Vol. 14 No. 4 (2025)
Full Research Articles

Agriculture 4.0: Technological adoption, drivers, benefits and challenges in Italy. A descriptive survey

PDF Supplementary Materials
  • Cosimo Pacciani,
  • Eleonora Catellani,
  • Andrea Bacchetti,
  • Chiara Corbo,
  • Federica Ciccullo,
  • Marco Ardolino
Cosimo Pacciani
Department of Management Engineering, Politecnico di Milano, Via Lambruschini, 4b 20156 - Milano, Italy
Eleonora Catellani
Department of Management Engineering, Politecnico di Milano, Via Lambruschini, 4b 20156 - Milano, Italy
Andrea Bacchetti
Department of Mechanical and Industrial Engineering, University of Brescia, Via Brianze, 38 25123 - Brescia, Italy
Chiara Corbo
Department of Management Engineering, Politecnico di Milano, Via Lambruschini, 4b 20156 - Milano, Italy
Federica Ciccullo
Department of Management Engineering, Politecnico di Milano, Via Lambruschini, 4b 20156 - Milano, Italy
Marco Ardolino
Department of Mechanical and Industrial Engineering, University of Brescia, Via Brianze, 38 25123 - Brescia, Italy
DOI: https://doi.org/10.36253/bae-17382

Published 2025-07-14

Keywords

  • agriculture 4.0,
  • smart farming,
  • digital agriculture,
  • survey

How to Cite

Pacciani, C., Catellani, E., Bacchetti, A., Corbo, C., Ciccullo, F., & Ardolino, M. (2025). Agriculture 4.0: Technological adoption, drivers, benefits and challenges in Italy. A descriptive survey. Bio-Based and Applied Economics, 14(4), 101–119. https://doi.org/10.36253/bae-17382

Copyright (c) 2025 Cosimo Pacciani, Eleonora Catellani, Andrea Bacchetti, Chiara Corbo, Federica Ciccullo, Marco Ardolino

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Crossref
Scopus
Google Scholar
Europe PMC

Abstract

This study aims to examine the current state of awareness regarding Agriculture 4.0 (A4.0) among Italian agricultural enterprises and to analyse variations in adoption levels, expressed needs, perceived benefits, challenges and barriers to digitalisation. Drawing on data from a descriptive survey conducted among Italian farms in 2024, this study presents findings from 1,248 respondents. The results indicate varying levels of adoption of A4.0 solutions, with monitoring systems and connected vehicles being the most widely implemented. The primary drivers for A4.0 adoption include farm management, operational control, and the enhancement of production efficiency, all of which are associated with significant perceived benefits. However, challenges such as limited interoperability and skill shortages hinder A4.0 implementation, while financial and structural constraints remain major barriers for farms seeking to transition to A4.0. This study offers valuable insights to inform policymakers, industry stakeholders, and researchers in fostering a more effective and inclusive digital transformation in the Italian agricultural sector.

