Adapting Knowledge and Human Resources to Digital Entrepreneurship in Tourism

The digital transformation of tourism and hospitality businesses has been studied mainly as a matter of business models, platforms, and technology adoption, while the cognitive and organizational-learning processes that determine whether the workforce adapts at the pace of technological change have received less attention, especially in the small and micro enterprises that dominate the sector. Following a theory-synthesis approach, this conceptual paper integrates three frameworks, each selected because it explains a different level of the adaptation problem: (a) the SECI model of tacit-to-explicit knowledge conversion (organizational knowledge flow); (b) the Metacognitive Creative Destruction (MCD) model, which explains how individuals deliberately abandon outdated mental schemas before constructing new ones (individual and group cognition); and (c) research on AI sycophancy, the documented tendency of large language models trained with human feedback to agree with users rather than challenge them (technological context). Their integration leads to a claim that none of the three makes separately: AI use intensity and the density of contradiction that employees actually encounter are distinct variables, and the relationship between them depends on how AI tools are configured and how managers design work. The framework is developed into ten research propositions, each stating a single directional relationship, together with a measurement logic for empirical testing. The paper sets out a research agenda and concludes that, in tourism businesses whose service depends on tacit, experiential knowledge, staff are a central source of competitive advantage and that using this knowledge requires sustainable, employee-centred human resource management.