Voice intelligence is a revolutionary "zero-touch" type of human-machine interaction based on spoken language. There has been a recent increase in the number and variations of voice assistants and applications that help users to acquire information. The increased popularity of voice intelligence, however, has not been reflected in the customer value chain. Current research on the socio-technological aspects of human-technology interaction has emphasized the importance of anthropomorphism and user identification in the adoption of the technology. Prior research has also pointed out that user perception toward the technology is key to its adoption. Therefore, this research examines how anthropomorphism and multimodal biometric authentication influence the adoption of voice intelligence through user perception in the customer value chain. In this study we conducted a between-subjects online experiment. We designed a 2 × 2 factorial experiment by manipulating anthropomorphism and multimodal biometric authentication into four conditions, namely and a combination of these two factors. Subjects were recruited from Amazon MTurk platform and randomly assigned to one of the four conditions. The results drawn from the empirical study showed a significant direct positive effect of anthropomorphism and multimodal biometric authentication on user adoption of voice intelligence in the customer value chain. Moreover, the effect of anthropomorphism is partially mediated by users' perceived ease of use, perceived usefulness, and perceived security risk. This research contributes to the existing literature on human-computer interaction and voice intelligence by empirically testing the simultaneous impact of anthropomorphism and biometric authentication on users' experience of the technology. The study also provides practitioners who wish to adopt voice intelligence in the commercial environment with insights into the user interface design.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9428311 | PMC |
| http://dx.doi.org/10.3389/frai.2022.831046 | DOI Listing |
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