A methodology for calculating the unmet passenger demand in the air transportation industry

Keyphrases

• Air Transportation 100%
• Airline Market 11%
• Airlines 11%
• Airport 100%
• Big Cities 11%
• Bootstrap Distribution 11%
• Confidence Level 11%
• Demand Forecasting 11%
• Demand-based 11%
• Distribution Function 22%
• Economic Conditions 11%
• Function Learning 11%
• Historical Data 11%
• Hub Airport 11%
• Machine Learning Algorithms 22%
• Market Size 33%
• Mixing Time 11%
• Number of Passengers 11%
• Number of Services 11%
• OD Pair 11%
• Origin-destination 66%
• Passenger Demand 100%
• Proposed Methodology 11%
• Risk Level 11%
• Socioeconomic Factors 11%
• Socioeconomic Variables 11%
• Statistical Analysis 11%
• Strategic Decisions 11%
• Time Series Methods 11%
• Transportation Industry 100%
• Unconstraint 11%
• Unmet 100%
• Unmet Demand 66%

Social Sciences

• Air Transportation Industry 100%
• Aircraft 10%
• Airline 20%
• Airports 100%
• Demand Forecast 10%
• Machine Learning Algorithm 20%
• Seasonal Variation 10%
• Seasonality 10%
• Time Series 10%
• USA 10%

Economics, Econometrics and Finance

• Air Transportation Industry 100%
• Airline 20%
• Airport 100%
• Machine Learning 20%
• Macroeconomic Performance 10%
• Market Size 30%
• Time Series 10%
• United States of America 10%