The aim of the present study is to identify influential factors of travel intention under the context of highly developed IT society today. Due to the development of IT and diversified ways of technology convergence, individual travelers become highly efficient in travel-related information processing. As predicted, the results of both Korean and Chinese samples show that acquaintance recommendation, autonomy, relatedness, and technology self-efficacy are significantly related with the travel information acquisition and travel intention. In this study, smartPLS, which is widely used in social science, was used. PLS is a useful analytical tool for determining causality between variables. The present study will make practical contributions by enhancing the accuracy of travel recommendation services from the perspective of technology convergence. The results of this study are expected to provide guidelines for travel-related companies to develop personalization and customization services through big data and artificial intelligence techniques when they want to design travel recommendation systems.