IDEAS home Printed from https://ideas.repec.org/a/oup/erevae/v49y2022i1p33-81..html
   My bibliography  Save this article

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.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/erae/jbaa031
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Schimmelpfennig, David & Ebel, Robert, 2011. "On the Doorstep of the Information Age: Recent Adoption of Precision Agriculture," Economic Information Bulletin 291945, United States Department of Agriculture, Economic Research Service.
    2. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    3. Oriana Bandiera & Imran Rasul, 2006. "Social Networks and Technology Adoption in Northern Mozambique," Economic Journal, Royal Economic Society, vol. 116(514), pages 869-902, October.
    4. Timothy Conley & Udry Christopher, 2001. "Social Learning Through Networks: The Adoption of New Agricultural Technologies in Ghana," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 668-673.
    5. Maheswari, R. & Ashok, K.R. & Prahadeeswaran, M., 2008. "Precision farming technology, adoption decisions and productivity of vegetables in resource-poor environments," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 21(Conferenc).
    6. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    8. Khanna, Madhu & Zilberman, David, 1997. "Incentives, precision technology and environmental protection," Ecological Economics, Elsevier, vol. 23(1), pages 25-43, October.
    9. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    10. Athanasios Balafoutis & Bert Beck & Spyros Fountas & Jurgen Vangeyte & Tamme Van der Wal & Iria Soto & Manuel Gómez-Barbero & Andrew Barnes & Vera Eory, 2017. "Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics," Sustainability, MDPI, vol. 9(8), pages 1-28, July.
    11. Paxton, Kenneth W. & Mishra, Ashok K. & Chintawar, Sachin & Roberts, Roland K. & Larson, James A. & English, Burton C. & Lambert, Dayton M. & Marra, Michele C. & Larkin, Sherry L. & Reeves, Jeanne M. , 2011. "Intensity of Precision Agriculture Technology Adoption by Cotton Producers," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 40(1), pages 1-12, April.
    12. Riccardo Scarpa & Mara Thiene & Tiziano Tempesta, 2007. "Latent class count models of total visitation demand: days out hiking in the eastern Alps," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 38(4), pages 447-460, December.
    13. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    14. Edward Morey & Jennifer Thacher & William Breffle, 2006. "Using Angler Characteristics and Attitudinal Data to Identify Environmental Preference Classes: A Latent-Class Model," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 34(1), pages 91-115, May.
    15. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, October.
    16. Brouwer, Roy & Lienhoop, Nele & Oosterhuis, Frans, 2015. "Incentivizing afforestation agreements: Institutional-economic conditions and motivational drivers," Journal of Forest Economics, Elsevier, vol. 21(4), pages 205-222.
    17. Madhu Khanna & Onesime Faustin Epouhe & Robert Hornbaker, 1999. "Site-Specific Crop Management: Adoption Patterns and Incentives," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 21(2), pages 455-472.
    18. Enikő Lencsés & István Takács & Katalin Takács-György, 2014. "Farmers’ Perception of Precision Farming Technology among Hungarian Farmers," Sustainability, MDPI, vol. 6(12), pages 1-14, November.
    19. Schimmelpfennig, David, 2016. "Farm Profits and Adoption of Precision Agriculture," Economic Research Report 249773, United States Department of Agriculture, Economic Research Service.
    20. 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.
    21. McBride, William D. & Daberkow, Stan G., 2003. "Information And The Adoption Of Precision Farming Technologies," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 21(1), pages 1-18.
    22. Albert Moerkerken & Julia Blasch & Pieter Beukering & Erik Well, 2020. "A new approach to explain farmers’ adoption of climate change mitigation measures," Climatic Change, Springer, vol. 159(1), pages 141-161, March.
    23. Ebel, Robert M. & Schimmelpfennig, David E., 2011. "The Information Age and Adoption of Precision Agriculture," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, pages 1-1.
    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. Douadia Bougherara & Lea Gosset & Raphaële Préget & Sophie Thoyer, 2023. "Innovativeness, innovation adoption and priming: Nudging farmers in a large-scale randomized experiment in France," Post-Print hal-04227775, HAL.
    2. 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.
    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.

