چکیده مقاله
The purpose of this study is to examine the role of artificial intelligence AI in enhancing supply chain resilience through predictive and adaptive approaches in risk management This research is applied and quantitative in nature, utilizing structural equation modeling PLS SEM Data were collected from 300 supply chain managers and specialists across various industries in Iran, and analyses were performed using Smart PLS 4 software The results revealed that AI’s predictive and adaptive capabilities have a significant positive impact on risk management and supply chain resilience Moreover, risk management partially mediates the relationship between AI and resilience Findings indicate that adaptive AI capabilities exert the strongest overall effect on supply chain resilience β = 0 54 The simultaneous use of predictive and adaptive approaches can transform organizations into intelligent, dynamic, and resilient supply chains This study provides empirical and practical evidence for managers to design and implement proactive and adaptive decision making processes in supply chains using AI technologies
کلیدواژهها
نویسندگان
Zahra Foroutanfar
Department of Chemistry, Shahreza Branch, Islamic Azad University, Shahreza, Iran
شیوه ارجاع
Foroutanfar, Zahra,1404,Supply Chain Resilience Through Artificial Intelligence: Predictive And Adaptive Approaches In Risk Management,7h International Conference on Humanities, Educational Sciences, Law and Social Sciences
ارائهشده در
مجموعه مقالات هفتمین کنفرانس بین المللی علوم انسانی، علوم آموزشی، حقوق و علوم اجتماعی30 آبان 1404