Document Type : Original Article
Authors
1 Nothing
2 دانشگاه آزاد قم
3 دانشگاه آزاد تهران جنوب
Abstract
Nowadays, supply chain management has become more important due to the globalization of business markets. As complexity increases, the level of uncertainty and risk in the chain also increases. Therefore, supply chain risk management is one of the issues that has received attention from organizations. Digital transformation in the supply chain is associated with benefits such as improved efficiency, increased transparency, and accelerated processes, but at the same time it also brings with it numerous risks such as cyber threats, technology dependency, and organizational resilience. This research presents an empirical model for assessing the risks of digital transformation in a sustainable supply chain using backpropagation neural network (BPNN). Research data is collected from 120 companies active in manufacturing and logistics industries, and the model is evaluated with RMSE, MAE, and classification accuracy criteria. The results show that the proposed model is able to predict the level of digital risk with 93% accuracy. Sensitivity analysis also shows that cybersecurity has the greatest impact (coefficient 0.45) on the overall risk.
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