Nuanced user/stakeholder representation creates more-useful overall engineering system models. Design Optimization approaches paired with knowledge of Models of Decision-making creates the palette from which our research creates nuanced models of people within larger engineering models.
Design can trigger the better angels of our nature. Construction of Preference implies that decisions are malleable. A customer that would normally forget sustainability during a product purchase can, instead, seek it, in the right decision context. Through Test vs. Control Experiments, we have demonstrated that designers can create this context using a design method we created, and that customers respond positively to the resulting designs, seeking out sustainable information and ranking it important in product decisions.
Interactions with people best determine when and how to model complex human decisions. The IRIS lab uses Interviews, Observations, and Surveys to better understand how people approach and make Complex Decisions about sustainable products and technologies.