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Exploring Deep Savings: A Toolkit for Assessing Behavior-Based Energy Interventions
The document discusses the effectiveness of behavior-based energy interventions, particularly the role of feedback in energy conservation, analyzed through various studies. It highlights the variability in outcomes based on factors such as study population and feedback methodology, while also addressing methodological limitations in current research. Additionally, it outlines the next steps for toolkit development and testing in the context of energy efficiency.
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Exploring Deep Savings: A Toolkit for Assessing Behavior-Based Energy Interventions
- 1. Exploring Deep Savings: AToolkit for Assessing Behavior-Based Energy Interventions Beth Karlin Transformational Media Lab University of California, Irvine Papers listed here. Contact me for details: bkarlin@uci.edu.
- 2. Is Feedback Effective? 100+ studies conducted since 1976 Total n = 256,536 (mean 119/study) Mean r-effect size = .1174 (p < .001) Average energy savings: 9% Significant variability in effects (from negative effects to over 20% savings) Karlin, Ford & Zinger. (In Press). The Effects of Feedback on Energy Conservation: A Preliminary Theory and Meta-Analysis. Psychological Bulletin.
- 3. Is Feedback Effective? Itdepends… Moderators identified in meta-analysis • Study population (WHO?) • Study duration (HOW LONG?) • Frequency of feedback (HOW OFTEN?) • Feedback medium (WHAT TYPE?) • Disaggregation (WHAT LEVEL?) • Comparison (WHAT MESSAGE?) Karlin, Ford & Zinger. (In Press). The Effects of Feedback on Energy Conservation: A Preliminary Theory and Meta-Analysis. Psychological Bulletin.
- 4. Methodological Limitations 1. Notnaturalistic Participants generally recruited to participate May be different from “active adopters” 2. Not comparative Most studies tests one type of feedback (vs. control) Very few studies isolating or combining variables 3. Not testing mediation DV is energy use, but studies rarely test possible mediators to explain effectiveness Karlin, Ford & Zinger. (In Press). The Effects of Feedback on Energy Conservation: A Preliminary Theory and Meta-Analysis. Psychological Bulletin.
- 5. Methodological Limitations 1. Notnaturalistic Participants generally recruited to participate May be different from “active adopters” 2. Not comparative Most studies tests one type of feedback (vs. control) Very few studies isolating or combining variables 3. Not testing mediation DV is energy use, but studies rarely test possible mediators to explain effectiveness Karlin, Ford & Zinger. (In Press). The Effects of Feedback on Energy Conservation: A Preliminary Theory and Meta-Analysis. Psychological Bulletin.
- 6. Will they come? Ifyou build it,
- 7. Program x Outcome y Doesit work? Does program x lead to outcome y?
- 8. Program x Outcome y Questionsremain… What is the program? What is going on here? How do we measure outcomes? Does program x lead to outcome y?
- 9. Program x Outcome y Atheoretical approach Hypothesis / Theory Clearly defined and operationalized Metrics tested for reliability & validity Does program x lead to outcome y? How and for whom does program x lead to outcome y?
- 10. How and ForWhom?
- 11. How and forWhom?
- 12. Toolkits in otherfields
- 13. Toolkits in otherfields
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- 17. Psychometrics • Theory andtechnique of measurement: knowledge, abilities, attitudes, traits • Construction and validation of instruments: questionnaires, tests, assessments
- 18. Psychometrics Psychometric Properties 1.Factor Structure 2.Reliability 3. Criterion Validity 4. Sensitivity
- 19. Our Project Initial concept paper IEA DSMTask 24 Methods review Report for IEA Karlin et al., 2015 Toolkit Pilot testing Member country testing Consultation Feedback SCE Psychometric testing 2013 201620152014 PG&E Field testing (scheduled)
- 20. Methodological Review Karlin, Ford,Wu, & Nasser. (2015). What Do We Know About What We Know? A Review of Behaviour-Based Energy Efficiency Data Collection. IEA-DSM Task 24 Subtask 3 Report.
- 21. Karlin, Ford, Wu,& Nasser. (2015). What Do We Know About What We Know? A Review of Behaviour-Based Energy Efficiency Data Collection. IEA-DSM Task 24 Subtask 3 Report. Data Collection Methods Used
- 22. Instruments Provided? Karlin, Ford,Wu, & Nasser. (2015). What Do We Know About What We Know? A Review of Behaviour-Based Energy Efficiency Data Collection. IEA-DSM Task 24 Subtask 3 Report.
