According to the research gap analysis, what are the five main gaps identified in the study of AI-enabled hospitality workforce?

The research gap analysis identifies five main gaps: an overemphasis on technology adoption studies without longitudinal insight into sustained human-AI interaction effects; underdeveloped research on employee well-being, technostress, algorithmic management, and burnout; a contextual gap concentrated on developed economies and large hotels while ignoring emerging markets like India, small and medium-sized hotels, and informal service settings; limited exploration of ethical, governance, and trust issues such as surveillance, data privacy, transparency, and algorithmic bias; and a lack of integrative interdisciplinary models linking acceptance, work design, well-being, and socio-technical alignment in hybrid hospitality environments.

The first gap is that existing empirical research is technology-focused, prioritizing acceptance and usage through models like TAM and UTAUT. This approach captures early adoption but fails to show how prolonged human-AI interaction changes job identity, emotional labor, professional autonomy, and service meaning, largely because longitudinal studies of workforce adjustment across AI adoption stages are missing. The second gap concerns employee-centered outcomes: research on well-being, technostress, algorithmic management, and burnout remains premature, and there is insufficient evidence on whether AI acts as a job demand or a job resource for frontline workers, supervisors, and middle managers. The third gap is contextual, as the literature concentrates on developed economies and major global hotels, leaving limited empirical work on growing hospitality markets such as India, small and medium-sized hotels, and informal service environments that have different digital infrastructure, workforce capabilities, and organizational cultures. The fourth gap involves ethical, governance, and trust dimensions of human-AI collaboration, including surveillance, data privacy, transparency, and algorithmic bias, with little known about employees' feelings of fairness, accountability, and psychological safety under algorithmic management. The fifth gap is the absence of integrative and interdisciplinary models that simultaneously address acceptance, work design, well-being, and socio-technical alignment in hybrid hospitality settings; most studies adopt single-theory orientations, lacking holistic and humanistic frameworks.