Changes in air passenger demand as a result of the COVID-19 crisis: using Big Data to inform tourism policy.

Abstract

This paper develops a methodology for the early detection of reactivation of tourist markets to help mitigate the effects of the COVID-19 crisis, using Skyscanner data on air passenger searches (>5,000 million) and picks (>600 million), for flights between November 2018 and December 2020, through ForwardKeys. For future travel during the May to September 2020 period, the desire to travel (based on the number of flight searches) has dropped by about 30% in Europe and the Americas, and by about 50% in Asia, while intention to travel (the number of flight picks, the final selections amongst flight searches) has dropped a further 10–20%. Most source markets remain optimistic about air travel during the last quarter of 2020, suggesting a U shape recovery. However, optimism has dwindled as time passes, suggesting a flatline L shape. A traffic light dashboard for domestic and inbound air travel demand to Spain shows how destination managers might use Big Data relating to the early recovery of key source markets to develop targeted marketing strategies. We show how Big Data provides timely granular data essential in highly volatile situations, and we argue that destination management organisations must improve their Big Data analytical and evidence-based, decision-making skills.