Conducting agricultural research impact study amounts to an attempt to measure the effects of research outputs on
research objects or end-users. Several reasons can be given to support the need for the conduct of agricultural technology impact studies by or for an organization. One, agricultural research/adoption impact study provides information for policy makers and agricultural research funding agencies.
Two, the transfer of research-induced technology to farmers is the only way to measure research benefits to society. Thus, studies must measure technology adoption rate with diligent accuracy.
Three, agricultural research impact study provides feedback to scientists on which technologies or technology components are successful at farm levels, and what adjustments to the technologies are required at the research end.
Questionnaire was administered to 50 adopters and 50 non- adopters of the selected technology. In this regard, and because of the uncertainty of the diffusion of each technology among the end users, it was agreed to purposively produce separate lists (sample frames) of all adopters and non-adopters, from which samples of 50 respondents each were randomly obtained.
The study conducted economic and social impact assessment of some of the technologies generated and diffused by the NARIs over the 1997-2008 period. The economic impact assessment was undertaken using the Economic surplus method.
For the social impact component, other levels of analysis (the frequency classifications of the adoption profiles, assessments of
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the ease of adoption of the various technologies, the assessment of the risks associated with technology adoption, beneficiary assessments and the logit analysis of technology adoption decisions), which sought to understand adoption behaviour and beneficiary assessments of the respondents, were undertaken.
The results presented were derived from the Akino-Hayami model. This model allows the decomposition of the total (social) gains from innovation between consumers and producers.
The analysis for the relevant technologies was undertaken under scenarios of inelastic and elastic demand for each commodity.
All analysis was premised on a typical inelastic commodity supply value. The scenarios of elastic demand for food crops were analyzed merely for comparisons with the more likely scenarios of inelastic food demand.
All results presented cover the period 1997 to 2008, except that the technologies deferred in terms of their years of release for adoption. In all situations, the total gains to society from each technology are the sum of the gains to the consumers and producers.