A meta-analysis of factors driving the adoption of precision agriculture

Using a literature pool spanning 23 years, this meta-analysis quantifies the effect of factors underlying the adoption of precision agriculture. Unlike statistical significance, which demonstrates how likely adoption is due to chance, effect size indicates the importance of a factor to adoption. This meta-analysis finds that perceived profitability, consultants and use of a computer factors have a moderate effect. However, the findings should not be regarded as definitive because of issues of sample size and heterogeneity embedded in a number of the reference studies. This latter point is re-enforced by observation of other factors that had a negligible effect on adoption. Whether future studies will provide meaningful policy implications depend on a careful understanding and selection of factors, models, and statistical treatment in relation to decision-making paths and their context.