IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i5p1084-d1149507.html
   My bibliography  Save this article

Precision Farming: Barriers of Variable Rate Technology Adoption in Italy

Author

Listed:
  • Margherita Masi

    (Department of Veterinary Medical Science, University of Bologna—Alma Mater Studiorum, 40064 Bologna, Italy)

  • Jorgelina Di Pasquale

    (Department of Veterinary Medicine, University of Teramo, 64100 Teramo, Italy)

  • Yari Vecchio

    (Department of Veterinary Medical Science, University of Bologna—Alma Mater Studiorum, 40064 Bologna, Italy)

  • Fabian Capitanio

    (Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80121 Napoli, Italy)

Abstract

Research dealing with the adoption of various precision agriculture technologies has shown that guidance and recording tools are more widespread than reactive ones (such as variable rate technology), with much lower utilization rates in European case studies. This study aims to analyze the propensity to innovate variable rate technologies among young Italian farmers. A cluster analysis was carried out revealing four groups. The first two groups represent non-adopters who think technological innovation is very complex from a technical point of view, as well as not very accessible as capital-intensive technology. The third and fourth groups represent adopters. The third reports an early level of adoption, still considering the cost of access a major barrier to technology implementation. The fourth, on the other hand, shows a more intensive level and considers the lack of institutional support a major limitation. The cluster with the most intensive adoption is characterized by the youngest age group, the farms with the largest size, and a prevalence of female entrepreneurs. The need for management training in day-to-day business operations upon adoption is detected for all groups. This paper identified relevant drivers and barriers in characterizing the adopting farm of variable rate technologies. Results may offer insights to the policy maker to better calibrate support interventions.

