Optimal Consumer Behavior for Buying Flight Tickets Under Price Risk

Dynamic pricing and revenue management has grown more and more popular over last decade, when internet has made dynamic pricing easy and affordable. This phenomenon has been heavily studied from company perspective, however consumer point of view is nearly completely left out. This thesis tries to answer following questions: What is the optimal time to purchase flight tickets? and which factors should be taken into account when buying a ticket. To answer above questions, ticket price data from Finnair’s website was gathered from 6 routes and 3 continents for over 4-month time period. Data contained price information from 6 different purchasing periods and actions like use of VPN was made to ensure unbiased data. Price data was collected through normal browsing mode and incognito mode to test if pricing depended of consumers browsing history. From all of the purchasing periods cheapest- and cheapest changeable ticket price was chosen to analysis. Main method used in this thesis was Stochastic Dominance. Usually Stochastic Dominance is used to rank portfolios in financial analysis, but it is also suitable method for ranking different purchasing periods. Methods main benefit is the ability to give conclusive results without knowing consumers exact utility function. As a result, it was possible to find out that 6 months before departure ranked first or second in all of the routes chosen. It was also possible to determine that in general flight tickets should be bought at least three months before departure. After this point it isn’t probable to get better bargain. It was also shown that incognito mode made no difference in ticket pricing and Finnair is not using consumer tracking in their pricing models. Analysis of cheapest- and cheapest changeable ticket revealed that price difference was generally constant between them. This study provided valuable information for consumers to determine when they should buy their flight tickets and which other factors they should take into account in the process. There are also many possibilities to expand future research such as other hospitality industries or retail business