Level of decentralisation of global production networks - strategy-oriented design of decision-making autonomy

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Companies operating in global production networks today are confronted with grown structures, suboptimal coordination efforts and a lack of strategy consistency, which can have far-reaching consequences for the entire network. To overcome these challenges and to improve the performance of production networks, companies need a holistic system that supports them in making the core decisions of global production at the right points in the production network. However, current implementations of such systems are mostly based exclusively on rigid checklists and generic tools, without forcing a comprehensive consideration of the production network and its environment.The objective of this research proposal is therefore to develop a methodology for the best practice design of the decentralisation level of global production networks that allows core production decisions for specific production networks to be allocated between a corporate headquarters and a single production site for different strategic framework conditions and different types of internal and external complexity of the production network. Based on an analysis and description of the core decisions and their influencing factors, interdependencies between these elements are determined with the help of an empirical study using multivariate analysis methods as well as through simulation studies. Furthermore, these interdependencies are used to identify a best practice design of the decentralisation level of decisions for specific global production networks. The best practice design is achieved through various design guidelines and recommendations for action from e.g. the fields of digitalisation or organisation theory, which are proposed to the specific production networks by the methodology to be developed. Through this approach, which combines empirical methods as well as quantitative methods with action measures, a strategy-oriented design of decision autonomy in global production networks is to be achieved. The developed methodology will be validated in the context of case studies from the manufacturing industry.