Akademik Veri Yönetim Sistemi
Journal of Policy Research in Tourism, Leisure and Events, 2026 (ESCI, Scopus)
Under the circumstances of the increased pace of technological change and growing concern with environmental issues, the complex factors of tourism demand should be studied under a strict scrutiny. The current investigation examines the nonlinear and time--varying interrelations between the artificial intelligence (AI), carbon emissions, economic growth, trade openness, exports, and tourism demand in four of the most advanced economies in the world (Germany, Japan, South Korea, and the United States) between the years 2011 and 2020. Using panel data, the research quantifies linear effects using IV-GMM and also indicates the overall variables' effects, and quantifies country-specific results using quantile-on-quantile regression (QQR) to clarify the nonlinear dynamics. This two-fold-methodology reveals strong linear and distribution-related effects of macro-economic, environmental and technological factors on tourism. According to the results of IV-GMM, AI, carbon emissions, economic growth and openness of trade have positive effects on the tourism sector, but exports have a negative average impact. On the other hand, results by QQR show large nonlinearities: AI positively impacts tourism initially but shifts to a disruptive effect at high adoption rates; carbon emissions positively affect tourism until reaching a threshold then crowding-out effects occur; economic growth impacts tourism positively but only to a point and then affects tourism adversely; the impacts of trade openness and exports change between positive and crowding-out effects with increasing intensities. These asymmetric effects indicate that the effect of each determinant on tourism not only differs in magnitude but also at different phases of both economic and tourism development.