Active travel in the university setting: Assessing the effects of social behavior, socioeconomics, and spatial location
Isabel Cunha
University of Lyon
https://orcid.org/0000-0001-6566-9336
Catarina Cadima
University of Porto
https://orcid.org/0000-0002-4969-5013
DOI: https://doi.org/10.5198/jtlu.2024.2473
Keywords: Travel behavior, Active travel, Accessibility, Survey, University students
Abstract
University campuses are pooling efforts to promote active mobility to reduce their negative impacts on the urban environment, which is significantly influenced by the overreliance on motorized modes of transport. Providing sufficient and safe accessibility conditions for active travel has been highlighted as a crucial strategy for transforming campuses into more livable and sustainable areas in cities. To further explore the likelihood of active mobility uptake at university campuses, this study explored university students’ mobility patterns over time, examining the role of social behavior, socioeconomics, and spatial location factors. The Faculty of Engineering at the University of Porto, Greater Oporto, Portugal, provided the empirical focus for this research. The data analyzed were acquired through surveys of representative samples and spatial analysis over the academic years of 2012, 2017, and 2023. The statistical analysis explained the tendencies and multifactorial influences on travel behavior among university students. Results indicated that travel distance is associated with housing options and travel costs, whereas access to a metro station was associated with walking or cycling. Hence, this study contributed to a deeper understanding of active travel behavior. It provided insights to guide planning practitioners and decision makers in creating integrated transport policy packages that address the barriers and needs of the university community and the surrounding neighborhoods.
References
Akar, G., Fischer, N., & Namgung, M. (2013). Bicycling choice and gender case study: The Ohio State University. International Journal of Sustainable Transportation, 7(5), 347–365. https://doi.org/10.1080/15568318.2012.673694
Almeida, L.S. & Freire, T. (2008). Metodologia da Investigação em Psicologia e Educação. Braga: Psiquilíbrios (5ª Edição).
Anable, J. (2005). “Complacent car Addicts”; or “aspiring environmentalists”? Identifying travel behavior segments using attitude theory. Transport Policy, 12(1), 65–78. https://doi.org/10.1016/j.tranpol.2004.11.004
Bai, Y., Cao, M., Wang, R., Liu, Y., & Wang, S. (2022). How street greenery facilitates active travel for university students. Journal of Transport and Health, 26(August 2021), 101393. https://doi.org/10.1016/j.jth.2022.101393
Balsas, C. J. L. (2003). Sustainable transportation planning on college campuses. Transport Policy, 10(1), 35–49. https://doi.org/10.1016/S0967-070X(02)00028-8
Banister, D. (2011). Cities, mobility and climate change. Journal of Transport Geography, 19(6), 1538–1546. https://doi.org/10.1016/j.jtrangeo.2011.03.009
Beirão, G., & Cabral, J. S. (2008). Market segmentation analysis using attitudes toward transportation exploring the differences between men and women. Transportation Research Record, 2067, 56–64. https://doi.org/10.3141/2067-07
Bicalho, T., Silva, C., Cunha, I., Teixeira, J., & Proença, A. (2019). Planners’ attitudes towards the cycling potential of their cities – Creating awareness for attitude change. Travel Behavior and Society, 17(July), 96–103. https://doi.org/10.1016/j.tbs.2019.08.002
Bonham, J., & Koth, B. (2010). Universities and the cycling culture. Transportation Research Part D: Transport and Environment, 15(2), 94–102. https://doi.org/10.1016/j.trd.2009.09.006
Bopp, M., Wilson, O. W. A., Duffey, M., & Papalia, Z. (2019). An examination of active travel trends before and after college graduation. Journal of Transport and Health, 14(February), 100602. https://doi.org/10.1016/j.jth.2019.100602
