Dataset for Benchmarking Operational Resilience and Heterogeneous Recovery of Indian Passenger Airlines after COVID-19
Description
This dataset supports the research article “Benchmarking Operational Resilience and Heterogeneous Recovery of Indian Passenger Airlines after COVID-19.” The data were compiled and processed from publicly available publications of the Directorate General of Civil Aviation (DGCA), Government of India. The analytical panel covers FY2015–16 to FY2024–25 and contains 134 airline-year observations for 22 Indian passenger airlines. The reproducibility package includes the processed master panel, variable definitions, quality and structural-event flags, analytical-cohort eligibility, pre-COVID baseline calculations, normalized passenger and passenger load factor (PLF) trajectories, common-horizon resilience profiles, descriptive recovery typologies, exploratory panel-model eligibility data, model outputs, and sensitivity analyses. The primary resilience comparison uses eight structurally comparable airlines with a pre-COVID baseline defined as the mean of FY2017–18 and FY2018–19 and a common recovery horizon from FY2020–21 to FY2022–23. The exploratory modelling panel contains 35 structurally valid post-shock airline-year observations from nine airlines. Passenger activity and PLF are treated as separate operational-resilience dimensions. Fleet change is included only as contextual information on capacity adaptation. Structural events including mergers, cessation, restructuring, entry, and partial operating years are explicitly flagged to avoid invalid longitudinal comparisons. The underlying DGCA publications remain the original public data source. Users of this dataset should acknowledge and cite the relevant DGCA publications in addition to citing this repository record.