Factors driving individuals' usage intention of artificial intelligence (AI) assistants in e-commerce : perspectives of users and non-users

Alnefaie, Ahlam Eid A

Factors driving individuals' usage intention of artificial intelligence (AI) assistants in e-commerce : perspectives of users and non-users

Alnefaie, Ahlam Eid A

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Publication Type:: Thesis
Issue Date:: 2024

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Field	Value	Language
dc.contributor.author	Alnefaie, Ahlam Eid A
dc.date.accessioned	2024-12-02T21:10:45Z
dc.date.available	2024-12-02T21:10:45Z
dc.date.issued	2024
dc.identifier.uri	http://hdl.handle.net/10453/182308
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	This PhD research explores factors driving individuals’ intention to use Artificial Intelligence (AI) assistants or chatbots in e-commerce from the perspectives of both users and non-users. The study identifies key determinants influencing the adoption of AI assistants in e-commerce. It employs both quantitative and qualitative approaches to achieve this objective. This research conducted a multi-method approach. In the first phase (Phase A), a quantitative method was employed to investigate the relationships between the constructs in the study model, and the Partial Least Square Structural Equation Modelling (PLS-SEM) and several statistical techniques were adopted. In the second phase (Phase B), a qualitative approach was conducted by applying natural language processing techniques to analyse reviews of the Louis Vuitton brand's e-commerce applications. The findings demonstrate that all proposed factors significantly impact users and non-users in the e-commerce context, thereby supporting all research hypotheses. This PhD research contributes to theory and practice by expanding the Technology Acceptance Model (TAM) with two additional external factors. This inclusion enables for the assessment of factors influencing AI assistant adoption from consumer, societal, and marketing perspectives. Moreover, the study provides new empirical data on this subject in the context of technology adoption studies. Furthermore, it offers a variety of practitioners in the field of e-commerce relevant information and advice about the utilisation of AI assistants, which enables them to make more informed decisions regarding the development and implementation of AI assistant technologies.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/182308/1/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2024 Ahlam Eid A Alnefaie
dc.rights	au.edu.uts.lib/cph
dc.title	Factors driving individuals' usage intention of artificial intelligence (AI) assistants in e-commerce : perspectives of users and non-users	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

This PhD research explores factors driving individuals’ intention to use Artificial Intelligence (AI) assistants or chatbots in e-commerce from the perspectives of both users and non-users. The study identifies key determinants influencing the adoption of AI assistants in e-commerce. It employs both quantitative and qualitative approaches to achieve this objective. This research conducted a multi-method approach. In the first phase (Phase A), a quantitative method was employed to investigate the relationships between the constructs in the study model, and the Partial Least Square Structural Equation Modelling (PLS-SEM) and several statistical techniques were adopted. In the second phase (Phase B), a qualitative approach was conducted by applying natural language processing techniques to analyse reviews of the Louis Vuitton brand's e-commerce applications. The findings demonstrate that all proposed factors significantly impact users and non-users in the e-commerce context, thereby supporting all research hypotheses. This PhD research contributes to theory and practice by expanding the Technology Acceptance Model (TAM) with two additional external factors. This inclusion enables for the assessment of factors influencing AI assistant adoption from consumer, societal, and marketing perspectives. Moreover, the study provides new empirical data on this subject in the context of technology adoption studies. Furthermore, it offers a variety of practitioners in the field of e-commerce relevant information and advice about the utilisation of AI assistants, which enables them to make more informed decisions regarding the development and implementation of AI assistant technologies.

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http://hdl.handle.net/10453/182308