Digital Nudging for Sustainable Options in Two-Stage Decision-Making

Last registered on April 16, 2024
View Trial History

Pre-Trial

Trial Information

General Information

Title
Digital Nudging for Sustainable Options in Two-Stage Decision-Making
RCT ID
AEARCTR-0013237
Initial registration date
April 05, 2024

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 16, 2024, 1:02 PM EDT

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

Locations

Country
Germany
Region

Primary Investigator

Name
Maximilian Habla
Affiliation
Ulm University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Natalie Rupp
PI Affiliation
Ulm University
Contact Investigator
PI Name
Andrea Wrabel
PI Affiliation
Ulm University
Contact Investigator
PI Name
Mischa Seiter
PI Affiliation
Ulm University
Contact Investigator
PI Name
Steffen Zimmermann
PI Affiliation
Ulm University
Contact Investigator

Additional Trial Information

Status
In development
Start date
2024-04-06
End date
2024-04-19
Keywords
Behavior, Environment & Energy, Firms & Productivity
Additional Keywords
Digital Nudging, Sustainability, Two-Stage Decision-Making, Employee Behaviour
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
As company emissions significantly contribute to climate change, government organizations are implementing policies to encourage companies to reduce their carbon footprint, such as the European Union's Sustainability Act. To comply with these policies, one proposed method is to direct employees’ attention to sustainable options using digital nudging. However, the literature on the effectiveness of digital nudging in promoting sustainable decision-making remains inconclusive. In addition, there is a lack of knowledge about the potential spillover effects of digital nudging on subsequent sustainable behavioral intentions.
Our research aims to fill this gap by investigating the effects of digital nudging to guide employees to more sustainable decisions within a two-stage decision-making process. Therefore, we employ an online experiment, in a controlled environment, using crowd workers. Our between-subjects design ensures that participants randomly encounter one of four possible digital nudge scenarios: (i) receiving a digital nudge at both decision stages, (ii) only at the first decision stage, (iii) solely at the second decision stage, or (iv) not receiving a digital nudge at any stage.
External Link(s)

Registration Citation

Citation
Habla, Maximilian et al. 2024. "Digital Nudging for Sustainable Options in Two-Stage Decision-Making." AEA RCT Registry. April 16. https://doi.org/10.1257/rct.13237-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
We will collect data from online crowd workers located in the US and Europe who are at least 18 years old. Each participant will be randomly assigned to one of our four experimental groups.
Intervention Start Date
2024-04-06
Intervention End Date
2024-04-19

Primary Outcomes

Primary Outcomes (end points)
(Sustainable) decisions in the first and second decision stages.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment will follow a full factorial 2 x 2 design. Participants will be confronted with a two-stage decision scenario of booking a business trip. They will be randomly divided into one of four experimental groups, each subject to different conditions formulated by two independent variables:
- Digital Nudge in the first decision stage (Present vs. Absent)
- Digital Nudge in the second decision stage (Present vs. Absent)
Experimental Design Details
On the welcome page of the experiment, we will inform participants about the procedure and potential exclusions through attention checks. Participants will then be presented with a simulated business trip scenario. They are instructed to immerse themselves into the situation of booking a trip from their office location to a client's office using the company's travel booking portal. Since the company will cover the trip expenses, the portal only displays travel options that comply with the company's travel policy and therefore does not include prices.

Booking the business trip using the company’s travel booking portal will consist of the following steps:
1. Participants must choose departure and destination cities according to the scenario description.
2. Participants must choose their mode of transportation, either a train or a plane. Depending on their experimental group assignment, they may receive a digital nudge in the form of a green badge next to the train option, indicating that this option saves 84% CO2 emissions compared to the plane.
3. Participants must choose their fare class, with options of first or second class for trains and business or economy class for planes. Depending on their group assignment, a digital nudge in the form of a green badge is used to indicate that second-class and economy-class travel can save 33% CO2 emissions.

After completing the travel booking process, participants will be asked to answer a questionnaire designed to measure their behaviors and decision-making processes. Additionally, the crowd working platform will directly provide participants' sociodemographic data.
Randomization Method
Participants will be randomly assigned to the experimental groups by a designated function of the software SoSci Survey.
Randomization Unit
Randomization will be done at the participant level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clusters
Sample size: planned number of observations
Our sample size will be calculated based on the results of our experimental pre-test using G-Power Analysis.
Sample size (or number of clusters) by treatment arms
Our sample size will be calculated based on the results of our experimental pre-test using G-Power Analysis.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

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