The logic I aim to establish is rooted in utility theory, which suggests that utility maximisation can motivate farmers to adopt new technologies. In some countries, however, the adoption of new technologies remains low. Many studies attribute this to a lack of awareness regarding their economic benefits. To evaluate these benefits, specific indicators of economic sustainability were selected. If the hypothesis is validated—demonstrating that these technologies provide economic advantages for farmers—it would suggest that adopting them enables farmers to achieve higher utility compared to non-adopters. Consequently, this would not only reinforce the utility theory framework but also contribute to economic sustainability while advancing several Sustainable Development Goals (SDGs).
Does this logical framework seem correct, or could additional elements be included to strengthen it further?
Your framework structure is well-placed, indeed. However, I feel like it is a little bit limited on an economic basis only. Are you talking about large-scale farmers only, or does it also include small-scale farmers?
If it is all types of farmers, I think it would be better to include non-economic factors as well.
Thank you very much for the reply. As the country has only 93% small farmers and rest is medium and large. So i will adopt random sampling. Can you propose some non-economic indicator as you mentioned i also should consider including and please give an idea how to relate them with this study?
My apologies my first answer came out wrong. Well, I was suggesting instead of only limiting the problem to be lack of awareness of the economic benefits by farmers regarding the adaptation of new technologies, you could also add the socio-economic elements like the perception of the farmers regarding the new technologies which can be influenced by age, gender and also culture. (Just a suggestion)
But overall, your framework is really good!
Your question was very interesting and i even am thinking about that. About socio demographic, information and perception related variables will be included. But when in the literature its stating that adoption can enhance benefit like yield and production cost but after analysing you find no yield change impact then you cant prove hypothesis. Or you dont have actial yield data because farmers dont tell truth about input use and yield. So in these cases how to framework.
Sounds interesting. Hope that the Q would go deep into some specific & effective new tech (e.g. crop variety, pesticide, machine etc.) without proper application, that more practical parameters can be measured and evaluated before and after adoption. Or specific Agro scene can be focused (e.g. Orchard, paddy field, herd and so on).
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