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Consumer adoption of smart in-store technology: assessing the predictive value of attitude versus beliefs in the technology acceptance model

ABSTRACT An explosion of smart technologies provides fashion retailers with innovative ways to transform the shopping experience and capitalise on strategic opportunities. Due to the fast growth of smart in-store technology (SIST) applications in retailing (e.g. tablets, smartphones, WiFi, augmented reality, apps, video, virtual catalogues, and smart tags), it is critical for academic researchers as well as retailers to understand consumer responses to these technologies. Thus, we examined the applicability of the technology acceptance model (TAM) for explaining consumer adoption of SIST. Online survey data (N = 657) were collected from US consumer panels managed by a marketing research firm in three different SIST settings (i.e. virtual mirror, socially interactive dressing room, and Radio Frequency IDentification music tag). The data indicated that the effects of the TAM beliefs on behavioural intention varied across the three SIST settings. Results also showed mixed evidence about the full mediating role of attitude in applying the TAM to SIST.