Exploring the linkage between remote work and workation in a DT-ANN approach: an East Asia perspective

The global spread of COVID-19 gave rise to semi-compulsory telecommuting, which has facilitated new work-leisure styles, such as workations, as an alternative form of tourism that responds to post-pandemic-era challenges. We investigated 800 cases of teleworkers in Taiwan and Japan using decision tree (DT) and artificial neural network (ANN) analyses, and estimated and classified teleworkers’ experience/inexperience with workations. Our results revealed that remote workers’ society/culture and work roles were strong predictors of their experience/inexperience with workations. For both the DT and ANN models, inexperience, rather than experience, was found to be the prediction’s more suitable target category for marketers.