Modelling adaptive policies in the smartphone supply chain

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The emergence of the Covid-19 pandemic has induced new challenges for supply chain management, including unexpected demand drop or surge, supply shortages, and reduced productivity. It is expected that these challenges will continue in the coming years as the pandemic still lingers on. This raises the issue within the supply chain domain to address unknown uncertainties, such as Covid-19. However, appropriate methods to address these types of uncertainty are not prevalent within supply chain management. This study addresses unknowable uncertainties with a novel method. An adaptive approach is proposed that aims to enhance the robustness of the supply chain of a major smartphone company situated in Europe by applying a combined approach of System Dynamics and the Dynamic Adaptive Planning (DAP) framework. Previous applications of the DAP concept have been explored in fields, such as Transport planning, e.g. Jittrapirom et al. (2018) and Marchau et al. (2019), but not yet in supply chain management. System Dynamics provides a tool to compare a business-as-usual scenario with a hypothetical improved scenario with DAP implemented, thus enabling us to quantify the expected enhancements from the DAP application. This study shows that, in a simulation model formulated based on semi-structured interviews with supply chain actors and quantified based on expert assumptions, the DAP, formulated in a participative modelling session, shows behaviour that, depending on what is most important: low inventories or high sales, improves the resilience of the supply chain performance to uncertainty by implementing adaptive policies.
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