Predicting the resilience of hotel companies after the covid-19 health crisis

Abstract

The tourism industry is a major branch of the service sector contributing to national wealth creation. It is one of the main drivers of employment and foreign exchange drainage in the economies. However, some tragic events affect and slow down its development. Moreover, the epidemiological context of the coronavirus has deeply affected the sector, implying a total halt of all tourism activities at the national and international levels. This paper will analyze a set of resilience determinants, assisting the tourism industry during the covid-19 pandemic specifically the classified hotel units to overcome this health crisis. In an attempt to predict the resilience of hotel businesses, this study will mobilize generalized linear models, specifically the "logit" model using the binary logistic regression method. As a result, the characteristics related to the hotel environment, the strategies implemented, the personal traits of the manager, and the characteristics specific to hotel organizations contribute significantly to overcoming the negative consequences of this epidemic.