Optimized Influence Targeting for Adoption in Social Networks

Although decision processes are often described at the individual level of cognition (e.g. Tversky and Kahnemann The particular beliefs instantiated within the model are (1981)), they are subject to social and cultural influences based on a combination of results from empirical studies at both the interpersonal and societal levels. The adoption of technology adoption by Venkatesh et al. (2003). of new technology depends on various factors, such The UTAUT model combines eight of the most prominent as the type of technology, the context or culture in which technology-acceptance models observed in the literature and the technology is introduced, and the individual decisions provides a definitive list of variables that are critically relevant by people within that culture, as most individuals evaluate to an individual's Behavioral Intention (BI) and Use Behavior an innovation from the subjective evaluations of peers who (UB) for adopting a new technology, including Performance have adopted an innovation (see Watts and Dodds (2007) Expectancy (PE), Effort Expectancy (EE), Social for a discussion of network-diffused influence). These influences Influence (SI), Facilitating Conditions (FC), and Voluntariness propagate through the social network as a function of Use (VoU). of agent interactions.