US airlines have experienced unprecedented turbulence over the past 15 years from the 9/11 terrorist attacks and subsequent drastic reduction in air travel volumes to the global financial crisis and skyrocketing oil prices in 2008e2009 (Belobaba et al., 2015; Jang et al., 2011). These sequences of major events have caused the efficiency and productivity of US airlines to fluctuate. This change in operational efficiency has induced mergers among US carriers in order to survive in the competitive airline industry and enhance competitiveness and efficiency (Barros et al., 2013; Lenartowicz et al., 2013; Merkert and Morrell, 2012). Indeed, over the past decade, several mergers among US airlines have occurred (e.g., DeltaeNorthwest, UnitedeContinental, and SouthwesteAirTran) to varying degrees of success.

A vast amount of previous studies employ data envelopment analysis (DEA) models to quantify the efficiency and productivity of US airlines (Assaf and Josiassen, 2012; Barros et al., 2013; Cheng, 2010; Duygun et al., 2016; Franke, 2004; Lee and Worthington, 2014; Li et al., 2015; Min and Joo, 2016). Furthermore, some of recent studies have suggested the successful implementation of mergers and acquisitions (M&A) based on annual static efficiency, while others have found dynamic productivity changes in the airline sector (Barbot et al., 2008; Barros and Couto, 2013; Belobaba et al., 2011; Pires and Fernandes, 2012).

The survival strategy of individual airlines is to respond actively to changes in the technology and market structure of the airline service industry. This study, therefore, suggests strategic operational plans to cope with the fluctuations in the internal and external environment and identify best-practice US airlines that others can emulate.