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<p>Sorghum, a drought-tolerant crop, has been cultivated in sub-Saharan Africa (SSA) for many decades. However, the considerable variation in adoption rates and the fact that it is not adopted or even dis-adopted in certain areas require a deeper understanding. This scoping review examines the state of knowledge on the socio-economic factors influencing sorghum adoption based on 52 empirical studies in SSA and explores the extent to which these results differ by methodology. The statistically significant results were mixed, making it difficult to determine the most effective predictors of sorghum adoption. This indicates that the effect of a particular variable depends on the context of use, the location of the study, and the measurement methods employed. In addition, several biases related to the analytical models were identified, including biases in adoption analysis, heterogeneity in decision-making, small sample size bias, non-independence of observations, multicollinearity, and endogeneity. Critical gaps include the need for further analysis of dis-adopters and gender-specific decision-making within households during the adoption process.</p>

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What do we know, and what are we missing from sorghum adoption studies in sub-Saharan Africa? A scoping review

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月18日

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  • Kennedy Vaati Mutuku,
  • Stijn Speelman,
  • Mary Orinda,
  • Calleb Olweny,
  • Marijke D’Haese

摘要

Sorghum, a drought-tolerant crop, has been cultivated in sub-Saharan Africa (SSA) for many decades. However, the considerable variation in adoption rates and the fact that it is not adopted or even dis-adopted in certain areas require a deeper understanding. This scoping review examines the state of knowledge on the socio-economic factors influencing sorghum adoption based on 52 empirical studies in SSA and explores the extent to which these results differ by methodology. The statistically significant results were mixed, making it difficult to determine the most effective predictors of sorghum adoption. This indicates that the effect of a particular variable depends on the context of use, the location of the study, and the measurement methods employed. In addition, several biases related to the analytical models were identified, including biases in adoption analysis, heterogeneity in decision-making, small sample size bias, non-independence of observations, multicollinearity, and endogeneity. Critical gaps include the need for further analysis of dis-adopters and gender-specific decision-making within households during the adoption process.