| 000 | 01116cam a2200181 4500500 | ||
|---|---|---|---|
| 005 | 20260322005559.0 | ||
| 041 | _afre | ||
| 042 | _adc | ||
| 100 | 1 | 0 |
_aHarfouche, Antoine _eauthor |
| 700 | 1 | 0 |
_aSaba, Peter _eauthor |
| 700 | 1 | 0 |
_aTite, Thrycia _eauthor |
| 245 | 0 | 0 | _aEthical, informed, and explainable AI (EIX-AI) in the face of fluctuations in agricultural demand |
| 260 | _c2026. | ||
| 500 | _a48 | ||
| 520 | _aThis research, conducted as part of the “GreenMinds AI” project, examines the integration of ethical, informed, and explainable artificial intelligence (EIX-AI) into agricultural supply chains, with a specific focus on the Lebanese context. Drawing on Design Science Research and the Kano model, the study demonstrates that EIX-AI enables the reconciliation of performance, ethics, and sustainability, while enhancing user adoption through explanatory tools such as SHAP and LIME. | ||
| 786 | 0 | _nRevue française de gestion | 326 | 1 | 2026-02-18 | p. 51-73 | 0338-4551 | |
| 856 | 4 | 1 | _uhttps://shs.cairn.info/journal-revue-francaise-de-gestion-2026-1-page-51?lang=en&redirect-ssocas=7080 |
| 999 |
_c1749639 _d1749639 |
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