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All issues Volume 216 (2025) SHS Web Conf., 216 (2025) 01011 References
Open Access
Issue
SHS Web Conf.
Volume 216, 2025
International Conference on the Impact of Artificial Intelligence on Traditional Economic Sectors (ICIAITES 2025)
Article Number 01011
Number of page(s) 9
Section Intelligent Systems and Digital Transformation in Agricultural Economy and Sustainable Development
DOI https://doi.org/10.1051/shsconf/202521601011
Published online 23 May 2025
  1. T.F. dos Santos, A legal approach: artificial intelligence, agribusiness and the 2030 agenda. Observatório de la economía latinoamericana 22, e7892–e7892 (2024) [CrossRef] [Google Scholar]
  2. M. Ardiana, et al., Increasing business eco-efficiency and competitive advantage through the application of green accounting. Buletin Penelitian Sosial Ekonomi Pertanian Fakultas Pertanian Universitas Haluoleo (2023) [Google Scholar]
  3. A. Di Vaio, L. Varriale, L. Trujillo, R. Palladino, Artificial intelligence in the agri-food system: Rethinking sustainable business models in the COVID-19 scenario. Sustainability 12, 4851 (2020). https://doi.org/10.3390/su12124851 [CrossRef] [Google Scholar]
  4. M. Ryan, G. Isakhanyan, B. Tekinerdogan, An interdisciplinary approach to artificial intelligence in agriculture. NJAS: Impact in Agricultural and Life Sciences 95, (2023). https://doi.org/10.1080/27685241.2023.2168568 [CrossRef] [Google Scholar]
  5. S. Vadlamudi, Agri-food system and artificial intelligence: Reconsidering imperishability. Asian Journal of Applied Science and Engineering 7, 125–132 (2018). https://doi.org/10.18034/ajase.v7i1.44 [Google Scholar]
  6. Y. Peng, et al., Riding the waves of artificial intelligence in advancing accounting and its implications for sustainable development goals. Sustainability 15, 7152 (2023). https://doi.org/10.3390/su15097152 [CrossRef] [Google Scholar]
  7. R. Hasan, et al., Managing artificial intelligence in international business: Toward a research agenda on sustainable production and consumption. Thunderbird International Business Review (2024). https://doi.org/10.1002/tie.22228 [Google Scholar]
  8. C. Ganeshkumar, et al., Artificial intelligence in agricultural value chain: Review and future directions. Journal of Agribusiness in Developing and Emerging Economies 11, 436–455 (2021). https://doi.org/10.1108/JADEE-11-2020-0241 [Google Scholar]
  9. A. Cavazza, et al., Artificial intelligence and new business models in agriculture: The "ZERO" case study. Management Decision 61, 1089–1106 (2023). https://doi.org/10.1108/MD-06-2022-0821 [Google Scholar]
  10. A. Cavazza, et al., Artificial intelligence and new business models in agriculture: A structured literature review and future research agenda. British Food Journal 125, 1754–1772 (2023). https://doi.org/10.1108/BFJ-10-2022-0915 [Google Scholar]
  11. Naman, et al., Utilizing artificial intelligence (AI) for sustainable agriculture: Precision farming as a catalyst for environmental conservation. International Journal of Agriculture Extension and Social Development 7, 80–89 (2024) [Google Scholar]
  12. E. Oybek, A. Dilfuza, D. Usmonova, M.G. Abdusamatovna, E.D.B. Ogli, Unlocking the Potential of Blockchain Technology in the Digital Economy: A Comprehensive Analysis of Decentralized Social Networking Platforms, in Proceedings of the International Conference on Next Generation Wired/Wireless Networking (Springer Nature Switzerland, Cham, 2023), pp. 355–364 [Google Scholar]
  13. K.P. Reddy, et al., Farm_era: Precision farming with GIS, AI pest management, smart irrigation, data analytics, and optimized crop planning, in Proceedings of the International Congress on Information and Communication Technology (Springer, 2024), pp. 392–403. https://doi.org/10.1007/978-981-99-2968-0_33 [Google Scholar]
  14. H. Issa, et al., An artificial intelligence (AI)-readiness and adoption framework for agritech firms. Social Science Research Network (SSRN) (2022). https://doi.org/10.2139/ssrn.4278793 [Google Scholar]
  15. K. Šiber Makar, Driven by artificial intelligence (AI) -Improving operational efficiency and competitiveness in business, in Proceedings of the 2023 International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (IEEE, 2023), pp. 1234–1240. https://doi.org/10.23919/MIPRO56727.2023.10124056 [Google Scholar]
  16. V. Muto, et al., Artificial intelligence and the great reset: Impacts and perspectives for Italian SMEs business model innovation. Systems 12, 12 (2024). https://doi.org/10.3390/systems12010012 [Google Scholar]
  17. D. Hernandez, et al., The role of artificial intelligence in sustainable agriculture and waste management: Towards a green future. International Transactions on Artificial Intelligence (ITALIC) 3, 45–59 (2024) [Google Scholar]
  18. K. Joshi, et al., Automation intervention for monitoring agriculture farming scale: A review, in 2023 International Conference on Computing Communication and Networking Technologies (ICCCNT) (IEEE, 2023), pp. 1–5. https://doi.org/10.1109/ICCCNT60038.2023.10241384 [Google Scholar]
  19. G.S. Panesar, et al., Artificial intelligence in business development and agile software, in 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (IEEE, 2022), pp. 652–657. https://doi.org/10.1109/ICACITE53722.2022.9823613 [Google Scholar]
  20. S. Gupta, et al., A case study of artificial intelligence being used to reshape business. International Journal of Electrical Electronics and Computers 6, 18–23 (2021) [Google Scholar]
  21. Y. García-Vera, et al., Automatización de procesos contables mediante inteligencia artificial: Oportunidades y desafíos para pequeños empresarios ecuatorianos. Revista Transdisciplinaria de Estudios Sociales y Tecnológicos 3, 100–115 (2023) [Google Scholar]
  22. W.K. Alazzai, et al., Smart agriculture solutions: Harnessing AI and IoT for crop management. E3S Web of Conferences 452, 01034 (2024). https://doi.org/10.1051/e3sconf/202345201034 [Google Scholar]
  23. N. Tsolakis, et al., Towards AI driven environmental sustainability: An application of automated logistics in container port terminals. International Journal of Production Research 59, 1503–1524 (2021). https://doi.org/10.1080/00207543.2020.1768047 [Google Scholar]
  24. N. Rane, et al., Business intelligence and artificial intelligence for sustainable development: Integrating internet of things, machine learning, and big data analytics for enhanced sustainability. Social Science Research Network (SSRN) (2024). https://doi.org/10.2139/ssrn.4762589 [Google Scholar]
  25. V. Sáiz-Rubio, F. Rovira-Más, From smart farming towards agriculture 5.0: A review on crop data management. Agronomy 10, 207 (2020). https://doi.org/10.3390/agronomy10020207 [CrossRef] [Google Scholar]
  26. J.L. Tingey-Holyoak, J.D. Pisaniello, P. Buss, Embedding smart technologies in accounting to meet global irrigation challenges. Meditari Accountancy Research 29, 1146–1178 (2021) [CrossRef] [Google Scholar]
  27. A. Ghandar, et al., A dynamic data driven application system to manage urban agricultural ecosystems in smart cities, in 2018 International Conference on Universal Village (IEEE, 2018), pp. 1–6. https://doi.org/10.1109/UV.2018.8642120 [Google Scholar]

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