Evaluating logistic regression and geographically weighted logistic regression models for predicting orange-fleshed sweet potato adoption intention in Benin.

ABSTRACT: The low adoption rate of biofortified crops, like orange-fleshed sweet potatoes (OFSP), by farmers remains a major food security concern. Accurate forecasting models for OFSP adoption intention are essential for breeding and introduction projects. This study aims to (i) identify key predictors of OFSP adoption intention among farmers in Benin, integrating various factors, and (ii) investigate regional variations in these predictors through different modeling approaches. We used a diverse set of predictors, including social, geographical, and psychological constructs, to model adoption intention in different sweet potato production areas in Benin. Both logistic regression (LR) and geographically weighted logistic regression (GWLR) models were developed and assessed. The GWLR model significa

SUBMITTER: Ahoudou I 

PROVIDER: S-EPMC11909162 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature