1. 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

2. Outline
Introduction
Integration
Collecting Data
Analyzing Data
Conclusion

3. 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

4. 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

5. Outline
Introduction
Integration
Collecting Data
Analyzing Data
Conclusion

6. 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,
explain
lightbulbs C

7. Outline
Introduction
Integration
Collecting Data
Analyzing Data
Conclusion

8. 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.

9. 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.

10. 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?

11. 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

12. Outline
Introduction
Integration
Collecting Data
Analyzing Data
Conclusion

13. 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?

14. 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

15. 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

16. 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

17. 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

18. Outline
Introduction
Integration
Collecting Data
Analyzing Data
Conclusion

19. 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

20. 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