Buehler, R., Broaddus, A., Sweeney, T., Zhang, W., White, E., & Mollenhauer, M. (2021). Changes in travel behavior, attitudes, and preferences among e-scooter riders and nonriders: First look at results from pre and post e-scooter system launch surveys at virginia tech. Transportation Research Record, 2675(9), 335–345. https://doi.org/10.1177/03611981211002213
Cadima, C., Silva, C., & Pinho, P. (2020). Changing student mobility behavior under financial crisis: Lessons from a case study in the Oporto University. Journal of Transport Geography, 87(July), 102800. https://doi.org/10.1016/j.jtrangeo.2020.102800
Chahine, R., Luo, H., Cai, H., & Gkritza, K. (2024). A comparative study of bike-sharing and e-scooter sharing users and services in a college town during COVID-19. Case Studies on Transport Policy, 15(December 2023), 101130. https://doi.org/10.1016/j.cstp.2023.101130
Chillón, P., Molina-García, J., Castillo, I., & Queralt, A. (2016). What distance do university students walk and bike daily to class in Spain. Journal of Transport and Health, 3(3), 315–320. https://doi.org/10.1016/j.jth.2016.06.001
Crotti, D., Grechi, D., & Maggi, E. (2022). Reducing the carbon footprint in college mobility: The car commuters’ perspective in an Italian case study. Environmental Impact Assessment Review, 92(November 2021), 106702. https://doi.org/10.1016/j.eiar.2021.106702
Cunha, I., & Silva, C. (2023). Assessing the equity impact of cycling infrastructure allocation: Implications for planning practice. Transport Policy, 133(December 2022), 15–26. https://doi.org/10.1016/j.tranpol.2022.12.021
Cunha, I., Silva, C., & Büttner, B. (2023). Practitioners’ perspectives on cycling equity: Bridging the gap between planning priorities. Transportation Research Part D: Transport and Environment, 123(July), 103902. https://doi.org/10.1016/j.trd.2023.103902
Cunha, I., Silva, C., Büttner, B., & Toivonen, T. (2024). Pursuing cycling equity? A mixed-methods analysis of cycling plans in European cities. Transport Policy, 145(October 2023), 237–246. https://doi.org/10.1016/j.tranpol.2023.11.001
De Angelis, M., Mantecchini, L., & Pietrantoni, L. (2021). A cluster analysis of university commuters: Attitudes, personal norms and constraints, and travel satisfaction. International Journal of Environmental Research and Public Health, 18(9), 4592. https://doi.org/10.3390/ijerph18094592
De Wet, T., Dzinotyiweyi, T., & Ellison, G. T. H. (2021). How might bicycle ownership/access and cycling expertise influence the design of cycling promotion interventions at the University of Johannesburg? Journal of American College Health, 69(8), 842–850. https://doi.org/10.1080/07448481.2020.1711761
Delmelle, E. M., & Delmelle, E. C. (2012). Exploring spatio-temporal commuting patterns in a university environment. Transport Policy, 21, 1–9. https://doi.org/10.1016/j.tranpol.2011.12.007
Efe, M., Demirbag, M., & Katharina, B. (2018). Electric mobility in Europe : A comprehensive review of motivators and barriers in decision making processes. Transportation Research Part A, 109(January), 1–13. https://doi.org/10.1016/j.tra.2018.01.017
Etminani-Ghasrodashti, R., Paydar, M., & Hamidi, S. (2018). University-related travel behavior: Young adults’ decision making in Iran. Sustainable Cities and Society, 43(May), 495–508. https://doi.org/10.1016/j.scs.2018.09.011
Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). Thousand Oaks, CA: Sage Publications.
Gössling, S. (2020). Integrating e-scooters in urban transportation: Problems, policies, and the prospect of system change. Transportation Research Part D: Transport and Environment, 79(January), 102230. https://doi.org/10.1016/j.trd.2020.102230
Havet, N., & Bouzouina, L. (2024). Bicycle use in the university community: Empirical analysis using MobiCampus-UdL data (Lyon, France). Journal of Transport and Land Use, 17(1), 299–320.
