New approaches to modeling resilient decisions under deep uncertainty to manage the downstream supply chain

Background: The supply chain process has been widely modeled, especially with respect to the optimization of system performance. Recent years have highlighted the outbreak of many crises, such as the financial crisis of 2008, COVID-19, and the semiconductor shortage. The impact of such crises has become more challenging for manufacturers, particularly in the automotive industry. In this context, the present study was undertaken with the specific aim of providing an integrated approach for resilient decision-making under deep uncertainty (DMDU), especially in the downstream supply chain. Methods: The research is based on design science research (DSR) and case study methodologies. A design methodology was used to develop the framework. A case study is included to prove the pertinence of the framework. Results: The findings of this study demonstrate that the suggested comprehensive approach is helpful for companies and could help top management with strategic decision-making when customers decide to increase or decrease demand. This paper develops and models two approaches that help firms to manage and make resilient decisions when the supply chain is facing deep uncertainty, such as the bullwhip effect. Finally, the proposed models are implemented in a real-life case study within an automotive company to illustrate the applicability and efficacy of the proposed approach. Conclusions: To the best of our knowledge, this is the first study suggesting this approach. The paper is original and contributes towards sharing a new approach to understanding the supply chain within an uncertain context. As part of its contribution, the study draws attention to how managers and executors should integrate this approach into the global strategy of a company. Moreover, it explores some of the most complex variables that affect supply chain performance under high demand variation so it is possible to clearly show the risks associated with obsolete materials and products.

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Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).