dc.description.abstract | Different models have been used in analysing agricultural data to establish level of agricultural
productivity given various factors including land size, use of inputs, use of extension and modern
technology, labour, capital etc. A few researchers have tried to understand farmers‟ attitudes towards
farming and how this affects their on-farm practice
A TNS Global farmers‟ study in Tanzania funded by Bill and Melinda Gates 2011- focused on farmer
agricultural productivity using a mix of Simple Regression and descriptive analysis based on the
various factors of production. Findings showed that the more the farmers spent resources appropriately
on factors that affect productivity; correct use of inputs, timeliness in land preparation, planting and
input application etc, the better there land productivity. But those who actually improved on-farm
practice were less than 50% of the target population, yet the entire population was exposed to the same
treatment by the project. This is definitely an interesting result. One would wish to understand why the
success rate is that low
In this study, I have used the TNS data to try and understand if farmers‟ attitude towards farming has a
relation with their positive change in practice which would likely increase production. I attempted
extraction of attitudinal constructs using factor analysis. Factor analysis on 43 likert-scale questions
about farmer‟s attitudes was performed in order to obtain farmers‟ attitudinal segments. Six factors
corresponding to different themes of farmer attitudes were obtained. These are Information focus,
Negative-don‟t tell me to change, status quo is safer‟, Change orientation, Passive dependence,
Heritage-„Farming is my destiny‟, Resigned unhappiness- „No hope to improve so would prefer to be
something else‟. Then used regression analysis to assess the impact of various other observable
variables on the attitudinal segmentation, which revealed a positive relationship between farmer
attitudes and their level of agricultural productivity with the more positive, information focused farmers
showing energies to perform well while the negative ones who have somewhat not very good attitude
not performing very well. On average an increase in the covariates studied here reinforced positive
attitudes and lowered scores for the negative attitudes. The analysis presented in this thesis forms a
basis for further research into the impact different attitudes have on farmers‟ productivity. | en_US |