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This paper studies the market entry patterns and evolving strategies adopted by Southwest and JetBlue. Based on the quarterly data from US T100 Domestic Segment database, we trace Southwest's successful market entries from 1993 to 2016, and those of JetBlue from 2000 to 2016, and estimate a set of discrete choice models to investigate the factors that may attract or deter route entries by Southwest and JetBlue. These factors reflect route distance, traffic demand, market power of the carriers, route competition, and connectivity and traffic concentration at endpoint airports, etc. The paper also examines the similarity and dissimilarity between Southwest and JetBlue with respect to the effects of these factors on their entry decisions, and how their route entry decisions have evolved over time. Our results indicate that both Southwest and JetBlue are more likely to enter routes where they have higher market share in terms of traffic and connectivity at endpoint airports, but they are less likely to enter routes involving endpoint airports with higher concentration in either traffic or connectivity. While Southwest appears to prefer routes with short to medium distance in the 1990s, it has started to target longer distance routes since 2000. JetBlue has consistently preferred longer distance routes. While the number of legacy rivals on a given route may deter market entry by Southwest, it does not appear to have any significant effect on the entry decisions by JetBlue. Moreover, the presence of other LCCs may have deterred the market entry by Southwest during the 1993–1999 period, and by JetBlue during the 2000–2006 period, its entry-deterrence effects has been becoming less important as the two airlines continue their growth and market expansion. The results further suggest that Southwest has continued to be hesitant to enter routes that have asymmetric traffic volume at endpoint airports, but it has become more drawn to routes with broader connections and higher traffic at endpoint airports as it moves into the business passenger segment. [ABSTRACT FROM AUTHOR]

Highlights: [•] We study efficiency of 44 US airports including delays, noise and local pollution. [•] We perform a directional distance function and a second-stage analysis. [•] With no bad outputs greater aircraft size leads to higher technical efficiency. [•] The larger the dimensions of the airport the higher the technical efficiency. [•] Results are sensitive to the inclusion of the undesirable outputs. [Copyright &y& Elsevier]

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