Evaluating the Impact of AI-Driven Training on Microenterprises: Evidence from Pakistan

Last registered on November 01, 2023

Pre-Trial

Trial Information

General Information

Title
Evaluating the Impact of AI-Driven Training on Microenterprises: Evidence from Pakistan
RCT ID
AEARCTR-0012371
Initial registration date
October 26, 2023

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
November 01, 2023, 4:01 PM 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

Affiliation
Tufts University

Other Primary Investigator(s)

PI Affiliation
University of Delaware

Additional Trial Information

Status
In development
Start date
2024-02-01
End date
2025-05-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
A standard business training program is classroom-based and teaches a range of better business practices. Evaluations of these programs show mixed evidence, particularly in developing countries, and highlight that selection matters. Additionally, there are concerns around the inability to adapt content to the specific needs of the businesses and the high costs of training. It is thus important to find ways to share customized knowledge, reduce the cost of training, and identify policies to help the most dynamic entrepreneurs grow. To deal with these concerns, this project focuses on teaching high-growth-potential microenterprise owners how to use generative AI, specifically ChatGPT, for their business activities.

We aim to use a randomized control trial to study how training business owners in using ChatGPT to then in turn train themselves affects their productivity and entrepreneurial success. We aim to explore this question in the context of Pakistan, a lower-middle-income country in South Asia. Given the varying entrepreneurial challenges and opportunities that men and women encounter in a developing country like Pakistan, we also plan to conduct a heterogeneity analysis to dissect the impact of this AI-based training intervention through the gender lens.
External Link(s)

Registration Citation

Citation
Rehman, Attique and Sarah Shaukat. 2023. "Evaluating the Impact of AI-Driven Training on Microenterprises: Evidence from Pakistan." AEA RCT Registry. November 01. https://doi.org/10.1257/rct.12371-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-05-01
Intervention End Date
2024-12-31

Primary Outcomes

Primary Outcomes (end points)
business knowledge, profits, sales, number of customers
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our approach will involve a randomized controlled trial, comprising of two treatment arms and a control group, with each group consisting of around 400 small firms, stratified by gender (power calculations will determine the exact sample size). Firms will either receive generative AI training or training on how to use Google for their business activities in the two treatment arms. The control group will receive no training.
Experimental Design Details
Not available
Randomization Method
randomization in Stata
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
NA
Sample size: planned number of observations
1200
Sample size (or number of clusters) by treatment arms
400 in each
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number