科研之友
微信
新浪微博
Facebook
分享链接
摘要
To mitigate the oversold penalty cost of overbooking, airlines are gradually paying attention to the intelligence-based opaque selling strategy to coordinate the capacities among flights. Using this opaque selling strategy, the airline sets a number of seats on several flights as "opaque seats" based on automatically estimated consumer attributes from big data, and the ticket buyers will not be informed about the exact flight information until a few days before departure. These flights with opaque seats should share most commonalities from a user point of view and yet have a few differences, such as close departure/arrival times or nearby departure/destination airports. These differences, however, are acceptable to customers who are insensitive to them when choosing a flight and therefore they might choose to book opaque seats in exchange for a price discount offered by the airline. To explore the effectiveness of this selling strategy, the current paper models a newsvendor problem with stochastic demand. The optimal pricing decision and capacity allocation are obtained and analyzed. Results show that there exists a relationship between the optimal allocated capacities of these flights, and the airline can adjust its capacities to the optimal values according to this relationship. Besides, the airline is suggested to allocate more capacities for opaque seats if the demand variance is high or the variation of consumer's preferences is low; on the contrary, the airline should set a lower price for the opaque seat when the variance or the variation is high. Numerical experiments are presented to show the effectiveness of opaque selling strategy, and the result indicates that in most cases this strategy brings a 40% profit increment compared to conventional strategy.
