Smart parking intervention: impact on university mobility

Efficient parking management is a persistent challenge in high-density environments such as university campuses, where limited supply, fluctuating demand, and diverse user needs often result in congestion, increased search time, and user dissatisfaction. Smart-parking technologies have shown promise in urban contexts; however, there is a lack of empirical evidence that evaluates their effectiveness in academic settings. This study addresses that gap by assessing the impact of a real-time, permit-tailored, smart-parking application designed to improve parking efficiency and user satisfaction. Surveys were conducted at a large public university to measure parking behavior, perceived availability, enforcement fairness, and overall satisfaction, and the responses pre-implementation (N=873) and post-implementation (N=105) of the app were compared, using a quasi-experimental design. Ordinal logistic regression models were developed to identify and compare key satisfaction determinants across both datasets, and assumption checks confirmed the validity of the models, with variance inflation factors indicating low multicollinearity and the parallel lines test supporting the proportional odds assumption. The results revealed improvements across several key dimensions after the application’s implementation. Notable findings include reduced perceived difficulty in finding parking; fewer reports of preferred zones being full; and improved perceptions of the fairness of cost, communication of rules, and equity of enforcement. While openness to AI-driven solutions did not reach statistical significance, its post-intervention increase suggests growing acceptance of technology in parking management. The study offers actionable insights for university administrators, transportation planners, and policymakers by demonstrating how real-time, user-specific parking guidance can improve both operational outcomes and user satisfaction.