Examining the interplay between artificial intelligence and the agri-food industry
Artificial intelligence (AI) has advanced at an astounding rate and transformed numerous economic sectors. Nevertheless, a comprehensive understanding of how AI can improve the agri-food industry is lacking. In addition, there is a notable dearth of research on AI that investigates the influence of...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2022-01-01
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| Series: | Artificial Intelligence in Agriculture |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589721722000095 |
| _version_ | 1828090606809776128 |
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| author | Abderahman Rejeb Karim Rejeb Suhaiza Zailani John G. Keogh Andrea Appolloni |
| author_facet | Abderahman Rejeb Karim Rejeb Suhaiza Zailani John G. Keogh Andrea Appolloni |
| author_sort | Abderahman Rejeb |
| collection | DOAJ |
| description | Artificial intelligence (AI) has advanced at an astounding rate and transformed numerous economic sectors. Nevertheless, a comprehensive understanding of how AI can improve the agri-food industry is lacking. In addition, there is a notable dearth of research on AI that investigates the influence of AI on agri-food resources and educates practitioners on the significance of knowledge-based and smart agriculture. We utilised bibliometric analysis to investigate the present state of the art and emerging trends in the relationship between AI and the agri-food industry. The research identified three distinct growth phases and the most prevalent AI strategies in the industry. In addition, we analysed key trends and offered researchers and practitioners insightful recommendations for future research. Using resource-based view (RBV) as the theoretical lens, this study established a framework emphasising the long-term effects of AI on various agri-food resources and proposed several research propositions. In addition, AI-related obstacles have been identified and categorised into four major categories. Lastly, the originality of the article lies in its numerous research suggestions and recommendations for advancing the AI field in the agri-food industry. |
| first_indexed | 2024-04-11T06:00:28Z |
| format | Article |
| id | doaj.art-0be4e52ce1ca4214922459fbabe8052e |
| institution | Directory Open Access Journal |
| issn | 2589-7217 |
| language | English |
| last_indexed | 2024-04-11T06:00:28Z |
| publishDate | 2022-01-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Artificial Intelligence in Agriculture |
| spelling | doaj.art-0be4e52ce1ca4214922459fbabe8052e2022-12-22T04:41:42ZengKeAi Communications Co., Ltd.Artificial Intelligence in Agriculture2589-72172022-01-016111128Examining the interplay between artificial intelligence and the agri-food industryAbderahman Rejeb0Karim Rejeb1Suhaiza Zailani2John G. Keogh3Andrea Appolloni4Department of Management and Law, Faculty of Economics, University of Rome Tor Vergata, Via Columbia, 2, Rome 00133, Italy; Corresponding author.Faculty of Sciences of Bizerte, University of Carthage, Tunis, TunisiaDepartment of Management, Faculty of Business and Economics, University Malaya, Kuala Lumpur, 50203, MalaysiaHenley Business School, University of Reading, Greenlands, Henley-on-Thames RG9 3AU, UKDepartment of Management and Law, Faculty of Economics, University of Rome Tor Vergata, Via Columbia, 2, Rome 00133, ItalyArtificial intelligence (AI) has advanced at an astounding rate and transformed numerous economic sectors. Nevertheless, a comprehensive understanding of how AI can improve the agri-food industry is lacking. In addition, there is a notable dearth of research on AI that investigates the influence of AI on agri-food resources and educates practitioners on the significance of knowledge-based and smart agriculture. We utilised bibliometric analysis to investigate the present state of the art and emerging trends in the relationship between AI and the agri-food industry. The research identified three distinct growth phases and the most prevalent AI strategies in the industry. In addition, we analysed key trends and offered researchers and practitioners insightful recommendations for future research. Using resource-based view (RBV) as the theoretical lens, this study established a framework emphasising the long-term effects of AI on various agri-food resources and proposed several research propositions. In addition, AI-related obstacles have been identified and categorised into four major categories. Lastly, the originality of the article lies in its numerous research suggestions and recommendations for advancing the AI field in the agri-food industry.http://www.sciencedirect.com/science/article/pii/S2589721722000095Artificial intelligenceAgricultureFarmingMachine learningDeep learningBibliometric analysis |
| spellingShingle | Abderahman Rejeb Karim Rejeb Suhaiza Zailani John G. Keogh Andrea Appolloni Examining the interplay between artificial intelligence and the agri-food industry Artificial Intelligence in Agriculture Artificial intelligence Agriculture Farming Machine learning Deep learning Bibliometric analysis |
| title | Examining the interplay between artificial intelligence and the agri-food industry |
| title_full | Examining the interplay between artificial intelligence and the agri-food industry |
| title_fullStr | Examining the interplay between artificial intelligence and the agri-food industry |
| title_full_unstemmed | Examining the interplay between artificial intelligence and the agri-food industry |
| title_short | Examining the interplay between artificial intelligence and the agri-food industry |
| title_sort | examining the interplay between artificial intelligence and the agri food industry |
| topic | Artificial intelligence Agriculture Farming Machine learning Deep learning Bibliometric analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2589721722000095 |
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