Foresight and Crisis Management of Tourism Industry in Covid-19 Pandemic Using an Artificial Neural Network Model

Tourism industry, as the most diverse and largest industry in the world, is the most important source of income and creation of job opportunities for many countries of the world, which is considered as the engine of development. Undoubtedly, such an industry is very vulnerable to all kinds of natural, human, and biological crises. The outbreak of Covid-19 crisis around the world has posed serious challenges to the industry. The purpose of this study wasto present a neural network model that has been developed by modeling the experiences of different countries in dealing with crises and their policies. Relying on its generalizability, the proposed neural network model is able to model the dynamics between the “policies/factors and conditions” governing ecosystems and the “effectiveness of the adopted policies” to determine the effectiveness of the forthcoming policies for the Corona Pandemic Crisis. Using the proposed neural network model and providing information about the policies/factors and conditions governing the Iranian tourism industry, the outputs of the model indicate that the best policy adopted to return to pre-crisis climate conditions in Iran is using the “combined” policy. "Economic and financial preparedness to deal with the crisis" in the first place and with a slight difference in policy "combined focus on domestic tourism with preparedness to deal with the crisis" is the next, which according to the criteria of sustainable tourism development and economic sanctions in Iran, the second policy is much more practical. Therefore, solutions are suggested forthese conditions, such as traditional tourism planning for domestic tourists and virtual tourism planning for foreign tourists, development of rural tourism and emphasis on creative and safe tourism.