhtarian, P. (2005). Wanting to travel, more or less: Exploring the determinants of the deficit and surfeit of personal travel. Transportation, 32(2), 135–164. https://doi.10.1007/s11116-004-2219-8

Cordera, R., Coppola, P., Dell’Olio, L., & Ibeas, Á. (2016). Is accessibility relevant in trip generation? Modelling the interaction between trip generation and accessibility taking into account spatial effects. Transportation, 44, 1577–1603. https://doi.10.1007/s11116-016-9715-5

Cui, M., & Levinson, D. (2019). Primal and dual access. Geographical Analysis, 52(3), 452–474. https://doi.10.1111/gean.12220

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

De Vos, J., & Witlox, F. (2016). Do people live in urban neighborhoods because they do not like to travel? Analyzing an alternative residential self-selection hypothesis. Travel Behavior and Society, 4, 29–39. https://doi.10.1016/j.tbs.2015.12.002

DfT. (2018a). Average number of trips, miles and time spent travelling by trip purpose (Table nts0403). London: Department for Transport. Retrieved from https://www.gov.uk/ government/statistical-data-sets/nts04-purpose-of-trips

DfT. (2018b). Time taken to travel to work by region of workplace (Table tsgb0110). London: Department for Transport. Retrieved from https://www.gov.uk/government/statistical -data-sets/tsgb01-modal-comparisons

Diener, E. E. (1985, feb). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71–75. https://doi.10.1207/s15327752jpa4901_13

Diener, E. E. (2006). Understanding scores on the satisfaction with life scale. Urbana-Champaign, IL: University of Illinois.

Ewing, R., & Cervero, R. (2010). Travel and the built environment: A meta-analysis. Journal of the American Planning Association, 76(3), 265–294. https://doi.10.1080/01944361003766766

García-López, M. Á., & Moreno-Monroy, A. I. (2016). Income segregation and urban spatial structure: Evidence from Brazil. (Working paper No. 2016/08.) Caracas: CAF Development Bank of Latin America.

Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge, UK: Cambridge University Press.

Geurs, K., & Ritsema van Eck, J. (2001). Accessibility measures: Review and applications (RIVM report 408505 006). Bilthoven, the Netherlands: RIVM - National Institute of Public Health and the Environment.

Geurs, K., & van Wee, B. (2004). Accessibility evaluation of land-use and transport strategies: Review and research directions. Journal of Transport Geography, 12(2), 127–140. http://doi.10.1016/j.jtrangeo.2003.10.005

Handy, S., & Thigpen, C. (2019). Commute quality and its implications for commute satisfaction: Exploring the role of mode, location, and other factors. Travel Behavior and Society, 16, 241–248. https://doi. 10.1016/j.tbs.2018.03.001

Hansen, W. G. (1959). How accessibility shapes land use. Journal of the American Institute of Planners, 25(2), 73–76. https;//doi.10.1080/01944365908978307

Humagain, P., & Singleton, P. A. (2020). Investigating travel time satisfaction and actual versus ideal commute times: A path analysis approach. Journal of Transport & Health, 16, 100829. https//doi.10.1016/j.jth.2020.100829

Jain, J., & Lyons, G. (2008). The gift of travel time. Journal of Transport Geography, 16(2), 81–89. https://doi.10.1016/j.jtrangeo.2007.05.001

Lancée, S., Veenhoven, R., & Burger, M. (2017). Mood during commute in the Netherlands: What way of travel feels best for what kind of people? Transportation Research Part A: Policy and Practice, 104, 195–208. https://doi.10.1016/j.tra.2017.04.025

Mokhtarian, P. (2019). Subjective well-being and travel: Retrospect and prospect. Transportation, 46, 493513. https://doi.10.1007/s11116-018-9935-y

Morris, E. A., & Guerra, E. (2015). Are we there yet? Trip duration and mood during travel. Transportation Research Part F: Traffic Psychology and Behavior, 33, 38–47. https://doi.10.1016/ j.trf.2015.06.003

Morris, E. A., & Zhou, Y. (2018). Are long commutes short on benefits? Commute duration and various manifestations of well-being. Travel Behavior and Society, 11, 101–110. https://doi.10.1016/j.tbs.2018.02.001

Morris, J., Dumble, P., & Wigan, M. (1979). Accessibility indicators for transport planning. Transportation Research Part A: General, 13(2), 91–109. https://doi.10.1016/0191-2607(79)90012-8

