Consumers acceptance of artificially intelligent (AI) device use in service delivery

•This study tests an artificial intelligent device use acceptance model.•The model provides insights on consumer acceptance/rejection of AI device.•Level of anthropomorphism enhances customers’ effort expectancy.•Emotion determines acceptance and rejection of AI devices.•A multi-stage appraisal is n...

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Bibliographic Details
Published in:International journal of information management 2019-12, Vol.49, p.157-169
Main Authors: Gursoy, Dogan, Chi, Oscar Hengxuan, Lu, Lu, Nunkoo, Robin
Format: Article
Language:English
Subjects:
Acceptance
Adoption
AI devices
Anthropomorphism
Artificial intelligence
Customer services
Customers
Intention
Model testing
Services
Technology
Technology Acceptance Model
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Summary:•This study tests an artificial intelligent device use acceptance model.•The model provides insights on consumer acceptance/rejection of AI device.•Level of anthropomorphism enhances customers’ effort expectancy.•Emotion determines acceptance and rejection of AI devices.•A multi-stage appraisal is necessary to understand behavioral outcomes. This study develops and empirically tests a theoretical model of artificially intelligent (AI) device use acceptance (AIDUA) that aims to explain customers’ willingness to accept AI device use in service encounters. The proposed model incorporates three acceptance generation stages (primary appraisal, secondary appraisal, and outcome stage) and six antecedents (social influence, hedonic motivation, anthropomorphism, performance expectancy, effort expectancy, and emotion). Utilizing data collected from potential customers, the proposed AIDUA model is tested. Findings suggest that customers go through a three-step acceptance generation process in determining whether to accept the use of AI devices during their service interactions. Findings indicate that social influence and hedonic motivation are positively related to performance expectancy while anthropomorphism is positively related to effort expectancy. Both performance and effort expectancy are significant antecedents of customer emotions, which determines customers’ acceptance of AI device use in service encounters. This study provides a conceptual AI device acceptance framework that can be used by other researchers to better investigate AI related topics in the service context.
ISSN:0268-4012
1873-4707
DOI:10.1016/j.ijinfomgt.2019.03.008