Impact of digital assistant attributes on millennials' purchasing intentions: a multi-group analysis using PLS-SEM, artificial neural network and fsQCA

Sharma, Manu, Joshi, Sudhanshu, Luthra, Sunil and Kumar, Anil (2022) Impact of digital assistant attributes on millennials' purchasing intentions: a multi-group analysis using PLS-SEM, artificial neural network and fsQCA. Information Systems Frontiers. ISSN 1572-9419

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Abstract / Description

The rising population of millennials, coupled with Digital Assistants (DA) and online purchasing trends among consumers have gained increasing attention by global marketers. The study evaluates the influence of DA attributes on the purchasing intention (PUI) of millennials. A combined approach of PLS-SEM, Artificial Neural Network (ANN) and Fuzzy-set Qualitative Comparative Analysis (fsQCA) is used to predict the PUI of 345 millennials. Also, multi-group analysis is employed to uncover the influence of gender on the relationship between PUI and DA attributes. The findings suggest that DA attributes may amplify purchasing intention among millennials, especially through perceived interactivity and anthropomorphism. Further, the moderating role of gender was found significant on the inter-relationship of perceived interactivity and PUI. This research is a pioneer study in the area of artificial intelligence, conversational commerce, DA and AI-powered chatbots. This study will help marketers and practitioners to predict millennial purchasing intentions. An evaluation of this paper may help them to foster immersive and effective engagement through DA.

Item Type:	Article
Additional Information:	The version of record of this article, first published in Information Systems Frontiers, is available online at Publisher’s website: http://dx.doi.org/10.1007/s10796-022-10339-5
Uncontrolled Keywords:	artificial intelligence; conversational commerce; chatbots; millennials; customer purchase; interactivity; artificial neural network
Subjects:	600 Technology > 650 Management & auxiliary services
Department:	Guildhall School of Business and Law
Depositing User:	Anil Kumar
Date Deposited:	02 Sep 2022 10:10
Last Modified:	11 Nov 2022 11:45
URI:	https://repository.londonmet.ac.uk/id/eprint/7885

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