Suggested Citation

  • Margherita Masi & Jorgelina Di Pasquale & Yari Vecchio & Fabian Capitanio, 2023. "Precision Farming: Barriers of Variable Rate Technology Adoption in Italy," Land, MDPI, vol. 12(5), pages 1-16, May.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:5:p:1084-:d:1149507
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/5/1084/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/12/5/1084/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Isik, Murat & Khanna, Madhu, 2002. "Uncertainty and spatial variability: incentives for variable rate technology adoption in agriculture," Risk, Decision and Policy, Cambridge University Press, vol. 7(3), pages 249-265, December.
    2. Roberts, Roland K. & English, Burton C. & Larson, James A. & Cochran, Rebecca L. & Goodman, W. Robert & Larkin, Sherry L. & Marra, Michele C. & Martin, Steven W. & Shurley, W. Donald & Reeves, Jeanne , 2004. "Adoption of Site-Specific Information and Variable-Rate Technologies in Cotton Precision Farming," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 36(1), pages 1-16, April.
    3. Kotsiri, Sofia & Rejesus, Roderick M. & Marra, Michele C. & Velandia, Margarita M., 2011. "Farmers' Perceptions about Spatial Yield Variability and Precision Farming Technology Adoption: An Empirical Study of Cotton Production in 12 Southeastern States," 2011 Annual Meeting, February 5-8, 2011, Corpus Christi, Texas 98689, Southern Agricultural Economics Association.
    4. SOTO Iria & BARNES Andrew & BALAFOUTIS Athanasios & BECK Bert & SANCHEZ FERNANDEZ Berta & VANGEYTE Jurgen & FOUNTAS Spyros & VAN DER WAL Tamme & EORY Vera & GOMEZ BARBERO Manuel, 2019. "The contribution of precision agriculture technologies to farm productivity and the mitigation of greenhouse gas emissions in the EU," JRC Research Reports JRC112505, Joint Research Centre.
    5. Sunding, David & Zilberman, David, 2001. "The agricultural innovation process: Research and technology adoption in a changing agricultural sector," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 4, pages 207-261, Elsevier.
    6. Madhu Khanna, 2001. "Sequential Adoption of Site-Specific Technologies and its Implications for Nitrogen Productivity: A Double Selectivity Model," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(1), pages 35-51.
    7. Donika MALOKU, 2020. "Adoption Of Precision Farming Technologies: Usa And Eu Situation," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 22, pages 7-14, May.
    8. Hanson, Erik D. & Cossette, Max K. & Roberts, David C., 2022. "The adoption and usage of precision agriculture technologies in North Dakota," Technology in Society, Elsevier, vol. 71(C).
    9. Schimmelpfennig, David, 2016. "Farm Profits and Adoption of Precision Agriculture," Economic Research Report 249773, United States Department of Agriculture, Economic Research Service.
    10. Barnes, A.P. & Soto, I. & Eory, V. & Beck, B. & Balafoutis, A. & Sánchez, B. & Vangeyte, J. & Fountas, S. & van der Wal, T. & Gómez-Barbero, M., 2019. "Exploring the adoption of precision agricultural technologies: A cross regional study of EU farmers," Land Use Policy, Elsevier, vol. 80(C), pages 163-174.
    11. Marco Medici & S?ren Marcus Pedersen & Giacomo Carli & Maria Rita Tagliaventi, 2019. "Environmental Benefits of Precision Agriculture Adoption," Economia agro-alimentare, FrancoAngeli Editore, vol. 21(3), pages 637-656.
    12. Robert Finger & Scott M. Swinton & Nadja El Benni & Achim Walter, 2019. "Precision Farming at the Nexus of Agricultural Production and the Environment," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 313-335, October.
    13. Margherita Masi & Marcello Rosa & Yari Vecchio & Luca Bartoli & Felice Adinolfi, 2022. "The long way to innovation adoption: insights from precision agriculture," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-17, December.
    14. Vecchio, Yari & De Rosa, Marcello & Adinolfi, Felice & Bartoli, Luca & Masi, Margherita, 2020. "Adoption of precision farming tools: A context-related analysis," Land Use Policy, Elsevier, vol. 94(C).
    15. Schimmelpfennig, David & Ebel, Robert, 2016. "Sequential Adoption and Cost Savings from Precision Agriculture," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(1), pages 1-19, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Concetta Cardillo & Luca Bartoli & Marcello De Rosa & Martina Francescone & Margherita Masi & Hanae Sahir & Yari Vecchio, 2024. "Exploring Diversification Strategies among Italian Farms," Sustainability, MDPI, vol. 16(20), pages 1-13, October.
    2. Beata Michaliszyn-Gabryś & Joachim Bronder & Wanda Jarosz & Janusz Krupanek, 2024. "Potential of Eco-Weeding with High-Power Laser Adoption from the Farmers’ Perspective," Sustainability, MDPI, vol. 16(6), pages 1-26, March.
    3. Marilena Gemtou & Konstantina Kakkavou & Evangelos Anastasiou & Spyros Fountas & Soren Marcus Pedersen & Gohar Isakhanyan & Kassa Tarekegn Erekalo & Serafin Pazos-Vidal, 2024. "Farmers’ Transition to Climate-Smart Agriculture: A Systematic Review of the Decision-Making Factors Affecting Adoption," Sustainability, MDPI, vol. 16(7), pages 1-34, March.
