Investigating Operational Predictors of Future Financial Distress in the US Airline Industry

We investigate the predictive power of operational performance on future financial distress in the context of the US airline industry. We focus on four areas of operational performance: revenue management, operational efficiency, service quality, and operational complexity. Using quarterly data from 1988 through 2013, we find that airlines that have inferior revenue management, lower aircraft utilization, and higher operational complexity face higher future financial distress. Interestingly, average service quality, measured by on†time performance and mishandled baggage rate, is not associated with future financial distress, but extreme service failures, measured by long delays (over two hours) and passenger complaints with the government regarding mishandled bags, have a positive association with future financial distress. Using the association between current operational performance and future financial distress, we build a model to predict financial distress. Out†of†sample analyses show that our forecasting model outperforms a financial ratio†based benchmark model up†to eight quarters before the measurement of financial distress. Our findings inform firms, regulators, and investors by demonstrating that operational performance metrics contain useful information to predict future financial distress.