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The Impact of AI-Enabled Checkouts on Shoppers’ Attitudes and Purchase Intent in Saudi Arabia

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Thesis(2.3 MB)

Date

2021

Authors

Supervisor

Van Esch, Patrick

Item type

Thesis

Degree name

Master of Business

Journal Title

Journal ISSN

Volume Title

Publisher

Auckland University of Technology

Abstract

Checkout technology enabled by artificial intelligence (AI) is a new innovation in the rapidly changing retail sector. The first example of this technology was recently launched by Amazon. This research was conducted in Saudi Arabia to examine shoppers’ attitudes towards AI-enabled checkouts and their purchase intent. Using a sample of 655 Saudi respondents, convenience was examined as boundary condition (Study 1) and anxiety as the underlying causal mechanism (Study 2). The results show that there was a positive impact of AI-enabled checkouts on purchase intent, with a direct interaction but a negative impact on purchase intent when anxiety mediated the interaction. However, the convenience associated with AI-enabled checkouts played a role in reducing anxiety. This study provides several contributions to the developing framework of marketing literature and offers to marketers and retail owners a better understanding of the influence of AI-enabled checkouts on shoppers’ attitudes. Furthermore, by explaining shoppers' attitudes towards AI-enabled checkouts, this study indicates that the perceived convenience of such checkouts can reduce anxiety in acceptance of this innovative technology. The results also suggest that measures should be taken to increase public awareness of an AI-enabled system before its adoption, as some consumers may find it a source of anxiety and so avoid it. Thus, the findings presented here can help researchers, marketers, and managers in choosing the steps to take in order to maximize the benefits of AI-enabled checkouts.

Description

Keywords

AI-Enabled Checkouts, Traditional checkouts, Shopping convenience, Anxiety, Purchase intent

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DOI

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Permanent link

https://hdl.handle.net/10292/14207

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Masters Theses