Frameworks and strategic decision-making

Last registered on April 29, 2026
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Pre-Trial

Trial Information

General Information

Title
Frameworks and strategic decision-making
RCT ID
AEARCTR-0014471
Initial registration date
April 26, 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, 3:48 PM EDT

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

Locations

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Primary Investigator

Name
Hyunjin Kim
Affiliation
INSEAD
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Other Primary Investigator(s)

PI Name
Nety Wu
PI Affiliation
INSEAD
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Additional Trial Information

Status
In development
Start date
2026-04-23
End date
2026-06-30
Keywords
Behavior, Firms & Productivity
Additional Keywords
Strategic decision-making
JEL code(s)
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
This project aims to understand how using frameworks affects the crafting of strategic options.
External Link(s)

Registration Citation

Citation
Kim, Hyunjin and Nety Wu. 2026. "Frameworks and strategic decision-making." AEA RCT Registry. April 29. https://doi.org/10.1257/rct.14471-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-04-23
Intervention End Date
2026-06-30

Primary Outcomes

Primary Outcomes (end points)
We will observe the following outcomes:
(1) the number of total options that the student brainstormed
(2) the number/share of strategic (rather than operational) options that the student brainstormed
(3) a binary measure of whether the options were mutually exclusive
(4) the number/share of options that suggest that the company continue its current strategy (vs. exit or expand)
(5) binary measures of whether the best-chosen option is to "continue", "exit", or "strategic"
Primary Outcomes (explanation)
Some of the measures will be coded by two independent coders (or a fine-tuned LLM) using a rubric who are blind to the random assignment, e.g.:
(1) whether the options are strategic or operational
(2) whether the options are mutually exclusive
(3) whether the options suggest that the company continue its current strategy vs. exit or expand

Secondary Outcomes

Secondary Outcomes (end points)
All participants will be asked to articulate a problem statement and their thought process in developing the problem statement.
Survey questions to all participants: (1) Describe how you developed your options; (2) How confident are you in the options you have developed? (3) How would you describe the difficulty of the task? (4) Which specific data from the case did you rely on the most to complete this exercise? (5) Beyond the data provided in the case, what additional data would be helpful for you to complete this exercise?
Additional survey questions to non-control arms: (1) Did you find the framework provided in the instructions helpful in developing your options? (2) Please elaborate on why it was helpful or not helpful.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This project aims to understand how using a framework affects the crafting of strategic options. This project is an extension of prior works (Kim, Hyunjin and Nety Wu. 2022. "Frameworks and strategic decision-making." AEA RCT Registry. October 03. https://doi.org/10.1257/rct.10146-1.0. Kim, Hyunjin and Nety Wu. 2023. "Frameworks and strategic decision-making." AEA RCT Registry. February 21. https://doi.org/10.1257/rct.10961-1.0. Kim, Hyunjin and Nety Wu. 2023. "Frameworks and strategic decision-making." AEA RCT Registry. September 20. https://doi.org/10.1257/rct.12114-1.0. Kim, Hyunjin and Nety Wu. 2024. "Frameworks and strategic decision-making." AEA RCT Registry. February 14. https://doi.org/10.1257/rct.12963-1.0. Kim, Hyunjin and Nety Wu. 2024. "Frameworks and strategic decision-making." AEA RCT Registry. April 02. https://doi.org/10.1257/rct.13245-1.0).
Experimental Design Details
Not available
Randomization Method
Individuals are randomized by Qualtrics randomizer.
Randomization Unit
Simple randomization at the individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
1000 participants
Sample size (or number of clusters) by treatment arms
250 participants control, 250 participants with integrated framework, 250 participants with words-only, 250 participants with Ansoff framework
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
With 250 participants per arm, simple randomization, no clustering, the minimum detectable effect sizes at 80% power are: - Continuous DV (number of strategic options): Cohen's d = 0.31 - Binary DV (mutual exclusivity): a difference of 11.36 percentage points Calculation is based on parameters from previously run experiments. The confirmatory family comprises 5 pre-registered pairwise contrasts: integrated vs. control, integrated vs. words-only, integrated vs. single-framework (Ansoff), control vs. words-only, and control vs. single-framework. The remaining pairwise contrast (words-only vs. single-framework) is exploratory.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
INSEAD Institutional Review Board
IRB Approval Date
2025-12-03
IRB Approval Number
2022-67mbaE
Analysis Plan