Worker Heterogeneity and Firm Productivity

Last registered on June 23, 2020

Pre-Trial

Trial Information

General Information

Title
Worker Heterogeneity and Firm Productivity
RCT ID
AEARCTR-0004270
Initial registration date
June 07, 2019
Last updated
June 23, 2020, 2:36 AM EDT

Locations

Region

Primary Investigator

Affiliation
University of British Columbia

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2019-05-03
End date
2021-07-01
Secondary IDs
Abstract
This project will be a Randomized Controlled Trial (RCT) aimed at studying the impact of worker heterogeneity on team production in a production plant in India. The plant employs over 900 workers. This study will experimentally vary exposure of workers to non-coreligionists, in order to study whether greater contact at the workplace can affect attitudes and in turn impact productivity. We will complement high frequency production data from the firm with a range of baseline and endline survey measures of out-group preferences and perceptions to answer this question.
External Link(s)

Registration Citation

Citation
Ghosh, Arkadev. 2020. "Worker Heterogeneity and Firm Productivity ." AEA RCT Registry. June 23. https://doi.org/10.1257/rct.4270-3.1
Former Citation
Ghosh, Arkadev and Arkadev Ghosh. 2020. "Worker Heterogeneity and Firm Productivity ." AEA RCT Registry. June 23. https://www.socialscienceregistry.org/trials/4270/history/71035
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2019-11-25
Intervention End Date
2020-03-25

Primary Outcomes

Primary Outcomes (end points)
- High frequency daily team level output data obtained from the firm.


- Different measures of implicit and explicit out-group perceptions and prejudice across treatment arms


- Workers will participate in lab-in-the-field experiments at endline in order to understand mechanisms that result in productivity differences in religiously mixed and homogeneous teams
Primary Outcomes (explanation)
- Production Data will be obtained directly from the firm which is recorded daily at the firm. Such data are recorded primarily at the line level and not at the section level. Production data for some sections are available which will be used. In addition, during the course of the intervention, production supervisors will record their own assessment of each section's performance daily.

- Measures of out-group perception and prejudice constructed using survey data in order to analyze whether contact with individuals from other religious groups affect preferences and how these effects vary across sections that require high and low dependency amongst workers

- There will be direct measures of social distance, for example survey questions on cross-religion communication at workplace and preferences towards having non-coreligionist supervisors

- An Implicit Association Test (IAT) where workers associate identifiable Hindu and Muslims names with positions in the hierarchy at the firm to understand whether workers have bias towards their own religious group occupying higher positions.

These outcomes will be compared across treatment arms at baseline and endline.

UPDATE: The intervention was successfully completed before covid-19 lockdown restrictions were imposed in India, late in March 2020. Production data has been collected from the firm. Only a phone survey could be conducted thereafter due to the restrictions in place. A detailed endline survey with Implicit Association Tests (IATs) and lab games could not therefore be conducted. The trial end date is therefore extended to next year so that if conditions permit, these can be conducted later.

Secondary Outcomes

Secondary Outcomes (end points)
- Political preferences (political affiliation, preference over bills)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment involves randomizing workers in the firm into religiously mixed and homogeneous teams and tracking productivity. Team production will be studied over a period of 4-5 months after the intervention. The hypothesis we want to test through this intervention is whether greater contact with non-co-coreligionists affects perception, prejudice and productivity. Understanding heterogeneity in these effects with respect to the production technology is an important objective of this study. Production data will be complemented with baseline and endline survey data to understand mechanisms driving productivity differences across groups.

Experimental Design Details
This study is aimed at understanding the effect of religious team composition on team productivity and how the effects vary with production technology. The firm in which the experiment will take place produces packaged bakery products. It has 6 different production lines, each of which has multiple sections. Workers in each section of a production line perform different tasks which eventually lead to production of the final product.

There is large variation across sections in the degree of dependency amongst workers. There are some sections which require workers to directly depend on each other for the production process to move without interruption, for e.g. workers standing next to each other before a conveyor belt with each worker responsible for picking every alternate piece of moving product to pack. Other sections such as mixing and baking, require lower direct dependency amongst workers - they have greater control over process speed and require coordination with other workers at a lower frequency than high dependency sections. Dependency is measured using time-use data with a stopwatch - the proportion of time (out of every 10 minutes) that workers are directly dependent on each other for production to occur without interruption. Work monotony and stress are likely to be greater in high dependency sections.


The intervention will involve randomizing workers in high and low dependency sections into religiously mixed or non-mixed sections. The objective of the intervention is to analyze whether there are differential effects on team output depending on whether high or low dependency sections in a production line have mixed teams. More specifically, we want to test whether there is greater output loss from having mixed teams in high dependency sections as opposed to low dependency ones. The study will also focus on how these effects vary by worker tenure.

Production in the firm occurs in 3 different shifts (morning, afternoon and night). There are a total of 6 production lines and therefore (6 x 3) = 18 shifts of production per day at maximum capacity. Workers in each section of a production line perform different tasks which eventually lead to the final product.


Workers will be randomized into teams in such a way that, for each production line, one shift will have all its high dependency sections mixed (in terms of religious composition of workers) whereas the low dependency sections will have a homogeneous group (Hindus) of workers. The second shift will have exactly the opposite structure i.e. the low dependency sections will be mixed and the high dependency sections non-mixed. The third shift will either be similar to the first shift or the second shift.

Randomization Method
Done through STATA on a computer.
Randomization Unit
Individual, Team
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
16-18 production-line teams
100-110 production line-section teams

Sample size: planned number of observations
Approximately 600 firm workers. Daily production data from 6 production lines for approximately 5 months - 1500 shifts of production data
Sample size (or number of clusters) by treatment arms
750 shifts of production data for each of the two different treatment groups
Workers in high or low dependency sections will be randomized either into mixed or non-mixed teams.

Approximate number of workers in each type of section:

Low Dependency-Non-Mixed : 100
Low Dependency- Mixed : 105
High Dependency-Non-Mixed : 190
High Dependency-Mixed : 150
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
UBC BREB
IRB Approval Date
2019-05-03
IRB Approval Number
H19-00729

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials