Noor, Nurhafihz, Rao Hill, Sally, and Troshani, Indrit (2021) Recasting Service Quality for AI-Based Service. Australasian Marketing Journal, 30 (4). pp. 297-312.

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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.

Item ID:	79177
Item Type:	Article (Research - C1)
ISSN:	1839-3349
Keywords:	Service quality; artificial intelligence; anthropomorphism; proactiveness
Copyright Information:	Published Version: © 2021 Australian and New Zealand Marketing Academy. AAM maybe made open access in an Institutional Repository without embargo.
Date Deposited:	06 Jul 2023 02:21
FoR Codes:	35 COMMERCE, MANAGEMENT, TOURISM AND SERVICES > 3506 Marketing > 350611 Service marketing @ 50% 35 COMMERCE, MANAGEMENT, TOURISM AND SERVICES > 3506 Marketing > 350608 Marketing theory @ 50%
SEO Codes:	15 ECONOMIC FRAMEWORK > 1503 Management and productivity > 150303 Marketing @ 100%
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