Airline Choice

Abstract

Widespread use of e-commerce in the airline industry is generating data at unprecedented scale, thus rendering it amenable to decision analysis. Classification accuracy is one of the key factors in forecasting and in the decision sciences. The traditional classification analysis was carried out by several methods such as ANOVA, Logit, Probit. However, for decision analysis algorithms and decision trees have emerged for classification analysis. The objective of the article is to analyze the airline choice data using the traditional ANOVA and compare them with the decision trees and different algorithms.