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

Abstract

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.