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Airline Choice: A Comparison of Classifiers in Traditional Analysis vs Decision Trees

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  • Archana Shrivastava

    (Amity School of Business, Amity University Uttarpradesh, Noida, India)

  • P. James Daniel Paul

    (Ernst and Young LLP, Bengaluru, India)

  • J.K. Sharma

    (Amity School of Business, Amity University Uttarpradesh, Noida, India)

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.

Suggested Citation

  • Archana Shrivastava & P. James Daniel Paul & J.K. Sharma, 2020. "Airline Choice: A Comparison of Classifiers in Traditional Analysis vs Decision Trees," International Journal of Business Analytics (IJBAN), IGI Global, vol. 7(2), pages 34-53, April.
    • Handle: RePEc:igg:jban00:v:7:y:2020:i:2:p:34-53
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