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The Performance Effects of Relative Performance Information and Feedback Detail: Evidence from a Field Experiment in Austria
Last registered on July 01, 2019

Pre-Trial

Trial Information
General Information
Title
The Performance Effects of Relative Performance Information and Feedback Detail: Evidence from a Field Experiment in Austria
RCT ID
AEARCTR-0004141
Initial registration date
May 02, 2019
Last updated
July 01, 2019 4:23 AM EDT
Location(s)

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Primary Investigator
Affiliation
WHU – Otto Beisheim School of Management
Other Primary Investigator(s)
Additional Trial Information
Status
On going
Start date
2018-10-09
End date
2019-12-01
Secondary IDs
Abstract
We seek to establish how feedback can be customized to optimize performance. We will extend knowledge on this topic by using a field experiment in a competitive sport setting (a commercial training simulator used by elite football clubs) to scientifically establish the types of feedback that work best on average and for players of different profiles. Specifically, we will test the performance effects of relative performance feedback (absolute vs relative vs absolute and relative) and feedback detail (high-level vs detailed). We will do so by randomly assigning different types of feedback to the players (high-level and absolute, high-level and relative, high-level and both absolute and relative, detailed and absolute, detailed and relative, detailed and both absolute and relative).
External Link(s)
Registration Citation
Citation
Koppers, Sebastian. 2019. "The Performance Effects of Relative Performance Information and Feedback Detail: Evidence from a Field Experiment in Austria." AEA RCT Registry. July 01. https://doi.org/10.1257/rct.4141-3.0.
Former Citation
Koppers, Sebastian. 2019. "The Performance Effects of Relative Performance Information and Feedback Detail: Evidence from a Field Experiment in Austria." AEA RCT Registry. July 01. https://www.socialscienceregistry.org/trials/4141/history/49029.
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Experimental Details
Interventions
Intervention(s)
Subjects perform a football (soccer) drill in a training simulator at a field site (professional football training facility). Between each round of the drill, the subjects receive feedback on their performance on that round of the drill.
Intervention Start Date
2018-10-09
Intervention End Date
2019-12-01
Primary Outcomes
Primary Outcomes (end points)
We employ two measures of player performance on the drill: accuracy of passes (as measured by meters from target), and reaction time of player (as measured by duration in time in seconds from release of ball until pass hits target area). These measures are captured by the football training simulating. We also measure the subjects' heart rates whilst they perform the drill. This serve to proxy for effort (level of heart rate) and stress (variability of heart rate).
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
We conduct a post-experiment survey to measure the following constructs: perceived value of feedback about performance, social comparison involvement, information quantity, focus, shift of focus, focus on best or worst, influence of feedback on focus, motivation, trust, and perceived threat of feedback.
Secondary Outcomes (explanation)
Perceived value of feedback is based on items from Zingoni & Byron (2017). Social comparison involvement is based on Tafkov (2013). Focus, shift of focus, focus on best or worst, influence of feedback on focus, information quantity and motivation are measured using items specifically developed for this study. The measure of trust is based on Kizilcec (2016). Perceived threat of feedback uses the instrument developed in Zingoni & Byron (2017).
Experimental Design
Experimental Design
We employ a fully-interacted 3x2 design to evaluate the performance effects of relative performance feedback and feedback detail.
Experimental Design Details
Not available
Randomization Method
Subjects are randomly assigned to one of six treatment groups. To do this, we employ a quasi-blocked randomization design, whereby we generate a random sequence of numbers to assign male subjects to treatment and a random sequence of numbers to assign female participants to treatment. We do this to make sure that fewer female participants do not cluster in one treatment group and bias experimental results (true blocked randomization not possible due to no-shows of registered participants).
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
180 individuals
Sample size: planned number of observations
180 individuals
Sample size (or number of clusters) by treatment arms
We assigned our total sample evenly across each of the treatment cells: Absolute & High- level (30 subjects), Absolute & Detailed (30 subjects), Relative & High-level (30 subjects), Relative & Detailed (30 subjects), Absolute & Relative & High-level (30 subjects), Absolute & Relative & Detailed (30 subjects)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Performance as measured by handling time. Given a sample size of 90 subjects per treatment arm, the minimum detectable effect size is .08 seconds, which is equivalent to change in performance by 0.4 standard deviations (or 3% of the mean level of performance).
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number