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The Effects of Individual Variables, Farming System Characteristics and Perceived Barriers on Actual Use of Smart Farming Technologies: Evidence from the Piedmont Region, Northwestern Italy

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  • Federica Caffaro

    (Institute for Agricultural and Earthmoving Machines (IMAMOTER) of the National Research Council (CNR) of Italy, Strada delle Cacce 73, 10135 Torino, Italy)

  • Eugenio Cavallo

    (Institute for Agricultural and Earthmoving Machines (IMAMOTER) of the National Research Council (CNR) of Italy, Strada delle Cacce 73, 10135 Torino, Italy)

Abstract

Smart Farming Technologies (SFTs) have a real potential to deliver more productive and sustainable agricultural production. However, limited empirical research is available on the role played by objective and subjective factors in the adoption of such disruptive innovations, especially in the Italian context. This study investigated the role of education, farm size, being a sole farmer, and perceived barriers in affecting the use of SFTs in a sample of Italian farmers from the Piedmont region (North-West Italy). Three hundred and ten farming operators were questioned via a paper-and-pencil questionnaire. The analyses showed that low levels of education and working on-farm alone were positively associated with perceived economic barriers, which in turn were negatively associated with the adoption of SFTs. Farm size had a positive direct effect on SFT adoption. The results pointed out the need for targeted policies and training interventions to encourage the use of SFTs.

Suggested Citation

  • Federica Caffaro & Eugenio Cavallo, 2019. "The Effects of Individual Variables, Farming System Characteristics and Perceived Barriers on Actual Use of Smart Farming Technologies: Evidence from the Piedmont Region, Northwestern Italy," Agriculture, MDPI, vol. 9(5), pages 1-13, May.
    • Handle: RePEc:gam:jagris:v:9:y:2019:i:5:p:111-:d:233686
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    7. Shang, Linmei & Heckelei, Thomas & Gerullis, Maria K. & Börner, Jan & Rasch, Sebastian, 2021. "Adoption and diffusion of digital farming technologies - integrating farm-level evidence and system interaction," Agricultural Systems, Elsevier, vol. 190(C).
    8. Rübcke von Veltheim, Friedrich & Claussen, Frans & Heise, Heinke, 2020. "Autonomous Field Robots in Agriculture: A Qualitative Analysis of User Acceptance According to Different Agricultural Machinery Companies," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305587, German Association of Agricultural Economists (GEWISOLA).
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