http://ir.mu.ac.ke:8080/jspui/handle/123456789/36 2026-04-20T14:33:16Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/9683 Factors influencing household participation in extraction of forest products in mount Kenya forest, Nyeri County, Kenya Mwangi, Flora Caroline Forests play a critical role in sustaining rural livelihoods through provision of timber and non-timber forest products for both domestic and commercial use. However, unsustainable extraction of these products threatens the ecological and socio- economic benefits for over two million people who live around the forests, necessitating a deeper understanding of the factors influencing household participation in forest product extraction in Mount Kenya Forest, Nyeri County. This was actualized by testing the null hypothesis that there is no significant relationship between the social, economic, and environmental factors and participation in extraction of forest products based on the theory of tragedy of the commons. The research employed a cross-sectional survey design, utilizing both descriptive and inferential statistics. Data was collected from 361 households living within 10 kilometers radius of the forest through structured questionnaires and analyzed using a binary logistic regression model. Findings indicated that 77% of households engaged in forest resource extraction, with 70.91% utilizing products for both domestic and commercial purposes. Firewood collection was the most common activity (36.01%), followed by lumbering and farming. Socioeconomic characteristics such as household size, income levels, education, and occupation of the respondents significantly influenced forest dependency. Additionally, 61.5% of respondents lacked awareness of sustainable harvesting techniques and forest management policies, contributing to unsustainable practices. Encouragingly, 86% of respondents express willingness to participate in conservation initiatives without monetary compensation, indicating strong potential for community-driven conservation strategies. Social, economic, and environmental factors were found to significantly influence participation with household size, income level, and proximity to the forest (p=0.0000<0.05) emerging as key determinants. The model yielded a pseudo R² of 0.8920, indicating strong explanatory power. Education (β = -0.1090, p =0.002< 0.05) and awareness (β = - 0.0479, p =0.000< 0.05) of forest management practices were found to negatively correlate with extraction, suggesting that increased knowledge and awareness reduces dependence. The study concludes that social, economic, and environmental factors significantly influence household participation. Based on these findings, the study recommends enhanced community sensitization on sustainable resource use through extension officers, alternative livelihood programs and employment of sustainable harvesting techniques such as selective and rotational harvesting. Strengthening forest management policies, promoting agroforestry, and increasing access to clean energy alternatives such as Liquefied Petroleum Gas (LPG) and biogas are essential for reducing forest dependence and ensuring sustainable resource use. Additionally, integrating rural households into conservation efforts through Community Forest Associations (CFAs) can enhance sustainable forest management. These strategies can help balance forest conservation with the livelihood needs of forest-adjacent communities. Further research should explore panel data analysis on forest dependence specifically investigating how forest dependence evolves over time, considering economic growth, conservation policies, and population dynamics. 2025-01-01T00:00:00Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/9682 Factors influencing adoption and intensity of use of artificial insemination technology among farmers in Alego-Usonga Sub-County, Siaya County, Kenya Awuor, Gislar Olwana Artificial Insemination (AI) is a breeding technology that can be used in dairy cows to help in upgrading of the local breeds within their own setting to increase milk production. Despite the positive benefits of A.I technology such as the ability to get superior genes with a capacity to improve milk productivity, the adoption level has been low in Alego-Usonga Sub-county where an observable peak of 40.72% A.I service in 2016 was realized among smallholder dairy farmers. Therefore this study aimed at establishing the factors influencing A.I technology adoption and intensity among smallholder dairy farmers in Alego-Usonga Sub-County. The specific objectives were to determine the effect of Social, Economic, Technical and Institutional factors on adoption of AI technology among smallholder dairy farmers in Alego-Usonga Subcounty. The Innovation Diffusion Theory guided this study. The study area was Alego- Usonga Sub-County, Siaya County, Kenya. The study population was all smallholder dairy farmers in Alego- Usonga Sub-County. Cross-sectional survey design was used in this study. Multistage random sampling techniques was employed to sample 378 dairy farmers from a population of 22965 dairy farmers from the six wards. Structured questionnaires were used to collect primary data. Double Hurdle Model was used analyze factors influencing adoption and intensity of AI technology. Multivariate data analysis was performed using STATA Software. Results of the probit model showed that age of the respondents (β=0.253, p=0.013), education level (β=0.201, p=0.000), experience (β=0.121, p=0.041), milk sales (β=0.001, p=0.003), AI cost (β=0.542, p=0.008), worker’s skill on heat detection (β=0.198, p=0.047), semen type (β=0.345, p=0.000), AI reliability (β=1.862, p=0.000), and availability of the inseminator (β=0.85, p=0.000) positively and significantly influenced AI technology adoption in the study area. On the other hand, only training on livestock production (β=-0.496, p=0.028) negatively and significantly influenced AI technology adoption in the study area. Results of the truncated regression showed that age of the respondents (β=0.05, p=0.000), education level (0.042, p=0.000), experience (β=0.058, p=0.001), and training on livestock production (β=0.056, p=0.009) positively and significantly influenced the intensity of AI technology use in the study area. On the other hand, group membership (β=-0.038, p=0.03), and availability of the inseminator (β=-0.048, p=0.024) negatively and significantly influenced the intensity of AI technology adoption in the study area. The study recommends the introduction of adult learning sessions for farmers in a bid to improve their literacy levels. There is need to conduct training needs assessments before the trainings are carried out so as to capture the farmers’ interest together with the environment. Farmers should also enhance the skills of their workers by allowing