Base rate / discount rate + household items – behaviourally informed EPFS design incorporating the graphical representation of household items as well as the base annual and discounted annual bill rates to aid respondents in making comparisons 1.3 Research questions Of available options, what is the preferred design and content for a one-page EPFS? Among behaviourally informed EPFS designs, will study participants prefer to examine both base annual bill rate as well as discounted annual bill rate or just base annual bill rate alone? Among behaviourally informed EPFS designs, will study participants prefer the graphical representations of houses, household items, or a bar graph? 1.4 Limitations There are several limitations associated with this mixed methods design. First, interpreting a primary outcome (engagement with and preference for an EPFS design) will be complex and nuanced because there is no single primary outcome measure: ‘engagement’ is difficult to measure in this experimental context. Second, some framed field questions will be purely hypothetical (e.g. “how likely is it you might change energy plans if you observed a fact sheet like this one that indicated you would be better off”). Thus, from the perspective of revealed preferences it will be difficult to tell how much of an effect the treatment fact sheets would have on ‘actual’ energy literacy or energy-related decision-making. Third, a very small subset of framed field questions is differentiated by experimental group. This is because we wanted to ask one bespoke survey question about each EPFS design. 2. Methods 2.1 Framed field experiment Our study is interested in testing EPFS designs across a representative sample of Australia that is 21 years or older. The sample is drawn from the 300,000-person Online Research Unit survey panel. ORU attempts to recruit a nationally representative sample of the Australian population through online and offline (telephone and post) recruitment methods. The survey mandates age, sex, and postcode location quotas to generate a nationally representative sample. Survey respondents receive a financial incentive at a physical Australian post to ensure they are Australian residents. For this survey, respondents receive approximately AUD 1.50. To address the possibility of missing data, respondents are replaced if they do not complete the survey.
Status quo Bar Base rate + houses Base rate + household items Base rate / discount rate + houses Base rate / discount rate + household items F (p-value) E2* (continuous on E4 (ordinal on 0-11) E5* (continuous on *Note that the mean scores for Questions E2 and E5 are pooled across Likert-scales for five and three statements, respectively. Main outcome 2 – comparisons of treatment effect for each experimental group Coefficient (S.E.) 95% Confidence Interval Significance Bar graph Base rate + houses Base rate + household items Base rate / discount rate + houses Base rate / discount rate + household items 5. References Briarbird. 2017. “Enhanced website feasibility report: Energy Made Easy website” on behalf of Australian Energy Regulator. Judkins, D.R. and Porter, K.E. “Robustness of ordinary least squares in randomized clinical trials”. Statistics in Medicine. Wiley. Montgomery, D.C. 2013. Design and Analysis of Experiments: International Student Version. 8th ed. Wiley.