Modelling a strategic quotation system for airline group demand

Abstract

Competition in the airline industry is a fierce environment which every airline faces on a daily basis. It is a well-known phenomenon that airlines are facing huge financial challenges and all their strategic business decisions focuses on the customer needs. The ultimate customer needs can be summed up to two main requirements, cheap travelling fares and excellent service. Having this mindset airlines have to redesign their way of selling in order to meet these requirements as much as possible. Airlines had created specific products to segment their market and strategically push their market segments in order to generate revenue. These products undergo continuous improvement processes in order to fulfil the customer needs. One of these products is group traffic. The group traffic product generates substantial revenue for an airline and deserves to have specific attention. Decision support systems (DSS) are available to manage the complexity of group traffic as their irregular behaviour impacts an airline's inventory in a critical way. This idea of this project is to develop a DSS which is capable to support the irregular behaviour of group bookings and moreover use artificial intelligence for strategic quoting. For each group quotation the application shall calculate six input variables based on flight inventory, demand, group size and request delay. These inputs will be then fuzzified by the pricing engine and a strategic group fare shall be calculated. The rules defining the Fuzzification and Defuzzification methods are built by the application based on the market's preset strategy, which will be filed with a fuzzy control language file. Strategies have to be built on good basis and not on gut feelings. In this regard a second application is built in order to simulate the group traffic behaviour which forecasts the revenues, load factors and spoilage of seats. Using Von Neumann's distributions and other modelling techniques data is generated and quoted through the strategic pricing engine. The visual group behaviour is plotted and statistics are calculated for strategy evaluation. By adjusting the simulation inputs the strategies are aligned to the desired forecasts. Managing group traffic is challenging however having the right tools will make such strategic decisions easier.