PDF Supplementary Materials

References

  1. Abbasi, R., Martinez, P., and Ahmad, R. (2022). The Digitization of Agricultural Industry – a Systematic Literature Review on Agriculture 4.0. Smart Agricultural Technology, 2: 100042. https://doi.org/10.1016/j.atech.2022.100042.
  2. Addorisio, R., Casolani, N., Maesano, G., Coderoni, S., Perito, M.A., Mattetti, M., Canavari, M., 2025. Barriers and drivers of digital agriculture adoption: Insights from Italian farming stakeholders. https://doi.org/10.18461/ijfsd.v16i1o1
  3. Ahmed, B., Shabbir, H., Naqvi, S. R., and Peng, L. (2024). Smart Agriculture: Current State, Opportunities, and Challenges. IEEE Access, 12: 144456-78. https://doi.org/10.1109/ACCESS.2024.3471647.
  4. Albiero, D., De Paulo, R. L., Felix Junior, J. C., Da Silva Gomes Santos, J., and Melo, R. P. (2020). Agriculture 4.0: A Terminological Introduction. Revista Ciência Agronômica, 51(5). https://doi.org/10.5935/1806-6690.20200083.
  5. Araújo, S. O., Peres, R. S., Barata, J., Lidon, F., and Ramalho, J. C. (2021). Characterising the Agriculture 4.0 Landscape - Emerging Trends, Challenges and Opportunities. Agronomy, 11(4): 667. https://doi.org/10.3390/agronomy11040667.
  6. Assimakopoulos, F., Vassilakis, C., Margaris, D., Kotis, K., and Spiliotopoulos, D. (2024). The Implementation of “Smart” Technologies in the Agricultural Sector: A Review. Information, 15(8): 466. https://doi.org/10.3390/info15080466.
  7. Balasundram, S. K., Shamshiri, R. R., Sridhara, S., and Rizan, N. (2023). The Role of Digital Agriculture in Mitigating Climate Change and Ensuring Food Security: An Overview. Sustainability, 15(6): 5325. https://doi.org/10.3390/su15065325.
  8. Balyan, S., Jangir, H., Tripathi, S. N., Tripathi, A., Jhang, T., and Pandey, P. (2024). Seeding a Sustainable Future: Navigating the Digital Horizon of Smart Agriculture. Sustainability, 16(2): 475. https://doi.org/10.3390/su16020475.
  9. Bongiovanni, R., and Lowenberg-Deboer, J. (2004). Precision Agriculture and Sustainability. Precision Agriculture, 5: 359-387. https://doi.org/10.1023/B:PRAG.0000040806.39604.aa.
  10. Bokusheva, R., and S. Kimura (2016). Cross-Country Comparison of Farm Size Distribution. OECD Food, Agriculture and Fisheries Papers, No. 94, OECD Publishing, Paris. https://doi.org/10.1787/5jlv81sclr35-en
  11. Cambra Baseca, C., Sendra, S., Lloret, J., and Tomas, J. (2019). A Smart Decision System for Digital Farming. Agronomy, 9(5): 216. https://doi.org/10.3390/agronomy9050216.
  12. Cisilino, F., Licciardo, F., 2022. Potential and Complexity of Implementing Financial Instruments in the Framework of Rural Development Policies in Italy – The Friuli Venezia Giulia Revolving Fund. Sustainability 14, 16090. https://doi.org/10.3390/su142316090
  13. Da Silveira, F., Da Silva, S. L. C., Machado, F. M., Barbedo, J. G. A., and Amaral, F. G. (2023). Farmers’ Perception of the Barriers That Hinder the Implementation of Agriculture 4.0. Agricultural Systems, 208: 103656. https://doi.org/10.1016/j.agsy.2023.103656.
  14. Da Silveira, F., Lermen, F. H., and Amaral, F. G. (2021). An Overview of Agriculture 4.0 Development: Systematic Review of Descriptions, Technologies, Barriers, Advantages, and Disadvantages. Computers and Electronics in Agriculture, 189: 106405. https://doi.org/10.1016/j.compag.2021.106405.
  15. Dayıoğlu, M., and Turker, U. (2021). Digital Transformation for Sustainable Future - Agriculture 4.0: A Review. Tarım Bilimleri Dergisi, 27. https://doi.org/10.15832/ankutbd.986431.
  16. Escribà-Gelonch, M., Liang, S., Van Schalkwyk, P., Fisk, I., Van Duc Long, N., and Hessel, V. (2024). Digital Twins in Agriculture: Orchestration and Applications. Journal of Agricultural and Food Chemistry, 72(19): 10737-52. https://doi.org/10.1021/acs.jafc.4c01934.
  17. Fragomeli, R., Annunziata, A., and Punzo, G. (2024). Promoting the Transition towards Agriculture 4.0: A Systematic Literature Review on Drivers and Barriers. Sustainability, 16(6): 2425. https://doi.org/10.3390/su16062425.
  18. Gabriel, A., Gandorfer, M., 2023. Adoption of digital technologies in agriculture – an inventory in a European small-scale farming region. Precision Agric 24, 68-91.
