Amos-based risk forecast of manufacturing supply chain

Abstract

Manufacturing supply chain is vulnerable to various risks, because of its complex network structure, as well as the strong sensitivity of manufacturing to the dynamic market changes. Therefore, the management of supply chain risks has become the focus of manufacturers. To help Chinese enterprises reduce or eliminate supply chain risks, this paper puts forward several hypotheses and a risk forecast model for manufacturing through theoretical analysis. By the Amos method, the hypotheses were tested through path analysis with empirical data. Finally, an artificial neural network (ANN) was adopted to verify the effectiveness of the proposed Amos model. The study provides the reference for preventing supply chain risks and promoting the healthy development of manufacturing enterprises.