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Snakes and ladders: unpacking the personalisation-privacy paradox in the context of AI-enabled personalisation in the physical retail environment
journal contribution
posted on 2023-06-10, 05:54 authored by Ana Isabel Canhoto, Brendan James Keegan, Maria RyzhikhArtificial intelligence (AI) is expected to bring to the physical retail environment the kind of mass personalisation that is already common in online commerce, delivering offers that are targeted to each customer, and that adapt to changes in the customer’s context. However, factors related to the in-store environment, the small screen where the offer is delivered, and privacy concerns, create uncertainty regarding how customers might react to highly personalised offers that are delivered to their smartphones while they are in a store. To investigate how customers exposed to this type of AI-enabled, personalised offer, perceive it and respond to it, we use the personalisation-privacy paradox lens. Case study data focused on UK based, female, fashion retail shoppers exposed to such offers reveal that they seek discounts on desired items and improvement of the in-store experience; they resent interruptions and generic offers; express a strong desire for autonomy; and attempt to control access to private information and to improve the recommendations that they receive. Our analysis also exposes contradictions in customers’ expectations of personalisation that requires location tracking. We conclude by drawing an analogy to the popular Snakes and Ladders game, to illustrate the delicate balance between drivers and barriers to acceptance of AI-enabled, highly personalised offers delivered to customers’ smartphones while they are in-store.
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Publication status
- Published
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- Published version
Journal
Information Systems Frontiers: a journal of research and innovationISSN
1387-3326Publisher
Springer NatureExternal DOI
Page range
1-20Department affiliated with
- Management Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2023-01-10First Open Access (FOA) Date
2023-01-18First Compliant Deposit (FCD) Date
2023-01-10Usage metrics
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