Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/134857
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Type: Journal article
Title: Recasting Service Quality for AI-Based Service
Author: Noor, N.
Rao Hill, S.
Troshani, I.
Citation: Australasian Marketing Journal, 2022; 30(4):297-312
Publisher: Elsevier
Issue Date: 2022
ISSN: 1441-3582
1839-3349
Statement of
Responsibility: 
Nurhafihz Noor, Sally Rao Hill, Indrit Troshani
Abstract: Artificial intelligence service agents (AISA), such as chatbots and virtual assistants, are becoming increasingly pervasive in service. Research to date has not adequately addressed how the unique nature of AISA shape consumers’ service quality expectations. A deeper understanding of AISA service quality is important for their successful deployment in the service sector. To address this gap, we reviewed marketing and information systems literatures and conducted qualitative in-depth interviews with 37 informants, inclusive of 28 AISA users and nine AISA experts. We developed a conceptual framework for how consumers use and evaluate AISA. Twelve service quality dimensions emerged from the qualitative evidence representing AISA service quality, two of which align with AISA’s unique characteristics. The study extends the service quality theory to a new context and offers fresh insights for theory and practice. It culminates with a research agenda to advance research on AISA service quality.
Keywords: service quality; artificial intelligence; anthropomorphism; proactiveness
Description: First published online: April 5, 2021
Rights: © 2022 by Australian and New Zealand Marketing Academy. Published by Elsevier Ltd. All rights reserved.
DOI: 10.1177/18393349211005056
Published version: https://journals.sagepub.com/doi/10.1177/18393349211005056
Appears in Collections:Business School publications

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