    4. Alyssa Schmidt & Kevan W. Lamm & Abigail Borron & Alexa J. Lamm, 2024. "Examining the Relationship between Geographic Groupings and Perspective of Critical Community Issues: An Audience Segmentation Analysis," Land, MDPI, vol. 13(5), pages 1-20, May.
    5. Beata Michaliszyn-Gabryś & Joachim Bronder & Janusz Krupanek, 2024. "Social Life Cycle Assessment of Laser Weed Control System: A Case Study," Sustainability, MDPI, vol. 16(6), pages 1-28, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Hanson, Erik D. & Cossette, Max K. & Roberts, David C., 2022. "The adoption and usage of precision agriculture technologies in North Dakota," Technology in Society, Elsevier, vol. 71(C).
    3. Alfons Weersink & Murray Fulton, 2020. "Limits to Profit Maximization as a Guide to Behavior Change," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 67-79, March.
    4. Wang, Tong & Jin, Hailong & Sieverding, Heidi & Kumar, Sandeep & Miao, Yuxin & Rao, Xudong & Obembe, Oladipo & Mirzakhani Nafchi, Ali & Redfearn, Daren & Cheye, Stephen, 2023. "Understanding farmer views of precision agriculture profitability in the U.S. Midwest," Ecological Economics, Elsevier, vol. 213(C).
    5. Vecchio, Yari & Di Pasquale, Jorgelina & Del Giudice, Teresa & Pauselli, Gregorio & Masi, Margherita & Adinolfi, Felice, 2022. "Precision farming: what do Italian farmers really think? An application of the Q methodology," Agricultural Systems, Elsevier, vol. 201(C).
    6. Madhu Khanna, 2021. "Digital Transformation of the Agricultural Sector: Pathways, Drivers and Policy Implications," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(4), pages 1221-1242, December.
    7. Johannes Munz & Heinrich Schuele, 2022. "Influencing the Success of Precision Farming Technology Adoption—A Model-Based Investigation of Economic Success Factors in Small-Scale Agriculture," Agriculture, MDPI, vol. 12(11), pages 1-21, October.
    8. Späti, Karin & Huber, Robert & Finger, Robert, 2021. "Benefits of Increasing Information Accuracy in Variable Rate Technologies," Ecological Economics, Elsevier, vol. 185(C).
    9. Nathan D. DeLay & Nathanael M. Thompson & James R. Mintert, 2022. "Precision agriculture technology adoption and technical efficiency," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 195-219, February.
    10. 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).
    11. Madhu Khanna & Shady S. Atallah & Saurajyoti Kar & Bijay Sharma & Linghui Wu & Chengzheng Yu & Girish Chowdhary & Chinmay Soman & Kaiyu Guan, 2022. "Digital transformation for a sustainable agriculture in the United States: Opportunities and challenges," Agricultural Economics, International Association of Agricultural Economists, vol. 53(6), pages 924-937, November.
    12. Ingram, Julie & Maye, Damian & Bailye, Clive & Barnes, Andrew & Bear, Christopher & Bell, Matthew & Cutress, David & Davies, Lynfa & de Boon, Auvikki & Dinnie, Liz & Gairdner, Julian & Hafferty, Caitl, 2022. "What are the priority research questions for digital agriculture?," Land Use Policy, Elsevier, vol. 114(C).
    13. Oksana Hrynevych & Miguel Blanco Canto & Mercedes Jiménez García, 2022. "Tendencies of Precision Agriculture in Ukraine: Disruptive Smart Farming Tools as Cooperation Drivers," Agriculture, MDPI, vol. 12(5), pages 1-15, May.
    14. Michels, Marius & von Hobe, Cord-Friedrich & Mußhoff, Oliver, 2020. "Understanding the Adoption of Drones in German Agriculture," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305579, German Association of Agricultural Economists (GEWISOLA).
    15. 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).
    16. Yari Vecchio & Marcello De Rosa & Gregorio Pauselli & Margherita Masi & Felice Adinolfi, 2022. "The leading role of perception: the FACOPA model to comprehend innovation adoption," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-19, December.
    17. Michels, Marius & von Hobe, Cord-Friedrich & Mußhoff, Oliver, 2020. "Understanding the Adoption of Drones in German Agriculture," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305579, German Association of Agricultural Economists (GEWISOLA).
    18. DeLay, Nathan & Comstock, Haden, 2021. "Recent Trends in PA Technology Adoption and Bundling in CornProduction: Implications for Farm Consolidation," Western Economics Forum, Western Agricultural Economics Association, vol. 19(2), December.
    19. Iordanis Parikoglou & Grigorios Emvalomatis & Fiona Thorne, 2022. "Precision livestock agriculture and productive efficiency: The case of milk recording in Ireland," Agricultural Economics, International Association of Agricultural Economists, vol. 53(S1), pages 109-120, November.
    20. Kangogo, Daniel & Dentoni, Domenico & Bijman, Jos, 2021. "Adoption of climate‐smart agriculture among smallholder farmers: Does farmer entrepreneurship matter?," Land Use Policy, Elsevier, vol. 109(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:12:y:2023:i:5:p:1084-:d:1149507. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.