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This paper reviews the state-of-art articles on instructional technologies for hospitality and tourism education. The types of technologies, roles in instruction, theoretical underpinnings, assessments, benefits, and challenges are synthesized. Education context, knowledge, skills, and attitudes developed through instructional technologies are also explored. Virtual reality, virtual games, social media, online courses, and simulations have been primarily used. Instructional technologies were applied to facilitate content delivery, practice, communication, assessments, feedback, and authentic learning experiences. Most studies did not ground their educational technologies in defensible learning theories. Only a limited number of studies employed adoption theories to examine the intention of using technologies. Further studies should investigate whether certain instructional technologies provide significant benefits to learning relative to their costs. 

Fast technological developments have transformed the tourism and hospitality services and the labor market. The outbreak of the COVID-19 pandemic exposed the vulnerability of the tourism and hospitality workforce. There is insufficient prior work about creating better work conditions and greater career opportunities for hospitality and tourism professionals in the swiftly changing labor market. To this end, this article analyzes the historical employee–employer relationships in the tourism and hospitality industry. It presents a new employee-sharing model framework for enhancing resilience and flexibility for hospitality and tourism enterprises and workers. 

Purpose This study reviews existing research and current applications of artificial intelligence (AI) in the hospitality and tourism industry. It further proposes a new evaluation framework to inform the susceptibility of AI adoptions. Design/methodology/approach This is a synthesis and evaluation study that qualitatively summarizes and presents findings on AI applications in the hospitality and tourism industry. Current AI applications are rated using a seven-dimensional framework based on Rogers' (2003) diffusion theory. Findings AI adoption susceptibility in the hospitality and tourism industry varies based on the type of AI. Search/booking engines, virtual agents and chatbots rank high in the adoption susceptibility. Research limitations/implications This study bridges innovation diffusion theoretical underpinnings and AI applications. The findings support researchers, developers and managers in evaluating the adoption susceptibility of AI technologies in the hospitality and tourism industry. Originality/value This paper is among the few that focus on assessing AI adoption susceptibility in the hospitality and tourism industry. This paper develops a theory-based framework for systematically evaluating AI innovations in hospitality and tourism.