Henning, E., Ferreira Schubert, T., & Ceccatto Maciel, A. (2020). Modelling of university student transport mode choice in Joinville: A binary logistic model for active modes. Journal of Sustainable Development of Energy, Water and Environment Systems, 8(4), 678–691. https://doi.org/10.13044/j.sdewes.d7.0303
Huo, J., Yang, H., Li, C., Zheng, R., Yang, L., & Wen, Y. (2021). Influence of the built environment on E-scooter sharing ridership: A tale of five cities. Journal of Transport Geography, 93(May), 103084. https://doi.org/10.1016/j.jtrangeo.2021.103084
Ibrahim, A. N. H., Borhan, M. N., Darus, N. S., Yunin, N. A. M., & Ismail, R. (2022). Understanding the willingness of students to use bicycles for sustainable commuting in a university setting: A structural equation modelling approach. Mathematics, 10(6), 861. https://doi.org/10.3390/math10060861
Kelarestaghi, K. B., Ermagun, A., & Heaslip, K. P. (2019). Cycling usage and frequency determinants in college campuses. Cities, 90(February), 216–228. https://doi.org/10.1016/j.cities.2019.02.004
King, S. B., Kaczynski, A. T., Knight Wilt, J., & Stowe, E. W. (2020). Walkability 101: A multi-method assessment of the walkability at a university campus. SAGE Open, 10(2), 1–19. https://doi.org/10.1177/2158244020917954
Kinigadner, J., Büttner, B., Wulfhorst, G., & Vale, D. (2020). Planning for low carbon mobility: Impacts of transport interventions and location on carbon-based accessibility. Journal of Transport Geography, 87(November 2019), 102797. https://doi.org/10.1016/j.jtrangeo.2020.102797
Kutela, B., & Teng, H. (2019). The influence of campus characteristics, temporal factors, and weather events on campuses-related daily bike-share trips. Journal of Transport Geography, 78(November 2018), 160–169. https://doi.org/10.1016/j.jtrangeo.2019.06.002
Lopes, M., Mélice Dias, A., & Silva, C. (2021). The impact of urban features in cycling potential – A tale of Portuguese cities. Journal of Transport Geography, 95(June), 103149. https://doi.org/10.1016/j.jtrangeo.2021.103149
Lundberg, B., & Weber, J. (2014). Non-motorized transport and university populations: An analysis of connectivity and network perceptions. Journal of Transport Geography, 39, 165–178. https://doi.org/10.1016/j.jtrangeo.2014.07.002
Maas, S., Attard, M., & Caruana, M. A. (2020). Assessing spatial and social dimensions of shared bicycle use in a Southern European island context: The case of Las Palmas de Gran Canaria. Transportation Research Part A: Policy and Practice, 140(December 2019), 81–97. https://doi.org/10.1016/j.tra.2020.08.003
Marquet, O., & Miralles-Guasch, C. (2014). Walking short distances. The socioeconomic drivers for the use of proximity in everyday mobility in Barcelona. Transportation Research Part A: Policy and Practice, 70, 210–222. https://doi.org/10.1016/j.tra.2014.10.007
Martin, A., Suhrcke, M., & Ogilvie, D. (2012). Financial incentives to promote active travel: An evidence review and economic framework. American Journal of Preventive Medicine, 43(6), e45–e57. https://doi.org/10.1016/j.amepre.2012.09.001
Mateo-Babiano, I., Tiglao, N. M. C., Mayuga, K. A., Mercado, M. A., & Abis, R. C. (2020). How can universities in emerging economies support a more thriving cycling culture? Transportation Research Part D: Transport and Environment, 86(July), 102444. https://doi.org/10.1016/j.trd.2020.102444
Moosavi, S. M. H., Ma, Z., Armaghani, D. J., Aghaabbasi, M., Ganggayah, M. D., Wah, Y. C., & Ulrikh, D. V. (2022). Understanding and predicting the usage of shared electric scooter services on university campuses. Applied Sciences (Switzerland), 12(18), 9392. https://doi.org/10.3390/app12189392
Moreno, C., Allam, Z., Chabaud, D., Gall, C., & Pratlong, F. (2021). Introducing the “15-minute city”: Sustainability, resilience and place identity in future post-pandemic cities. Smart Cities, 4(1), 93–111. https://doi.org/10.3390/smartcities4010006
