Global airlines: Modeling profitability and portfolio for allocation to international regions

This dissertation examines an alternative strategic planning method allocating airline seats to international regions. Portfolio theory is adapted to the U.S. global airline industry where available seat miles are allocated to the Asia/Pacific, European and Latin American regions based on measures of risk. Empirical airline data collected from Bureau of Transportation Statistics was used to develop OLS linear regression and multi-objective optimization models that allocate the optimal percentage of available seat miles to maximize operating profits while minimizing the risk of losing operating profits. This dissertation examines the differences in three model specifications and compares the optimal solutions to actual results obtained by U.S. global airlines. First, the Mean-Variance approach is used, followed by the second approach, the Mean-Value-at-Risk (VaR) approach, and finally, the third optimization approach that uses Value-at-Risk and OLS regression model parameter estimates for optimization model development.;The results of the research indicate that the three models outperform airlines' actual financial performance and improve airlines' financial standing through diversification. The Mean-Variance and Regression-VaR approaches return similar optimization results while the Mean-VaR approach routinely outperforms the other two approaches.