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

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dc.title Can Alexa serve customers better? AI-driven voice assistant service interactions en
dc.contributor.author Malodia, Suresh
dc.contributor.author Ferraris, Alberto
dc.contributor.author Sakashita, Mototaka
dc.contributor.author Dhir, Amandeep
dc.contributor.author Gavurová, Beáta
dc.relation.ispartof Journal of Services Marketing
dc.identifier.issn 0887-6045 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2022
dc.type article
dc.language.iso en
dc.publisher Emerald Publishing
dc.identifier.doi 10.1108/JSM-12-2021-0488
dc.relation.uri https://www.emerald.com/insight/content/doi/10.1108/JSM-12-2021-0488/full/html
dc.subject artificial intelligence en
dc.subject automated service interactions en
dc.subject dual-factor en
dc.subject conversational commerce en
dc.subject human–computer interaction en
dc.subject voice assistants en
dc.description.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. en
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1011310
utb.identifier.obdid 43883864
utb.identifier.scopus 2-s2.0-85144195940
utb.identifier.wok 000900029900001
utb.source j-scopus
dc.date.accessioned 2023-02-15T08:06:26Z
dc.date.available 2023-02-15T08:06:26Z
utb.contributor.internalauthor Gavurová, Beáta
utb.fulltext.sponsorship 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”.
utb.wos.affiliation [Malodia, Suresh] Indian Inst Management Ahmedabad, MICA Sch Ideas, Ahmadabad, India; [Ferraris, Alberto] Univ Turin, Dept Management, Turin, Italy; [Ferraris, Alberto] Ural Fed Univ, Grad Sch Econ & Management, Lab Int & Reg Econ, Ekaterinburg, Russia; [Sakashita, Mototaka] Keio Business Sch, Grad Sch Business Adm, Yokohama, Japan; [Dhir, Amandeep] Univ Agder, Dept Management, Sch Business & Law, Grimstad, Norway; [Dhir, Amandeep] Univ Stavanger, Norwegian Sch Hotel Management, Stavanger, Norway; [Dhir, Amandeep] North West Univ, Optentia Res Focus Area, Potchefstroom, South Africa; [Gavurova, Beata] Tomas Bata Univ Zlin, Fac Management & Econ, Zlin, Czech Republic
utb.scopus.affiliation MICA School of Ideas, Indian Institute of Management Ahmedabad, Ahmedabad, India; Department of Management, University of Turin, Italy; Graduate School of Business Administration, Keio Business School, Yokohama, Japan; Department of Management, University of Agder School of Business and Law, Grimstad, Norway; Faculty of Management and Economics, Tomas Bata University in Zlin, Zlin, Czech Republic; Laboratory for International and Regional Economics, Graduate School of Economics and Management, Ural Federal University, Yekaterinburg, Russian Federation; Norwegian School of Hotel Management, University of Stavanger, Stavanger, Norway; Optentia Research Focus Area, North-West University, Potchefstroom, South Africa
utb.fulltext.projects NFP313011BWN6
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