Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns

Abstract

Sourcing strategy analysis in the settings of supply chain (SC) flexibility in regard to single vs. dual sourcing has been a well-explored area over the last two decades. In recent years, single vs. dual sourcing analysis has been increasingly introduced in SC disruption management. Since most of the decision-support models for SC sourcing strategy adaptation in the case of disruptions presume real-time information and coordination, the issues of big data and business intelligence needs to be included into the consideration. A SC simulation model with consideration of capacity disruption and big data along with experimental results are presented. Based on both literature analysis and modelling example, managerial insights are derived. A set of sensitivity experiments allows us to illustrate the model's behaviour. The analysis suggests recommendation on using single sourcing, capacity flexibility and dual sourcing for different combinations of demand and inventory patterns. The paper is concluded by summarising the most important insights and outlining future research agenda.