Analyzing Social-Psychological Factors Affecting the Acceptance of Demand Response Programs Candace Pang & Elizabeth Price Young Scholars Program Mentors: Dr. Xiaojing Xu, Erica Davis, Jackson Lanier Faculty member: Dr. Chien-fei Chen July 18, 2016 NSF-DOE Engineering Research Center, CURENT University of Tennessee, Knoxville differentiate from others

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Social-Psychology & Behavioral Studies How people act, think, and feel in society as a whole Process of a social system through organization and structure E

Importance of Social Studies in Energy Research To provide a different, often overlooked perspective to problem-solving Focus on behavior and demand Collaboration among disciplines is necessary Sovacool, B. K. (2014). Diversity: Energy studies need social science.Nature, 511(7511), 529. E

Outline Introduction Integration Collecting Data Analyzing Data Conclusion

Integrating Social Psychology Emphasize social topics in the scientific process Problem-oriented vs. technology-oriented Interdisciplinary crosswork, comparison, & cooperation Sovacool, B. K., Ryan, S. E., Stern, P. C., Janda, K., Rochlin, G., Spreng, D., ... & Lutzenhiser, L. (2015). Integrating social science in energy research. Energy Research & Social Science, 6, 95-99. explain lightbulbs C

Outline Introduction Integration Collecting Data Analyzing Data Conclusion

Descriptive Statistics Ethnic background Who is our sample? White, Caucasian; not Hispanic 55.8% African American, Black 11.1% Hispanic, Latino 24.0% Asian, Asian American 6.2% American Indian, Native American .5% Multi-race 2.4% Gender* 51% Female 49% Male Income level Less than $34,999 31.6% $35,000-$99,999 42.1% $100,000+ 25.7% representative E *We recognize that gender is a spectrum rather than a binary; however, for the purposes of our data analysis, we included male and female.

Demand Response (DR) Programs Reducing/shifting electricity usage during peak hours Time-based rates & financial incentives To balance supply and demand Can lower electricity costs utilities? grid? C Department of Energy, Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them.” A Report to the United States Congress Pursuant to Section 125 of the of the Energy Policy Act of 2005, 2006.

Survey Questions The final sample for this analysis included 1600 participants from Tennessee, Texas, Virginia, and California. The relevant demand response questions included: A/C Devices and Settings, and DR programs. A/C Devices and Settings questions gives insight on how much energy a participant regularly consumes. DR program questions indicate how likely participants are to join certain DR programs. At what times of the day is someone at your home? What type of cooling system do you have at home during the summer? What type of heating system do you have at home during the winter? What is your cooling temperature setting when someone is at home during the summer vs. when someone is not at home? What is your heating temperature setting when someone is at home during the winter vs. when someone is not at home? What is your monthly electricity bill in the winter vs. in the summer?

DR Program Questions The types of DR programs used: The DR program questions asked the participants if they would be willing to participate in particular DR programs without incentives. The types of DR programs used: Installation of an A/C switcher Installation of an automatic A/C thermostat adjuster (3 degrees max) Installation of a heat pump switcher Installation of an automatic heat pump thermostat adjuster (3 degrees max) Manual power consumption reduction via encouragement from your utility company

Outline Introduction Integration Collecting Data Analyzing Data Conclusion

Social-Psych Factors, Segmentation and Demand Response (DR) Our Key Question: How do we predict acceptance of Demand Response programs from demographic variables and social-psychological factors?

Predictors of HVAC-related DR Behaviors Energy Use Info Demographics Social-Psychological Average Monthly Bill Age Energy Concern Stay Home (9am-5pm) Gender Bill Consciousness Light Use Income Need for Comfort Thermostat Settings Education Need for Convenience Night Adjustments Political Orientation Need for Control House Sqft Trust Household Size Subjective Norm Weather Region Perceived Control give examples Block 1 Block 2 Block 3

Demographics & Social-Psych Impacts on Energy Behavior Independent Variable Dependent Variable B Value & Significance Age .489*** Teens -1.275*** Energy Consumption: Cooling Temperature in Summer Energy Concern 1.389* linear temp- indicator .765*** Bill Consciousness -.810*** Comfort Need

Demographics & Social-Psych Impacts on Energy Behavior Independent Variable B Value & Significance Age -.140* Number in Home .240* Energy Concern .264** Bill Consciousness .466*** Trust .225* Comfort Need -.242* Social Norms .545*** Need for Control -.399* DR: Acceptance of Automatic Thermostat Device to Reduce Energy Consumption

Demographics & Social-Psych Impacts on Energy Behavior Independent Variable B Value & Significance Age .122* Number in Home .250** Energy Concern .171* Bill Consciousness .260* Comfort Need -.659*** Social Norms .498*** Perceived Behavioral Control .224* DR: Acceptance of Reducing Energy Consumption by Encouragement

Outline Introduction Integration Collecting Data Analyzing Data Conclusion

Answer How do we predict acceptance from demographic variables and social-psychological factors? Demographic variables: The older the participant was, the less likely he/she was to accept DR programs. The greater number of people in their household, the more likely they were to accept the DR programs. Social-psychological factors: The more energy concern, bill consciousness, trust, social norms, perceived behavioral control, less comfort need, and need for control a participant had, the more likely he/she was to accept DR programs. hypothesis

Thank You Thank you for your time. A special thanks to our mentors for their guidance throughout this program: Dr. Chen Dr. Xiaojing Xu Erica Davis Jackson Lanier