Hybrid System Dynamics—Agent-Based Simulation for Research in Economics and Business

In a rapidly evolving business environment, the question of searching of effective methods and tools for researching and analyzing economic entities becomes more and more important. One of the ways of studying this world of growing dynamic complexity and supporting the process of decision-making is the use of computer simulation. According to the reference literature, there are three most commonly used methods of computer simulation for research in management: system dynamics, discrete event, and agent-based simulation. However, the complex, multifaceted nature of modern-day economic and business systems can pose considerable challenges for single-methodology simulation approach. In such cases, it may be that (should be removed) an alternative simulation approach, using either another modeling paradigm or a hybrid approach, could provide a simpler, more natural, or more efficient solution. Hybrid simulation, defined as a combination of two or more computer simulation methods, has become an increasingly common approach to modeling complex systems in the past two decades. The study concentrates on one particular hybrid—that involving agent-based simulation (ABS) and system dynamics (SD). It aims to discuss the issue of combining system dynamics and agent-based simulation approaches for research in economics and business. First, the two methods will be briefly characterized with the indication of their differences and similarities. Then, the possible ways of combining them in a single model will be described. Finally, examples of hybrid SD-ABS model applications in economics and business will be presented.