Individual Differences in Information Processing in Networked Decision Making

Abstract : In todays networks, individuals frequently face the problem of information overload. The amount of information available for a decision is often much larger than a person can process to make an informed decision. Past research has shown that individuals can differ significantly in how they use information in making decisions. Individuals may differ in their willingness to seek and incorporate more information into their decision making, some relying more on information at hand than simple heuristics. Individuals desire to reach a closure quickly by making a decision may differ as well, depending on situational factors such as the level of inherent ambiguity or uncertainty in the decision. These factors have not yet been studied deeply in the context of networked information processing in terms of their impact on the timeliness and accuracy of decisions. In this paper, we address this problem by introducing an agent-based model that incorporates four characteristics representing individual differences: competence, engagement, decisiveness and reliance on neighbors opinions for corroboration. Based on a novel way of modeling the degree of problem difficulty, we investigate the impact of individual differences in networked decision making through comprehensive simulation experiments. Our simulation results show that being more engaged with a task does not always improve team performance and can lead to information overload if it is coupled with high information push activity. Similarly, heuristic decisions as a result of high decisiveness can be useful in various problem settings and can be further improved by a small amount of corroboration.