Enhancing trust in online grocery shopping through generative AI chatbots

Generative Artificial Intelligence (GAI) is witnessing a lot of adoption across industries, but literature is yet to fully document the nuances of these applications. We develop a comprehensive framework for understanding the factors that affect trust in online grocery shopping (OGS) using GAI chatb...

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Bibliographic Details
Published in:Journal of business research 2024-07, Vol.180, p.114737, Article 114737
Main Authors: Chakraborty, Debarun, Kumar Kar, Arpan, Patre, Smruti, Gupta, Shivam
Format: Article
Language:English
Subjects:
Chatbots
Elaboration Likelihood Model
Generative Artificial Intelligence (AI)
Online Shopping
Status Quo Bias Theory
Trust
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Summary:Generative Artificial Intelligence (GAI) is witnessing a lot of adoption across industries, but literature is yet to fully document the nuances of these applications. We develop a comprehensive framework for understanding the factors that affect trust in online grocery shopping (OGS) using GAI chatbots. Our exploratory study was conducted via interviews, which helped to build our model. We integrate the Elaboration Likelihood Model (ELM) and Status Quo Bias (SQB) theory to develop the Unified Framework for Trust on Technology Platforms. In our confirmatory study, by analyzing 372 responses from users, using structural equation modelling (SEM), we initially validate our path model. Subsequently, we used fuzzy set qualitative comparative analysis (fsQCA) to check the causal combinations to explain different trust levels. Apart from perceived regret avoidance, all of the other factors had a significant effect on attitude and trust. Perceived anthropomorphism moderated the associations between interaction quality, credibility, threat, and attitude.
ISSN:0148-2963
1873-7978
DOI:10.1016/j.jbusres.2024.114737