Perceptions of electricity-use communications: effects of information, format, and individual differences

Abstract

Electricity bills could be an effective strategy for improving communications about consumers’ electricity use and promoting electricity savings. However, quantitative communications about electricity use may be difficult to understand, especially for consumers with low energy literacy. Here, we build on the health communication and graph comprehension literature to inform electricity bill design, with the goal of improving understanding, preferences for the presented communication, and intentions to save electricity. In a survey-based experiment, each participant saw a hypothetical electricity bill for a family with relatively high electricity use, covering information about (a) historical use, (b) comparisons to neighbors, and (c) historical use with appliance breakdown. Participants saw all information types in one of three formats including (a) tables, (b) bar graphs, and (c) icon graphs. We report on three main findings. First, consumers understood each type of electricity-use information the most when it was presented in a table, perhaps because tables facilitate simple point reading. Second, preferences and intentions to save electricity were the strongest for the historical use information, independent of format. Third, individuals with lower energy literacy understood all information less. We discuss implications for designing utility bills that are understandable, perceived as useful, and motivate consumers to save energy.

Keywords:

• electricity-use information
• graphs
• energy literacy

Funding and Acknowledgements

This work was supported by the U.S. Department of Energy (DE-OE0000300 and DE-OE0000204) via a cost-share arrangement with the Carnegie Mellon Electricity Industry Center as well as the center for Climate and Energy Decision Making (SES-0949710; SES-1463492), through a cooperative agreement between the National Science Foundation and Carnegie Mellon University. Casey Canfield was supported by the National Science Foundation Graduate Research Fellowship (1121895). This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. We thank Denise Caruso, Barbara Bugosh, and Jack Wang for their help in conducting the research. In addition, we are grateful to Baruch Fischhoff, Yasmina Okan, Eric Stone, and anonymous reviewers from CMU’s Engineering and Public Policy faculty for their comments on an earlier draft. details have been set correctly.

Disclosure statement

The authors have no financial interest or benefit arising from the direct applications of their research.

Notes

1. To provide households with feedback about their appliance-specific electricity use, homes may need to be instrumented with appliance-level meters. Lower cost options include estimating appliance use based on consumer-provided information (e.g. Residential Energy Consumption Survey, www.eia.gov/consumption/residential), which may not be as accurate.