We use analytical approaches to identify critical knowledge about a decision with high uncertainty, as well as mixed methods to identify how the decision makers conceptualize the decision problem.

A mental models approach to developing communications and interventions seeks to close critical gaps between the what people “should” know with current beliefs, understandings, and capabilities. We have applied this approach to varied decision contexts from energy efficiency to contraceptive decision making.

In a 2012 study, our team utilized this approach to analyze how consumers understand implementation of smart grid technologies. Researchers conducted unstructured phone interviews to compile a list of consumer beliefs about smart meters, a sensor that collects accurate data on real-time energy consumption in the home. From this data, a questionnaire was constructed to test consumer beliefs on a larger scale.

The research identified a positive predisposition to the technology. It also identified uncertainty and misconceptions about smart meters. This mental models approach allows researchers and policymakers to pinpoint the gaps in understanding and develop effective communication to correct the erroneous beliefs.

Featured paper: Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters

Other research: A decision science approach for integrating social science in climate and energy solutions

Krishnamurti T, Eggers SL, Fischhoff B. (2008). The impact of over-the-counter availability of Plan B on teens’ contraceptive decision making. Soc Sci Med. 67(4), 618-627.