Travel-organisation channels play a crucial role in shaping the adoption of sustainable practices, as travellers navigate both digital and non-digital options. This study investigates how these channels influence sustainable behaviours by applying Bayesian networks within a probabilistic framework. The model traces the cascade from demographic profiles to travel propensity, channel use, and behavioural outcomes, enabling the identification of direct and mediated effects as well as the simulation of what-if intervention scenarios. Results show that single channels generate only moderate gains: lists of private accommodation and through a friend, relative or acquaintance consistently achieve higher probability across several behaviours, while metasearch platforms are particularly effective in encouraging local consumption. For resource-efficiency practices–such as choosing lower-footprint transport, reducing waste, and reducing water use–probabilities remain highly similar across channels, indicating that stronger outcomes depend on combinations of complementary channels. The importance of the study lies in demonstrating that channel decisions are not neutral but actively shape sustainable pathways. By clarifying which channels have the greatest leverage and showing that integrated strategies are more effective than isolated actions, the research provides actionable insights for destination managers, policymakers, and platform designers. More broadly, it advances the literature by introducing a probabilistic modelling framework that enhances the understanding of multichannel decision-making and sustainability-oriented behaviours, while also highlighting the value of Bayesian networks as a transparent tool to inform sustainable tourism interventions.