Multi-Unit Search: An Experimental Approach

Last registered on September 17, 2024

Pre-Trial

Trial Information

General Information

Title
Multi-Unit Search: An Experimental Approach
RCT ID
AEARCTR-0014339
Initial registration date
September 10, 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
September 17, 2024, 11:39 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
The University of Queensland

Other Primary Investigator(s)

PI Affiliation
The University of Queensland
PI Affiliation
Universidad Adolfo Ibanez

Additional Trial Information

Status
In development
Start date
2024-09-16
End date
2024-10-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We will explore individuals' selling behavior when they hold multiple indivisible units of a good and encounter buyers stochastically, each offering to purchase a limited number of units at a per-unit price. The experiment thus examines the dynamic selling behavior of sellers when they face uncertainty about future opportunities to sell their items.
External Link(s)

Registration Citation

Citation
Breig, Zachary, Jose Carrasco and Allan Hernandez-Chanto. 2024. "Multi-Unit Search: An Experimental Approach." AEA RCT Registry. September 17. https://doi.org/10.1257/rct.14339-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-09-16
Intervention End Date
2024-10-31

Primary Outcomes

Primary Outcomes (end points)
The primary outcome variable will be the reservation prices chosen by subjects.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We use a within-subject design to study how subjects make search decisions in multi-unit search problems. Subjects see a series of search problems with varying characteristics in a random order.
Experimental Design Details
Not available
Randomization Method
Randomization is done via the experimental software.
Randomization Unit
Subjects see problems in a random order.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
200 subjects
Sample size: planned number of observations
See pre analysis plan for details
Sample size (or number of clusters) by treatment arms
See pre analysis plan for details
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
See pre analysis plan for details
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Queensland BEL LNR
IRB Approval Date
2023-12-18
IRB Approval Number
2023/HE002373
Analysis Plan

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