Evaluating Advisory Service Delivery Mechanisms for Boosting the Adoption of Crop-Shrub-Livestock Innovation Bundles: Experimental Evidence From Mali and Senegal

Last registered on January 27, 2025

Pre-Trial

General Information

Title

RCT ID

AEARCTR-0015265

Initial registration date

January 23, 2025

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

January 27, 2025, 9:59 AM EST

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

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name

Tesfamicheal Wossen

Affiliation

IITA

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Christian Grovermann

PI Affiliation

Forschungsinstitut für Biologischen Landbau Stiftung (FiBL)

Contact Investigator

PI Name

Assane Beye

PI Affiliation

Universite Cheikh Anta Diop (UCAD)

Contact Investigator

Additional Trial Information

Status

On going

Start date

2020-09-30

End date

2025-09-30

Keywords

Agriculture, Behavior, Environment & Energy

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

In the West African Sahel, over 80% of rangelands and farmlands are severely affected by land degradation and soil erosion, threatening agricultural productivity and rural livelihoods. Integrating crops, shrubs, and livestock into farming systems presents a transformative opportunity to restore soil health, increase yields, enhance climate resilience, and improve food security. Despite these significant benefits, adoption of these integrated practices by smallholder farmers remains limited. This study explores the potential of tailored advisory services to promote the adoption of crop-shrub-livestock innovation bundles and assesses their impact on farm productivity and resilience.

Using a randomized controlled trial, we evaluate the effectiveness of two distinct extension models: (1) in-person engagement through living labs and farmer field schools, and (2) a blended approach that combines farmer field schools with digital-based advisory services. By providing robust empirical evidence on the relative efficacy of these advisory delivery mechanisms, this research contributes to the design of scalable, context-specific strategies for promoting sustainable agricultural innovations in the Sahel, offering valuable insights for policymakers and development practitioners aiming to scale transformative agricultural innovations.

External Link(s)

Registration Citation

Citation

Beye, Assane, Christian Grovermann and Tesfamicheal Wossen. 2025. "Evaluating Advisory Service Delivery Mechanisms for Boosting the Adoption of Crop-Shrub-Livestock Innovation Bundles: Experimental Evidence From Mali and Senegal." AEA RCT Registry. January 27. https://doi.org/10.1257/rct.15265-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2021-01-01

Intervention End Date

2024-12-31

Primary Outcomes

Primary Outcomes (end points)

Awareness and knowledge: awareness and knowledge about improved crop-shrub-livestock practices
Uptake: Adoption of improved crop-shrub-livestock integration practices
(c) Productivity and resilience: These benefits are measured by evaluating impacts on crop productivity (mean yield) as well as the stability of crop yield (variability) and resilience to shocks (downside risk and hence food security).
(d) Resource use efficiency: Improvement in resource use efficiency (e.g., changes in the efficiency of fertilizer). For example, reduction in the use of inorganic fertiliser without offsetting yield is beneficial to the environment.
(e) Livestock and crop products: Changes in the level/importance of livestock and crop products (e.g. milk or millets), which are particularly relevant for income generation, food security and nutrition.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

-Resource use efficiency
-Productivity and resilience: These benefits are measured by evaluating impacts on crop productivity (mean yield) as well as the stability of crop yield (variability) and resilience to shocks (downside risk and hence food security).
- Cost-effectiveness of in-person and digital-based extension approaches

Secondary Outcomes (explanation)

Experimental Design

1) In-person engagement through living labs and farmer field schools (T1): Lead farmers are identified in each village to host demonstration plots for hands-on learning. These farmers participate in local innovation platforms, coach others, and facilitate structured field days and learning sessions to co-create knowledge on CSL practices such as pruning, species selection, and integrating shrubs with other ecological innovations. Demonstration plots and regular farmer field schools foster familiarity with and encourage the adoption of CSL practices.

2) A blended approach combining farmer field schools with digital-based advisory services (T2): This approach replaces in-person coaching with digital advisory support for lead farmers, using tools such as mobile applications, videos, and SMS. T2 aims to reach a broader audience of farmers, reduce logistical challenges, and ensure scalable and efficient dissemination of sustainable agricultural innovations. Both T1 and T2 rely on lead farmers to multiply knowledge and facilitate learning, with T2 emphasizing scalability through digital solutions.

3) Control group: Villages in the control group receive no intervention.

Experimental Design Details

Not available

Randomization Method

By computer

Randomization Unit

Villages

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

90 villages.

Sample size: planned number of observations

7 households per village.

Sample size (or number of clusters) by treatment arms

30 villages (T1); 30 villages (T2) and 30 villages (control)

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

15%

Supporting Documents and Materials

IRB

Institutional Review Boards (IRBs)

IRB Name

IRB Approval Date

IRB Approval Number

Analysis Plan