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

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Abstract

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.

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Acknowledgements

The authors thank the editor and anonymous reviewers for their constructive comments on an earlier version of this paper. This work on meta-analysis also benefited from discussions with Jacqueline Ho of RCSI UCD Malaysia Campus.

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  1. Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor, Malaysia

    Yeong Sheng Tey

  2. The University of Adelaide, Urrbrae, South Australia, 5064, Australia

    Mark Brindal

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Tey, Y.S., Brindal, M. A meta-analysis of factors driving the adoption of precision agriculture. Precision Agric 23, 353–372 (2022). https://doi.org/10.1007/s11119-021-09840-9

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