Analysis of the Human Barriers to Using Bicycles as a Means of Transportation in Developing Cities

In the context of mounting mobility issues in Latin American cities, bicycles are emerging as a vital sustainable solution. However, their widespread adoption is hindered by various obstacles. This study aimed to identify and prioritize human factors inhibiting bicycle use in Colombia to support the development of effective public policies, given that research in this area mainly focuses on designing and developing road infrastructure for cyclists. An artificial intelligence classification methodology was applied to data from a self-administered online survey of 2068 participants. An objective variable was constructed to classify respondents as “potential users” or “non-potential users,” and three models (Logistic Regression, Random Forest, and XGBoost) were used to analyze the predictive power of different barriers. The results from the three models consistently show that personal, convenience, and safety perception barriers are significantly more important predictors than infrastructure factors. Specifically, inconvenience due to subsequent activities, perceived insecurity when cycling, and concern about sweating were consistently ranked as the most critical barriers. Therefore, to effectively promote cycling, public policies should address not only infrastructure development but also the mitigation of subjective and logistical barriers. Thus, these results can inform the design of more holistic mobility programs and serve as a foundation for future research on sustainable mobility.