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dc.contributor.authorAndrew, Rogers
dc.contributor.authorMakindara, Jeremia
dc.contributor.authorMgale, Yohana
dc.date.accessioned2022-02-11T09:21:01Z
dc.date.available2022-02-11T09:21:01Z
dc.date.issued2022-01
dc.identifier.urihttps://repository.irdp.ac.tz/handle/123456789/352
dc.description.abstractThe study was conducted to investigate the technical, allocative and economic efficiency of keeping introduced chicken strain; Kuroiler and Sasso at the farm level by using the input constrained Stochastic Data Envelopment Analysis. Data were collected from farmers who participated in the African Chicken Genetic Gain project. The study applied a developmental research design, which involved providing of pre-brooded chicks to farmers in selected sites. The on-farm test involved a total of 202 farmers who were provided with six weeks old chicks. The findings show that farmers in the study sites were technically, allocatively and economically inefficient. The mean technical, allocative and economic efficiency indices were 19.9%, 68.8% and 12.9% respectively. In this regard, the study confirms the hypothesis that on average, smallholder chicken farmers were economically inefficient leading to the conclusion that there is considerable scope to improve chicken production and productivity through improving economic efficiency in input allocation and use. It is therefore, recommended that scaling up of the introduced chicken strains must be integrated with technical knowledge to ensure efficiency improves in keeping the introduced chicken strains. Moreover, actors in the poultry subsector should create better market information systems for efficient input procurement and sale of outputs.en_US
dc.language.isoen_USen_US
dc.publisherInternational Scholars Journalsen_US
dc.subjectEconomic Efficiencyen_US
dc.subjectStochastic DEAen_US
dc.subjectChicken Strainsen_US
dc.subjectFarm levelen_US
dc.titleTechnical, allocative and economic efficiencies of keeping newly introduced chicken strains among smallholder farmers in selected areas of Tanzania: an application of stochastic data envelopment analysis approachen_US
dc.typeArticleen_US


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