Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceNowadays a significant part of the objects (things) surrounding us have embedded technology like sensors, wireless, communication, and data analysis capabilities. Everyday digital artifacts lead us to information based on artifacts known as the Internet of things (IoT). The growing interest in these digital everyday artifacts from end-users, and their impact on use and individual performance were the catalyst for this research. This study aims to understand the perceived value influencing the use of IoT on individuals' performance. We suggest combining the task-technology fit (TTF) and the value-based adoption model (VAM) to evaluate the effect of IoT on individual performance. In this study we will implement an online questionnaire, which will be addressed to an IoT user’s audience. To test the model we used 303 valid responses. Findings suggest that TTF, use, user satisfaction, and perceived usefulness are important drivers to explain IoT individuals’ performance. Moreover, our results reveals that age moderates the relationship between perceived benefits and individual performance. Understanding the implication of IoT on individual performance will foment new insights and advantages for IoT managers and attract potential users
