The role of interaction quality in use of AI-based voice-assistant systems : evidence from Finland.

Abstract

This study focuses on the influence of interaction quality on users’ intention to use AI-based voice assistance systems (VAS). The study is conducted in Finland and reveals users’ behaviors toward AI-based VAS utilization. The researcher conducted empirical testing to understand the impact of information quality and system quality on interactions with an intention to use AI-based VAS. The research design was quantitative survey-based research, and primary data through self-administrated surveys was collected from Finland. Item response theory was utilized to determine the population of the study, and the researcher received 100 fully filled responses. The data was analyzed using partial least square (PLS) regression software. PLS was used for structural equation modeling (SEM) and for advanced analysis (i.e., model testing). The findings of the study show that system quality and information quality are positively and strongly related to the interaction quality of AI-based VAS. In addition, the results indicated that consumers were more likely to use AI-based VAS when the interaction quality is higher. The current research has both practical and theoretical implications. From a theoretical perspective, the research adds to the IS (Information System) success model and the existing debate on user interactions with technology. From a managerial point of view, the researcher concludes that technology developers and innovators should enhance the quality of information and systems of AI-based VAS so that people can interact with AI-based VAS more effectively. The limitations and future research of the study are discussed at the end of the thesis.