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Supply vs. Demand Constraints for E-Commerce Adoption

Last registered on July 08, 2022


Trial Information

General Information

Supply vs. Demand Constraints for E-Commerce Adoption
Initial registration date
June 30, 2022

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
July 08, 2022, 9:15 AM EDT

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



Primary Investigator

University of Illinois - Urbana Champaign

Other Primary Investigator(s)

PI Affiliation
DIME, World Bank
PI Affiliation
DIME, World Bank

Additional Trial Information

On going
Start date
End date
Secondary IDs
Illinois IRB18668
Prior work
This trial does not extend or rely on any prior RCTs.
E-commerce continues to grow in importance, but many MSME’s have not invested in their firm’s ability to sell online. This may be due to a lack of know-how (a “supply-side” constraint), or simply due to a lack of perceived benefit for selling online (a “demand-side” constraint). We test the relative importance of these two types of constraints using two randomized evaluations in the country of Georgia. In a first experiment we randomize which firms are offered a training program on how to get their firms online. In a second experiment we offer some firms a
promise that we would make a large purchase from them if we were able to make that purchase online. We will compare the likelihood that firms sell online in the months after our treatment.
External Link(s)

Registration Citation

Coville, Aidan, Adam Osman and Caio Piza. 2022. "Supply vs. Demand Constraints for E-Commerce Adoption." AEA RCT Registry. July 08.
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Experimental Details


Training intervention: A 3-day face-to-face training on e-commerce basics, and covered: (Day 1) How to use Google, Face-
book, Instagram and Trip Advisor to increase the visibility of your business; (Day 2) How to understand customersˆa profiles, and how to register in e-commerce platforms to increase sales (like, Airbnb, and other local platforms) and; (Day 3) How to develop a business model, access financial opportunities and grants, and participate in public procurement opportunities.

Demand Shock: Eligible firms were contacted by phone and told that an implementing partner would like to order their goods or services, with the condition that it would have to be done online. Firms were given two weeks in which to ensure they had an online business profile that included, at a minimum, their business name, logo, description of their goods and services (including photos and/or videos), contact in-
formation for how to make an order, and an option for review feedback on the site. Once the site was in place, they would place an order. Payments were needed to be made by bank transfer or directly on the website (no cash option), and the firm had to be able to deliver the product to the partner offices in Tbilisi. In the case of services, this would come in the form of a voucher. Firms were either provided the ”high” or the ”low” demand shock offer. The ”low” demand shock offer was priced to be equivalent to the cost of the e-commerce training ($ 130) and the ”high” demand shock was set at $ 780 - five times the size of the ”low” offer.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Ability to sell good online
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Business performance (revenue, number of customers, innovation)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Experiment 1: Interested businesses were randomized into being provided the e-commerce training or to serve as a control group.

Experiment 2: Businesses were randomized into 3 groups: small demand shock, large demand shock, control.

For experiment 2 we stratified by a firms "readiness" to sell online. We split firms into 3 groups, a "likely ready" group, a "more effort group", and an "unlikely to be ready" group. As of the writing of this registration we have not yet collected data on the "unlikely to be ready group" but we expect them to respond least to the demand shock.
Experimental Design Details
Randomization Method
Randomization don in office by a computer.
Randomization Unit
Individual (firm owner) level
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Experiment 1: 858 firms

Experiment 2: 283 firms
Sample size: planned number of observations
Experiment 1: 858 firms Experiment 2: 283 firms
Sample size (or number of clusters) by treatment arms
Experiment 1: 220 control, 638 treatment

Experiment 2: 76 small shock, 76 large shock, 131 control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
University of Illinoi
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials