Forecasting recovery period of the airfreight transportation from Covid-19 pandemic by using time series modelling - Tüzün Tolga İnan (Logistics Research, 2022)
COVID-19 has a dramatically negative effect globally, so all transportation modes also airfreight have been affected negatively. This study aims to forecast the airfreight load factor by applying time series to the selected variables. After providing general information about COVID-19, the forecasting results apply to the time series modeling finding the getting back time into the recovery period. It analyzes between January 2016-May 2021 with available tonne-kilometer, revenue tonne-kilometer, load factor, gross domestic product, domestic and international freight. The findings show that the cargo load factor is affected by domestic transportation in the long-term and international transport in the short-term periods. So, airfreight is firstly affected by international transport due to its global position. The forecast results show that the recovery period started in February 2021 and will continue with a robust growth trend in July 2021 due to the changing airlines' focus on freight transportation. After the completion of vaccination, primarily related to passenger transportation, airfreight transportation also benefits from this growth trend with the configuration change of aircraft'. This paper's contribution shows the necessity to minimize the economic damage by using passenger aircraft for freight transport to increase the speed of the recovery period in terms of GDP.
Keywords: 650; COVID-19; forecasting; vector error correction model; airfreight transportation; load factor