Title of Paper

Measuring International Tourism Demand to the United States: System Theory Perspective

Author Bios (50 Words for each Author)

Adiyukh Berbekova is a PhD candidate at the Isenberg School of Management, University of Massachusetts, Amherst. Her research interests include crisis management in destinations, quality of life, and destination performance.

Muzaffer Uysal is a professor and chair of the Department of Hospitality and Tourism Management, Isenberg School of Management at the University of Massachusetts, Amherst. His current research interests center on tourism demand/supply interaction, impact and tourism development, and quality of life research in tourism and hospitality.

Albert George Assaf is a professor and Hadelman Family Faculty Fellow at the Isenberg School of Management, University of Massachusetts, Amherst. His work has appeared in several tourism, management, and economic journals, such as Tourism Management, Journal of Travel Research, Annals of Tourism Research, and Journal of Retailing.

Abstract (150 Words)

Identifying relevant factors that affect tourism demand is of utmost importance for destinations in planning future tourism development. Drawing on the system theory of quality of life and consumer demand theory, this study offers a novel conceptualization of tourism demand, that moves beyond a mere economic perspective. The Multilayer Perceptron Artificial Neural Network model is employed to examine the impact of diverse quality of life dimensions of both source and destination countries in predicting tourist arrivals to the United States. The findings suggest that along with traditional demand determinants (e.g. per capita income, relative exchange rate), objective quality of life indicators are significant predictors of tourism demand. The study concludes with theoretical and practical implications.

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Measuring International Tourism Demand to the United States: System Theory Perspective

Identifying relevant factors that affect tourism demand is of utmost importance for destinations in planning future tourism development. Drawing on the system theory of quality of life and consumer demand theory, this study offers a novel conceptualization of tourism demand, that moves beyond a mere economic perspective. The Multilayer Perceptron Artificial Neural Network model is employed to examine the impact of diverse quality of life dimensions of both source and destination countries in predicting tourist arrivals to the United States. The findings suggest that along with traditional demand determinants (e.g. per capita income, relative exchange rate), objective quality of life indicators are significant predictors of tourism demand. The study concludes with theoretical and practical implications.