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Cette présentation sera précédée par celle de Quan Zhou.

City dwellers often struggle with on-street parking in many cities, where they generally need to pay for parking in advance. However, drivers usually cannot accurately foresee how much parking time they need. Compared to traditional payment methods, i.e., cash and credit card through on-site meters, mobile payment applications provide more flexibility: Drivers can adjust their parking sessions remotely if a longer stay is in need. Utilizing data from an online survey and high-resolution transaction records provided by a municipal agency in a densely populated North American city, we analyze how different payment methods and hourly parking prices affect drivers' parking behavior, street parking occupancy, and search time to find an available parking spot. Our findings reveal that mobile payments facilitate shorter parking duration, which in turn improves the turnover rate of parking spaces and reduces the overall search time. Furthermore, we observe that a driver's parking behavior is not solely determined by price or payment method but rather by the interaction of both factors, making it essential for any policy analysis to consider this interplay. In particular, lower hourly rates lead to higher payments, with this effect being most pronounced for cash payments and second most pronounced for mobile payments in comparison to credit card payments. To provide further guidance to municipalities, we simulate street parking to show that a driver's behavior is shaped by the interaction between price and payment method, which in turn affects occupancy and search time. Our simulation study finds that progressive pricing and mobile payment adoption, along with pricing strategies, significantly impact both operational metrics compared to constant pricing.