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Can Alexa serve customers better? AI-driven voice assistant service interactions

Suresh Malodia (MICA School of Ideas, Indian Institute of Management Ahmedabad, Ahmedabad, India)
Alberto Ferraris (Department of Management, University of Turin, Italy and Laboratory for International and Regional Economics, Graduate School of Economics and Management, Ural Federal University, Yekaterinburg, Russian Federation)
Mototaka Sakashita (Graduate School of Business Administration, Keio Business School, Yokohama, Japan)
Amandeep Dhir (Department of Management, University of Agder School of Business and Law, Grimstad, Norway; Norwegian School of Hotel Management, University of Stavanger, Stavanger, Norway and Optentia Research Focus Area, North-West University, Potchefstroom, South Africa)
Beata Gavurova (Faculty of Management and Economics, Tomas Bata University in Zlin, Zlin, Czech Republic)

Journal of Services Marketing

ISSN: 0887-6045

Article publication date: 21 December 2022

157

Abstract

Purpose

This study aims to examine customers’ willingness to engage in service interactions enabled by artificial intelligence (AI) controlled voice assistants (VA). Drawing on the tenets of dual-factor theory, this study measures the impact of both enablers and inhibitors – mediated by trust in Alexa – on customers’ intentions to transact through VAs.

Design/methodology/approach

Data from a survey of 290 users of VAs from Japan was collected through “Macromill”. The authors used a covariance-based path analysis technique for data analysis after establishing the validity and reliability of the measures.

Findings

The results of this study demonstrate that convenience and status-seeking act as enablers and positively influence trust in VAs, whereas risk barrier acts as an inhibitor and negatively influence trust in VAs. In turn, trust in VAs positively influences the intention to use VAs for transactional service interactions. This association is positively moderated by technology comfort.

Originality/value

This study applies dual-factor theory to the context of VAs – a context that scholars have, to date, examined solely from a technology adoption perspective. For the first time, the authors adopt a dual-factor approach to identify a new set of antecedents for customers’ intentions to use VAs for transactional service interactions.

Keywords

Acknowledgements

The paper is an output of the project NFP313011BWN6 “The implementation framework and business model of the Internet of Things, Industry 4.0 and smart transport”.

Citation

Malodia, S., Ferraris, A., Sakashita, M., Dhir, A. and Gavurova, B. (2022), "Can Alexa serve customers better? AI-driven voice assistant service interactions", Journal of Services Marketing, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JSM-12-2021-0488

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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