Replication Data for Breaking Barriers to Adoption: A Multi-Stakeholder Platform Approach to Promoting Improved Common Bean Varieties among Farmers in Malawi

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Kadakoma Rambiki, Ivy; Magreta, Ruth; Phiri, Alexander; Birachi, Eliud Abucheli; Larochelle, Catherine; Mutua, Mercy Muli; Rubyogo, Jean Claude; Nkhata, Wilson, 2024, "Replication Data for Breaking Barriers to Adoption: A Multi-Stakeholder Platform Approach to Promoting Improved Common Bean Varieties among Farmers in Malawi", https://doi.org/10.7910/DVN/MHZQV0, Harvard Dataverse, V1, UNF:6:y9AEt1QsbTHDrXqRFriXQA== [fileUNF]

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Description	The study’s data is from a survey that was conducted to address the objective of transforming seed systems to respond to common bean varieties’ demand through multi-stakeholder platforms in the Malawi Multi-stakeholder Platform (MSP) project. The output of the project hypothesis was evidence that using the MSP-based Participatory Variety Evaluation (PVE) approaches increases awareness and accelerates uptake of new market-demanded varieties. The study's main objective was to assess the influence of MSPs and farmers' attitudes on the uptake of improved common bean varieties. The survey was conducted in Dedza, Mzimba, and Kasungu districts of Malawi, which are among those areas where common bean is mostly cultivated by farmers owing to favorable soil type, climatic conditions, and rainfall patterns. In the MSP project design, Dedza district, which is in the central region, and Mzimba district, in the northern region of Malawi, were the intervention areas. Kasungu district, which is in the central region and borders Mzimba district, is the counterfactual site. Methodology:The study used a multi-staged sampling procedure where, in the first stage, purposive sampling was used to select districts and Extension Planning Areas (EPAs) within each district. Sections, villages, and farmer households were then selected randomly. The information was collected at the household level, with the principal decision maker in a household responding to the full survey. The study collected data from 797 farmer households, of which 62% were from intervention areas and 38% were from counterfactual areas. Data analysis was done using STATA and MS-Excel. (2024-04)
Subject	Social Sciences; Agricultural Sciences
Keyword	Participatory Varietal Selection, Africa, Crops for Nutrition and Health
License/Data Use Agreement	Custom Dataset Terms

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	1 to 3 of 3 Files	Original Format Archival Format (.tab)
	01a. DATA DESCRIPTION FOR FARMERS' UPTAKE MANUSCRIPT.docx MS Word - 28.2 KB Published Sep 16, 2024 3 Downloads MD5: c540c95665378f2f5acd1bc184a46b87 Data dictionary Documentation	Access File File Access Public Download Options MS Word Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	01b. DATA DICTIONARY FOR FARMERS' UPTAKE MANUSCRIPT.xlsx MS Excel Spreadsheet - 10.3 KB Published Sep 16, 2024 3 Downloads MD5: c34d03ae1051c3d5a8c40a332da704b7 Data dictionary Documentation	Access File File Access Public Download Options MS Excel Spreadsheet Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	02b. Replication data for Farmer uptake manuscript.tab Tabular Data - 53.3 KB Published Sep 16, 2024 11 Downloads 17 Variables, 797 Observations UNF:6:y9AEt1QsbTHDrXqRFriXQA== STATA dataset Data	Preview "02b. Replication data for Farmer uptake manuscript.tab" Preview "02b. Replication data for Farmer uptake manuscript.tab" Access File File Access Public Download Options Stata 14 Binary (Original File Format) Tab-Delimited RData Download Metadata DDI Codebook v2 Data File Citation Download EndNote XML Download RIS Download BibTeX Explore Options Data Explorer v2

