Rethinking Novel Tourism Demand Modelling and Forecasting Due to COVID-19: Uncertainty, Structural Breaks and Data

Dear Colleagues,

Due to the SARS-CoV-2 virus and the resulting COVID-19 disease, many will be reading this under some type of self-isolation or mandated confinement or quarantine, or may have experienced it recently. Times of great uncertainty have a huge impact on every aspect of our lives. After we eventually overcome the health, medical, social, environmental, economic, and financial crisis which is capturing all of our present thoughts and actions, it will be necessary to implement strategies to recover from the catastrophe that this once-in-a-century phenomenon has left on our devastated planet.

Obviously, the limitations of mobility and the application of social distancing measures have had significant impacts on the tourism industry. Unlike the other major industry that contributes substantially to the world GDP (i.e., energy), tourism has been one of the most severely affected industries. The world has never experienced such a long period in which tourism was literally shut down for such an extended period. Consequently, tourism will face many challenges in the coming months and years to recover from the devastation of COVID-19.

In this context, this Special Issue focuses on the challenges faced in providing novel tourism demand modelling and forecasting methods post COVID-19. Any strategies need to be based on the behavior of inbound and outbound tourists. The primary purpose is to shed light on how we can provide insights into many important aspects of tourism demand. This covers a broad scope from theoretical to empirical contributions, as well as other important considerations, such as:

• Behavioral change;
• Uncertainty, risk, risk perception;
• Related health risks;
• Structural breaks;
• Duration of shocks;
• Limited data models and availability of data;
• Early and advanced indicators;
• Hybrid forecasting;
• Forecast based on scenarios;
• Arrivals versus revenues;
• Behavior of specific segments;
• Case studies from different origins and destinations;
• Impact of policy and industry measures;
• Linkages between tourism and economy;
• Income and price elasticities.

As the conventional modelling and forecasting of tourism demand is not likely to hold during and after the coronavirus pandemic, with or without a safe, reliable, efficient, and accessible vaccine, novel modelling and forecasting methods need to be developed. This is the intended purpose of the present Special Issue.

Dr. Vicente Ramos
Prof. Dr. Chia-Lin Chang
Prof. Dr. Michael McAleer
Guest Editors

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