Tourism Innovation Ecosystems: Insights from Theory and Empirical Validation

This study develops and empirically validates a theoretical model designed to assess the performance of tourism innovation ecosystems by integrating the dimensions of innovation, technology, and sustainability—dimensions that have typically been examined in isolation within the literature. The empirical investigation was conducted at two major tourism destinations: a pilot phase in Las Vegas, followed by the main study in Orlando, USA. Data collection was facilitated via the Amazon Mechanical Turk (MTurk) platform, and analysis was conducted using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM), enabling the examination of eight hypotheses across seven constructs. The findings provided evidence of both convergent and discriminant validity and supported five of the eight proposed hypotheses. Specifically, the study confirmed significant relationships among technology acceptance and adoption, adoption and innovation generation, innovation and both sustainability and overall ecosystem performance, and adoption and sustainability. Conversely, collaboration and actor-integration barriers did not exhibit significant effects in Orlando, which is consistent with its mature institutional environment. Innovation emerged as a mediating variable linking technology and sustainability, exerting a substantial influence on overall ecosystem performance. This research advances the theoretical consolidation of the tourism innovation ecosystem concept and offers actionable insights for destination managers aiming to foster innovation, facilitate the adoption of connective technologies, and implement sustainable strategies. The proposed model demonstrates empirical robustness and practical relevance, providing a comprehensive framework for analyzing and enhancing smart, resilient tourism destinations.