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Field
Abstract
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Before
This study examines whether limited access to high‑quality demand information constrains the growth of small retailers in developing countries and whether an AI‑driven mobile application that pools sales data across shops can overcome this barrier. One thousand Lusaka‑based retail shops will be randomly assigned to (i) an inventory‑management app only (control); (ii) the app plus product recommendations generated from data pooled across a relatively small number of similar shops (e.g., 10 shops); or (iii) the app plus recommendations generated from data on a larger number of similar shops (e.g., 100).. We will followup with the shops 4 times during and immediately after the intervention, and again 3 months later, in order to collect detailed data on adoption of the recommended products, weekly sales, and business income. Results will inform policies aimed at supporting SME productivity through digital data‑sharing platforms.
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After
This study examines whether limited access to high‑quality demand and supplier information constrains the growth of small retailers in developing countries and whether an AI‑driven mobile application that pools sales data across shops can overcome this barrier. It will further test what the returns are to increasing the size of the data pool. One thousand Lusaka‑based retail shops will be randomly assigned in equal proportion to (i) an inventory‑management app only (control); (ii) the app plus lower-priced supplier recommendations generated from data pooled across a relatively small number of similar shops; or iii) the app plus lower-priced supplier recommendations generated from data pooled across a relatively large number of similar shops; or (iv) the app plus product recommendations generated from data on similar shops. Further, within the arm assigned to receive product recommendations, half the stores will receive a buy-back offer to mitigate against the risk of adopting new products that do not sell well. We will followup with the shops 3 times during and immediately after the intervention, and again 3 months later, in order to collect detailed data on adoption of the recommended products and suppliers, weekly sales, and business income. Results will inform policies aimed at supporting SME productivity through digital data‑sharing platforms.
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Field
Trial Start Date
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Before
August 07, 2025
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After
February 05, 2026
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Field
Trial End Date
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Before
June 20, 2026
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After
August 09, 2026
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Field
Last Published
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Before
August 08, 2025 06:55 AM
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After
February 04, 2026 09:16 PM
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Field
Intervention (Public)
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Before
Intervention Components:
1. Inventory‑management mobile application (basic logging & analytics). Shops receive in‑person onboarding and three weeks of usage incentives to ensure high app engagement.
2. AI‑generated product recommendations based on pooled sales data from a small or large pool of similar shops.
3. Information about the size of the pool of shops used for generating the recommendations
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After
Intervention Components:
1. Inventory‑management mobile application (basic logging & analytics)
2. AI-generated supplier recommendations
3. AI‑generated product recommendations
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Field
Intervention Start Date
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Before
September 15, 2025
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After
March 23, 2026
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Field
Intervention End Date
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Before
October 31, 2025
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After
May 24, 2026
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Field
Primary Outcomes (End Points)
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Before
We will specify our primary and secondary outcomes in a pre-analysis plan, which will be lodged before followup data collection begins. We plan to capture data on the following:
Adoption of the recommended product
Sales & gross margin of recommended and existing products
Total sales revenue
Total business income / profit
Changes in suppliers or supplier search behaviour
Number of customers (footfall)
Number of distinct products stocked & inventory turnover
Introduction of other new products
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After
We will specify our primary and secondary outcomes in a pre-analysis plan, which will be lodged before followup data collection begins. We plan to capture data on the following:
Adoption of the recommended product
Purchases from the recommended supplier
Sales & gross margin of recommended and existing products
Total sales revenue
Total business income / profit
Changes in suppliers or supplier search behaviour
Number of customers (footfall)
Number of distinct products stocked & inventory turnover
Introduction of other new products
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Field
Experimental Design (Public)
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Before
An individually randomised controlled trial with 1,000 shops divided equally across three arms.
Treatment Arms:
o T0 (Control) – App only
o T1 – App + recommendations from a smaller pool of comparable shops
o T2 – App + recommendations from a larger pool of comparable shops
Cross‑Randomisation: Within T1 and T2, shops are randomised as to whether the pool size (small vs large) is explicitly revealed.
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After
An individually randomised controlled trial with 1,000 shops divided equally across three arms.
Treatment Arms:
T0 (Control) – App only
T1 – App + supplier recommendations from a smaller pool of comparable shops
T2 – App + supplier recommendations from a larger pool of comparable shops
T3 - App + product recommendations from comparable shops
Cross‑Randomisation: Within T3, we will randomise whether stores also receive a buy-back offer, protecting them against the risk of the recommended product not selling well.
All shops receive in‑person onboarding and three weeks of usage incentives to ensure high app engagement.
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Field
Sample size (or number of clusters) by treatment arms
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Before
T0 = 333 firms; T1 = 333 firms; T2 = 334 firms
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After
T0 = 250 firms; T1 = 250 firms; T2 = 250 firms; T3 = 250 firms
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