Purpose This study aims to better understand how intellectual capital (IC) of tourism destinations is formed and developed for sustainability by leveraging artificial intelligence (AI). Notably, co-evolution allows conceiving destinations as ecosystems in which relationships between the various stakeholders involved at multiple-levels are circular, with mutual influence and dialectical. Design/methodology/approach A conceptual framework is developed building on some insights from evolving IC research, the co-evolutionary perspective in tourism and AI- and machine learning-based methods for destination modelling. The framework is then operationalised through an AI-driven data model, which is designed, developed and applied to two Italian destinations (Costa dei Trabocchi and Gargano) following the participatory action research approach. Findings The AI-driven data model serves as a core component of the structural capital of the investigated destinations, shaping their human capital at different levels, which in turn contributes to reinforce, and is reinforced by, relational capital. Within this dynamic, the strategic intentionality of policymakers and decision makers, inter-organisational knowledge exchange, team learning and multistakeholder decision making are identified as key determinants that enable AI-generated information to effectively orient multilevel stakeholders towards shared goals, thereby supporting effective co-adaptations within tourism destinations that create value for all involved. Originality/value Our interdisciplinary research provides a novel AI-driven data tool and a co-evolutionary explanation of the processes it leverages, which drive tourism destinations' IC for sustainability.
Baiocco et al. (Tue,) studied this question.