Multi-criteria Analysis of Disruption Risks for Supply Chains Due to Pandemics

• Autor(a) principal: Neto, J. Martino [UNESP]
• Data de Publicação: 2022
• Outros Autores: Salomon, Valerio Antonio Pamplona [UNESP]
• Tipo de documento: Capítulo de livro
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1007/978-3-031-07333-5_7; http://hdl.handle.net/11449/246074
• topic: Agile supply chains; Analytic hierarchy process; Automotive industry; Case study; Coronavirus Disease 2019; Customers; Demand planning; Efficient supply chain; Ideal Solution; Latin America; Model; Multi-criteria decision analysis; Responsive supply chain; Risk management; Suppliers; Supply chain management; Technique of Order Preference; TOPSIS

Coronavirus Disease 2019 (COVID-19) affected global economics and society, unprecedentedly. Supply chains, linking customers, manufacturers, and suppliers, are more susceptible to disruption risks when facing pandemics, like COVID-19. As matter of fact, there is an emerging literature on supply chain management (SCM) and COVID-19. This chapter explores how supply chain managers may evaluate supply chain risks due to pandemics. Managers may analyze alternatives to mitigate the situation. The purpose of this chapter is to present a mathematical model for assessing disruption risks in supply chains affected by pandemics. A multi-criteria decision analysis (MCDA) model is developed from the consolidated literature of SCM. Analytic Hierarchy Process (AHP) and Technique of Order Preference by Similarity to Ideal Solution (TOPSIS), two leading MCDA methods were combined in the development of the assessment model. The model is tested with the case study of a multinational automotive company that operates in both efficient and responsive supply chains. For efficient supply chains, the model resulted in a focus on capacity management, demand planning, and sales forecasting, to avoid risks disruptions. For responsive supply chains, the focus shall move to operations management.