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Empowering Workers: Evidence from Auto Manufacturing in China

Last registered on June 23, 2017

Pre-Trial

Trial Information

General Information

Title
Empowering Workers: Evidence from Auto Manufacturing in China
RCT ID
AEARCTR-0002286
Initial registration date
June 23, 2017

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
June 23, 2017, 4:38 PM EDT

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

Last updated
June 23, 2017, 6:55 PM EDT

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

Locations

Region

Primary Investigator

Affiliation

Other Primary Investigator(s)

PI Affiliation

Additional Trial Information

Status
On going
Start date
2016-05-01
End date
2018-06-01
Secondary IDs
Abstract
Our research seeks to understand the impact of increasing workers’ input and participation in decision-making within a firm on outcomes, including productivity, retention and well-being. We are working with an automobile manufacturing firm in China on a set of randomized field experiments with production line workers and their managers. We propose two experimental designs. The first looks at the effects of empowering workers by giving them more choice in determining their own compensation scheme. The second experiment looks at managerial compensation and its intersection with giving workers more voice in that process.


External Link(s)

Registration Citation

Citation
Cai, Jing and Shing-Yi Wang. 2017. "Empowering Workers: Evidence from Auto Manufacturing in China." AEA RCT Registry. June 23. https://doi.org/10.1257/rct.2286-2.1
Former Citation
Cai, Jing and Shing-Yi Wang. 2017. "Empowering Workers: Evidence from Auto Manufacturing in China." AEA RCT Registry. June 23. https://www.socialscienceregistry.org/trials/2286/history/206396
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2016-08-01
Intervention End Date
2017-06-01

Primary Outcomes

Primary Outcomes (end points)
productivity metrics, job retention, well being measures, earnings, promotion, empowerment, soft skills, social relationships and team work
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Production line workers at the firm are organized into teams that are headed by a manager. Our randomization will occur at the team level with approximately an equal number of teams in treatment and control.
Experimental Design Details
Production line workers at the firm are organized into teams that are headed by a manager. Our randomization will occur at the team level with approximately an equal number of teams in treatment and control. The randomization will be stratified by plant, whether they are above or below median team size and whether they are above or below median in productivity in the prior year.
Randomization Method
randomization done in office by a computer
Randomization Unit
team level
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
100
Sample size: planned number of observations
2000
Sample size (or number of clusters) by treatment arms
50 treatment teams and 50 control teams
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Pennsylvania, office of regulation
IRB Approval Date
2016-01-28
IRB Approval Number
824013

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
April 28, 2017, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
August 31, 2017, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
1251 workers in 76 teams (where teams are the unit of randomization)
Was attrition correlated with treatment status?
Yes
Final Sample Size: Total Number of Observations
1251 workers in 76 teams (where teams are the unit of randomization)
Final Sample Size (or Number of Clusters) by Treatment Arms
50% of teams
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials

Description
Journal Article
Citation
Jing Cai, Shing-Yi Wang, Improving Management Through Worker Evaluations: Evidence from Auto Manufacturing, The Quarterly Journal of Economics, Volume 137, Issue 4, November 2022, Pages 2459–2497.