  19. Gebbers, R., and Adamchuk, V. (2010). Precision Agriculture and Food Security. Science, 327(5967): 828-31. https://doi.org/10.1126/science.1183899.
  20. Giampietri, E., Yu, X. and Trestini, S. (2020). The role of trust and perceived barriers on farmer’s intention to adopt risk management tools. Bio-based and Applied Economics, 9(1): 1-24. https://doi.org/10.13128/bae-8416.
  21. Giorgio, A., Penate Lopez, L.P., Bertoni, D., Cavicchioli, D., Ferrazzi, G., 2024. Enablers to Digitalization in Agriculture: A Case Study from Italian Field Crop Farms in the Po River Valley, with Insights for Policy Targeting. Agriculture 14, 1074. https://doi.org/10.3390/agriculture14071074
  22. Giua, C., Materia V., and Camanzi, L. (2022). Smart Farming Technologies Adoption: Which Factors Play a Role in the Digital Transition?. Technology in Society 68: 101869. https://doi.org/10.1016/j.techsoc.2022.101869
  23. Gonzales-Gemio, C., and Sanz-Martín, L. (2025). Socioeconomic Barriers to the Adoption of Carbon Farming in Spain, Italy, Egypt, and Tunisia: An Analysis Based on the Diffusion of Innovations Model. Journal of Cleaner Production 498: 145155. https://doi.org/10.1016/j.jclepro.2025.145155
  24. Javaid, M., Haleem, A., Singh, R. P., and Suman, R. (2022). Enhancing Smart Farming through the Applications of Agriculture 4.0 Technologies. International Journal of Intelligent Networks, 3: 150-64. https://doi.org/10.1016/j.ijin.2022.09.004.
  25. Jin, X. B., Yu, X. H., Wang, X. Y., Bai, Y. T., Su, T. L., and Kong, J. L. (2020). Deep Learning Predictor for Sustainable Precision Agriculture Based on Internet of Things System. Sustainability, 12(4): 1433. https://doi.org/10.3390/su12041433.
  26. Khanna, M. et al. (2024) ‘Economics of the Adoption of Artificial Intelligence–Based Digital Technologies in Agriculture’, Annual Review of Resource Economics, 16(1), 41-61. https://doi.org/10.1146/annurev-resource-101623-092515.
  27. Klerkx, L. and Rose, D. (2020) ‘Dealing with the game-changing technologies of Agriculture 4.0: How do we manage diversity and responsibility in food system transition pathways?’, Global Food Security, 24, 100347. Available at: https://doi.org/10.1016/j.gfs.2019.100347.
  28. Kumar Kasera, R., Gour, S., and Acharjee, T. (2024). A Comprehensive Survey on IoT and AI Based Applications in Different Pre-Harvest, during-Harvest and Post-Harvest Activities of Smart Agriculture. Computers and Electronics in Agriculture, 216: 108522. https://doi.org/10.1016/j.compag.2023.108522.
  29. Lezoche, M. et al. (2020). Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture. Computers in Industry, 117, 103187. https://doi.org/10.1016/j.compind.2020.103187.
  30. Maffezzoli, F., Ardolino, M., and Bacchetti, A. (2022a). The Impact of the 4.0 Paradigm in the Italian Agricultural Sector: A Descriptive Survey. Applied Sciences, 12(18): 9215. https://doi.org/10.3390/app12189215.
  31. Maffezzoli, F., Ardolino, M., Bacchetti, A., Perona, M., and Renga, F. (2022b). Agriculture 4.0: A Systematic Literature Review on the Paradigm, Technologies and Benefits. Futures, 142: 102998. https://doi.org/10.1016/j.futures.2022.102998.
  32. Meemken, E.-M. et al. (2024). Digital innovations for monitoring sustainability in food systems. Nature Food, 5(8), 656-660. https://doi.org/10.1038/s43016-024-01018-6.
  33. Menozzi, D., Fioravanzi, M. and Donati, M. (2015). Farmer’s motivation to adopt sustainable agricultural practices. Bio-based and Applied Economics, 4(2): 125-147 Pages. https://doi.org/10.13128/bae-14776.
  34. Mhlanga, D. and Ndhlovu, E. (2023). Digital Technology Adoption in the Agriculture Sector: Challenges and Complexities in Africa. In: Human Behavior and Emerging Technologies. Edited by Z. Yan, 2023, pp. 1–10. Available at: https://doi.org/10.1155/2023/6951879.
  35. Mühl, D.D. and De Oliveira, L. (2022). A bibliometric and thematic approach to agriculture 4.0. Heliyon, 8(5), e09369. https://doi.org/10.1016/j.heliyon.2022.e09369.
  36. Oliveira, L. F. P., Moreira, A. P., and Silva, M. F. (2021). Advances in Agriculture Robotics: A State-of-the-Art Review and Challenges Ahead. Robotics, 10(2): 52. https://doi.org/10.3390/robotics10020052.
