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Subjective preferences for agricultural technology attributes and their influence on technical efficiency of smallholder maize farmers in Nakuru County, Kenya
Dissertation (MSc Agric (Agricultural Economics))--University of Pretoria, 2022.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2022
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| _version_ | 1867613675771133952 |
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| access_status_str | Open Access |
| author2 | Mungatana, Eric D. |
| author_browse | Mungatana, Eric D. |
| author_facet | Mungatana, Eric D. |
| collection | Thesis |
| dc_rights_str_mv | © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MSc Agric (Agricultural Economics))--University of Pretoria, 2022. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/85613 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:39:55.528Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/85613 Subjective preferences for agricultural technology attributes and their influence on technical efficiency of smallholder maize farmers in Nakuru County, Kenya Mungatana, Eric D. mbakazachary@gmail.com Jourdain, Damien Mbaka, Zachary Simba UCTD Technical efficiency Best-worst scaling Farming goals Farming technology Smallholder farmers Principal component analysis (PCA) Cluster analysis Cluster groups Dissertation (MSc Agric (Agricultural Economics))--University of Pretoria, 2022. The study investigates whether the subjective utility of goals driving farmers' technology choices influence technical efficiency, with objectives of improving allocation choices, and providing effective extension services. Main goals of smallholder maize farmers were identified using the best-worst scaling (BWS) approach and efficiency scores generated using stochastic frontier analysis (SFA). A comparison between farming goals and technical efficiency was established using principal component analysis (PCA), cluster analysis, and one-way ANOVA. The study used data collected from 187 randomly selected smallholder maize farmers from Nakuru County, in Kenya. The most crucial goals of farming technology were found to be increasing crop yields, decreasing production costs, and reducing pests and diseases. The least important goals of farming technology were, decreasing on-farm soil erosion, decreasing water requirement through the cropping cycle, and decreasing off-farm pollution. Mean efficiency score was 61% and not statistically significant across the cluster groups, implying that subjective preferences of farming technology do not influence technical efficiency among the group. All coefficients of farming goals were negative when regressed against SFA generated efficiency scores, inferring that current farming technologies lack important farming goals that drive them. The study concluded that subjective utilities of farming goals do not have a significant influence on technical efficiency, contrary to our expectation. we therefore recommend further research to be conducted, to test the robustness of the results and identify reasons for negative and significant relationship between off-farm environmental services and production efficiency. The study is the first one of its kind to relate subjective utility of goals driving farmers’ technology choices and technical efficiency, immensely contribution to the existing literature Borlaug Higher Education for Agricultural Research and Development (BHEARD) Agricultural Economics, Extension and Rural Development MSc Agric (Agricultural Economics) Unrestricted 2022-05-23T07:49:23Z 2022-05-23T07:49:23Z 2022 2022 Dissertation * S2022 https://repository.up.ac.za/handle/2263/85613 en © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Technical efficiency Best-worst scaling Farming goals Farming technology Smallholder farmers Principal component analysis (PCA) Cluster analysis Cluster groups Subjective preferences for agricultural technology attributes and their influence on technical efficiency of smallholder maize farmers in Nakuru County, Kenya |
| title | Subjective preferences for agricultural technology attributes and their influence on technical efficiency of smallholder maize farmers in Nakuru County, Kenya |
| title_full | Subjective preferences for agricultural technology attributes and their influence on technical efficiency of smallholder maize farmers in Nakuru County, Kenya |
| title_fullStr | Subjective preferences for agricultural technology attributes and their influence on technical efficiency of smallholder maize farmers in Nakuru County, Kenya |
| title_full_unstemmed | Subjective preferences for agricultural technology attributes and their influence on technical efficiency of smallholder maize farmers in Nakuru County, Kenya |
| title_short | Subjective preferences for agricultural technology attributes and their influence on technical efficiency of smallholder maize farmers in Nakuru County, Kenya |
| title_sort | subjective preferences for agricultural technology attributes and their influence on technical efficiency of smallholder maize farmers in nakuru county kenya |
| topic | UCTD Technical efficiency Best-worst scaling Farming goals Farming technology Smallholder farmers Principal component analysis (PCA) Cluster analysis Cluster groups |
| url | https://repository.up.ac.za/handle/2263/85613 |