Nahal, T., & Mitra, R. (2018). Facilitators and barriers to winter cycling: Case study of a downtown university in Toronto, Canada. Journal of Transport and Health, 10(May), 262–271. https://doi.org/10.1016/j.jth.2018.05.012
Nematchoua, M. K., Deuse, C., Cools, M., & Reiter, S. (2020). Evaluation of the potential of classic and electric bicycle commuting as an impetus for the transition towards environmentally sustainable cities: A case study of the university campuses in Liege, Belgium. Renewable and Sustainable Energy Reviews, 119(June 2019), 109544. https://doi.org/10.1016/j.rser.2019.109544
Nikiforiadis, A., Paschalidis, E., Stamatiadis, N., Paloka, N., Tsekoura, E., & Basbas, S. (2023). E-scooters and other mode trip chaining: Preferences and attitudes of university students. Transportation Research Part A: Policy and Practice, 170(December 2022), 103636. https://doi.org/10.1016/j.tra.2023.103636
Pajares, E., Büttner, B., Jehle, U., Nichols, A., & Wulfhorst, G. (2021). Accessibility by proximity: Addressing the lack of interactive accessibility instruments for active mobility. Journal of Transport Geography, 93, 103080. https://doi.org/10.1016/j.jtrangeo.2021.103080
Park, Y., & Akar, G. (2019). Understanding the effects of individual attitudes, perceptions, and residential neighborhood types on university commuters’ bicycling decisions. Journal of Transport and Land Use, 12(1), 419–441. https://doi.org/10.5198/jtlu.2019.1259
Pazhuhan, M., Soltani, A., Ghadami, M., Shahraki, S. Z., & Salvati, L. (2022). Environmentally friendly behaviors and commuting patterns among tertiary students: The case of University of Tehran, Iran. Environment, Development and Sustainability, 24(5), 7435–7454. https://doi.org/10.1007/s10668-022-02266-x
Pereira, R. H. M. (2019). Future accessibility impacts of transport policy scenarios: Equity and sensitivity to travel time thresholds for bus rapid transit expansion in Rio de Janeiro. Journal of Transport Geography, 74(March 2018), 321–332. https://doi.org/10.1016/j.jtrangeo.2018.12.005
Rahman, Z., Nostikasari, D., Donavalli, B., Madanu, S., Roeglin, N., Mattingly, S., & Casey, C. (2018). Evaluating bicycle and pedestrian infrastructure in environmental justice communities. Journal of Transport & Health, 9, S53–S54. https://doi.org/10.1016/j.jth.2018.05.040
Ribeiro, P., Fonseca, F., & Meireles, T. (2020). Sustainable mobility patterns to university campuses: Evaluation and constraints. Case Studies on Transport Policy, 8(2), 639–647. https://doi.org/10.1016/j.cstp.2020.02.005
Ribeiro, P. J. G., & Fonseca, F. (2022). Students’ home-university commuting patterns: A shift towards more sustainable modes of transport. Case Studies on Transport Policy, 10(2), 954–964. https://doi.org/10.1016/j.cstp.2022.03.009
Rybarczyk, G., & Gallagher, L. (2014). Measuring the potential for bicycling and walking at a metropolitan commuter university. Journal of Transport Geography, 39, 1–10. https://doi.org/10.1016/j.jtrangeo.2014.06.009
Schneider, R. J., & Willman, J. L. (2019). Move closer and get active: How to make urban University commutes more satisfying. Transportation Research Part F: Traffic Psychology and Behavior, 60, 462–473. https://doi.org/10.1016/j.trf.2018.11.001
Silva, C., Teixeira, J., Proença, A., Bicalho, T., Cunha, I., & Aguiar, A. (2019). Revealing the cycling potential of starter cycling cities: Usefulness for planning practice. Transport Policy, 81(April), 138–147. https://doi.org/10.1016/j.tranpol.2019.05.011
Sims, D., Bopp, M., & Wilson, O. W. A. (2018). Examining influences on active travel by sex among college students. Journal of Transport and Health, 9(May), 73–82. https://doi.org/10.1016/j.jth.2018.05.009
Small, K. A., Economics, U. T., Verhoef, E. T., Small, K. A., Verhoef, E. T., & Economics, S. (2007). The Economics of Urban Transportation. Abingdon-on-Thames, Oxforshire, England: Routledge.
