A survey experimental study for increasing public support for various electricity pricing schemes via public trust in electric utility

Last registered on October 18, 2021

Pre-Trial

General Information

Title

RCT ID

AEARCTR-0008367

Initial registration date

October 15, 2021

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

October 18, 2021, 9:36 AM EDT

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

Locations

Country

Korea (Republic of)

Region

Primary Investigator

Name

Jinwook Shin

Affiliation

Seoul National University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Syngjoo Choi

PI Affiliation

Seoul National University

Contact Investigator

PI Name

Booyuel Kim

PI Affiliation

Seoul National University

Contact Investigator

PI Name

Sungmin Lim

PI Affiliation

Seoul National University

Contact Investigator

PI Name

Heerae Lee

PI Affiliation

Seoul National University

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Additional Trial Information

Status

On going

Start date

2021-10-12

End date

2021-10-22

Keywords

Behavior, Environment & Energy

Additional Keywords

Electricity Tariffs

JEL code(s)

Q41, Q42, Q48, Q54, D91

Secondary IDs

Prior work

This trial is based on or builds upon one or more prior RCTs.

Abstract

We design the experiment to test whether and to what extent information about the electric utilities can change public support for various electricity pricing schemes that are designed and implemented by the organization via public trust in the organization. We use a 2 (competence-based information vs. no information) by 2 (integrity-based information vs. no information) between-subjects factorial design. Participants are randomly allocated to one of the four experimental conditions, each having a sample size of 1,125. Competence-based information is a statement about organizational experience and expertise in electric utility business, while integrity-based information is a statement about organizational honesty, openness, and concern for public interest. After receiving information, respondents read a brief description about four different types of electricity pricing schemes. Then, respondents are given a 5-point Likert-scale to gauge their support for each scheme, from strongly support to strongly oppose.

External Link(s)

Registration Citation

Citation

Choi, Syngjoo et al. 2021. "A survey experimental study for increasing public support for various electricity pricing schemes via public trust in electric utility." AEA RCT Registry. October 18. https://doi.org/10.1257/rct.8367-1.0

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Experimental Details

Interventions

Intervention(s)

There will be an information provision treatment that influences factors that may affect acceptance of the alternative electricity pricing schemes. The factors considered are (1) competence-based trust and (2) integrity-based trust for electric utilities. Competence-based information is a statement about organizational experience and expertise in electric utility business, while integrity-based information is a statement about organizational honesty, openness, and concern for public interest.

Intervention Start Date

2021-10-12

Intervention End Date

2021-10-22

Primary Outcomes

Primary Outcomes (end points)

After receiving information, respondents read a brief description about four different types of electricity pricing schemes: a fuel cost pass-through adjustment rate, a regional differential pricing, a time-of-use tariff, and net metering. Then, respondents are given a 5-point Likert-scale to gauge their support for each scheme, from strongly support to strongly oppose.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Perceived cost and benefit of the four different types of electricity pricing schemes (5-point Likert-scale)
Public trust in electric utilities (5-point Likert-scale)

Secondary Outcomes (explanation)

Experimental Design

The treatment is conducted with a 2 x 2 factorial design. Participants are randomly assigned to one of the four groups: 1) control group, 2) competence-based trust group, 3) integrity-based trust group, and 4) both competence-based and integrity-based group, each having a sample size of 1,125.

Experimental Design Details

Randomization Method

Randomization will be done in an office by a computer.

Randomization Unit

The randomization unit is individual.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

4,500 people

Sample size: planned number of observations

4,500 people

Sample size (or number of clusters) by treatment arms

The participants will be randomly assigned to either the control group (no information provision) or one of the three treatment groups. We plan to recruit 1,125 people per group.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

We select a nationally representative sample of 4,500 electricity consumers aged 19 and above in South Korea. The number of samples was calculated based on a power level of 0.8 and a Cohen's d level of 0.2 under a significance level of 0.05. The minimum number of people per group to satisfy the criteria was estimated to be 400.

Supporting Documents and Materials

IRB