Impact of Information, Goal Setting, Feedback & Rewards on Energy Use Behaviours: A Review & Meta-Regression Analysis of Field Experiments

Transcription

1 Impact of Information, Goal Setting, Feedback & Rewards on Energy Use Behaviours: A Review & Meta-Regression Analysis of Field Experiments Ken Tiedemann Power Smart, British Columbia Hydro BECC November 2010

2 Introduction Experimental research on energy-related behaviours has typically used randomized controlled experiments and focussed on the impact of a limited number of instruments including information, rewards, goal setting and feedback Most research has been guided by one of two perspectives: rational choice theory and the theory of planned behaviour Rational choice theory assumes that consumers maximize utility subject to relevant constraints: for this theory information and rewards appear to be particularly important Theory of planned behaviour assumes that consumers decisions are driven by actual control and intention: for this theory goal setting and feedback appear to be particularly important Page 2

3 Data and Method To identify potentially relevant studies, we reviewed various social, psychological and economics journals and databases Relevant studies had to meet the following criteria: (1) the study s target group was households; and (2) there had to be a plausible research design involving measurement of treatment effects compared to a baseline, to a comparison group or both We identified, reviewed and summarized over fifty studies to determine whether or not an effect size could be calculated from the available information in the study For ten of these studies involving twenty-eight treatments, an effect size could be calculated, where the effect size is defined as the mean treatment effect divided by the standard deviation of the treatment effect Modeled effect size as a function of a constant and four main treatments using White s robust OLS regression Page 3

4 Regression Models (White s robust OLS, outcome variable is effect size, n = 28) Model 1 Model 2 Model 3 Model 4 Model 5 Constant 0.41*** (0.059) 0.42*** (0.051) (0.045) 0.49*** (0.086) -0.24** (0.12) Info 0.28*** (0.13) *** (0.074) Goal setting ** (0.15) (0.098) Feedback *** (0.095) *** (0.010) Rewards *** (0.21) 0.43* (0.21) Adj R AIC Page 4

5 Conclusions A number of utilities have undertaken pilot programs aimed at understanding which interventions are most effective in reducing residential energy consumption through behavioural change This study provides a meta-regression analysis of residential energy behavioural savings, using an extensive review of the literature which found twenty-eight treatments from ten experiments for which an effect size could be calculated Experimental treatments were classified according to whether the interventions were information, goal setting, feedback, rewards or combinations of these interventions White s robust regression was then used to model the impact of these alternative interventions on the effect size Page 5

6 Conclusions We compared five regression models on the basis of the Akaike's information criterion, and we found that Model 5, which uses all of the regressors, is the preferred model We can compare the two theories of behaviour by comparing the sum of the relevant coefficients in Model 5 Sum of the coefficients for the rational choice model (impact of information and rewards) is 0.64 Sum of the coefficients for the theory of planned behaviour model (impact of goal setting and feedback) is 0.76 This suggests that the preliminary conclusion that the theory of planned behaviour may be more appropriate in the context of analysis of behavioural change and energy use Page 6

7 References [1] Martiskainen, M., 2007, Affecting Consumer Behaviour on Energy Demand, Final Report to EDF Energy, Sussex Energy Group, March [2] Geller, E. S., 1981, Evaluating Energy Conservation Programs: Is Verbal Report Enough?, Journal of Consumer Research 8. [3] Abrahamse, W., L. Steg, C. Vlek and T. Rothengatter, 2005, A Review of Intervention Studies Aimed at Household Energy Conservation, Journal of Environmental Psychology, 25. [4] Herring, H. and R. Royal, 2007, Technological Innovation, Energy Efficient Design and the Rebound Effect, Technovation 27(4). [5] Lutzenhiser, L., 1993, Social and Behavioral Aspects of Energy Use, Annual Review of Energy and the Environment 18. [6] Jackson, T., Motivating Sustainable Consumption, Report to the Sustainable Development Research Network, Centre for Environmental Strategy, Sussex University. [7] Becker, G., 1976, The Economic Approach to Human Behavior, University of Chicago Press. [8] Ajzen, I. and M. Fishbein, 1989, Understanding Attitudes and Predicting Social Behavior, Englewood Cliffs, NJ: Prentice-Hall. Page 7