We have identified several barriers (i.e., lack of information about the label, lack of knowledge about the value and consequences of getting the label, social norm, lack of pro-environmental identity, the design of the label and its understanding and difficulty in the processing steps). We search to identify which barrier(s) can predict the perceived importance of getting the label in Canadian population.

We also want to identify what other factors predicts the perceived importance of getting the home energy label? Other factors include Home characteristics, Home general knowledge, Home energy use, Self-report home energy efficiency of their home.

Finally, we have designed behaviourally-informed digital messages that address each of the mentioned barriers. Each participant will see one message. We are seeking to identify which of these digital communication(s) increase the perceived importance of getting the home energy label.

All participants will answer the barriers questions, they also rate the perceived importance of getting the label. In a multiple regression, the indexed barriers will be tested to identify the main ones.

For the digital communications, each participant is randomly assigned to see one interventional message, there are six messages and a control message. Interventional messages are followed by an Outcome (i.e., perceived importance of getting the label). In a one-way ANCOVA, we will test the effect of these messages.

In the mentioned multiple regression, the dependent variable is the baseline perceived importance of getting a home energy label (i.e., before seeing the interventional messages) . And the independent variables are all barriers (i.e., lack of information, Care, Value and Consequences, Social Norm, Social Consensus, Label design, Understanding Rating, Processing Steps and Pro-environmental ID).

For the one-way ANCOVA, the perceived importance of getting the label is the dependent variable, whereas the digital messages are independent variables, and we control for ownership status (i.e., whether participants are homeowners, home sellers or homebuyers)as the covariate.

Multiple regression: Identifying the barrier(s) that are the main players in willingness to get the label.
Dependent variable: baseline perceived importance of getting a home energy label
Independent variables: all barriers (i.e., lack of information, Care, Value and Consequences, Social Norm, Social Consensus, Label design, Understanding Rating, Processing Steps and Pro-environmental ID)

One-way ANCOVA: Identifying which intervention(s) increase the willingness to get the label (I.e., outcome), while controlling for ownership status as the covariate.
Dependent variable: post-intervention perceived importance of getting a home energy label
Independent variable: Digital interventional messages.

All analysis will be run in SPSS. The data cleaning steps that are taken by Qualtrics Panels include:
• Exclusions of partial responses (i.e., incomplete surveys), potential participants who reported being under 18 years of age or not being a resident of Canada.
• A professional data scrub which will identify and remove poor quality responses, such as “straight-lining” responses, poor open-ended question responses, duplicate participants, speeding responses, etc.
Note: Given the mean time of survey completion in soft launch data (i.e., 600 second), the response rate cut-off is set to 400 seconds, any participant who finished the survey faster than that was excluded from the data set. There are three screening questions, participants under any of these conditions cannot answer to this survey and are excluded:
Age: participants under 18
Location of primary home: Outside of Canada
Home Ownership status: Not a homeowner, nor a perspective homebuyer (defined as the intention to buy a home in the next 2 years.)