An integrated Markov decision process and nested logit consumer response model of air ticket pricing

The paper attempts to propose an optimal air ticket pricing model during the booking horizon by taking into account passengers' purchasing behavior of air tickets. A Markov decision process incorporating a nested logit consumer response model is established to modeling the dynamic pricing process. The proposed model is estimated and applied using the data collected in a multi-airport region with competition in China. Results indicate that, by considering air ticket purchasing behavior, air ticket price can be set dynamically and optically in response to the changes in exogenous factors which are not controlled by airlines.