Influenza vaccine and work productivity:evidence from food delivery driver

Last registered on October 13, 2025

Pre-Trial

Trial Information

General Information

Title
Influenza vaccine and work productivity:evidence from food delivery driver
RCT ID
AEARCTR-0016744
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 15, 2025, 9:54 AM EDT

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

Last updated
October 13, 2025, 9:22 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
University of International Business and Economics

Other Primary Investigator(s)

PI Affiliation
Tianjin University
PI Affiliation
Tianjin University

Additional Trial Information

Status
In development
Start date
2025-07-15
End date
2026-06-15
Secondary IDs
National Natural Science Foundation of China
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study evaluates the impact of financial incentives on influenza vaccination uptake and explores whether vaccination improves health outcomes and, in turn, worker productivity. We conduct a randomized controlled field experiment with approximately 750 food delivery drivers in China. The experiment has two main components. First, we examine the causal impact of financial incentives on vaccine uptake by providing influenza vaccine subsidies covering 50% and 100% of the average vaccine cost, using a control group that receives no subsidy. We then track participants’ vaccination decisions and key productivity outcomes, including order volume, on-time delivery rate, average delivery duration, and the number of positive customer reviews. Second, we study the role of peer influence in vaccination behavior by observing how the vaccination choices of vaccinated food delivery drivers affect the vaccination decisions of other participants. The findings will shed light on how financial incentives and the behavior of peers jointly shape health behavior and productivity in a high-frequency labor market setting.
External Link(s)

Registration Citation

Citation
Wang, Yizhi, Shenshen Yang and Chan Yu. 2025. "Influenza vaccine and work productivity:evidence from food delivery driver ." AEA RCT Registry. October 13. https://doi.org/10.1257/rct.16744-2.0
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Experimental Details

Interventions

Intervention(s)
This research aims at studying the impact of financial incentives on the take-up willingness of influenza vaccine. Moreover, the researchers examine the relationship between influenza vaccine and health outcomes. If health is improved after taking the vaccine, do we observe an increase in the worker productivity as well. Meanwhile, the researchers quantify the peer influence in the willingness to take the vaccination. Our first intervention includes a financial incentive on vaccine uptake by providing influenza vaccine subsidies covering 50% and 100% of the average vaccine cost, using a control group that receives no subsidy. Our second intevention is the information diffusion where we randomize participants into peer-on and peer-off groups where the peer-on group receives information of the vaccination decision of their vaccinated peers every two days (SMS messages).
Intervention Start Date
2025-10-15
Intervention End Date
2026-03-15

Primary Outcomes

Primary Outcomes (end points)
1. take up the influenza vaccination or not 2.The self-reported health (mental, physical health) 3. worker productivity of food delivery drivers (volumes of order, duration, reviews)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conducted a randomized controlled trial to examine the impact of influenza vaccination on vaccine uptake and worker productivity among food delivery drivers in China. In addition, we quantify the peer influence associated with vaccination behavior. Approximately 750 drivers were recruited for the study. After collecting baseline demographic and socioeconomic information—including gender, age, education, marital status, wage, job experience, working hours, health status, medical history, health behavior, and health insurance coverage—participants were randomly assigned to one of three treatment groups or a control group across two rounds of vaccination.

The field experiment consisted of four groups in total: one control group and three treatment groups. Participants in the control group received no financial incentive for vaccination and no information about the vaccination status of their peers. The first treatment group received a low financial incentive, offering participants a 50% discount on the average vaccination cost, without any group information. The second treatment group received a high financial incentive, offering a 100% subsidy of the average vaccine cost. The third treatment group received peer information only—participants were informed of other drivers’ vaccination outcomes but received no financial incentive. Comparing vaccination uptake between the peer-information group and the control group allows us to identify the role of social influence in vaccination decisions. Random assignment ensures that any observed differences in outcomes can be attributed to the vaccination incentives rather than to pre-existing individual characteristics.

Worker productivity was tracked throughout the study period using four key performance indicators: (1) order volume (total number of completed deliveries), (2) on-time delivery rate (percentage of orders delivered as scheduled), (3) average delivery duration, and (4) number of positive customer reviews. By comparing productivity outcomes across the four groups, we evaluate whether vaccination incentives affect not only vaccine uptake but also subsequent work performance.
Experimental Design Details
Not available
Randomization Method
Creating treatment and control groups by computer software STATA for randomization.
Randomization Unit
Individual randomization
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
750 food delivery drivers
Sample size: planned number of observations
4800
Sample size (or number of clusters) by treatment arms
200 in high and low financial incentive treatment, 200 in control groups. The remaining 150 in peer-on group.
Around 750 clusters.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Individual clustering
IRB

Institutional Review Boards (IRBs)

IRB Name
Tianjin University
IRB Approval Date
2025-07-15
IRB Approval Number
TJUE2025-H-S-032