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Field
Trial Title
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Before
Why Don’t You Take a Leaf Out of Her Book?
An Experiment on Social Search
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After
The Choices of Others:
An Experiment on Social Search
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Trial End Date
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Before
January 31, 2024
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After
February 28, 2026
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Last Published
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Before
December 21, 2023 08:00 AM
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After
December 20, 2025 11:34 AM
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Intervention End Date
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Before
January 31, 2024
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After
February 28, 2026
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Experimental Design (Public)
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Before
In a between-subjects design, we exogenously vary: i) whether second movers can observe the choices made by one of the first movers who faced the same decision environment, and ii) the presence of reputational mechanisms allowing second movers to identify which reliable first movers to follow.
More precisely, conditional on having access to some social information, we manipulate - in a 2x2 factorial design - whether second movers can choose which first mover to observe from and the availability of reputational information on first movers.
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After
In a between-subjects design, we exogenously vary: i) whether second movers can observe the choices made by one of the first movers who faced the same decision environment, and ii) the presence of reputational mechanisms allowing second movers to identify which reliable first movers to follow.
More precisely, conditional on having access to some social information, we manipulate - in a 2x2 factorial design - whether second movers can choose which first mover to observe from and the availability of reputational information on first movers. Our Benchmark treatment with social information is characterized by exogenous matching and the absence of reputational information on matched first movers.
We include an additional treatment condition: the Benchmark-ROBOT condition. This condition is equivalent to our Benchmark (exogenous matching and no reputational information on first movers), with the only difference that matched first movers are not human peers but computerized agents. Computerized agents are programmed to always behave optimally, given their search cost and the quality of the first action sampled, as defined by our theoretical model.
Overall, the experiment counts 6 treatment conditions:
1) No social information
2)-5) Social information with human first movers
6) Social information with computerized first movers
Participants are evenly allocated across treatment conditions.
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Randomization Method
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Before
Experimental sessions' randomization into treatments is done in office by a computer.
Upon registration, participants are assigned to one of the experimental sessions: subjects enrolled in the first (scheduled) experimental session are assigned to the benchmark treatment, in which participants make choices in isolation, in the absence of social information; subjects enrolled in any of the following experimental sessions are randomly assigned to one of the four social information treatment conditions.
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After
Experimental sessions' randomization into treatments is done in office by a computer.
Upon registration, participants are assigned to one of the experimental sessions: subjects enrolled in the first (scheduled) experimental session are assigned to the treatment in which participants make choices in isolation, in the absence of social information; subjects enrolled in any of the following experimental sessions are randomly assigned to one of the four main social information treatment conditions, or to the additional one with computerized first movers.
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Randomization Unit
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Before
Experimental sessions; within each session, participants are further randomly assigned by the computer software oTree (used to program the experiment) into five groups, numbered I to V, of four participants each: all participants belonging to the same group - irrespective of the treatment condition - are exposed to the same set of alternative options in the same order.
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After
Randomization into treatments happens at the experimental session level.
Within each session (treatment), participants are further randomly assigned to a matching group: all participants belonging to the same matching group, irrespective of the treatment condition, are exposed to the same set of alternative options, in the same order. Each matching group is composed of four participants: for each treatment condition, there are twelve matching groups, numbered I to XII, in total.
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Planned Number of Clusters
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Before
25 Groups
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After
72 Clusters (12 matching-groups of 4 participants each per treatment condition)
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Planned Number of Observations
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Before
100 Participants
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After
288 Participants
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Sample size (or number of clusters) by treatment arms
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Before
20 Participants (5 Groups) per Treatment arm
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After
48 Participants (12 Clusters) per Treatment arm
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Power calculation: Minimum Detectable Effect Size for Main Outcomes
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Before
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After
This sample size (12 clusters of 4 participants each per treatment arm, for a total of n=48 participants per treatment) would allow us to detect a MDE of 0.125 (1/8) standard deviations on second movers' overall propensity to imitate first movers, in a cross-sectional analysis. This corresponds to an economically meaningful variation, equivalent to roughly less than 3 percentage points.
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