Frameworks and strategic decision-making

Last registered on September 20, 2023

Pre-Trial

Trial Information

General Information

Title
Frameworks and strategic decision-making
RCT ID
AEARCTR-0012114
Initial registration date
September 14, 2023

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
September 20, 2023, 10:27 AM 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

Affiliation
Harvard University

Other Primary Investigator(s)

PI Affiliation
INSEAD

Additional Trial Information

Status
In development
Start date
2023-09-15
End date
2024-09-15
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 a framework affects the crafting of strategic options.
External Link(s)

Registration Citation

Citation
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
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-09-15
Intervention End Date
2023-09-22

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 "expand"
Primary Outcomes (explanation)
Some of the measures will be coded by two independent coders 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)
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?
Additional survey questions to the treatment group only: (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.
Peer evaluations of option quality, binary variable on how detailed the option is, various details about the nature of the option, and group-level outcomes on strategic options. Secondary outcomes will be collected and coded based on feasibility (e.g., if budget allows).
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 and 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). We plan to run the same experiment on a new cohort of students.
Experimental Design Details
Not available
Randomization Method
Individuals are randomized into control and treatment by stratifying on gender and industry (whether they worked in consulting), using a computer.
Randomization Unit
Randomization is conducted at the individual level. Each participant is first randomly assigned to the treatment or the control group, stratified on gender and industry (whether they worked in consulting). Then, within each group, participants are randomly assigned to subgroups for further brainstorming of options.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
131 students
Sample size (or number of clusters) by treatment arms
65 participants control, 66 participants treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
The INSEAD Institutional Review Board
IRB Approval Date
2023-09-06
IRB Approval Number
2022-67mbaA