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Task-level causal effects of maintenance staffing shortages on aircraft-on-ground (AOG) and reliability

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  • Dela Peña, Arthur C.
  • Rutao, Meredith I.

Abstract

Staffing shortages in aircraft maintenance are a critical driver of operational cost and reliability, yet most studies focus on aggregated effects, obscuring task-level dynamics. This study provides quasi-experimental evidence linking staffing intensity (SI) and skill mix (SM) to aircraft-on-ground (AOG) exposure, deferrals, and repair reliability in a multi-base Maintenance, Repair, and Overhaul (MRO) setting. Using 24–36 months of operational data across five stations, we apply a staggered difference-in-differences event-study design, Cox proportional hazards modeling, and mediation analysis to estimate direct and indirect effects of staffing fluctuations. Shortage episodes are identified using station-specific SI thresholds, with outcomes measured in AOG minutes, deferrals per 100 departures, and time-to-closure. Results show shortages increase AOG exposure by 0.10 per 1000 flight hours and deferrals by 0.07 per 100 departures. Higher SI accelerates closure (Hazard Ratio HR ≈ 1.11) and reduces repeat-defect risk (OR 0.88–0.91), with two-thirds of the effect mediated through variance in turnaround time (TAT) and deferral reduction. Effects are concentrated at night, during rainfall, at smaller bases, and in Air Transport Association (ATA) 21/24 systems. Policy simulations show skill-mix upgrades yield the lowest cost per AOG-minute avoided, offering actionable strategies for risk-based staffing and predictive rostering.

Suggested Citation

  • Dela Peña, Arthur C. & Rutao, Meredith I., 2026. "Task-level causal effects of maintenance staffing shortages on aircraft-on-ground (AOG) and reliability," Research in Transportation Economics, Elsevier, vol. 115(C).
    • Handle: RePEc:eee:retrec:v:115:y:2026:i:c:s0739885925001842
    DOI: 10.1016/j.retrec.2025.101701
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    References listed on IDEAS

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    1. Matias D. Cattaneo & Luke Keele & Rocio Titiunik, 2021. "Covariate Adjustment in Regression Discontinuity Designs," Papers 2110.08410, arXiv.org, revised Aug 2022.
    2. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    3. Rogerio Adriano da Fonseca Santiago & Natasha Benjamim Barbosa & Henrique Gomes Mergulhão & Tassio Farias de Carvalho & Alex Alisson Bandeira Santos & Ricardo Cerqueira Medrado & Jose Bione de Melo Fi, 2024. "Data-Driven Models Applied to Predictive and Prescriptive Maintenance of Wind Turbine: A Systematic Review of Approaches Based on Failure Detection, Diagnosis, and Prognosis," Energies, MDPI, vol. 17(5), pages 1-24, February.
    4. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    5. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
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