For designers, the model provides guidance for offering user-customized settings for DVAs, according to user preferences. Future research should quantitatively investigate the relationships between user profiles and acceptance. Rejection relates to the deviceвЂ™s autonomous decision-making and privacy control capabilities, as well as the style of interaction, when the DVA acts as though it was a friend. Red lines appear for some applications, indicating that they are technically feasible but, at least currently, rejected. The framework suggests four gradations each representing an advanced application of artificial intelligence. This paper contributes to the existing literature by exploring the attributes that influence the perception of DVAs and providing a graduated framework for organizing the accepted and desired degree of smartness for DVAs. Using a qualitative content analysis, a category system for the degree of product smartness (PS) of DVAs is developed. The qualitative research design is based on interviews with users and non-users of DVAs. The existing literature lacks research on the critical characteristics and properties of DVAs, as well as a categorization of their smartness in the light of the advances in artificial intelligence. Of course, they can be used only to talk to, but that greatly restricts what the assistants are capable of. DVAs are not designed to work in isolation. Therefore, the decision to buy and use a DVA is different.

We argue that digital voice assistants (DVAs) are different from other smart products because DVAs are not self-contained products. This research investigates the conditions for the acceptance of digital voice user interfaces focusing on the accepted and desired degree of product smartness. As firms integrate digital assistants into their operations, they must help customers properly define what to expect from the firmвЂ™s interactive experience. This study provides evidence that customer expectations are being satisfied through the digital assistant interaction experience. The results confirmed that expectations and confirmation of expectations have a positive and significant relationship on customer satisfaction with digital assistants. PLS-SEM was used to analyse 244 survey responses to examine this research gap. At present, there is little empirical evidence of customer satisfaction with digital assistants. This study reflects the contextual experiences of the respondents. Yet, the functional and topical use of a digital assistant tends to vary by individual. Individuals can use digital assistants to perform basic personal tasks as well as for more advanced capabilities. Digital assistants (e.g., AppleвЂ™s Siri, AmazonвЂ™s Alexa, GoogleвЂ™s Google Assistant) are highly complex and advanced artificial intelligence (AI) based technologies.

The perfect assistant kw .pdf