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, researchers employed the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). For this research paper, seven variables were analyzed: 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. Researchers carried out an online survey with 304 responses. The obtained sample was analyzed with Structural Equation Modeling (SEM) through IBM SPSS V. 27.0 and AMOS V 27.0. The main study results reveal that factors, such as 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 users' 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 the knowledge gap on this topic, as it is an emerging technology. This investigation also provides relevant information on how to successfully implement these technologies.

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El objetivo de esta investigación es revisar y comparar a través de un enfoque bibliométrico la TAM/TAM2/TAM3 y la UTAUT/UTAUT2 para determinar cuál es el modelo más adecuado para estudiar las nuevas tecnologías. Los datos se obtuvieron de la base de datos Web of Science. Se examinaron 2.450 publicaciones, relacionadas con TAM/TAM2/TAM3 y 5.145 publicaciones de la UTAUT/UTAUT2 durante el período 2016-2021. Los hallazgos confirman que cada vez más investigadores utilizan la UTAUT/UTAUT2. Esta revisión ofrece una visión holística que servirá para que futuros investigadores puedan seleccionar los modelos más apropiados en sus disciplinas de estudio.

This study aims at presenting a market trend in the space of video games for interacting with potential customers. The development of a video segment shows a noticeable increase in interest and tracked improvements in the user experience. As part of the implementation of the new strategy focused on consumer behavior around the advergames, the opinions of players lead to a value proposition. Additionally, the study on advergames impact and adoption of the market trend led to a seeding start-up, Devolver Digital: Devolverland Expo. In order to establish the analysis and assessment from a qualitative and quantitative base, a focused group and a questionnaire were provided in order to measure data and track its implementation. By interacting with a focus group and creating a tool for analysis, the study shows that adoption in video games and specifically, advergames, is closely related to experience as it is improved and evolving from the setting; however, this marketing method has areas for improvement within digital marketing to stand out to social ads, SEO, and SEM.

The objective of this research is to understand, predict and explain what factors influence organizations and induce individuals to accept technology. Through the methodology of content analysis and based on the Web of Science database and through the MAXQDA software, this document analyzes and reviews the ten most important theories and models of technology acceptance used in recent years. This review offers a holistic view that will help future researchers to select the most appropriate theories to apply to their field of study.