them also to attend trainings. The government should step in by subsidizing the cost of AI and funding trainings and workshops as this will encourage many farmers who were unable to take up the technology to adopt it 2025-01-01T00:00:00Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/8232 Analysis of the relationship between selected Macroeconomic variables and carbon Emission in Kenya Njumwa, Gichuki James Climate change and carbon dioxide (CO 2 ) emissions are significant threats to the agricultural sector in Kenya. While the sector is critical to the country's economy, its high demand for agricultural inputs such as fertilizers is contributing to the problem of CO 2 emissions. To address this challenge, it is necessary to understand the nexus between CO 2 emissions and macroeconomic variables. Therefore, this study aimed to analyze the relationships between selected macroeconomic variables and CO 2 emissions in Kenya using the Environmental Kuznets Curve hypothesis as a guiding theory. The study adopted a time series research design, and secondary data from the World Bank Database, Kenya National Bureau of Statistics, and the Environmental Performance Index covering the period from 1983 to 2019 were utilized. To test for unit root factors, the Augmented Dickey-Fuller Test, Phillips-Perron, and Zivot- Andrews tests were employed. The Vector Error Correction Model and Johansen Co- integration analysis were applied to estimate long- and short-run relationships between the study variables. The results showed that during the short run, only Foreign Direct Investment had a statistically significant relationship with CO 2 emissions (z = -6.55, p < 0.05). However, during the long run, all the macroeconomic variables had a statistically significant relationship with CO 2 emissions at p < 0.05. Specifically, the study found an indirect and statistically significant relationship between agricultural output and CO 2 emissions in Kenya during the long run (z = -3.65, p < 0.01). Moreover, Foreign Direct Investment and CO 2 emissions exhibited a direct and statistically significant relationship during the long run (z = 10.61, p < 0.01), while trade openness and CO 2 emissions had an indirect relationship (z = -3.41, p < 0.01). Additionally, inflation and CO 2 emissions had an indirect relationship in Kenya (z = -3.12, p < 0.01). The study concludes that sustainable agricultural practices should be adopted in Kenya to minimize CO 2 emissions in the short run. Additionally, Foreign Direct Investment should be geared towards investing in more efficient agricultural technologies to reduce CO 2 emissions. The findings suggest that policymakers should consider more education and awareness on sustainable agricultural practices that will minimize Carbon dioxide emission even during the short run in Kenya. Additionally, Foreign Direct Investment should be geared towards more efficient technology in agriculture to reduce Carbon dioxide emission in Kenya. Overall, this study contributes to the literature on the relationships between macroeconomic variables and CO 2 emissions in Kenya. The study has some limitations, such as data limitations and potential sources of bias. Nonetheless, the study provides important insights into the links between macroeconomic variables and CO 2 emissions, which can inform policymaking aimed at promoting sustainable development in Kenya. 2023-01-01T00:00:00Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/7922 Determinants of choice of pineapple marketing channels among smallholder farmers in Bureti Sub- County, Kericho County, Kenya Cherotich, Betty Bureti Sub- County in Kericho County has a large concentration of pineapple farmers. The area produces large quantities of pineapples from time to time. Despite producing high quantity pineapples, smallholder farmers in Bureti Sub- County fetch low farm- gate prices, hence low household income. The general objective of this study was to analyze factors affecting choice of pineapple marketing channels among the smallholder farmers in Bureti Sub-County, Kericho County, Kenya. The study was guided by the transaction cost theory and random utility maximization theory. The target population of the study was the smallholder pineapple farmers in Bureti Sub- County. The study utilized a descriptive cross- sectional research design in data collection. The estimated population of pineapple farmers targeted in the study area was 5,940. Multi-stage, proportionate and simple random sampling techniques were employed in the study to select 179 respondents from the four electoral wards. The selected Wards included Kisiara, Chemosot, Tebesonik and Cheboin. Primary data was collected using semi- structured questionnaires. This was supplemented by secondary data using content analysis from different published sources. Data was analyzed using STATA software. Multinomial Logit Model (MNL) was used in this study to analyze variables such as transaction costs, socio- economic and institutional factors of the smallholder pineapple marketing in Bureti Sub- County, Kericho County, Kenya. The results showed that variables that significantly influenced the choice of marketing included; age, gender, household size, education level, price of output, type of transport, group membership, contractual arrangement, extension access, distance to market, negotiation cost and transport cost. Based on the results, determinants of choice of marketing channels were identified to influence the farmers’ decisions in pineapple marketing. It is necessary for the government to make provision for social and economic facilities that would act as incentives especially to smallholder farmers to improve pineapple marketing. The study recommends that the government and other policy makers should advice farmers on the benefits of contract marketing such as reduced marketing search costs and ready market for their pineapple produce. The County government must also promote extension service delivery through modern technologies such social media platforms and promote formation of pineapple marketing groups in order to improve the bargaining power and negotiation skills of smallholder farmers. The existence of transaction costs such as high transport cost could be due to long distances to the selling point and poor road conditions in the study area hence limiting the participation in a marketing channel. Interventions aimed at reducing transaction costs would be possible through proper prioritization of improvement and development of access roads in pineapple growing areas by the county government. The study also recommends that the government and other policy makers must encourage farmers to participate in competitive and lucrative markets as well as choosing appropriate marketing channels such as group markets with high prices. 2023-01-01T00:00:00Z