Coherence, Specification and Effectiveness of Agricultural Innovation Systems in Benin
Asian Journal of Agricultural Extension, Economics & Sociology · pp. 1–11 · Published 23 Oct 2019
10.9734/ajaees/2019/v36i330247Abstract
Aims: This paper explores possible approaches of assessing the effectiveness of AIS with the main hypothesis that ex ante analysis of advisory service systems integrating local perspectives can help for early evaluation of their chance of success. Study Design: The AIS developed by the Cotton Boosting Project and the District Center for Agricultural Promotion were selected as case studies in Bembereke District in Northern Benin. We focused on advisory services provided by these institutions to farmers to better cope with soil fertility decline and the mortality of small ruminants. Methodology: We constructed an analytical framework based on organizational theories of agricultural services, structured around the concepts of level of (i) intern and extern coherence, (ii) specification and (iii) effectiveness of AIS. We conducted systematic field observations and semi-structured interviews with farmers and agricultural projects leaders to collect qualitative data on the components of AIS, their level of accuracy, the relations between these components, their appropriateness with the intervention contexts, farmers’ perceptions and satisfactions. Results: The AIS we investigated displayed lack of coherence between objectives, services provided, human and material resources deployed and assets of targeted groups. Specific characteristics of the intervention environment such as rick factor were not often sufficiently considered by project leaders. Objectives and target groups were the less specified components. The low levels of harmony and accuracy between/of the components of the AIS were proportional to their unsatisfactory level of achieved performance, displayed by the persistence of soil degradation and the mortality of small ruminants. Conclusion: The levels of coherence and specification between/of the components of AIS can tell a lot about its probable level of effectiveness. Such an ex ante analysis may complement usual approaches used to assess the effectiveness of AIS.
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