Determinants for adopting agricultural innovations by rice farmers in the north-west region of Cameroon

Gaston G. Ngochembo, Roland A. Balgah, Mathias F. Fonteh


The importance of adopting agricultural innovations for farm productivity is well known. However, the rate of adoption is generally sub-optimal.  This study investigates the determinants for adopting agricultural innovations by rice farmers in the North West Region of Cameroon. A multi-stage sampling technique was employed to identify and collect data from 800 rice farmers in Ngoketunjia division, the most important rice-producing area in Bamenda Highlands agro-ecological zone in that region of Cameroon. A structured and pretested questionnaire was used to catalogue technologies available to rice farmers and factors that might influence their adoption. Descriptive statistics were used to analyze the adoption of available technologies, and binary logistic regression to identify key determinants for their adoption. Rice farmers adopted eight of the twenty-one technologies identified. The results showed that ten of the thirty-three variables tested in the regression analysis significantly influenced the adoption of innovations by rice farmers. Household size, farm size, level of motivation, number of extension visits, and the ongoing socio-political crisis had statistically significant and positive influence while, type of labour use, qualified personnel or hired labour, innovation institutions, property rights, and social norms affected innovations adoption negatively. Based on these results, it has been recommended that major rice-producing institutions in the study area should consolidate the positive drivers while addressing the negative ones. Given that the regression model explained less than 50% of the factors influencing technology adoption in the area, future research should expand the list of independent variables so that generated results could be of greater relevance to policy-makers interested in improving rice production in the study area. 


Innovation; Adoption; Technologies; Factors; Regression


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DOI: 10.33687/ijae.010.02.4083


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