Abstract: The assumption of traditional revenue management on passenger demand is independent and fails to fully account for passenger choice behavior. This paper discusses the revenue management and aircraft assignment problems considering passenger choice behavior. Observations from historical sales data reveal that passengers have a special preference for the lowest fare class. Therefore, the Spiked Multinomial Logit (Spiked -MNL) choice model is used in this paper to predict the potential real demand of passengers. Also, a joint model of revenue management and aircraft assignment considering passenger choice behavior is established, with the objective of maximizing airline profit. Case studies are conducted using actual sales transaction data from an airline to verify the feasibility of the proposed model and to evaluate its performance by comparison in different scenarios. Results show that the joint model yields an average profit of 5% higher than the independent model. In the comparison of different fleet sizes, the 5-aircraft joint model produces the highest profit, with an average profit of 6.6% higher than the 3-aircraft model and 7.3% higher than the 9-aircraft model. In addition, compared with traditional methods of predicting passenger demand using passenger choice models, the Spiked-MNL model can reflect actual passenger purchasing behavior more accurately, with an average profit of 0.7% higher than the Generalized Attraction Model (GAM) and 1.2% higher than the Multinomial Logit (MNL) model.