Factors shaping innovative behavior: A meta-analysis of technology adoption studies in agriculture

Abstract

This study conducts a meta-regression analysis to synthesize the marginal effects of 12 factors that frequently appear in empirical studies examining farmer's technology adoption behavior. The analysis includes 187 observational studies on technology adoption in agriculture, which are published in 32 peer-reviewed journals in the broader field of agricultural economics, covering farmer's adoption in 47 countries for a diverse range of agricultural technologies. Using this broad meta-dataset, we investigate whether each of the 12 determinants has a true effect on technology adoption rates and examine whether Type I and Type II publication bias are present in the adoption literature. Our results reveal that while most determinant factors significantly affect adoption rates, their marginal effects are generally of small magnitude and vary considerably by technology type and country group. Additionally, our results provide evidence of the presence of Type I publication bias in half of the factors considered and Type II publication bias in nearly all, underscoring the need for caution when interpreting results in the adoption literature by researchers and policymakers. Overall, the findings highlight the critical need for proactive measures to address publication bias and promote more transparent and credible research practices in agricultural economics.