Abstract
Service sector like aviation requires high fixed investment. The Fluctuating demand characteristic of aviation requires marketers to find ways of smoothing demand levels to match available capacity using dynamic pricing strategies. One of the main purposes of this paper is to review the price movements of low cost and full service airlines and determine the underlying variables influencing the price pattern. The methodology consisted of identifying seven independent variables to predict the price of an airline seat, price being the dependent one. Days preceding flight, day of week, month and some route dummy variables were identified as significant predictors for price of an airline seat, for both low cost and full service airlines. Airlines can use regression models to forecast prices for an airline seat so as to maximize the yield on available capacity and corresponding revenue. The vacant seats can be sold so as to fill the perishable capacity.
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