Are Ride-Sharing Platforms Tempting Riders with Optimistic Time Estimates? An Experimental Approach

Last registered on September 19, 2025
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Pre-Trial

Trial Information

General Information

Title
Are Ride-Sharing Platforms Tempting Riders with Optimistic Time Estimates? An Experimental Approach
RCT ID
AEARCTR-0016789
Initial registration date
September 15, 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
September 19, 2025, 10:00 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

Name
Jing Zhao
Affiliation
Hong Kong Polytechnic University
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Other Primary Investigator(s)

PI Name
Zhen Xi
PI Affiliation
Hong Kong Polytechnic University
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PI Name
Sean Cao
PI Affiliation
University of Maryland
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Additional Trial Information

Status
In development
Start date
2025-09-22
End date
2026-12-31
Keywords
Behavior, Firms & Productivity, Governance
Additional Keywords
Ride-Sharing Platforms
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Understanding how ride-sharing platforms estimate and communicate pick-up times is crucial for detecting platform behavior and prompting rider awareness of potential underestimation in Ride-Sharing Platforms (RSP). This study investigates whether the RSP systematically underestimate estimated pick-up durations (EPD). Using a randomized controlled trial (RCT) design on the ride sharing service of RSP in Hong Kong, we compare estimated and actual pick-up durations across varying conditions.
External Link(s)

Registration Citation

Citation
Cao, Sean, Zhen Xi and Jing Zhao. 2025. "Are Ride-Sharing Platforms Tempting Riders with Optimistic Time Estimates? An Experimental Approach." AEA RCT Registry. September 19. https://doi.org/10.1257/rct.16789-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2025-09-22
Intervention End Date
2026-12-31

Primary Outcomes

Primary Outcomes (end points)
Estimated travel duration of public transportation (BTE); Estimated pick-up durations (EPD); Actual pick-up durations (APD); Estimated Travel durations (ETD); Actual Travel durations (ATD).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Using a repeated ride-task design, participants were grouped by fixed origin–destination (OD) pairs to ensure comparable conditions and randomly assigned to treatment conditions (muted scripts with guided behaviors, public transportation exposure, and time windows). Spatial variation was introduced by assigning treatment groups to areas with limited transit options and control groups to areas with seamless transit accessibility. Participants were randomly assigned and trained to act as patient or impatient. Temporal variation was examined by comparing rush hour and non-rush hour routes. This framework systematically evaluates the interplay of spatial, temporal, and user-specific factors in shaping platform operations and user behavior.
Experimental Design Details
Not available
Randomization Method
Randomization will be done in office by coin flipping
Randomization Unit
Randomization were conducted at the participant level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Four participants will be divided into two groups.
Sample size: planned number of observations
We plan to use all ride-task requests generated by four trained participants following the standardized protocol. Therefore, the final sample size depends on actual field execution (e.g., successful matches, scripted cancellations, and any rescheduled rounds). At this stage, the estimated number of observations is ranges from 900-1,200 single-ride requests over the sample period.
Sample size (or number of clusters) by treatment arms
Two of the four participants will act as the treated impatient user and conduct around half of the rides.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Hong Kong Polytechnic University Institutional Review Board
IRB Approval Date
2025-09-15
IRB Approval Number
HSEARS20250913004
Analysis Plan