Forecasting a post-COVID-19 economic crisis using fuzzy cognitive maps: a Spanish tourism-sector perspective
Julio Vena-Oya, José Alberto Castañeda García, Miguel Ángel Rodríguez Molina
Abstract
Those in positions of leadership are accustomed to having to deal with complex and uncertain situations. However, the on-going COVID-19 pandemic has taken this challenge to a new level of complexity. Although econometric models are being used to predict economic scenarios relating to the fall-out from the pandemic, these forecasts do not factor-in the uncertainty generated by new changes announced weekly by policymakers. The aim of the present study is therefore to apply a fuzzy approach to develop a method for providing consistent and reliable forecasting scenarios that facilitate managers’ and policymaker’s decision-making in complex and uncertain situations. The chosen context of the study is the case of the potential consequences of COVID-19 for the international tourism sector in Spain, using fuzzy cognitive maps. This semi-quantitative model can help researchers to forecast the potential impact of major events in fuzzy or uncertain environments by constructing flexible and adaptable scenarios.