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Farmer preferences for adopting precision farming technologies: a case study from Italy

Author

Listed:
  • J Blasch
  • B van der Kroon
  • P van Beukering
  • R Munster
  • S Fabiani
  • P Nino
  • S Vanino

Abstract

Precision farming (PF) technologies can help to mitigate the environmental impact of agriculture by reducing fertiliser use and irrigation while saving cost for the farmer. However, these technologies are not widely adopted in Europe. We study farmers’ willingness to adopt PF technologies based on a choice experiment. Among other determinants, we explore the role of social influence for the valuation of PF technology features. The data are analysed using mixed and latent class logit models. Our results show that knowledge of fellow farmers who adopted the technology positively influences the valuation of PF technology features, stressing the importance of networks.

Suggested Citation

  • J Blasch & B van der Kroon & P van Beukering & R Munster & S Fabiani & P Nino & S Vanino, 2022. "Farmer preferences for adopting precision farming technologies: a case study from Italy," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(1), pages 33-81.
    • Handle: RePEc:oup:erevae:v:49:y:2022:i:1:p:33-81.
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    3. Maiti, Moinak, 2022. "Does improvement in green growth influence the development of environmental related technology?," Innovation and Green Development, Elsevier, vol. 1(2).
    4. Robert Finger, 2023. "Digital innovations for sustainable and resilient agricultural systems," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(4), pages 1277-1309.
    5. Passarelli, Mariacarmela & Bongiorno, Giuseppe & Cucino, Valentina & Cariola, Alfio, 2023. "Adopting new technologies during the crisis: An empirical analysis of agricultural sector," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    6. Osrof, Hazem Yusuf & Tan, Cheng Ling & Angappa, Gunasekaran & Yeo, Sook Fern & Tan, Kim Hua, 2023. "Adoption of smart farming technologies in field operations: A systematic review and future research agenda," Technology in Society, Elsevier, vol. 75(C).
    7. Huber, Robert & Späti, Karin & Finger, Robert, 2023. "A behavioural agent-based modelling approach for the ex-ante assessment of policies supporting precision agriculture," Ecological Economics, Elsevier, vol. 212(C).
    8. Luong, Tuan, 2023. "Network resilience and risk attitudes: Evidence from Vietnamese Vegetable Farming," 97th Annual Conference, March 27-29, 2023, Warwick University, Coventry, UK 334556, Agricultural Economics Society - AES.
    9. Stefania Troiano & Matteo Carzedda & Francesco Marangon, 2023. "Better richer than environmentally friendly? Describing preferences toward and factors affecting precision agriculture adoption in Italy," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-15, December.
    10. Ursula Ploll & Miguel Arato & Jan Börner & Monika Hartmann, 2022. "Sustainable Innovations: A Qualitative Study on Farmers’ Perceptions Driving the Diffusion of Beneficial Soil Microbes in Germany and the UK," Sustainability, MDPI, vol. 14(10), pages 1-23, May.
    11. Lehberger, Mira & Gruener, Sven, 2023. "(Why) Do farmers’ Big Five personality traits matter? – A systematic literature review," OSF Preprints jbx4p, Center for Open Science.

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