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The Impact of AI on Online Customer Experience and Consumer Behaviour. An Empirical Investigation of the Impact of Artificial Intelligence on Online Customer Experience and Consumer Behaviour in a Digital Marketing and Online Retail Context

Artificial Intelligence (AI) is adopted fast and wide across consumer industries and
digital marketing. This new technology has the potential to enhance online customer
experience and outcomes of customer experience. However, research relating to the
impact of AI is still developing and empirical evidence sparse. Taking a consumercentred
approach and by adopting Social Response Theory as theoretical lens, this
research addresses an overall research question pertaining to the implications of
online customer experience with AI on consumer behaviour. A quantitative research
strategy with positivist approach is adopted to gather a large sample (n= 489) of online
consumers who have previously interacted with AI-enabled technology. The collected
data is analysed statistically utilising Confirmatory Factor Analysis (CFA) and
Structural Equation Modelling (SEM). Empirical findings show strong positive effects
of anthropomorphism of AI, para-social interaction with AI, and performance
expectancy of AI on all three customer experience dimensions of informativeness,
entertainment and social presence. Additionally, there is strong statistical support for
the positive effect of informativeness and social presence on continued purchase
intentions (β= .379 and β= .315), while the effects of entertainment are less strong.
The mediating effects of customer experience have been assessed, highlighting social
presence as most important mediator. This research contributes to knowledge by
extending previous customer experience theory and quantifying the influence of online
customer experience with AI on purchase intentions and eWOM. The theoretical insights also translate into direct implications for marketing practice relating to the design, integration, and implementation of more consumer- and outcome-oriented AI applications. / Faculty of Management, Law and Social Sciences studentship

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/19777
Date January 2022
CreatorsKronemann, Bianca
ContributorsMahroof, Kamran, Rana, Nripendra P., Weerakkody, Vishanth J.P.
PublisherUniversity of Bradford, Faculty of Management, Law and Social Science
Source SetsBradford Scholars
LanguageEnglish
Detected LanguageEnglish
TypeThesis, doctoral, PhD
Rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.

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