Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants - García de Blanes Sebastián, María; Sarmiento Guede, José Ramón; Antonovica, Arta (Frontiers in Psychology, 2022)
Virtual Assistants, also known as conversational artificial intelligence, are transforming the reality around us. These virtual assistants have challenged our daily lives by assisting us in the different dimensions of our lives, such as health, entertainment, home, and education, among others. The main purpose of this study is to develop and empirically test a model to predict factors that affect users' behavioral intentions when they use intelligent virtual assistants. As a theoretical basis for investigating behavioral intention of using virtual assistants from the consumers´ perspective, there was employed the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). For this research paper there were analyzed seven variables, such as performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, habit, and price-value. In order to improve consumer behavior prediction, three additional factors were included in the study: perceived privacy risk, trust and personal innovativeness. There have been carried out an online survey with 304 responses. The obtained sample was analyzed with Structural Equation Modelling (SEM) through IBM SPSS V. 27.0 and AMOS V 27.0. Main study results reveal that factors, such habit, trust, and personal innovation, have a significant impact on the adoption of virtual assistants. However, on the other side, performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, price-value, and perceived privacy risk were not significant factors in the user's intention to adopt this service. This research paper examines the effect of personal innovation, security, and trust variables in relation to the use of virtual assistants. It contributes to a more holistic understanding of the adoption of these intelligent devices and tries to fill up the insufficient knowledge on this topic, as it is an emerging technology. This investigation also provides relevant information on how successfully implement these technologies.