Using forecasting to evaluate the impact of COVID‐19 on passenger air transport demand

Abstract

The COVID‐19 pandemic caused a drastic drop in passenger air transport demand due to two forces: supply restriction and demand depression. In order for airlines to recover, the key is to identify which force they are fighting against. We propose a method for separating the two forces of COVID‐19 and evaluating the respective impact on demand. Our method involves dividing passengers into different segments based on passenger characteristics, simulating different scenarios, and predicting demand for each passenger segment in each scenario. Comparing the predictions with each other and with the real situation, we quantify the impact of COVID‐19 associated with the two forces, respectively. We apply our method to a dataset from Air France–KLM and show that from March 1st to May 31st 2020, the pandemic caused demand at the airline to drop 40.3% on average for passengers segmented based on age and purpose of travel. The 57.4% of this decline is due to demand depression, whereas the other 42.6% is due to supply restriction. In addition, we find that the impact of COVID‐19 associated with each force varies between passenger segments. The demand depression force impacted business passengers between age 41 and 60 the most, and it impacted leisure passengers between age 20 and 40 the least. The opposite result holds for the supply restriction force. We give suggestions on how airlines can plan their recovery using our results and how other industries can use our evaluation method.

Reforming global supply chain management under pandemics: The GREAT‐3Rs framework

“…To be specific, Li et al. (2021) analyze the potential influence of COVID‐19 on passenger air transport demand and make forecasts under different cases by using simulation. Their results reveal that the two forces (i.e., supply restriction and demand depression) will have opposite impacts on air transport demand concerning different passenger segments.…”

“…Li et al. (2021) and Shen & Sun (2021) examine the huge uncertainty of demand under the COVID‐19 pandemic and make efforts to address it for supply chain resilience. To be specific, Li et al.…”

Designing supply chain strategies against epidemic outbreaks such as COVID‐19: Review and future research directions

“…In their paper entitled “Using forecasting to evaluate the impact of COVID‐19 on passenger air transport demand,” Li et al. (2023) studied the impact of the COVID‐19 pandemic on passenger air transport by proposing a forecasting approach to separate the supply restriction and demand depression arising from the COVID‐19 pandemic, and subsequently evaluated the impact of each force on the passenger air transport demand. Their method includes four steps: passenger segmentation (based on predefined groups), forecasting model selection (SARIMA), scenario simulation (business as usual versus the pandemic scenario), and prediction comparison.…”

“…They also showed that the impacts of demand depression and supply restriction were heterogeneous based on passenger segments (nine segments based on age group and purpose of the trip). Finally, they offered two strategies depending on passenger segments: (1) resume flights and (2) restore passenger confidence/increase passenger willingness to fly (Li et al., 2023).…”

Recovery Period of Air Transportation: Vector Error Correction Model

“…In the fourth study, Dube et al (2021) speci ed that because of air travel is in full swing, general problems will not resolve right away. He proposed to aviation specialists that safeguarding passengers' health and safety, planning ticket prices, boosting e ciency, ensuring high-quality in-ight amenities, and maintaining such safeguards is likewise essential for the development of air tra c. In the fth study, Li et al (2021) speci ed that there was a sharp drop in passenger air travel because of the COVID-19 for two reasons. These are the breakdown of demand and supply of restrictions.…”