Modeling and Simulation of Socio-Technical Systems: A Holistic Approach to Analyze, Design, and Control the Interactions between Technical and Social Systems

Technological advancement creates many opportunities for society, but simultaneously imposes new challenges to organizations. They have to utilize novel technologies to achieve competitive advantages, but many are deployed for no reason, other than being 'cutting edge'. To evaluate whether the use of a new technology can improve the performance, decision makers must understand the dynamics that emerge in socio-technical systems. The interactions between humans, technology, processes and organizational structures have to be jointly analyzed and optimized, because improving just one part may not yield the full potential or even derogate the overall performance. It is often very expensive to alter the actual system, which makes simulation models a very powerful method to investigate, evaluate or predict dynamic behavior. Considering that, Agent-based Modeling and Simulation (ABMS), Discrete Event Simulation (DES), and System Dynamics (SD) are frequently used paradigms, which differ significantly in terms of computational efficiency and the ability to capture human behavior. However, comprehensive simulation models are rare and researchers have claimed that existing paradigms are not suited to represent socio-technical systems sufficiently. Multi-method approaches, increased computer performance, and powerful simulation software might have changed this situation.

This thesis covers a wide range of applications to identify the challenges and opportunities for modeling and simulation of socio-technical systems. First, an extended summary introduces the topic and covers the theory about systems, models and simulations. Second, selected peer-reviewed research papers are summarized and concluded. Findings indicate that fundamental concepts from systems theory can guide the socio-technical modeling process. In particular, hierarchies can be used to define the rate of autonomy on every level and influence the paradigm selection respectively. Incorporated research publications propose new ways to model and simulate these systems. First, the Hierarchical Control Conceptual Modeling framework adds flexibility to DES, by enabling self-determined behavior. Subsequently, a fully hybrid approach enables the seamless integration of agent-based behavior without giving up the computational advantage of DES. Selected research studies reveal the applicability of these new methods within various domains, covering health care, manufacturing, maintenance, and logistics. They provide a more holistic and joint approach to analyze, design, or control socio-technical work structures, but also socio-organizational and macro-environmental systems.