A Statistical Approach to Explore the Effects of Business Model Change on Growth for the Airline Industry

Abstract

This article proposes an approach to answering questions on whether commonly observed changes made by the airline industry to their business model are effective for the growth of their business. We took a data driven evidence-based approach where we employed statistical models to test hypotheses articulated with an aim to answering the question how changes in business model influence the overall growth of the airline industry. Some of the models used in this data driven approach are time series models, especially, Autoregressive moving average of order (m, n) (ARMA (m, n)), vector autoregressive model of order p (VAR (p)) and generalized linear mixed models (GLMM).