  37. Onyenekwe, C.S. et al. (2023). Heterogeneity of adaptation strategies to climate shocks: Evidence from the Niger Delta region of Nigeria. Bio-based and Applied Economics, 12(1), 17-35. https://doi.org/10.36253/bae-13436.
  38. Papadopoulos, G., Arduini, S., Uyar, H., Psiroukis, V., Kasimati, A., and Fountas, S. (2024). Economic and Environmental Benefits of Digital Agricultural Technologies in Crop Production: A Review. Smart Agricultural Technology, 8, 100441. https://doi.org/10.1016/j.atech.2024.100441
  39. Peladarinos, N., Piromalis, D., Cheimaras, V., Tserepas, E., Munteanu, R. A., and Papageorgas, P. (2023). Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review. Sensors, 23(16), 7128. https://doi.org/10.3390/s23167128
  40. Pierce, F. J., and Nowak, P. (1999). Aspects of Precision Agriculture. Advances in Agronomy, 67, 1-85. https://doi.org/10.1016/S0065-2113(08)60513-1
  41. Polymeni, S., Plastras, S., Skoutas, D. N., Kormentzas, G., and Skianis, C. (2023). The Impact of 6G-IoT Technologies on the Development of Agriculture 5.0: A Review. Electronics, 12(12), 2651. https://doi.org/10.3390/electronics12122651
  42. Pradel, M., De Fays, M., and Seguineau, C. (2022). Comparative Life Cycle Assessment of Intra-Row and Inter-Row Weeding Practices Using Autonomous Robot Systems in French Vineyards. Science of The Total Environment, 838, 156441. https://doi.org/10.1016/j.scitotenv.2022.156441
  43. Rose, D. C., Wheeler, R., Winter, M., Lobley M., Chivers, C. (2021). Agriculture 4.0: Making it work for people, production, and the planet. Land Use Policy, 100. https://doi.org/10.1016/j.landusepol.2020.104933
  44. Rotz, S., Gravely, E., Mosby, I., Duncan, E., Finnis, E., Horgan, M., LeBlanc, J., Martin, R., Tait Neufeld, H., Nixon, A., Pant, L., Shall, V., Fraser, E. (2019). Automated pastures and the digital divide: How agricultural technologies are shaping labour and rural communities. Journal of Rural Studies, 68, 112-122. https://doi.org/10.1016/j.jrurstud.2019.01.023
  45. Sharma, V., Tripathi, A. K., and Mittal, H. (2022). Technological Revolutions in Smart Farming: Current Trends, Challenges and Future Directions. Computers and Electronics in Agriculture, 201, 107217. https://doi.org/10.1016/j.compag.2022.107217
  46. Sott, M. K., Furstenau, L. B., Kipper, L. M., Giraldo, F. D., Lopez-Robles, J. R., Cobo, M. J., Zahid, A., Abbasi, Q. H., and Imran, M. A. (2020). Precision Techniques and Agriculture 4.0 Technologies to Promote Sustainability in the Coffee Sector: State of the Art, Challenges and Future Trends. IEEE Access, 8, 149854–67. https://doi.org/10.1109/ACCESS.2020.3016325
  47. Sozzi, M., Ahmed, K., Ferrari, G., Zanchin, A., Grigolato, S., and Marinello, F. (2021). Connectivity in rural areas: A case study on internet connection in the Italian agricultural areas. IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), Trento-Bolzano, Italy, 466-470. https://doi.org/10.1109/MetroAgriFor52389.2021.9628665
  48. Sponchioni, G., Vezzoni, M., Bacchetti, A., Pavesi, M., and Renga, F. (2019). The 4.0 revolution in agriculture: A multi-perspective definition. XXIV Summer School “Francesco Turco” – Indust Syst Eng, 1, 143–149.
  49. van Selm, M., and Jankowski, N. W. (2006). Conducting Online Surveys. Quality and Quantity, 40, 435-456. https://doi.org/10.1007/s11135-005-8081-8
  50. Yousaf, A., Kayvanfar, V., Mazzoni, A., and Elomri, A. (2023). Artificial Intelligence-Based Decision Support Systems in Smart Agriculture: Bibliometric Analysis for Operational Insights and Future Directions. Frontiers in Sustainable Food Systems, 6, 1053921. https://doi.org/10.3389/fsufs.2022.1053921
  51. Zhai, Z., Martínez, J. F., Beltran, V., and Martínez, N. L. (2020). Decision Support Systems for Agriculture 4.0: Survey and Challenges. Computers and Electronics in Agriculture, 170, 105256. https://doi.org/10.1016/j.compag.2020.105256
  52. Zul Azlan, Z., Hazim, Z. F., Junaini, S. N., Bolhassan, N. A., Wahi, R., and Arip, M. A. (2024). Harvesting a Sustainable Future: An Overview of Smart Agriculture’s Role in Social, Economic, and Environmental Sustainability. Journal of Cleaner Production, 434, 140338. https://doi.org/10.1016/j.jclepro.2023.140338

Most read articles by the same author(s)