Examining the effects of industry transition to robotics, artificial intelligence, and service automation on hospitality and tourism students' critical outcomes: Quitting or quiet quitting?

Abstract

Forecasts suggest that artificial intelligence (AI) and robotics may ultimately substitute for a significant portion of the jobs presently available in the hospitality sector, imposing serious sustainability challenges for academia and industry. On the other hand, this transition has generated notable concerns regarding robotics, artificial intelligence, and service automation (RAISA) among hospitality and tourism students. The objective of this study is to examine the consequences of this trend: depression caused by RAISA (DCR), quiet quitting (QQ), and intention to quit school (ITQS). To collect the necessary data for the research objectives, we administered an online survey to full-time students in institutions affiliated with the Hospitality and Culinary Arts Alliance. Using partial least squares structural equation modeling, we evaluated our model. The study's findings asserted that concerns over RAISA (COR) are positively related to hospitality and tourism students' DCR, QQ, and ITQS. Additionally, DCR partially mediated the link between COR and the outcome variables. Several contributions to the theory and fruitful implications for higher educational institutions were discussed in the following.