Authors:
Daniel Mora
1
;
Robert Zimmermann
2
;
Douglas Cirqueira
3
;
Marija Bezbradica
3
;
Markus Helfert
4
;
Andreas Auinger
2
and
Dirk Werth
1
Affiliations:
1
Artificial Intelligence Lab, AWS Institute for Digitized Products and Processes, Saarbrücken, Germany
;
2
Digital Business Management, University of Applied Sciences Upper Austria, Styer, Austria
;
3
School of Computing, Dublin City University, Dublin, Ireland
;
4
Innovation Value Institute, Maynooth University, Maynooth, Ireland
Keyword(s):
Digital Shopping Assistant, Recommender Systems, Explainable Artificial Intelligence, Retail Sales, Digital Retail, Brick-and-Mortar.
Abstract:
Brick-and-mortar retailers need to stay competitive to the convenience provided by online channels. Technologies, such as personalized shopping assistants on smartphones can empower customers in-store towards a similar experience as in an online scenario. For instance, an augmented reality shopping assistance application with explainable recommendations (XARSAA) can mimic the behavior of recommender systems in personalizing offers to consumers in physical shops. However, before deploying such technologies, it is essential that retailers get to know the demographics of their customer base. Existing literature rarely addresses the influence of customers demographics towards XARSAA technologies. Therefore, we follow a design science approach, and develop an instantiation of a XARSAA artifact, which is artificially evaluated through a controlled online user experiment with 315 participants. Results illustrate multiple demographics which influence customers attitude towards an augmented r
eality shopping assistant application in brick-and-mortar stores. Additionally, we provide insights into the design of such technology to guide researchers in its implementation.
(More)