Flight Overbooking Models and Decisions

• Fang, Yue 

Abstract

United　Airlines　Inc.　(UAL)　is　a　major　American　airline　headquartered　in　Chicago　with　nine　domestic　and　international　hubs.　It　serves　342　destinations,　more　than　any　other　airline　does,　and　ranks　second　in　the　world　by　the　number　of　passenger-kilometers　flown　by　an　airline.
United　Airlines　Flight　3411　made　headline　news　on　April　9,　2017　after　an　involuntarily　denied　boarding　(IDB)　selection　process　resulted　in　passenger　David　Dao　being　forcibly　removed　from　the　aircraft　by　airport　police.　United　management　had　demanded　that　Dao　give　up　his　seat　on　the　overbooked　flight　for　United　employees　making　a　connecting　flight,　but　Dao　refused　and　the　situation　escalated　into　violence　with　airport　police.　
Airlines　routinely　sell　more　tickets　than　available　seats　to　compensate　for　cancellations　and　no-shows.　Overbooking　helps　airlines　maximize　revenues　and　is　perfectly　legal.　However,　the　practice　also　comes　with　risks,　as　evidenced　by　the　United　Airlines　incident　that　publicly　exposed　flaws　of　the　airline　overbooking　profit　model.　Why　do　airlines　overbook?　How　do　they　use　the　model　to　maximize　revenues?　What　are　the　appropriate　booking　limits?　In　this　case,　students　will　address　these　questions　after　learning　how　to　model　cancellation　and　no-show　uncertainty　using　the　simulation-based　overbooking　model　and　hence　improve　their　decision-making　ability　in　a　complex　and　uncertain　environment.

Keyword

• booking limits
• data analytics
• decision-making
• Monte Carlo Simulation
• optimization model formulation
• profit model
• revenue management

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