A Study on Deriving Experiential Attributes of Online Guided Tours: A Convergent Approach Using Participant Reviews and the Experience Economy Theory

Online guided tours have become an essential form of non-contact tourism, yet the experiential attributes shaping participants’ digital tour experiences remain underexplored. This study aims to identify the core experiential dimensions of online guided tours by analyzing user-generated review data and interpreting the findings through the experience economy framework. A dataset of 1506 participant reviews was collected from major online guided tour platforms and analyzed using text mining techniques, including TF-IDF and Latent Dirichlet Allocation (LDA). The results reveal the following seven experiential attributes: entertainment, education, esthetics, escapism, presence, interactivity, and digital environment. These findings indicate that online guided tours extend beyond traditional 4E experience dimensions, incorporating digitally mediated elements such as real-time communication and platform-driven immersion. The proposed “4E + 3D Model” captures the hybrid nature of digital tourism experiences, combining classic experiential factors with technology-enabled components. This study contributes to tourism experience research by empirically validating an expanded experiential structure suitable for digital contexts. It also demonstrates the value of user-generated review analysis for deriving authentic experiential insights. The results provide practical implications for enhancing online guided tour design, emphasizing real-time interactivity, digital esthetics, and system stability to improve participant experiences in virtual tourism settings.