Abstract:

Professionals have developed new pricing plans and methods as a result of market globalisation, which boosts worldwide competitiveness. In order to determine the best pricing strategy, airline firms frequently adjust the cost of tickets by taking into account a number of variables based on their own proprietary rules and algorithms. Artificial Intelligence (AI) models have been used recently for the latter job because of its various potentials in data generalisation, compactness, and quick adaptation. This study uses artificial intelligence (AI) techniques to analyse ticket price prediction in order to identify commonalities in the pricing strategies of various airline firms. More precisely, 136.917 data flights of Aegean, Turkish, Austrian, and Lufthansa Airlines for six well-known worldwide locations are used to extract a set of useful attributes. After the characteristics have been retrieved, a comprehensive analysis is carried out from the viewpoint of the customer looking for the cheapest ticket price, taking into account both an airline-based assessment that includes all destinations and a destination-based evaluation that includes all airlines.

Description:

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