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DC Field | Value | Language |
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dc.contributor.author | Kenduiwa, Angela A. | - |
dc.date.issued | 2016-10 | - |
dc.date.accessioned | 2019-01-24T09:16:40Z | - |
dc.date.available | 2019-01-24T09:16:40Z | - |
dc.identifier.uri | http://41.89.96.81:8080/xmlui/handle/123456789/1325 | - |
dc.description.abstract | The livestock sector is an important component of the Kenyan economy and contributes about 40% of the agricultural Gross Domestic Product (GDP) which is about 10% of the national GDP. Dairy farming sub-sector plays a very significant role in the development of the Kenyan economy due to its impact on the GDP, alleviation of poverty, food security, employment creation and provision of raw materials to milk processors. Over 70% of the dairy farmers in Kenya are smallholders. Lack of credit services has been known to constrain agricultural development among the smallholder farmers in developing countries. Microfinance aims at providing the needed credit services to smallholder farmers. Smallholder farmers in Longisa sub-county, Bomet County have accessed microfinance services since the 1990s. However, the dairy production has been far below the expected potential in the area. The study used a cross sectional survey research design because it allows researchers to collect data from a large sample and to use it in intensive analysis. The smallholder dairy cattle farmers constituted the respondents of the study. A proportionate stratified random sampling method was used to ensure each location was represented. Simple random sampling was used to select 152 respondents for study. The questionnaire used to collect data was developed by the researcher and validated by experts in applied community development. The research instruments were pilot tested to determine the reliability of the instrument in Bomet Central sub-county which neighbours Longisa sub-county. Stratified random sampling was used to select the pretest sample size of 30 smallholder dairy farmers. Using Cronbach's alpha, an index of 0.92 for the questionnaire was established. This implied that the reliability of the instrument was good. Descriptive statistics as well as inferential statistics technique were used to analyse data with the help of Statistical Packages for Social Sciences (SPSS version 20). Simple linear regression was used to determine the influence of the amount of credit accessed on the amount of milk produced. Ordered logistic regression was used to determine the influence of the amount of credit accessed on the breeds kept and animal husbandry while simple linear regression and ordered logistic were used to determine the influence of the amount of credit accessed on the training received by smallholder dairy farmers. To make reliable inferences from the data, all statistical tests were verified at α = 0.05 level of significance. The study revealed that the amount of microfinance credit accessed by smallholder in dairy farming have a significant and positive influence on the amount of milk produced per cow per lactation, the breeds of cattle kept as well as animal husbandry practices in the study area. This study recommends that smallholder dairy farmers should embrace microfinance credit in financing their dairy farming for them to realize higher milk yields. Farmers should also take advantage of the available and upcoming microfinance institutions in their effort to obtain the necessary finances for breed improvement and animal husbandry practices. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Egerton University | en_US |
dc.subject | Microfinance -- Dairy farming | en_US |
dc.title | Influence of smallholder dairy farmers’ participation in microfinance on dairy farming in Longisa Sub-County, Bomet County, Kenya | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Faculty of Education and Community Studies |
Files in This Item:
File | Description | Size | Format | |
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Influence of smallholder dairy farmers’ participation in microfinance on dairy farming in Longisa Sub-County, Bomet County, Kenya.pdf | 2.21 MB | Adobe PDF | View/Open |
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