Methodology for assessing the ability to control global value added networks using perfor-mance indicator-based modeling and in consideration of real decision-making structures by means of the agent-based simulation

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European companies are often a central part of value added networks, whose overall performance is crucial for the success of the companies in global competition. Therefore many organizations are faced with the challenge of controlling, influencing and optimizing the value added networks in the best interest of each company.Value added networks can be characterized by their composition of autonomous actors. These actors influence the overall behavior with their individual decision-making behavior, which is based on their targets. Thus, the prediction of the behavior and the controllability of networks, e.g. via approaches from supplier management, quality management as well as lean management methods, is a complex task. It has not yet been clearly defined, through which measurements companies should control or develop their cooperation with other actors in the value added network Main deficits of state of the art research are that the interlinked and interdependent intercompany production processes can yet only partially be described as well as the insufficient consideration of decentralized decision structures in analysis and identification of suitable management measures.The superordinated overall objective of the research project is to develop a conceptual evaluation methodology for the strategic management of production processes in global value added networks. This overall objective can be divided into two sub-targets:1. Development of a methodology for the identification of weak points or potential improvements, which have system-relevant effects on a focal company of the value added network in the dimensions costs, time and quality.2. Development of a methodology for the identification of suitable control measurements for a specific configuration of a value added network, considering their particular characteristics like decentralized decision structures, interdependencies, power relations, etc.In order to achieve the objective, a key performance indicator based description model for production processes in value added networks will be developed, enabling an easier description of complex process chains with variable level of detail while considering target system based decision structures. The resulting model will be implemented in an agent-based simulation environment.Furthermore the results of this research project will contribute to a refined understanding of the correlations in value added networks by bringing together the results of different research disciplines and leading them towards practical application.