Hospitality technology research underscores aligning features with user capacity. This study tests whether augmented reality (AR) characteristics (information enhancement, vividness, interactivity) raise perceived value at the post-check-in stage of peer-to-peer lodging and whether users’ information overload acts as a boundary condition. Affordance theory frames how feature–user alignments convert AR functionality into valued outcomes.
A two-wave online survey (N = 279; = 1-week lag) used a video-based Airbnb AR guestbook scenario. Constructs were measured with validated scales; confirmatory factor analysis established reliability/validity. structural equation modeling tested main and moderated effects; quadratic terms probed nonlinearity. Procedural/statistical remedies addressed common-method bias; controls included spatial presence, AR novelty and prior AR experience.
All three AR attributes positively predicted perceived value (R2 = 0.40). Information overload strengthened the information enhancement–value link and weakened the vividness–value link. The overload × interactivity term was not significant; a post-hoc test revealed a nonlinear, inverted-U moderation, with interactivity contributing most at moderate overload and attenuating at high overload.
Load-aware AR design is advised: structure, filter, and sequence content; layer vivid media through progressive disclosure and tune interactive controls to inferred load states. For peer-to-peer lodging, AR guestbooks should prioritize task-diagnostic guidance and optional depth, improving usability, word-of-mouth and revisit intentions while avoiding feature bloat.
Positions information overload as an actionable boundary condition that differentially governs AR attribute–value links and uncovers a nonlinear moderation for interactivity. Integrates affordance theory with limited-capacity and technostress perspectives, providing a template for evaluating and designing cognition-sensitive AR services in tourism and hospitality.
