The Capacity Allocation Model With Bounded-Rational Airline Passengers

Now airlines are generally adopting the revenue management systems for dynamic pricing or capacity allocation. However, traditional methods of revenue management such as EMSR are often based on the statistic laws of demand. They ignore customers’response behavior, which affect the efficiency of revenue management methods. This paper improves the classical EMSR model from the angle of bounded rationality, which can improve the effectiveness of the revenue management system.This paper mainly studies the following three problems:Firstly, it describes the airline passengers’ behavior based on prospect theory. Secondly, it uses discrete choice model and prospect theory to formulate an improved EMSR model with independent reference point. Lastly, it discusses an improved EMSR with associated reference point. For the first problem, the empirical study shows that passengers’ behavior has bounded-rationality characteristics. Furthermore, the paper explores the decision rule and utility measuration method of the passengers in revenue management situations. For the latter two issues, it calculates the transfer probability of lower price passengers, then modifies the demand distribution of higher price passengers, and computes the final capacity allocation. Numerical examples show that the improved model can significantly improve airlines’ revenue. The former model discusses the general regularity between WTP(Willingness to pay) and airlines’ revenue.The latter illustrates that reference effect will affect airlines’ revenue through analzing memory parameters.This study shows that airline passengers’ behavior has bounded-rationality characteristics. Also it verifies WTP can affect the transfer probability of passengers, which can affect the airlines’ revenue, so airlines may adjust passengers’ WTP to raise revenue through advertising and other means. In addition, passengers’ memory parameters also affect airlines’revenue. When airlines consider bounded-rational passengers, the revenue management strategies will be more effective as the memory parameters increases.