An Agent-based Environment for Dynamic Positioning of the Fogg Behavior Model Threshold Line

In this paper, it is presented a mathematical modeling for the action line, or threshold line, of the Fogg Behavior Model (FBM) as well as an analysis of its positioning in relation to the dataset. According to the mathematical modeling formation process for both Motivation and Ability axes, the action line evaluation was performed by simulations via agents. This behavioral model is mainly used as an empirical evaluation method applied to processes based on persuasive technologies. The results showed that the threshold line should not be fixed, as originally proposed in the model, but dynamically allocated based on the Kolmogorov mean. This dynamic allocation ensures its use as a visual feature towards greater efficiency in triggers implementations. This work aims to contribute with an approach that transits between theoretical and practical when related to applications that requires the FBM, thus allowing the use of this behavioral model with higher degree of certainty and thus maximizing efficiency in the evaluation and implementation processes based on persuasive technologies.