Abstract or concrete? The effects of language style and service context on continuous usage intention for AI voice assistants

Hai Lan, Xiaofei Tang, Yong Ye () and Huiqin Zhang
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Hai Lan: Southwestern University of Finance and Economics
Xiaofei Tang: Southwestern University of Finance and Economics
Yong Ye: Southwestern University of Finance and Economics
Huiqin Zhang: Chengdu University of Technology

Palgrave Communications, 2024, vol. 11, issue 1, 1-13

Abstract: Abstract The unprecedented growth in voice assistants (VAs) provided with artificial intelligence (AI) challenges managers aiming to harness various new technologies to enhance the competitiveness of their products. This article thus investigates how VAs can more effectively improve the user experience by focusing on the attributes of service contexts, matching a utilitarian-dominant (hedonic-dominant) context with concrete (abstract) language in VA–human interactions. Through such matching, VA companies can potentially create a beneficial congruity effect, leading to more favorable evaluations. The results of three studies therefore suggest that users prefer VAs with abstract language in a hedonic-dominant service context, but that VAs with concrete language are more competitive in a utilitarian-dominant service context. Furthermore, the perception of processing fluency mediates this effect. Accordingly, these findings provide a better understanding of AI–human interactions and open a straightforward path for managers or technology providers to enhance users’ continuous usage intention.

Date: 2024
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DOI: 10.1057/s41599-024-02600-w

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