Understanding Determinants of Making Airline Entry and Exit Decisions: Application of Logit Models

Abstract

Understanding patterns of entry and exit decisions and determinants shaping the patterns are necessary for airline planners in drawing a robust route map and gaining their own competitive advantages.  The study used logit models to exam the relationship between two separate binary dependent variables: entry versus no-entry, exit versus no-exit, and multiple independent variables.  Dataset was extracted from the Bureau of Transportation Statistics DB1B for Quarter 1 of 2018, then was reconstructed based on original and destination (O&D) airport pairs to gain insights.  The entry decision pattern model yielded seven significant factors: total passengers, average market fare, number of carriers, distance, low-cost carriers (LCC) existence, origin hub, and destination hub.  In the meantime, the exit decision pattern model yielded all the seven aforementioned factors and two other significant factors: route type and the business model of the largest share airline.  The findings made a practical implication to airline network planners in considering determinants affecting entry and exit decisions to build a more efficient and profitable network.