Evidence map›Paper›PMID 41647432›Full record

ArticleFrontiers in veterinary science2025

Thriving against the odds through positive deviant behavior: technology adoption and entrepreneurship among dairy farmers in Addis Ababa and Oromia in Ethiopia.

Ndungu Nyokabi, Gizachew Gemechu, Lisette Phelan, Johanna Lindahl, Adane Mihret, Stefan Berg, James L N Wood, Henrietta L Moore

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Article in Frontiers in veterinary science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Ndungu NyokabiInstitute for Global Prosperity, University College London, London, United Kingdom.
Gizachew GemechuArmauer Hansen Research Institute (AHRI), Addis Ababa, Ethiopia.
Lisette PhelanSchool of Sustainable Food and Farming, Harper Adams University, Edgmond, United Kingdom.
Johanna LindahlInternational Livestock Research Institute (ILRI), Nairobi, Kenya.
Adane MihretUniversity of Edinburgh Business School, Edinburgh, United Kingdom.
Stefan BergBernhard Nocht Institute for Tropical Medicine, Hamburg, Germany.
James L N WoodDepartment of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.
Henrietta L MooreInstitute for Global Prosperity, University College London, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Positive deviant (PD) farmers can be differentiated from the wider farming community by their inherent capacity to leverage farming innovations and technologies in addressing challenges faced in engaging in agricultural production. There is currently a limited body of literature on how positive deviance and entrepreneurial behavior allow some dairy farmers to develop strategies that enable them to cope better with and creatively overcome challenges faced by their peers. This study employed a positive deviance approach to identify innovative dairy farmers in urban and peri-urban areas of the Addis Ababa and Oromia administrative regions of Ethiopia. PD farmers were identified and selected through a descriptive study design, utilizing a purposive and snowball sampling approach based on the number of technologies adopted in a previous survey study and referrals from other farmers. Data were collected through key informant interviews and participant observation on selected farms. We observed that PD dairy farmers had adopted and/or modified a variety of technologies to overcome context-specific challenges faced, such as seasonal feed shortages exacerbated by climate change, reduced land size and availability of land for grazing and waste disposal, and restrictions on farming resulting from the development of urban areas. These technologies enabled farmers to improve feed production, manure disposal, breeding practices, the quality of livestock housing, and animal welfare and enabled them to control diseases and add value to milk production. This study underscores the important role that PD dairy farmers could play as social referents, not only for their peers in urban and peri-urban areas but also for policymakers, extension workers and academics who are interested in working with dairy farmers in co-identifying and co-developing solutions to challenges currently undermining the sustainability of the dairy sector in Ethiopia and beyond.

Indexed as

animal healthanimal welfarebiosecurity measureslivestock feedinglivestock housinglivestock productiontechnology adoption

Identifiers

PMID41647432
PMCPMC12870667

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.