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Field
Last Published
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Before
January 12, 2024 03:34 PM
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After
April 03, 2024 11:52 AM
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Field
Intervention (Public)
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Before
The intervention for this study involves access to digital advisory services through a mobile-based application called "farmbetter app". This application will be customized into three different models to provide access to digital advisory services to farmers. The three models include, Agent-based model, Self-service model, and Hybrid model which will form three treatments for this study. Under the Agent-based model, only the extension/village based agents will be able to download "farmbetter app" to access DAS and train farmers. Under the Self-service model, only farmers will be able to download the app to access DAS and use it independently, while Hybrid model, both the extension agents and the farmers will be able to download the app and share the information together.
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After
The intervention for this study involves access to digital advisory services through a mobile-based application called "farmbetter app". This application is customized into three different models that will provide access to digital advisory services (DAS) to farmers. The three models include, Agent-based model, Self-service model, and Hybrid model which form three treatments for this study. Under the Agent-based model, only the extension/village based agents will be able to download the "farmbetter app" to access DAS and train farmers. Under the Self-service model, only farmers will be able to download the app and use it independently to access DAS, while Hybrid model, both the extension agents and the farmers will be able to download the app and share the information together.
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Field
Primary Outcomes (End Points)
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Before
1. Awareness and knowledge of sustainable land management practices.
2. Adoption of sustainable land management practices (SLMPs).
3. Crop (maize for Uganda, and wheat and rice for India) productivity.
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After
1. Awareness and knowledge of sustainable land management practices.
2. Adoption of sustainable land management practices.
3. Crop yields (i.e., maize for Uganda; wheat and rice for India).
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Primary Outcomes (Explanation)
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Before
A list of questions to measure knowledge of sustainable land management practices will be prepared and farmers will be expected to respond with correct and wrong answers to the questions from which a knowledge score will be calculated. Awareness of sustainable land management practices will be measured as a dummy variable of whether farmers are aware of sustainable land management practices or not.
Adoption will be measured as a dummy variable taking a value of one if the farmers is an adopter of sustainable land management practices and zero if otherwise.
Crop yield will be measured as the total output aggregated from all the plots owned by the farmer in kilograms per acre per season. The yields data will be obtained from both the baseline, phone, and endline surveys. The main crops of interest will be maize in Uganda while in India, the crops will be wheat and rice.
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After
A list of knowledge questions on sustainable land management practices will be prepared and farmers will be expected respond with correct and wrong answers from which a knowledge score will be computed.
Awareness of sustainable land management practices will be measured as a dummy variable taking a value of one if the farmer is aware of sustainable land management practices and zero otherwise.
Adoption will be measured as a dummy variable taking a value of one if a farmer adopt any of the sustainable land management practices and zero otherwise.
Crop yields will be measured as the total output aggregated from all the plots owned by the farmer in kilograms per acre per season. The crop yields data will be obtained from the baseline, phone, and endline surveys. The main crops of interest will be maize in Uganda while in India, the crops will be wheat and rice.
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Experimental Design (Public)
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Before
The study will be a four-arm cluster randomized controlled trial with a total of 160 clusters (villages) in each country (Uganda and India). These clusters will be formed from the three DAS delivery models customized in the "farmbetter app" (Agent-based model, Self-service model, and Hybrid model) and a control group. Forty clusters (villages) will be randomly allocated to each treatment and the control with an allocation ratio of 1:1:1:1.
After randomization of villages into treatments and control group, listing of farmers will be done for each cluster both in treatment groups and control group. For a farmer to qualify, he/she must be involved in farming (agriculture and allied activities) and own a smartphone (either individually or as a family). The following preliminary information will be collected during farmers’ listing exercise; name of the farmer, age, gender, postal address, contact number, type of mobile ownership, digital literacy and common crops grown. Once the list is obtained, households will be randomized into treatments that match the treatment in which their village is under. In Uganda, those who own smartphones will be the host farmers while those who don’t will be attached to the lead farmers where one lead farmer host 5 farmers.
The trial is expected to run for three growing seasons. Two long seasons and one short season. The impact of DAS delivery models will be evaluated through two main surveys at the start (baseline) and end-line with continuous phone surveys at the end of each season. Baseline data was collected between August-September 2023, and an end-line survey will be conducted between December 2024 and February 2025. Each interview will take approximately 1 hour.
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After
The study is a four-arm cluster randomized controlled trial with a total of 160 clusters (or villages) in each country (i.e., Uganda and India). These clusters are formed from the three DAS delivery models customized in the "farmbetter app" (i.e., Agent-based model, Self-service model, and Hybrid model) and a control group. Forty clusters (or villages) are randomly allocated to each treatment and the control with an allocation ratio of 1:1:1:1.
Before the actual randomization of farmers to various treatment groups and control group, a listing exercise of farmers within the selected villages was conducted in Uganda and India. For a farmer to qualify, he/she must be involved in farming (agriculture and allied activities) and own a smartphone (either individually or as a family). The following preliminary information was collected during farmers’ listing exercise; name of the farmer, age, gender, contact number, type of mobile ownership, digital literacy and common crops grown. Once the list was obtained, the households were then randomized into three treatments and a control group.
The trial is expected to run for three growing seasons. Two long seasons and one short season in Uganda, and two wheat seasons and one rice season in India. The impact of DAS delivery models will be evaluated through two main surveys at the start (baseline) and end-line with continuous phone surveys at the end of each season.
Baseline data was collected between August-September 2023 for Uganda and India. The end-line survey will be conducted between December 2024 and February 2025. Each interview will take approximately 1 hour.
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Randomization Method
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Before
The randomization will be done using a computer following farmers' listing exercise in Uganda and India.
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After
The randomization was done using a computer following farmers' listing exercise in Uganda and India.
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Field
Additional Keyword(s)
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Before
Digital advisory (extension) services, Sustainable land agricultural practices, Adoption, Impact.
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After
Digital advisory services, Sustainable land management practices, Adoption, Impact.
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