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The aviation sector is critical in world connectivity but is subject to financial shocks because of capital-intensity and its dependence on several external factors, with fuel prices, global crises, and economic downturns as some of the main actors. Financial Crisis in Airlines results in a halt in operations, layoffs, and huge losses for the stakeholders. Therefore, early prediction of distress is important to sustain the system. The study assesses the financial status of about five airlines SpiceJet, AirAsia, Alliance Air, Emirates and IndiGo for the ensuing period of five years from 2020 to 2024. The paper uses secondary, audited financial statement data and the following four well-documented models to predict financial distress: Altman Z-Score, Ohlson O-Score, Zmijewski Model and the fourth is Pilarski P-Score. All the models take a distinct aspect of financial performance which are liquidity, profitability, leverage and efficiency, respectively. All the financial risk of SpiceJet is high consecutively, but Emirates has a very strong financial health consecutively, with IndiGo, while maintaining stability based on the analysis. AirAsia and Alliance Air on the path to recover. It also compares the predictive success of each model and concludes that the choice of model may greatly affect distress classifications. The results impart high-rated implications for airlines management, investors and policy makers to develop preemptive strategies in order to strengthen financial resilience.
"A Study On Financial Distress Prediction On Aviation Industry ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.10, Issue 4, page no.d1-d5, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504301.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator