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Identifying Design Feature Factors Critical to Acceptance of Smart Voice Assistant

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Cross-Cultural Design. Applications in Cultural Heritage, Tourism, Autonomous Vehicles, and Intelligent Agents (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12773))

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Abstract

The rapid development of artificial intelligence technology has made a variety of smart voice assistant products manufactured and widely used. Nevertheless, the influence of the design features of smart voice assistants on user acceptance is relatively vague. This study aimed to identify the design features that are critical to the acceptance of smart voice assistants by users. A questionnaire was designed and constructed. A total of 220 subjects participated in this survey. User acceptance is measured with perceived ease of use (PEOU), perceived usefulness (PU), attitude (AT) and intention to use (IU). Results showed that PU was significantly associated with smart voice assistant gender and PEOU. AT was significantly related to content diversity, personification, PEOU, and PU. IU was significantly related to sound quality, PU, and AT. The proposed model comprising demographic variables, design features, and acceptance-related variables could explain 49.3% of the variance in IU.

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Acknowledgements

This work was supported by grants from Natural Science Foundation of China (Project No. 71901033) and Beijing Natural Science Foundation (Project No. 9204029).

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Authors and Affiliations

  1. School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China

    Na Liu

  2. International School, Beijing University of Posts and Telecommunications, Beijing, China

    Ruoxuan Liu & Wentao Li

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  1. Na Liu
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  2. Ruoxuan Liu
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  3. Wentao Li
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Correspondence to Na Liu .

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Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Pei-Luen Patrick Rau

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Liu, N., Liu, R., Li, W. (2021). Identifying Design Feature Factors Critical to Acceptance of Smart Voice Assistant. In: Rau, PL.P. (eds) Cross-Cultural Design. Applications in Cultural Heritage, Tourism, Autonomous Vehicles, and Intelligent Agents. HCII 2021. Lecture Notes in Computer Science(), vol 12773. Springer, Cham. https://doi.org/10.1007/978-3-030-77080-8_30

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  • DOI: https://doi.org/10.1007/978-3-030-77080-8_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77079-2

  • Online ISBN: 978-3-030-77080-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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