Augmented reality in retail

Gary, Joston; Xixing, Zhou; Tang, Yuk Ming; Yang, Gu; Moreira, Antonio

http://hdl.handle.net/10400.2/20965

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Abstract(s)

Retail practice shows that augmented-reality shopping applications with similar technical quality can elicit widely different consumer reactions. This study proposes a dual-pathway Stimulus–Organism–Response model: a technical pathway linking augmented realism, information richness, and personalization to interaction satisfaction, and an emotion-priming pathway where anticipated emotions shape immersion, telepresence, and pleasure without technical appraisal. Both converge at inspiration, the sole System-2 construct converting experience into behavior. Data from quasi-experimental participants were analyzed using PLS-SEM, SHAP-interpreted gradient boosting, and K-Means robustness checks. Information richness showed the strongest technical effect, while anticipated emotions most strongly affected immediate experiences. Inspiration predicted purchase and cross-buying intentions. Machine-learning diagnostics supported the framework and revealed non-linear thresholds in key pathways, clarifying inconsistent AR outcomes and positioning inspiration as the cognitive bridge to purchase.