From Clicks to Bricks: How Artificial Intelligence Shapes Showrooming and Webrooming Effects on Purchase Intention

Showrooming, Webrooming, Artificial Intelligence, Decision Confidence, Perceived Value, Purchase Intention, Omnichannel Retailing

This study investigates how Artificial Intelligence (AI) reshapes the influence of showrooming and webrooming behaviors on consumer purchase intention within omnichannel retail environments. Grounded in the Stimulus–Organism–Response (S-O-R) framework, Information Processing Theory, and technology adoption perspectives such as the Technology Acceptance Model (TAM) and UTAUT, the research conceptualizes showrooming and webrooming as external stimuli that activate internal cognitive and evaluative states namely decision confidence and perceived value which subsequently drive purchase intention. Using a quantitative, cross-sectional design, primary data were collected through a structured questionnaire from omnichannel consumers, yielding 412 valid responses for analysis. Established multi-item measurement scales were employed to capture showrooming, webrooming, AI-enabled retail services (including personalization, recommendation systems, and chatbot assistance), decision confidence, perceived value, and purchase intention. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0, enabling simultaneous assessment of measurement reliability, construct validity, direct effects, mediation, and moderation relationships. The findings reveal that both showrooming and webrooming exert significant positive effects on purchase intention, while decision confidence and perceived value partially mediate these relationships. Importantly, AI-enabled retail services significantly strengthen the impact of both showrooming and webrooming on purchase intention, highlighting AI’s role as a critical technological moderator in omnichannel decision-making. The study offers actionable insights for retailers by demonstrating how AI-driven personalization and intelligent decision support can convert cross-channel search behaviors into purchase outcomes, while contributing theoretically by advancing an integrated, AI-enabled omnichannel consumer decision framework.