Organizational resilience of the airline industry using an Integrated epidemic and airline hub location model with traffic prediction

Epidemics can cause significant disruption and uncertainty in many aspects of human activities. Specifically, epidemics can negatively impact the airline industry and lead to flight disruptions between countries worldwide. Such disruptions can substantially impact air traffic management, affecting the roles of various airports, including hub airports that may need to be temporarily suspended. This study aims to provide insights into the impact of epidemics on air traffic management and proposes a model that identifies airports likely to play a hub role in consolidating transportation flows. To achieve this, the study offers an integrated discrete epidemic and airline hub location model to minimize transportation costs. The article also examines the organizational resilience and pro-silence of the airline industry in the context of epidemics, using machine learning techniques for predicting air passenger traffic. The developed model is optimized using the CPLEX solver over various epidemic situations. The findings suggest that dynamic localization of hubs can help miti-gate the risks associated with epidemics and that an appropriate resilience and pro-silence strategy can play a crucial role in overcoming the challenges of outbreaks