PhD Thesis Defense Presentation: Sena Onen Oz
Sena Onen Oz, a doctoral student at 51吃瓜网 in the Operations Management area will be presenting her thesis defense entitled:
Essays on Paid Street Parking Involving Pricing Strategies and Driver Behavior
Friday, August 8, 2025, at 9:00 a.m.
(The defense will be conducted in hybrid mode)
Student Committee Co-chairs: Professor Mehmet Gumus and Professor Wei Qi
Please note that the Defence will be conducted in hybrid mode. If you wish to participate, please contact the PhD office and we will provide you with the defence details.
Abstract
With growing concerns about urban congestion and the environmental impact of city transportation, this dissertation focuses on improving on-street urban parking systems from both a behavioral and operational perspective through two research projects. In the first study, we examine how different payment methods and hourly parking prices affect drivers鈥� parking payment amounts, street parking occupancy, and the search time to find an available parking spot. To do so, we first utilize data from an online survey in which we ask participants to specify their payment amounts under different scenarios. Our survey shows that participants assigned to the mobile payment option significantly pay less than participants assigned to the credit card or cash options. Using high-resolution transaction data provided by a municipal agency in a densely populated North American city, we also examine the effect of price and its interaction with the payment methods. This analysis reveals that, contrary to common assumptions in street parking planning, a driver鈥檚 payment amount is influenced not only by the parking price but also by its interaction with the payment method used. As the change in the payment amount would eventually affect occupancy and search time, we conduct a counterfactual analysis using a discrete event simulation. With this simulation, we further demonstrate that progressive pricing, along with mobile payment adoption, significantly impacts both search time and occupancy compared to linear pricing. In the second study, we aim to design a more accessible pricing strategy that cities could implement without expensive infrastructure. This study begins by investigating the factors influencing drivers鈥� parking preferences. Inspired by consumer behavior theory, this part of the study treats parking spaces as substitutable products and explores how drivers make choices under different parking attributes, such as price, distance to destination, and likelihood of extension. Our findings from the survey emphasize that drivers鈥� utility decreases as the levels of the parking attributes increase. In the second part of the study, we develop a strategic pricing model to optimize urban parking efficiency. Using the findings from our choice-based conjoint analysis, we dynamically incorporate predicted demand shifts based on pricing and spatial attributes into our optimization model, unlike traditional models that assume static demand. The optimization results show that (1) linear pricing leads to significant revenue loss, (2) both progressive and street-based pricing lead to higher revenue and occupancy, and their effectiveness depends on street characteristics and user behavior, and (3) the relative advantage of having a differentiated pricing policy compared to linear pricing peaks in medium duration and medium capacity environments where behavioral responsiveness and supply conditions are optimally aligned. In conclusion, this dissertation underscores the value of integrating behavioral insights into operational models to design adaptive parking systems that are both effective and implementable in real world urban contexts.