Citation Metadata

Persistent Identifier	doi:10.7910/DVN/MHZQV0
Publication Date	2024-09-16
Title	Replication Data for Breaking Barriers to Adoption: A Multi-Stakeholder Platform Approach to Promoting Improved Common Bean Varieties among Farmers in Malawi
Author	Kadakoma Rambiki, IvyLilongwe University of Agriculture and Natural Resources, African Centre of Excellence in Agricultural Policy Analysis, Department of Agricultural and Applied Economics Lilongwe University of Agriculture and Natural Resources, African Centre of Excellence in Agricultural Policy Analysis, Department of Agricultural and Applied Economicshttps://orcid.org/0000-0002-3763-4264 Lilongwe University of Agriculture and Natural Resources, African Centre of Excellence in Agricultural Policy Analysis, Department of Agricultural and Applied Economicshttps://orcid.org/0009-0005-3535-3417 International Center for Tropical Agriculture - CIAThttps://orcid.org/0000-0003-3444-549X Department of Agricultural and Applied Economicshttps://orcid.org/0000-0001-7655-7380 International Center for Tropical Agriculture - CIAThttps://orcid.org/0000-0003-2899-0678 International Center for Tropical Agriculture - CIAThttps://orcid.org/0000-0002-6966-0790 International Center for Tropical Agriculture - CIAThttps://orcid.org/0000-0003-2698-8398
Point of Contact	Use email button above to contact. Alliance Data Management (Bioversity International and the International Center for Tropical Agriculture)
Description	The study’s data is from a survey that was conducted to address the objective of transforming seed systems to respond to common bean varieties’ demand through multi-stakeholder platforms in the Malawi Multi-stakeholder Platform (MSP) project. The output of the project hypothesis was evidence that using the MSP-based Participatory Variety Evaluation (PVE) approaches increases awareness and accelerates uptake of new market-demanded varieties. The study's main objective was to assess the influence of MSPs and farmers' attitudes on the uptake of improved common bean varieties. The survey was conducted in Dedza, Mzimba, and Kasungu districts of Malawi, which are among those areas where common bean is mostly cultivated by farmers owing to favorable soil type, climatic conditions, and rainfall patterns. In the MSP project design, Dedza district, which is in the central region, and Mzimba district, in the northern region of Malawi, were the intervention areas. Kasungu district, which is in the central region and borders Mzimba district, is the counterfactual site. Methodology:The study used a multi-staged sampling procedure where, in the first stage, purposive sampling was used to select districts and Extension Planning Areas (EPAs) within each district. Sections, villages, and farmer households were then selected randomly. The information was collected at the household level, with the principal decision maker in a household responding to the full survey. The study collected data from 797 farmer households, of which 62% were from intervention areas and 38% were from counterfactual areas. Data analysis was done using STATA and MS-Excel. (2024-04)
Subject	Social Sciences; Agricultural Sciences
Keyword	Participatory Varietal Selection (AGROVOC) http://aims.fao.org/aos/agrovoc/c_12ecc6d9 Africa (Research Region) Crops for Nutrition and Health (Research Lever)
Topic Classification	technology adoption (AGROVOC) http://aims.fao.org/aos/agrovoc/c_e8e5cb81
Language	English
Producer	International Center for Tropical Agriculture (CIAT) https://ciat.cgiar.org/
Production Date	2022-05-31
Contributor	Data Manager: Mercy Muli Mutua Project Leader: Eliud Birachi
Funding Information	MSU-Michigan State University: A458-MSU(USA-USAID)-Transforming Seed Systems in Malawi, to respond to bean variety demand through multi-stakeholder platforms
Distributor	International Center for Tropical Agriculture (CIAT) https://ciat.cgiar.org/
Distribution Date	2023-09-15
Depositor	Alliance Data Management
Deposit Date	2024-04-18
Time Period	Start Date: 2021-05-01
Date of Collection	Start Date: 2022-05-19; End Date: 2022-06-01
Data Type	Survey Data; Socio-economic Data
Data Source	Primary data collected from farming households

Geospatial Metadata

Geographic Coverage	Malawi

Social Science and Humanities Metadata

Unit of Analysis	Household, individual farmers
Universe	Bean farmers in Malawi
Sampling Procedure	Multi-stage
Type of Research Instrument	Questionnaire

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