This paper proposes a model that extends the technology acceptance model (TAM) by identifying factors that influence consumers' acceptance of augmented reality (AR) self-service technologies (AR-based SSTs) in the retail sector, resulting in the Augmented Reality in Retail Model (ARiR Model).
This study is based on an online questionnaire responded to by 284 makeup-using women from Nicaragua and the USA. It is based on an AR mobile app used to shop in retail stores. Partial least squares-structural equation modelling was used to validate the ARiR model and test the hypotheses.
Aesthetics and navigation are significant predictors of perceived usefulness and perceived ease of use (PEOU), and self-efficacy also explains perceived ease of use. Technology readiness and the need for personal interaction were not found to be influencing factors. A cross-cultural comparison indicated that both countries have similar overall attitudes towards AR-based SSTs.
This paper provides insights into the perceived value of, and motives for customer acceptance of, AR-based SSTs, which can serve as guidelines for their future implementation. Furthermore, it validates and confirms the application of the proposed ARiR model for technology acceptance in both developed and developing countries.
The paper provides new insights for retailers on the implementation of AR at the point of sale.
The model extends the original TAM to AR and introduces five new constructs: need for personal interaction, aesthetics, navigation, self-efficacy and technology readiness. It was tested in both a developing and a developed country.
Funding: This research has been supported by the Generalitat Valenciana funded project “Rebrand”, grant number PROMETEO/2019/105, and by Rhumbo Project (European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No 813234).
Castillo S, M.J. and Bigne, E. (2021), "A model of adoption of AR-based self-service technologies: a two country comparison", International Journal of Retail & Distribution Management, Vol. 49 No. 7, pp. 875-898. https://doi.org/10.1108/IJRDM-09-2020-0380
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