A Sound Decision? The Impact of Audio Presentations on Economic Rationality

Last registered on May 30, 2025
View Trial History

Pre-Trial

Trial Information

General Information

Title
A Sound Decision? The Impact of Audio Presentations on Economic Rationality
RCT ID
AEARCTR-0016066
Initial registration date
May 27, 2025

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
May 30, 2025, 9:44 AM EDT

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

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Rui Guan
Affiliation
University of Kent
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Fadong Chen
PI Affiliation
Zhejiang University
Contact Investigator

Additional Trial Information

Status
In development
Start date
2025-05-28
End date
2026-05-28
Keywords
Behavior, Lab, Welfare
Additional Keywords
audio presentations, decision-making, economic rationality, perception, sequential information delivery
JEL code(s)
C99, D11, D81, D91
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This experiment extends our earlier work (AEARCTR-0007920 and AEARCTR-0012809) by examining how the speed of auditory presentation affects economic rationality. In laboratory-controlled settings, subjects are randomly assigned to one of three treatments, where decision problems are presented auditorily with options read at three speeds—"slow," "moderate," and "fast"—corresponding approximately to 90, 120, and 150 words per minute, respectively. We hypothesize that increasing presentation speed impairs decision-making, leading to lower levels of economic rationality. Specifically, we expect choice consistency with preference maximization to be highest in the slow condition, intermediate in the moderate, and lowest in the fast condition, consistent with a decreasing trend in rationality as presentation speed increases. Examining rationality measures across these conditions, we aim to isolate the impact of presentation rate on decision quality when information is delivered sequentially via audio. Our findings would shed light on the systematic role of presentation speed in understanding and modeling decision-making with auditory information.
External Link(s)

Registration Citation

Citation
Chen, Fadong and Rui Guan. 2025. "A Sound Decision? The Impact of Audio Presentations on Economic Rationality." AEA RCT Registry. May 30. https://doi.org/10.1257/rct.16066-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Participants are randomly assigned to one of three treatment conditions, which differ in the speed at which auditory presentations of decision problems are delivered: slow, moderate, or fast.
Intervention Start Date
2025-05-28
Intervention End Date
2026-05-28

Primary Outcomes

Primary Outcomes (end points)
Choice consistency
Primary Outcomes (explanation)
Choice consistency is a binary variable equal to 1 if a participant’s choices satisfy the Generalized Axiom of Revealed Preference (GARP). This indicates consistency with preference maximization as provided by revealed preference theory (Afriat, 1967; Varian, 1982). We hypothesize that faster presentation impairs decision-making, leading to lower choice consistency. Specifically:

H1: Choice consistency is higher in the slow-speed condition than in the moderate-speed condition.

H2: Choice consistency is higher in the slow-speed condition than in the fast-speed condition.

H3: Choice consistency is higher in the moderate-speed condition than in the fast-speed condition.

References:
Afriat, Sidney N. 1967. “The Construction of Utility Functions from Expenditure Data.” International Economic Review 8 (1): 67–77.
Varian, Hal R. 1982. “The Nonparametric Approach to Demand Analysis.” Econometrica 50 (4): 945–973.

Secondary Outcomes

Secondary Outcomes (end points)
The Houtman–Maks Index (HMI; Houtman and Maks, 1985); the number of GARP violations; more stringent variants of the above measures that additionally satisfy first-order stochastic dominance (FOSD); participants’ response times; and search behavior patterns, including the number of options considered.

References:
Houtman, Martijn, and Julian Maks. 1985. “Determining All Maximal Data Subsets Consistent with Revealed Preference.” Kwantitatieve Methoden 19 (1): 89–104.
Secondary Outcomes (explanation)
We include several robustness metrics. The HMI is the minimum number of choices that must be removed from a dataset to render the remaining set GARP-consistent; these removed observations are typically interpreted as choice mistakes. The number of GARP violations similarly quantifies deviations from economic rationality. Higher HMI scores or more GARP violations indicate lower levels of rationality. As further robustness checks, we consider FOSD-compliant variants, which impose a stricter normative benchmark for evaluating decision-making under risk. For exploratory analysis, we also examine response times and search patterns (e.g., the number of options clicked) as proxies for decision effort.

Experimental Design

Experimental Design
The experiment comprises three parts. In the first, participants make economic decisions based on their assigned treatment. In the second, they complete a series of cognitive tasks. In the third, they complete a set of questionnaires assessing attitudes toward inconsistency and demographic characteristics.
Experimental Design Details
Not available
Randomization Method
Randomization will be implemented via Qualtrics.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
360 participants
Sample size: planned number of observations
360 participants
Sample size (or number of clusters) by treatment arms
120 individuals in each treatment condition
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power is assessed via simulation using data from previous trials. We apply logistic regression to 10,000 simulated samples across a range of effect sizes for the primary outcome, choice consistency. Assuming 120 participants per treatment condition, 80% power, and a 5% significance level, each hypothesis's minimum detectable effect size is 0.83 log-odds, corresponding to an odds ratio of 2.3, or a 130% increase in the odds of choice consistency.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Academic Ethics Committee at Zhejiang University
IRB Approval Date
2025-05-23
IRB Approval Number
N/A
Analysis Plan