Understanding Factors Influencing Cycling Behaviour Among University Students and Staff: A Cross-Sectional Study

Isabel M. Martín-López, Olalla García-Taibo (), Antoni Aguiló and Pere Antoni Borràs
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Isabel M. Martín-López: Department of Physical Activity and Sport Sciences, CESAG, Comillas Pontifical University, 07013 Palma de Mallorca, Spain
Olalla García-Taibo: Department of Pedagogy and Specific Didactics, Balearic Islands University, 07122 Palma de Mallorca, Spain
Antoni Aguiló: Department of Nursing and Physiotherapy, Balearic Islands University, 07122 Palma de Mallorca, Spain
Pere Antoni Borràs: Department of Pedagogy and Specific Didactics, Balearic Islands University, 07122 Palma de Mallorca, Spain

Social Sciences, 2025, vol. 14, issue 5, 1-16

Abstract: Active commuting by bicycle offers health and environmental benefits, yet it remains uncommon among university populations. This study aimed to identify key factors influencing bicycle commuting among university students and staff based on cyclist typology and to assess the applicability of the Theory of Planned Behaviour (TPB) and socio-ecological models. A total of 305 students and 79 staff completed a questionnaire assessing sociodemographic, psychological, social, and environmental variables. Results revealed significant differences based on cyclist typology. Urban cyclists reported fewer perceived barriers (1.96 ± 0.59) and more advantages (3.61 ± 0.40) than non-cyclists (2.71 ± 0.56 and 3.26 ± 0.49, respectively; p < 0.001). While personal and psychological factors were most influential for non-cyclists, environmental aspects were more relevant for urban cyclists and cyclists. Multinomial logistic regression showed that for both cyclists and urban cyclists, bicycle ownership (OR = 0.098–0.104, p < 0.001) and intention to use (OR = 0.091–0.358, p ≤ 0.02) were key predictors of cycling behaviour. Although gender was only a significant predictor for cyclists (OR = 3.41, p = 0.003), this variable did not influence urban cycling behaviour. These findings support using TPB and socio-ecological models to design targeted, multilevel interventions.

Keywords: active transportation; sustainable mobility; health behaviour; bicycle; barriers; enablers; higher education (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2025
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