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- 25. Toolkit Development Heating devicesEnergy sources Insulation House structure Have
- 26. Toolkit Development Social expectations and Environmental concern Expected warmthlevels Maintaining traditions Think
- 27. Toolkit Development Turning on heater Puttingon jersey Maintaining heating technologies Drawing curtainsDo
- 28. Toolkit Development Have DoThink Have DoThink Energy Cultureat start Energy Culture at end Have DoThink Have DoThink Energy Culture at start Energy Culture at end Intervention Natural changes User experience Technology interaction ControlGroupTreatmentGroup
- 29. Toolkit Development Have DoThink Have DoThink Energy Cultureat start Energy Culture at end Have DoThink Have DoThink Energy Culture at start Energy Culture at end Intervention Natural changes User experience Technology interaction ControlGroupTreatmentGroup
- 30. Next Steps 1. Psychometrictesting (SCE) 2. Local field testing (PG&E / SCE) 3. Member country review 4. Global field testing 5. Wide scale adoption?
- 31. Beth Karlin Transformational MediaLab University of California, Irvine bkarlin@uci.edu Thank you! (comments and suggestions welcome)
Editor's Notes
- #3 When we have no idea… we might unplug to be safe. When we know…
- #4 When we have no idea… we might unplug to be safe. When we know…
- #5 Infrastructure is coming with the smart grid, technology is developed and being fine tuned via multiple presentation mediums AND culturally, we’re already there. Feedback is everywhere, calorie count of food, cotton counts on clothing. Information is popular!
- #6 Infrastructure is coming with the smart grid, technology is developed and being fine tuned via multiple presentation mediums AND culturally, we’re already there. Feedback is everywhere, calorie count of food, cotton counts on clothing. Information is popular!
- #7 Infrastructure is coming with the smart grid, technology is developed and being fine tuned via multiple presentation mediums AND culturally, we’re already there. Feedback is everywhere, calorie count of food, cotton counts on clothing. Information is popular!
- #8 Infrastructure is coming with the smart grid, technology is developed and being fine tuned via multiple presentation mediums AND culturally, we’re already there. Feedback is everywhere, calorie count of food, cotton counts on clothing. Information is popular!
- #9 Infrastructure is coming with the smart grid, technology is developed and being fine tuned via multiple presentation mediums AND culturally, we’re already there. Feedback is everywhere, calorie count of food, cotton counts on clothing. Information is popular!
- #10 Infrastructure is coming with the smart grid, technology is developed and being fine tuned via multiple presentation mediums AND culturally, we’re already there. Feedback is everywhere, calorie count of food, cotton counts on clothing. Information is popular!
- #13 65.9 billion kWh 5.8% of electricity in average home 7th most consuming activity behind: air conditioning, refrigeration, space heating, water heating, and lighting. Cost: 30-40 cents in an electric dryer; 15-20 cents in a gas dryer. Over its expected lifetime of 18 years, the average clothes dryer will cost you approximately $1,530 to operate. Do Not Use a Clothes Dryer........................ 23.6 million (21.2%) Use a Clothes Dryer.................................... 87.5 million (78.8%)
- #14 65.9 billion kWh 5.8% of electricity in average home 7th most consuming activity behind: air conditioning, refrigeration, space heating, water heating, and lighting. Cost: 30-40 cents in an electric dryer; 15-20 cents in a gas dryer. Over its expected lifetime of 18 years, the average clothes dryer will cost you approximately $1,530 to operate. Do Not Use a Clothes Dryer........................ 23.6 million (21.2%) Use a Clothes Dryer.................................... 87.5 million (78.8%)
- #15 65.9 billion kWh 5.8% of electricity in average home 7th most consuming activity behind: air conditioning, refrigeration, space heating, water heating, and lighting. Cost: 30-40 cents in an electric dryer; 15-20 cents in a gas dryer. Over its expected lifetime of 18 years, the average clothes dryer will cost you approximately $1,530 to operate. Do Not Use a Clothes Dryer........................ 23.6 million (21.2%) Use a Clothes Dryer.................................... 87.5 million (78.8%)
- #16 65.9 billion kWh 5.8% of electricity in average home 7th most consuming activity behind: air conditioning, refrigeration, space heating, water heating, and lighting. Cost: 30-40 cents in an electric dryer; 15-20 cents in a gas dryer. Over its expected lifetime of 18 years, the average clothes dryer will cost you approximately $1,530 to operate. Do Not Use a Clothes Dryer........................ 23.6 million (21.2%) Use a Clothes Dryer.................................... 87.5 million (78.8%)
- #17 65.9 billion kWh 5.8% of electricity in average home 7th most consuming activity behind: air conditioning, refrigeration, space heating, water heating, and lighting. Cost: 30-40 cents in an electric dryer; 15-20 cents in a gas dryer. Over its expected lifetime of 18 years, the average clothes dryer will cost you approximately $1,530 to operate. Do Not Use a Clothes Dryer........................ 23.6 million (21.2%) Use a Clothes Dryer.................................... 87.5 million (78.8%)
- #31 Infrastructure is coming with the smart grid, technology is developed and being fine tuned via multiple presentation mediums AND culturally, we’re already there. Feedback is everywhere, calorie count of food, cotton counts on clothing. Information is popular!