    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. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    2. 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.
    3. Danny Campbell & W. Hutchinson & Riccardo Scarpa, 2008. "Incorporating Discontinuous Preferences into the Analysis of Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 41(3), pages 401-417, November.
    4. Balogh, Péter & Török, Áron & Czine, Péter & Horváth, Péter, 2020. "A fogyasztói magatartás elemzése feltételes választási modellekkel - a mangalicakolbász példáján [Analysing consumer behaviour with conditional choice models, with Mangalica sausage as an example]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 474-494.
    5. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    6. Jinsoo Hwang & Seong Ok Lyu & Sun-Bai Cho, 2019. "In-Flight Casinos, Is It Really a Nonsensical Idea? An Exploratory Approach Using Different Choice Experiments," Sustainability, MDPI, vol. 11(11), pages 1-16, May.
    7. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    8. Solomon Tarfasa & Roy Brouwer, 2013. "Estimation of the public benefits of urban water supply improvements in Ethiopia: a choice experiment," Applied Economics, Taylor & Francis Journals, vol. 45(9), pages 1099-1108, March.
    9. 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).
    10. Hackbarth, André & Madlener, Reinhard, 2016. "Willingness-to-pay for alternative fuel vehicle characteristics: A stated choice study for Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 89-111.
    11. Stine Broch & Suzanne Vedel, 2012. "Using Choice Experiments to Investigate the Policy Relevance of Heterogeneity in Farmer Agri-Environmental Contract Preferences," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 51(4), pages 561-581, April.
    12. Chad M. Baum & Robert Weigelt, 2019. "How Where I Shop Influences What I Buy: The Importance of the Retail Format in Sustainable Tomato Consumption," Economic Complexity and Evolution, in: Andreas Chai & Chad M. Baum (ed.), Demand, Complexity, and Long-Run Economic Evolution, pages 141-169, Springer.
    13. Alessandro Mengoni & Chiara Seghieri & Sabina Nuti, 2013. "The application of discrete choice experiments in health economics: a systematic review of the literature," Working Papers 201301, Scuola Superiore Sant'Anna of Pisa, Istituto di Management.
    14. Julia Blasch & Mehdi Farsi, 2012. "Retail demand for voluntary carbon offsets - A choice experiment among Swiss consumers," IED Working paper 12-18, IED Institute for Environmental Decisions, ETH Zurich.
    15. Eric Ruto & Guy Garrod & Riccardo Scarpa, 2008. "Valuing animal genetic resources: a choice modeling application to indigenous cattle in Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 89-98, January.
    16. Giacomo Giannoccaro & Ruggiero Sardaro & Rossella de Vito & Luigi Roselli & Bernardo C. de Gennaro, 2020. "Politiche di gestione della risorsa idrica sotterranea a fini irrigui. Analisi delle preferenze degli agricoltori," Economia agro-alimentare, FrancoAngeli Editore, vol. 22(2), pages 1-27.
    17. Joan L. Walker & Moshe Ben-Akiva, 2011. "Advances in Discrete Choice: Mixture Models," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 8, Edward Elgar Publishing.
    18. Yang, Chih-Wen & Sung, Yen-Ching, 2010. "Constructing a mixed-logit model with market positioning to analyze the effects of new mode introduction," Journal of Transport Geography, Elsevier, vol. 18(1), pages 175-182.
    19. Ida, Takanori & Goto, Rei, 2009. "Interdependency among addictive behaviours and time/risk preferences: Discrete choice model analysis of smoking, drinking, and gambling," Journal of Economic Psychology, Elsevier, vol. 30(4), pages 608-621, August.
    20. Teferi, Ermias Tesfaye & Kassie, Girma T. & Pe, Mario Enrico & Fadda, Carlo, 2020. "Are farmers willing to pay for climate related traits of wheat? Evidence from rural parts of Ethiopia," Agricultural Systems, Elsevier, vol. 185(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:oup:erevae:v:49:y:2022:i:1:p:33-81.. 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/eaaeeea.html .

    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.