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Enhancing brick-and-mortar store shopping experience with an augmented reality shopping assistant application using personalized recommendations and explainable artificial intelligence

Zimmermann, Robert, Mora, Daniel, Cirqueira, Douglas ORCID: 0000-0002-1283-0453, Helfert, Markus ORCID: 0000-0001-6546-6408, Bezbradica, Marija ORCID: 0000-0001-9366-5113, Werth, Dirk, Weitzl, Wolfgang Jonas ORCID: 0000-0001-9208-435X, Riedl, René and Auinger, Andreas ORCID: 0000-0002-2672-0896 (2022) Enhancing brick-and-mortar store shopping experience with an augmented reality shopping assistant application using personalized recommendations and explainable artificial intelligence. Journal of Research in Interactive Marketing . ISSN 2040-7122

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Abstract

Purpose– The transition to omnichannel retail is the recognized future of retail, which uses digital technologies (e.g. augmented reality shopping assistants) to enhance the customer shopping experience. However, retailers struggle with the implementation of such technologies in brick-and-mortar stores. Against this background,thepresentstudyinvestigatestheimpactofasmartphone-basedaugmentedrealityshopping assistant application, which uses personalizedrecommendationsandexplainableartificialintelligencefeatures on customer shopping experiences. Design/methodology/approach– The authors follow a design science research approach to develop a shopping assistant application artifact, evaluated by means of an online experiment (n 5 252), providing both qualitative and quantitative data. Findings– Results indicate a positive impact of the augmented reality shopping assistant application on customers’ perception of brick-and-mortar shopping experiences. Based on the empirical insights this study also identifies possible improvements of the artifact. Research limitations/implications– This study’s assessment is limited to an online evaluation approach. Therefore, future studies should test actual usage of the technology in brick-and-mortar stores. Contrary to the suggestions of established theories (i.e. technology acceptance model, uses and gratification theory), this study shows that an increase of shopping experience does not always convert into an increase in the intention to purchase or to visit a brick-and-mortar store. Additionally, this study provides novel design principles and ideas for crafting augmented reality shopping assistant applications that can be used by future researchers to create advanced versions of such applications.

Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:Digital retail; Digital shopping assistant; Recommender systems; Explainable artificial intelligence; Retail sales
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:Emerald
Official URL:https://dx.doi.org/10.1108/JRIM-09-2021-0237
Copyright Information:© 2021 The Authors.
ID Code:27516
Deposited On:09 Aug 2022 11:03 by Thomas Murtagh . Last Modified 23 Mar 2023 15:15

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