Non-Invasive Personalized Normative Messaging Intervention for the Reduction of Household Energy Consumption

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

1705273 (Lee). Household fossil fuel consumption in the U.S. is responsible for approximately 22% of primary energy consumption and CO2 equivalent emissions. Consequently, it is an objective of this project to identify widely applicable intervention methods potentially capable of promoting environmentally responsible behaviors. The goal of this research is to advance understanding of how personalized normative comparison groups influence the effectiveness of normative feedback interventions through the development and validation of a non-invasive data mining-based behavior intervention framework, with field experiments conducted in homes in Holland, Michigan. Successful implementation of the research would significantly contribute to reducing harmful emissions from the built environment through the enhancement of pro-environmental feedback intervention design by providing a detailed first look into personalized normative feedback. Specific research objectives are: 1) to classify households into several meaningful groups sharing similar consumption patterns on the basis of hourly energy usage data, using non-invasive techniques; and 2) to generate and then empirically evaluate the effectiveness of personalized normative energy use feedback created with the use of readily available consumption data. The research is targeted to provide an in-depth understanding of both the reliability of personalized normative messages, and how and where energy use behavior changes. Further, it seeks to discover long-term effects of personalized normative feedback on household energy consumption and identify the effect of descriptive norm reference groups on energy consumption norm adherence and energy use. All of these could contribute to residential energy use reduction by advancing the theories for normative energy feedback. The findings on how and where personalized normative messaging changes occupant behavior in both the short and long term have important implications for energy reporting, policy making, and meeting of state and national energy reduction goals. In addition, lessons learned on personalized normative messaging on energy use can be readily applied to other pro-environmental behaviors (e.g., water consumption). Particularly, the proposed non-intrusive personalized feedback messaging framework may be capable of wide-scale deployment in advanced utility networks.