Solar Referrals with Reciprocity

Last registered on April 17, 2019

Pre-Trial

Trial Information

General Information

Title
Solar Referrals with Reciprocity
RCT ID
AEARCTR-0004114
Initial registration date
April 16, 2019

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
April 17, 2019, 8:25 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Primary Investigator

Affiliation
Lawrence Berkeley Nat'l Lab

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2018-08-01
End date
2019-09-30
Secondary IDs
Abstract
Advancing the deployment of solar technologies can yield economic benefits to individuals and benefits to wider segments of society. Although U.S. deployment of rooftop-solar technologies has soared in recent years, most installations have been concentrated among high-income households. Increasing solar deployment among LMI households represents a major opportunity to expand solar’s broader benefits while increasing equitable access to a valuable economic resource. In addition, the existing literature provides very limited information about the specific solar-related motivations and barriers of different socioeconomic groups. Research on energy efficiency and weatherization programs, however, suggests that LMI households may face a range of institutional, political, and social barriers—beyond the financial impediments faced by traditional solar customers—such as lack of information, poor roof suitability, and distrust of the organizations offering such programs. This research also indicates that leveraging social networks can increase program participation. For these reasons, our study focuses on behavioral-based strategies for increasing solar referrals and subsequent solar adoption among LMI households.

Based on the experience of the solar-installation organization that we are partnering with for our study, referrals from existing customers are the most effective pathway to new solar installations. Theories from behavioral economics and psychology may provide insights into ways to motivate these existing customers to expend the minor amount of effort needed to provide referrals, potentially leading to an increase in solar installations.

In brief, we are performing a randomized controlled trial of whether two behavioral interventions—reciprocity and streamlining—cause (1) an increase in referrals provided by existing customers, and (2) an increase in quality referrals, i.e., referrals that translate to leads and successful solar installations. A reciprocity group (n = 2,250) receives a non-contingent reward ($1 in cash) delivered via a referral-solicitation letter. A reciprocity + streamlining group (n = 2,250) also receives a referral form and pre-stamped envelope with the solicitation letter as well as an email with a direct link to a referral website. A control group (n = 2,250) receives referral solicitations without these strategies, in the form of postcards with basic information on how to provide referrals (via a phone number or website) and why it is important (this control group strategy is the current method used by our partner).

Other important methodological details are as follows. The power is sufficient to test our hypotheses in a way that is meaningful for U.S. solar energy. The method for randomizing is similar to stratifying and ensures a balanced panel for all groups. We have IRB approval. Our partner has already implemented the randomization and experiment, but no data have been transferred to the researchers. In fact, to our knowledge, our partner has not examined the data from the experiment.

If our results show an improvement in effort due to reciprocity and/or streamlining, they will have an immediate impact in that our partner may change their referral-request processes in all of the nine states in which it operates, and dissemination of the results through industry conferences likely will affect the methods of similar solar companies in the near term. If our results are roughly consistent with studies testing different versions and applications of reciprocity, they will provide an important link in understanding the underlying mechanism and theory of reciprocity. If our results are not consistent with existing literature, they will lead to research that can define the exact conditions and solicitation approaches that make reciprocity motivating.
External Link(s)

Registration Citation

Citation
Todd, Annika. 2019. "Solar Referrals with Reciprocity." AEA RCT Registry. April 17. https://doi.org/10.1257/rct.4114-1.0
Former Citation
Todd, Annika. 2019. "Solar Referrals with Reciprocity." AEA RCT Registry. April 17. https://www.socialscienceregistry.org/trials/4114/history/45134
Experimental Details

Interventions

Intervention(s)
Based on the experience of the solar-installation organization that we are partnering with for our study, referrals from existing customers are the most effective pathway to new solar installations. Theories from behavioral economics and psychology may provide insights into ways to motivate these existing customers to expend the minor amount of effort needed to provide referrals, potentially leading to an increase in solar installations.


In brief, we are performing a randomized controlled trial of whether two behavioral interventions—reciprocity and streamlining—cause (1) an increase in referrals provided by existing customers, and (2) an increase in quality referrals, i.e., referrals that translate to leads and successful solar installations. A reciprocity group (n = 2,250) receives a non-contingent reward ($1 in cash) delivered via a referral-solicitation letter. A reciprocity + streamlining group (n = 2,250) also receives a referral form and pre-stamped envelope with the solicitation letter as well as an email with a direct link to a referral website. A control group (n = 2,250) receives referral solicitations without these strategies, in the form of postcards with basic information on how to provide referrals (via a phone number or website) and why it is important (this control group strategy is the current method used by our partner).
Intervention Start Date
2018-09-19
Intervention End Date
2018-12-31

Primary Outcomes

Primary Outcomes (end points)
We will use OLS and logit specifications to test for differences between (1) the reciprocity group and the control group, (2) the reciprocity group and the reciprocity + streamlining group, and (3) the control group and the combined reciprocity and reciprocity + streamlining group, with respect to the following metrics:
• Number of households that provide at least one referral
• Total number of referrals
• Conditional on providing at least one referral, the average number of referrals
• Number of referrals that translate into solar installation leads (i.e., that lead to any contact between the installation organization and the household that was referred)
• Number of referrals that translate into prequalified solar installation leads (i.e., leads that meet requirements for roof angle, income level, etc.)
• Number of referrals that translate into contracted solar installations
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Based on the experience of the solar-installation organization that we are partnering with for our study, referrals from existing customers are the most effective pathway to new solar installations. Theories from behavioral economics and psychology may provide insights into ways to motivate these existing customers to expend the minor amount of effort needed to provide referrals, potentially leading to an increase in solar installations.


In brief, we are performing a randomized controlled trial of whether two behavioral interventions—reciprocity and streamlining—cause (1) an increase in referrals provided by existing customers, and (2) an increase in quality referrals, i.e., referrals that translate to leads and successful solar installations. A reciprocity group (n = 2,250) receives a non-contingent reward ($1 in cash) delivered via a referral-solicitation letter. A reciprocity + streamlining group (n = 2,250) also receives a referral form and pre-stamped envelope with the solicitation letter as well as an email with a direct link to a referral website. A control group (n = 2,250) receives referral solicitations without these strategies, in the form of postcards with basic information on how to provide referrals (via a phone number or website) and why it is important (this control group strategy is the current method used by our partner).
Experimental Design Details
Randomization Method
Done in office by a computer; method based on optimizing balance of treatment groups using a method commonly used in developmental economics.
Randomization Unit
household
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
7000 households
Sample size: planned number of observations
7000 households
Sample size (or number of clusters) by treatment arms
. A reciprocity group (n = 2,250) receives a non-contingent reward ($1 in cash) delivered via a referral-solicitation letter. A reciprocity + streamlining group (n = 2,250) also receives a referral form and pre-stamped envelope with the solicitation letter as well as an email with a direct link to a referral website. A control group (n = 2,250) receives referral solicitations without these strategies, in the form of postcards with basic information on how to provide referrals (via a phone number or website) and why it is important (this control group strategy is the current method used by our partner).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
From past campaigns, GRID has found that their response rate to both emails and postcards is about 1%. Based on power calculations with this percentage, this number of customers in each group is appropriate to be able to see an effect size of doubling this response, from 1% to 2%, at the 10% significance level.
IRB

Institutional Review Boards (IRBs)

IRB Name
Lawrence Berkeley National Lab
IRB Approval Date
Details not available
IRB Approval Number
APPROVAL NUMBER: 381H25JE23

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials