Bicycles are a sustainable alternative for urban mobility; however, their usage depends mainly on safety, convenience, and infrastructure availability, which have been widely studied. However, most studies have overlooked the importance of bicycle parking facilities in the network-planning process. In this work we aim to draw attention to the importance of including bicycle parking (BP) facilities in a well-thought-out bicycle infrastructure planning process highlighting the detrimental effects of not doing so for transportation equity, using Bogotá, Colombia, as a case study, where bicycle trips have multiplied in the last few years, reaching a 6.6 % modal share in 2019. To this end, we present a geospatial analysis and machine learning approach to assess the network coverage of bicycle parking spots. Additionally, we compared the city's bicycle trip patterns and applied a survey to know the perception of users (n = 397). The results show that the current distribution of bicycle parking in the city does not favour equity, given that it is not in line with the origin and destination of bicycle trips. This could widen socio-territorial inequity by affecting accessibility to bicycle use for daily commutes. To the best of our knowledge, this study presents the first assessment of the impact of parking distribution on the planning of bicycle infrastructure in the Global South.
Over the past 15 years, São Paulo, a megacity in Southeastern Brazil, has tackled its enduring mobility challenges by constructing over 500 km of bike routes and supporting various cycling initiatives, including recreational cycling programs, mobility strategies and bikeshare. Despite the generally positive impacts of these initiatives, the absence of robust causal evidence on their benefits can pose serious challenges for future investments in light of the existing social dynamic favoring the use of automobiles. Driven by the need to reduce motorized transport in Brazilian cities, we investigate the causal effects of bicycle routes on ridership between 2007 and 2017, focusing on travellers highly exposed to bike routes developed between 2008 and 2015. Using Difference-in-Differences models alongside Household Travel Surveys conducted before and after the interventions, we observed a modest but positive increase in cycling mode choice probability, ranging from 0.60 % to 1.37 %, among the highly exposed treatment groups. Our findings provide policymakers with valuable insights to support future cycling infrastructure planning and investment, demonstrating their potential net benefits even in car-dependent urban areas. By integrating these results into existing economic appraisal tools, policymakers can further assess additional benefits related to physical activity, health, and emissions reduction.