Embedding of real-world complexity modeling in adaptive supply chain systems engineering
Sun, Can; Rose, Thomas (Thesis advisor); Jarke, Matthias (Thesis advisor); Schmitt, Robert H. (Thesis advisor)
Aachen : RWTH Aachen University (2020, 2021)
Dissertation / PhD Thesis
Dissertation, RWTH Aachen University, 2020
Technological changes and globalization increase the turbulence and complexity of the supply chain. It requires firms to manage complexity and change successfully in order to achieve competitive advantages. The state-of-the-art analysis and practical problems collected from the real phenomena have shown that existing theoretical complexity measures cannot adequately support decision-making in practical use. Therefore, this thesis aims to build a comprehensive supply chain complexity measurement framework through detailed modeling and apply it in the changeable environment. The theoretical approach consists of two models and two frameworks. Due to the mix of social and technical attributes, the supply chain and its dynamic change can be modeled as sociotechnical systems. Supply chain complexity has two types: structural and dynamic. So a complexity measurement framework that is decomposed into different levels of complexity drivers is developed, and the corresponding measures are also derived. Changes have three scenarios, and each can be tackled with different strategies. Therefore, a decision-making framework for various change scenarios is proposed, and complexity as one of the decisive evaluation criteria is highlighted. The proposed solutions are validated with a set of real-world case studies from the semiconductor industry. Each case represents one change scenario and addresses the complexity from a particular perspective. For each case, the problem is analyzed and modeled with the support of proposed models and frameworks. After the evaluation of complexity, the best solution is also suggested. The results show that complexity can be measured by a set of indicators or formulas, and thus support decision-making by comparing the change-induced complexity. The research mainly contributes to theoretical and practical methodologies from three aspects: system modeling, complexity measurement, and change scenarios evaluation. The change-induced complexity measurement offers a fresh perspective on decision-making.