individual
What campus are you from?
Daytona Beach
Authors' Class Standing
Shivika Singh, Freshman
Lead Presenter's Name
Shivika Singh
Faculty Mentor Name
Jayendra Gokhale
Abstract
This study presents an AI-enhanced predictive model to assess airline profitability under the combined influence of macroeconomic trends and the adoption of sustainable aviation fuel (SAF). By including economic indicators such as GDP growth, inflation rates, and fuel price volatility with airline operational data, including ticket prices and fuel costs, the model simulates profitability across multiple carriers. Scenario-based analyses, encompassing optimistic, moderate, and pessimistic projections, illustrate different financial sensitivities between low-cost and legacy airlines.
Did this research project receive funding support from the Office of Undergraduate Research.
No
AI-Driven Predictive Analysis of Airline Profitability Under Macroeconomic Trends and Sustainable Fuel Adoption (SAF)
This study presents an AI-enhanced predictive model to assess airline profitability under the combined influence of macroeconomic trends and the adoption of sustainable aviation fuel (SAF). By including economic indicators such as GDP growth, inflation rates, and fuel price volatility with airline operational data, including ticket prices and fuel costs, the model simulates profitability across multiple carriers. Scenario-based analyses, encompassing optimistic, moderate, and pessimistic projections, illustrate different financial sensitivities between low-cost and legacy airlines.