The advent of the metaverse is reshaping the tourism sector, offering immersive digital experiences that transcend physical boundaries and establish new frontiers in destination marketing. The study investigates the consumer acceptance of metaverse tourism by integrating the technology acceptance model (TAM) with techno-stressors, techno-uncertainty and techno-complexity of metaverse technology. The study employs a hybrid approach using PLS-SEM, artificial neural networks (ANN), and fuzzy-set qualitative comparative analysis (fsQCA) techniques to provide a comprehensive understanding of the factors impacting the acceptance of metaverse tourism. Findings indicate that perceived enjoyment and perceived usefulness are key predictors of acceptance, while techno-uncertainty had a notable negative effect. The ANN analysis found perceived usefulness and enjoyment as critical factors of metaverse acceptance and provided greater predictive power. The fsQCA findings reveal five distinct configurations pathways to achieving consumer acceptance of metaverse tourism, with techno-complexity and perceived usefulness emerging as the core condition, demonstrating high coverage and consistency. The results from the hybrid approach offer a detailed understanding of how distinct combinations of factors collectively shape metaverse acceptance in the tourism sector, uncovering complex interactions that provide deeper insights than conventional methods. Finally, the study offers valuable theoretical contributions and practical implications for tourism professionals.