A BWS Application to Identify Factors Affecting User Preferences for Parking Choices at University Campuses

Abstract

Parking around university campuses has become a major issue in recent decades because of nearby congestion impacts. Objective: To determine the factors influencing parking lot selection, which is crucial to propose adequate parking demand management strategies. Materials and Methods: We evaluate different attributes using a best-worst scaling survey applied at Universidad de la Costa (CUC), Colombia. Using discrete choice modeling techniques, we identified the extent to which selected infrastructure attributes influence parking behavior. Results: Security and cover (roof) availability are the most relevant attributes of parking choice in the case study. Conclusions: Based on our results, we strongly recommend implementing a dynamic pricing rate, roof pricing, removing “reserved spots” and investing in security.

Walk this way: Pedestrian accessibility and equity in Barranquilla and Soledad, Colombia

“…The observed situation is the result of a historical promotion of motorised vehicles, dismissing the adoption of sustainable mobility policies that encourage active transport modes. Surely accessibility and equity issues should be incorporated in the development agenda for the cities, also considering the implementation of planning and transport policies to discourage the use of motorised transport (Arellana et al, 2012b;Orozco-Fontalvo et al, 2020;Ortúzar, 2019;Ramos et al, 2017).…”

User expectations and perceptions towards new public transport infrastructure: evaluating a cable car in Bogotá

“…Rank data and best-worst models are alternative methods to evaluate and compare perceptions and attitudes that characterize qualitative and subjective valuations. With this type of data, best-worst approximations are used to model the trip experience on public transport systems (Beck and Rose 2016), to measure the satisfaction of public transport services (Echaniz et al 2019), to identify barriers to walkability (Larranaga et al 2019), to assess the relative importance of different dimensions and criteria in logistics (Badri Ahmadi et al 2017;Rezaei et al 2018), and parking choice (Orozco-Fontalvo et al 2020). In addition, best-worst and rank data can be used to estimate consistent discrete choice models based on the random utility theory (Delle Site et al 2019).…”

Market segmentation for incentivising sustainable transport policies

“…Overcoming car dependence to promote public transport has been another challenge to achieving sustainability. To that end, car restricting policies, subsidies and parking management policies have been proposed (Guzman et al, 2020;Toro-González et al, 2020;Orozco-Fontalvo et al, 2020;Soto et al, 2018a). In that sense, the application of congestion charging has been widely accepted among academics as a measure in which the drivers are charged for the externalities they produce.…”