Analyzing the Antecedents and Consequences of Artificial Intelligence Technologies Adoption in supply chain: A Meta -synthesis approach

Artificial intelligence has been introduced as one of the most revolutionary technologies of the last few decades as an effective solution in the field of improving complex issues such as supply chains and distribution networks of materials and products. Therefore, the aim of the present study is to identify the antecedents and consequences of adopting artificial intelligence technology in the field of improving and strengthening the distribution network using the meta-synthesis technique of various meta-study methods. In the present study, the researcher analyzed the results and findings of previous researchers using a systematic review and qualitative meta-synthesis approach and coded the effective factors by performing the seven steps of the Sandelowski and Barroso method. By identifying the antecedents and consequences of adopting artificial intelligence technology, a conceptual model was classified into ۲ categories, ۱۶ factors, and ۱۲۱ components. The antecedents include: organizational factors, environmental factors, technological factors, human factors, institutional factors, economic factors, and environmental factors, and the consequences include: communication consequences, knowledge consequences, experiential consequences, financial consequences, product consequences, workforce consequences, organizational consequences, supply chain consequences, and environmental consequences. The results of this study indicate ۱۶ general and comprehensive factors in reputable studies of the past ten years on the adoption of artificial intelligence and its consequences. After studying and examining, it was found that different researchers, each emphasizing specific factors, introduced the antecedents and consequences of the adoption of artificial intelligence technology. Most of the reviewed articles emphasized organizational factors and human factors.

کلیدواژه ها:

Artificial intelligence ، supply chain ، logistics chain ، qualitative research ، Meta-synthesis approach