Due to the impact of globalization, companies have extended their borders across nations to launch products more competitively. However, globalization affects various uncertainties and risks that may limit the performance of supply chains. Research indicates that models that incorporate uncertainties and risks will help to improve the resilience of global supply chains. In the era of technology, we experience the abundance of textual data from various web-media resources related to companies, which can be deployed to understand the impact of risks on the chain. Accordingly, this study aims to utilize textual data collected from news articles and earnings call transcripts to assess the vulnerability of the suppliers and the chain. Among many, we considered supply chain resource limits as a subcomponent of vulnerability and collected textual data associated with its sub-factors. Then, we proposed an integrated factor analysis and Analytical Network Process (ANP) method to model the company’s supply chain resource limits index. Specifically, factor analysis was used to determine the latent constructs of the variables that are grouped under resource limits and their correlations. This latent construct and correlations were then applied as the interdependencies among variables in the ANP to discover the final importance weights of the variables in terms of supply chain resource limits. The results of the study showed that the shortages of capacity, components, and energy supply are the most critical sub-factors. The company’s supply chain resource limits index (SCRLI) can be further calculated to assist decision-makers of an enterprise in supply chain configuration design, and improve the supply chain resilience.

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