Soria-Lara, J. A., Marquet, O., & Miralles-Guasch, C. (2017). The influence of location, socioeconomics, and behavior on travel-demand by car in metropolitan university campuses. Transportation Research Part D: Transport and Environment, 53, 149–160. https://doi.org/10.1016/j.trd.2017.04.008
Sorkou, T., Tzouras, P. G., Koliou, K., Mitropoulos, L., Karolemeas, C., & Kepaptsoglou, K. (2022). An approach to model the willingness to use of e-scooter sharing services in different urban road environments. Sustainability (Switzerland), 14(23), 1–15. https://doi.org/10.3390/su142315680
Stein, P. P., & Rodrigues da Silva, A. N. (2018). Barriers, motivators and strategies for sustainable mobility at the USP campus in São Carlos, Brazil. Case Studies on Transport Policy, 6(3), 329–335. https://doi.org/10.1016/j.cstp.2017.11.007
Sun, G., Oreskovic, N. M., & Lin, H. (2014). How do changes to the built environment influence walking behaviors? A longitudinal study within a university campus in Hong Kong. International Journal of Health Geographics, 13, 1–10. https://doi.org/10.1186/1476-072X-13-28
Teixeira, J., & Cunha, I. (2023). The effects of COVID-19 on female and male bike sharing users: Insights from Lisbon’s GIRA. Cities, 132, 104058. https://doi.org/10.1016/j.cities.2022.104058
Thigpen, C. (2019). Do bicycling experiences and exposure influence bicycling skills and attitudes? Evidence from a bicycle-friendly university. Transportation Research Part A: Policy and Practice, 123(June 2018), 68–79. https://doi.org/10.1016/j.tra.2018.05.017
Tolley, R. (1996). Green campuses: Cutting the environmental cost of commuting. Journal of Transport Geography, 4(3), 213–217. https://doi.org/10.1016/0966-6923(96)00022-1
Tormo-Lancero, M. T., Valero-Mora, P., Sanmartin, J., Sánchez-García, M., Papantoniou, P., Yannis, G., … & Campos-Díaz, E. (2022). Development of a roadmap for the implementation of a sustainable mobility action plan in university campuses of emerging countries. Frontiers in Sustainable Cities, 3(January), 1–13. https://doi.org/10.3389/frsc.2021.668185
van Nijen, N., Ulak, M. B., Veenstra, S., & Geurs, K. (2024). Exploring factors affecting route choice of cyclists: A novel varying-contiguity spatially lagged exogenous modeling approach. Journal of Transport and Land Use, 17(1), 557–577.
Wang, C. H., Akar, G., & Guldmann, J. M. (2015). Do your neighbors affect your bicycling choice? A spatial probit model for bicycling to The Ohio State University. Journal of Transport Geography, 42, 122–130. https://doi.org/10.1016/j.jtrangeo.2014.12.003
Wang, K., & Akar, G. (2019). Gender gap generators for bike share ridership: Evidence from Citi Bike system in New York City. Journal of Transport Geography, 76(February), 1–9. https://doi.org/10.1016/j.jtrangeo.2019.02.003
Washington, S., Karlaftis, M., & Mannering, F. (2011). Statistical and econometric methods for transportation data analysis. Oxfordshire, England: Taylor & Francis.
Whalen, K. E., Páez, A., & Carrasco, J. A. (2013). Mode choice of university students commuting to school and the role of active travel. Journal of Transport Geography, 31, 132–142. https://doi.org/10.1016/j.jtrangeo.2013.06.008
Wilkinson, S., & Badwan, K. (2021). Walk this way: The rhythmic mobilities of university students in Greater Manchester, UK. Mobilities, 16(3), 373–387. https://doi.org/10.1080/17450101.2020.1833565
Wilson, O., Vairo, N., Bopp, M., Sims, D., Dutt, K., & Pinkos, B. (2018). Best practices for promoting cycling among university students and employees. Journal of Transport and Health, 9(November 2017), 234–243. https://doi.org/10.1016/j.jth.2018.02.007
Zhan, G., Yan, X., Zhu, S., & Wang, Y. (2016). Using hierarchical tree-based regression model to examine university student travel frequency and mode choice patterns in China. Transport Policy, 45, 55–65. https://doi.org/10.1016/j.tranpol.2015.09.006
Zhang, Y., & Xiaowei, H. (2024). The nonlinear impact of cycling environment on bicycle distance: A perspective combining objective and perceptual dimensions. Journal of Transport and Land Use, 17(1), 241–267.
Zhou, J. (2012). Sustainable commute in a car-dominant city: Factors affecting alternative mode choices among university students. Transportation Research Part A: Policy and Practice, 46(7), 1013–1029. https://doi.org/10.1016/j.tra.2012.04.001
Zhou, J. (2014). From better understandings to proactive actions: Housing location and commuting mode choices among university students. Transport Policy, 33, 166–175. https://doi.org/10.1016/j.tranpol.2014.03.004
Zhou, J. (2016). Proactive sustainable university transportation: Marginal effects, intrinsic values, and university students’ mode choice. International Journal of Sustainable Transportation, 10(9), 815–824. https://doi.org/10.1080/15568318.2016.1159357