Two-stage hybrid model for supplier selection and order allocation considering cyber risk

Abstract

In the context of collaborative manufacturing, cyber risk caused by cyber attacks may lead to severe supply chain disruption. Currently, supplier selection and order allocation is regarded as effective means to mitigate the risks that might cause disruption. Thus, we propose a two-stage hybrid model for supplier selection and order allocation under cyber risk. The hybrid model consists of fuzzy analytical hierarchy process (Fuzzy AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and two-stage mixed integer linear programming (MIP). Based on the extracted cyber risk indicators, a Fuzzy AHP is used to calculate the level of cyber risk of suppliers. TOPSIS is utilized to quantitatively evaluate the cyber risk of suppliers and determine the ranking of suppliers. Then, a two-stage MIP model is developed to support decision-making on order allocation. The first-stage decisions are determined without emergencies, and the second-stage decisions are determined under emergencies. The results reveal that application of the proposed two-stage hybrid model could mitigate the negative impacts of cyber risks. By providing a theoretical basis and quantitative method for cyber risk evaluation, this research is of theoretical and practical significance to the field of supply chain management.

Keywords:

• Collaborative manufacturing
• supplier selection
• order allocation
• cyber risk

Disclosure statement

The authors declare that there are no relevant financial or non-financial competing interests to report in this paper.

Data availability statement

The data that support the findings of this study are available from the corresponding author, Chaochao Liu, upon reasonable request.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the National Key Research and Development Program of China under Grant NO. 2020YFB1712001.