The Institutional Role Model: A System-Dynamic Approach to Reduce Complexity

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Abstract

The paper's primary objective is to make a scientific contribution by presenting an innovative, system-dynamic method for organisational change in the context of today's market complexity which is the institutional role model (IRM). It also aims to show why classical organisational theories no longer have the necessary degree of complexity to successfully tackle current challenges. The research process contains several steps. Firstly, it provides a literature-based analysis on why dynamic processes are needed to fully grasp today’s complexity as well as the ground theory related to the IRM. Secondly, governmental projects that have been conducted by the authors are analysed to provide concrete cases in which the IRM was used and proved to be the superior method to organize complex systems. The aim is to examine these case studies and make a general methodological contribution to how institutions can be structured using the institutional role model and they can effectively and successfully work together. The primary aim of the model is to ensure that tasks, responsibilities and roles are systematically assigned to the most appropriate institution over time through democratic and anonymous qualitative and quantitative processes. The dynamic approach of the IRM fully considers the technicalities of today’s technologies and is making sure that a high level of interoperability is guaranteed. This is one of the main assets of the IRM and making it more holistic and therefore better than previous working models. Through the anonymous and democratic questioning process the allocation of resources is optimized, since a great number of Institutions are filling out the IRM matrix and providing an assessment which institution is best suited to take over a specific role. This ensures that the organisation’s resources are used effectively and efficiently.

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APA

Schulz, W. H., & Franck, O. (2022). The Institutional Role Model: A System-Dynamic Approach to Reduce Complexity. International Journal of Sustainable Development and Planning, 17(2), 351–361. https://doi.org/10.18280/ijsdp.170201

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