An exploration of the U.S. Department of Energy’s 2009 Residential Energy Consumption Survey revealed a deep discrepancy between energy consumption habits of older adults (65+) and the rest of the population. Despite the impending increase in the size of this older adult population, there is no research into potential solutions for helping older adults reduce energy consumption to a level more in line with the rest of the United States. Cade’s team proposed a messaging intervention using “generative messaging” based on the theory of generativity proposed by social and developmental psychologist Eric Erickson, which states that older adults face a decision between finding fulfillment via nurturing future generations or enduring social stagnation. The challenge was to provide messaging that convinces older adults that changing energy consumption behavior for the benefit of those around them is an adequate means of achieving generative fulfillment. This tests a new incentive structure outside of the commonly attempted approaches (normative and financial). Because behavioral incentives have the estimated upper impact of a 20% reduction in energy consumption, Cade’s team believed that tailoring their approach to a specific subpopulation and using a new approach would help improve on the 3–5% reduction achieved by other studies.
At the National Renewable Energy Laboratory, Cade worked on analysis software called ComStock that allows users to model the entire commercial building stock of the United States and apply different energy-reducing measures to gauge potential savings. Cade’s role was to identify non-weather seasonal factors that impact energy use within commercial buildings and implement them within the model, generally by developing predictive models based on existing data related to factors such as tourism, hotel occupancy, and building-level electricity use, and then write OpenStudio measures to make necessary adjustments within the framework of ComStock.