Moya-Gómez, B., & García-Palomares, J. C. (2017). The impacts of congestion on automobile accessibility. What happens in large European cities? Journal of Transport Geography, 62, 148–159. https://doi.10.1016/j.jtrangeo.2017.05.014

ONS. (2017). The national statistics socio-economic classification (NS-SEC). Retrieved from https://perma.cc/RL6N-H4CN

Pritchard, J. P., Tomasiello, D., Giannotti, M., & Geurs, K. (2019a). An international comparison of equity in accessibility to jobs: London, São Paulo and the Randstad. Findings, February, 1–9. https://doi.10.32866/7412

Pritchard, J. P., Tomasiello, D., Giannotti, M., & Geurs, K. (2019b). Potential impacts of bike-and-ride on job accessibility and spatial equity in São Paulo, Brazil. Transportation Research Part A: Policy and Practice, 121, 386–400. https://doi.10.1016/j.tra.2019.01.022

R Core Team. (2020). R: A language and environment for statistical computing [Computer software]. Vienna: The R Project for Statistical Computing. Retrieved from https://www.R-project.org/

Redmond, L., & Mokhtarian, P. (2001). The positive utility of the commute: Modeling ideal commute time and relative desired commute amount. Transportation, 28(2), 179–205. https://doi.10.1023/A:1010366321778

Ribeiro, A. G., Baquero, O. S., de Almeida, S. L., de Freitas, C. U., Cardoso, M. R. A., & Nardocci, A. C. (2019). Influence of vehicular traffic density on hospital admissions due to respiratory tract cancer in the city of São Paulo, Brazil. Cadernos de Saúde Pública, 35(1), e00128518. https://doi.10.1590/0102-311X00128518

Shaw, F. A., Malokin, A., Mokhtarian, P., & Circella, G. (2019). Who doesn’t mind waiting? Examining the relationships between waiting attitudes and person and travel related attributes. Transportation, 48, 395-429. https://doi.10.1007/s11116-019-10054-2

Smith, D., Shen, Y., Barros, J., Zhong, C., Batty, M., & Giannotti, M. (2020). A compact city for the wealthy? Employment accessibility inequalities between occupational classes in the London metropolitan region 2011. Journal of Transport Geography, 86(June), 102767. https://doi.10.1016/j.jtrangeo.2020.102767

Stichting LISA. (2014). Landelijk InformatieSysteem van Arbeidsplaatsen (LISA). Retrieved from https://www.lisa.nl/home

St-Louis, E., Manaugh, K., van Lierop, D., & El-Geneidy, A. (2014). The happy commuter: A comparison of commuter satisfaction across modes. Transportation Research Part F: Traffic Psychology and Behavior, 26, 160–170. https://doi.10.1016/j.trf.2014.07.004

Stępniak, M., Pritchard, J. P., Geurs, K., & Goliszek, S. (2019). The impact of temporal resolution on public transport accessibility measurement: Review and case study in Poland. Journal of Transport Geography, 75, 8–24. htttps://doi.10.1016/j.jtrangeo.2019.01.007

van Ham, M. (2002). Urban form and job access: Disparate realities in the Randstad. In Job access, workplace mobility, and occupational achievement (pp. 13–34). Utrecht, the Netherlands: Eburon Publishers.

van Wee, B., & Geurs, K. (2016). The role of accessibility in urban and transport planning. In M. Bliemer, C. Mulley, & C. Moutou (Eds.), Handbook on transport and urban planning in the developed world (pp. 53–66). Cheltenham, UK: Edward Elgar Publishing. https://doi.10.4337/9781783471393.00010

Ye, R., De Vos, J., & Ma, L. (2020). Analyzing the association of dissonance between actual and ideal commute time and commute satisfaction. Transportation Research Part A: Policy and Practice, 132, 47–60. https://doi.10.1016/j.tra.2019.10.011

Yee, T. (2015). Vector generalized linear and additive models: With an implementation. New York: Springer. https://doi.10.1007/978-1-4939-2818-7

Zhu, J., & Fan, Y. (2018). Commute happiness in Xi’an, China: Effects of commute mode, duration, and frequency. Travel Behavior and Society, 11, 43–51. https://doi.10.1016/j.tbs.2018.01.001