Off-Peak Charging Subsidies and the Timing of Electric Vehicle Charging in South Korea

Last registered on April 29, 2026

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Pre-Trial

Trial Information

General Information

Title

Off-Peak Charging Subsidies and the Timing of Electric Vehicle Charging in South Korea

RCT ID

AEARCTR-0018457

Initial registration date

April 25, 2026

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 29, 2026, 3:43 PM EDT

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

Locations

Country

Korea (Republic of)

Region

nationwide; charging sessions on a commercial EV platform with country-wide coverage

Primary Investigator

Name

David Sungho Park

Affiliation

KDI School of Public Policy and Management

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Yeong Jae Kim

PI Affiliation

KDI School of Public Policy and Management

Contact Investigator

PI Name

David Woo

PI Affiliation

University of California, Davis

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2025-07-01

End date

2025-12-31

Keywords

Environment & Energy

Additional Keywords

electric vehicles, dynamic pricing, off-peak charging, time-of-use pricing, demand response, field experiment, South Korea, charging behavior

JEL code(s)

Q41; Q42; Q48; R41

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

This study evaluates the effect of short-term off-peak charging discounts on the timing and volume of electric vehicle (EV) charging in South Korea. The experiment recruits approximately 450 EV drivers from a commercial EV charging platform. After a baseline survey, drivers are randomly assigned to one of five conditions — four treatment arms crossing two discount intensities (20% or 40% off the standard charging rate) with two durations (one or two months), or a no-incentive control. Discounts apply only to charging sessions initiated during the off-peak window (22:00–08:00) and are issued as a reward balance (at partner platform) redeemable on later charging sessions within roughly one month. Outcomes are constructed from administrative charger-log data covering pre- and post-treatment periods. We plan to estimate each arm's effect on off-peak and total charging activity, and to examine heterogeneity by access to home and workplace charging and by pre-treatment charging patterns.

External Link(s)

Registration Citation

Citation

Kim, Yeong Jae, David Sungho Park and David Woo. 2026. "Off-Peak Charging Subsidies and the Timing of Electric Vehicle Charging in South Korea." AEA RCT Registry. April 29. https://doi.org/10.1257/rct.18457-1.0

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Experimental Details

Interventions

Intervention(s)

The intervention is a financial incentive, a percentage discount on the standard charging rate, applied to charging sessions initiated during the off-peak window (22:00–08:00) on the partner platform. Operationally, the discount is delivered as a credit to the participant's platform reward balance, equal to the discount rate times the off-peak session cost, and is posted automatically after each eligible session. Accumulated reward balance is redeemable on subsequent charging sessions on the same platform and expires approximately one month after issuance. Participants do not need to enter codes, opt in per session, or take any additional steps beyond plugging in during the eligible window. On-peak sessions and sessions outside a participant's intervention window are charged at the platform's standard rate, and the control group faces standard pricing throughout. Depending on treatment arm, the discount intensity is either 20% or 40% and the eligible window lasts either one or two months; the specific combination is determined by random assignment, and arm definitions are detailed in the Experimental Design section below.

Intervention (Hidden)

Intervention Start Date

2025-08-01

Intervention End Date

2025-09-30

Primary Outcomes

Primary Outcomes (end points)

We plan to capture data on the following user-day off-peak charging outcomes, constructed from administrative charger-log records on the partner platform:

- Any off-peak charging on the day (indicator for at least one charging session initiated between 22:00 and 08:00)
- Total off-peak charging duration (minutes)
- Total off-peak energy delivered (kWh)
- Total off-peak charging expenditure (KRW)

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

- Non-off-peak analogues of each primary outcome (any non-off-peak charging; non-off-peak minutes, kWh, and KRW)
- Total (all-hours) daily charging activity (any charging indicator; total minutes; total kWh; total KRW)
- Charger-type decompositions (fast chargers versus slow chargers) of the four primary off-peak outcomes
- Weekly analogues of the daily outcomes for event-study-style dynamic analysis

Secondary Outcomes (explanation)

Experimental Design

Approximately 500 EV drivers with active accounts on the partner EV charging platform are invited to participate following a baseline survey administered in July 2025. After completing the baseline survey, participants are randomly assigned to one of five conditions in a 2 × 2 factorial structure crossing discount intensity (20% or 40%) with duration (one or two months), plus a no-incentive control. Randomization is performed at the individual level with approximately equal allocation across arms. The five conditions are:

- T1: 20% off-peak discount for one month.
- T2: 40% off-peak discount for one month.
- T3: 20% off-peak discount for two months.
- T4: 40% off-peak discount for two months.
- Control: No incentive; standard platform pricing throughout.

Experimental Design Details

Randomization Method

Computer randomization in Stata, performed after baseline survey completion with a fixed seed.

Randomization Unit

Individual EV driver.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

500 individual drivers

Sample size: planned number of observations

500 individual drivers

Sample size (or number of clusters) by treatment arms

Approximately 100 drivers per arm across four treatment arms (T1–T4) and approximately 100 in the control group.

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

Approximately 0.40 standard deviations for any single treatment-vs-control contrast at the individual cross-section, under 5% significance level and 80% power.

Supporting Documents and Materials

IRB