Singapore Airlines: Profit recovery and aircraft allocation models during the COVID-19 pandemic

COVID-19 has severely impacted the global aviation industry, causing many airlines to downsize or exit the industry. For airlines which attempt to sustain their operations, they will need to respond to the increase in passenger and cargo demand, as countries recover slowly from the crisis due to the...

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Main Authors: CHEONG, Michelle L. F., CHONG, Ulysses M. Z., NGUYEN, Anne N. T. A., ANG, Su Yiin, DJOJOSAPUTRO, Gabriella P., ADIPRASETYO, Gordy, GADONG, Kendra L. B.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/6029
https://ink.library.smu.edu.sg/context/sis_research/article/7032/viewcontent/Singapore_Airlines_Profit_recovery_and_aircraft_allocation_model.pdf
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Institution: Singapore Management University
Language: English
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Summary:COVID-19 has severely impacted the global aviation industry, causing many airlines to downsize or exit the industry. For airlines which attempt to sustain their operations, they will need to respond to the increase in passenger and cargo demand, as countries recover slowly from the crisis due to the availability of vaccines. We built a series of spreadsheet models to first project the COVID-19 recovery rates by countries from 2021 to 2025, then forecast the passenger and cargo demand, using historical data as base figures. Using the financial and operation data, the revenue, expense, and profit can be projected, then an optimization model is used to determine the optimal number of aircrafts to be allocated to passenger and cargo respectively, and the number of aircrafts to be put into storage. We applied our models to data extracted on 26 October 2020 to obtain insights on the impact of COVID-19 on Singapore Airline’s profit recovery and aircraft allocation. Our sensitivity analysis shows that Singapore Airline’s profitability and aircraft allocation in 2023 and 2024 will be very sensitive to the vaccine release date. Our models can be applied to another airline, by replacing the financial and operation data, to provide similar insights.