Digital literacy, output market access, and demand for rural e-commerce

Last registered on November 30, 2022
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Pre-Trial

Trial Information

General Information

Title
Digital literacy, output market access, and demand for rural e-commerce
RCT ID
AEARCTR-0010444
Initial registration date
November 19, 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
November 30, 2022, 2:34 PM EST

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

Locations

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Primary Investigator

Name
Khadijat Amolegbe
Affiliation
University of Ilorin
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Other Primary Investigator(s)

PI Name
Senakpon Dedehouanou
PI Affiliation
University of Abomey-Calavi, Benin
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PI Name
Abdulazeez Muhammad-Lawal
PI Affiliation
University of Ilorin, Nigeria
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PI Name
Jenny Aker
PI Affiliation
Tufts University
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Additional Trial Information

Status
On going
Start date
2022-04-25
End date
2024-06-30
Keywords
Agriculture, Education
Additional Keywords
Digital, Literacy, Agriculture, Market, Marketing platforms, Nigeria
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The growth of digital marketing platforms is changing the food system and presents an opportunity to address the problem of access to the output market among rural farmers. However, digital transformation is accompanied by a growing digital divide due to limited digital literacy and tools, which may hinder rural farmers from exploring opportunities in the digital market. We launch a digital literacy intervention and assess the relationship between digital literacy and market access. We also explore how digital literacy can spur the demand for digital marketing platforms in rural areas. We assess the impact of the digital literacy intervention using a Randomised Controlled Trial by clustering at the community level and focusing on 3513 farming households in Nigeria. We then test how basic digital skills and access to digital marketing support via local marketing agents can improve farmers' access to the output market.
External Link(s)

Registration Citation

Citation
Aker , Jenny et al. 2022. "Digital literacy, output market access, and demand for rural e-commerce ." AEA RCT Registry. November 30. https://doi.org/10.1257/rct.10444-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-11-21
Intervention End Date
2023-01-20

Primary Outcomes

Primary Outcomes (end points)
Digital tools adoption (and farmers’ use of digital marketing platforms), sales value of arable crops cultivated by the farming household, the average gap in time between harvest and sales, average amount willing to pay to sell via a digital marketing platform (Agriple).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We use a cluster randomized control experiment design to assign subjects to treatments and control groups. We focus on three states in Nigeria and identify (list) farming communities with mobile network coverage and internet access. We stratify by the local government areas (LGAs) and then randomly assign communities (clusters) to the treatment and control, using the Stata command "randtreat" that performs random multiple treatment assignment across strata and deals with "misfits". Basically, we randomly assign farming communities to one of four groups:
1. Treatment group 1 - households in communities that will receive only the digital skills training intervention
2. Treatment group 2 - households in communities that will receive only support from trained local marketing agents
3. Treatment group 3 - households in communities that will receive both the training intervention and the support from trained local marketing agents
4. Control group will not receive any of the treatments
Experimental Design Details
Not available
Randomization Method

The randomization was done in the office by a computer using the Stata command “randtreat” which handles multiple treatments across strata and deals with "misfits" (Carril, 2017).
Randomization Unit
Community level
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
255 rural communities
Sample size: planned number of observations
3513
Sample size (or number of clusters) by treatment arms
3,513 farming households in 255 rural communities with 51 in each treatment arm and 102 in the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Ilorin Nigeria Ethical Review Committee
IRB Approval Date
2022-03-25
IRB Approval Number
UERC/ASN/2022/2350
Analysis Plan

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