Agent-Based Technologies for Research and Practical Use in Management

Abstract

Abstract This chapter examines the role of agent-based modelling and simulation in advancing theories and addressing operational and design issues within the realm of management science. We specifically explore the potential contributions of agent-based modelling and simulation to abductive and deductive reasoning. Through a theoretical lens, we argue that agent-based modelling and simulation is useful in exploring complex dynamics, and it thereby emerges as a potent tool for generating, refining, and selecting hypotheses. It facilitates a deeper understanding of the behaviours within complex adaptive systems—ranging from organizations to networks—thereby enabling the formulation of causally plausible explanations for observed phenomena. This capability is particularly crucial in environments where traditional analytical methods fall short due to inherent complexities. Furthermore, we discuss the role of agent-based modelling and simulation in operationalizing hypotheses for empirical testing, emphasizing its utility in translating theoretical concepts into testable models and identifying the boundary conditions under which these models hold true. In the context of operational and design issues, we argue that agent-based modelling and simulation supports the exploration of means–ends relations and the operationalization of design choices, thereby contributing to the development of innovative solutions and potentially better decision-making within organizations. Thereby, the method substantially contributes to bridging the gap between theory and practice within the field of management science, presenting it as an essential approach for navigating the complexities of contemporary management challenges.