Theoretical Foundations for Assessing Self-Driving Tractors Among Kenyan Smallholder Wheat Farmers: An Impact Analysis on Yields

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Hauptverfasser: Ngugi, Omondi, Ogot, Njoroge, Wanjiku, Timbuku, Muthoni, Kanju
Format: Recurso digital
Sprache:Englisch
Veröffentlicht: Zenodo 2012
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author Ngugi, Omondi
Ogot, Njoroge
Wanjiku, Timbuku
Muthoni, Kanju
author_facet Ngugi, Omondi
Ogot, Njoroge
Wanjiku, Timbuku
Muthoni, Kanju
contents <p>Self-driving tractors are increasingly adopted by smallholder farmers in Kenyan wheat cultivation regions to enhance productivity and efficiency. Theoretical analysis will be employed to develop a comprehensive model that considers factors such as tractor technology characteristics, farmer training programmes, and post-adoption support systems. The theoretical framework proposed provides a solid foundation for understanding how technology adoption can be harnessed to boost smallholder farming efficiency, particularly in contexts where traditional methods are labour-intensive and yield-restricted. Further empirical research should validate these theoretical insights by monitoring the long-term impacts of self-driving tractors on both productivity and sustainability across different wheat cultivation regions in Kenya.</p>
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language eng
publishDate 2012
publisher Zenodo
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spellingShingle Theoretical Foundations for Assessing Self-Driving Tractors Among Kenyan Smallholder Wheat Farmers: An Impact Analysis on Yields
Ngugi, Omondi
Ogot, Njoroge
Wanjiku, Timbuku
Muthoni, Kanju
Kenya
Geospatial Analysis
Participatory Research
GIS
Precision Agriculture
<p>Self-driving tractors are increasingly adopted by smallholder farmers in Kenyan wheat cultivation regions to enhance productivity and efficiency. Theoretical analysis will be employed to develop a comprehensive model that considers factors such as tractor technology characteristics, farmer training programmes, and post-adoption support systems. The theoretical framework proposed provides a solid foundation for understanding how technology adoption can be harnessed to boost smallholder farming efficiency, particularly in contexts where traditional methods are labour-intensive and yield-restricted. Further empirical research should validate these theoretical insights by monitoring the long-term impacts of self-driving tractors on both productivity and sustainability across different wheat cultivation regions in Kenya.</p>
title Theoretical Foundations for Assessing Self-Driving Tractors Among Kenyan Smallholder Wheat Farmers: An Impact Analysis on Yields
topic Kenya
Geospatial Analysis
Participatory Research
GIS
Precision Agriculture
url https://doi.org/10.5281/zenodo.18945580