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

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  • Yasin Alan
  • Michael A. Lapré

Abstract

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.

Suggested Citation

  • Yasin Alan & Michael A. Lapré, 2018. "Investigating Operational Predictors of Future Financial Distress in the US Airline Industry," Production and Operations Management, Production and Operations Management Society, vol. 27(4), pages 734-755, April.
    • Handle: RePEc:bla:popmgt:v:27:y:2018:i:4:p:734-755
    DOI: 10.1111/poms.12829
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    Cited by:

    1. Dominik Schreyer, 2019. "Football spectator no-show behaviour in the German Bundesliga," Applied Economics, Taylor & Francis Journals, vol. 51(45), pages 4882-4901, September.
    2. Jagjeevan Kanoujiya & Shailesh Rastogi, 2024. "Nexus between efficiency and financial distress of listed firms in India: a comparative study using frontier techniques," OPSEARCH, Springer;Operational Research Society of India, vol. 61(2), pages 835-866, June.
    3. Yuan Chen & Hsing Kenneth Cheng & Yang Liu & Jingchuan Pu & Liangfei Qiu & Ning Wang, 2022. "Knowledge‐sharing ties and equivalence in corporate online communities: A novel source to understand voluntary turnover," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3896-3913, October.
    4. L. M. Daphne Yiu & Hugo K. S. Lam & Andy C. L. Yeung & T. C. E. Cheng, 2020. "Enhancing the Financial Returns of R&D Investments through Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1658-1678, July.
    5. Jason R. W. Merrick & Claire A. Dorsey & Bo Wang & Martha Grabowski & John R. Harrald, 2022. "Measuring Prediction Accuracy in a Maritime Accident Warning System," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 819-827, February.

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