Corporate Investment

Abstract

Abstract This chapter explores the significance of agent-based modelling and simulation in advancing theories in the field of corporate investment. It sheds light on three primary contributions of agent-based techniques: testing assumptions in analytical models, modelling human behaviour realistically, and analysing contingency effects and resulting dynamic and nonlinear effects. First, agent-based modelling enables the rigorous testing of assumptions made in analytical models. By employing agent-based simulations alongside analytical approaches, researchers can critically evaluate the robustness of existing theories. This comparative analysis helps identify the limitations and refine the assumptions underlying corporate investment models, leading to more accurate and reliable theoretical frameworks. Second, agent-based techniques offer a more flexible and realistic means of modelling human behaviour in corporate investment. By incorporating factors such as biases, adaptive behaviour, learning processes, and social norms, agent-based models can capture the complexities of decision-making processes. This enhanced representation of human behaviour facilitates the development of a comprehensive behavioural theory of corporate investment, providing valuable insights into the factors influencing investment decisions and outcomes. Lastly, agent-based modelling allows for the systematic exploration of contingency effects on corporate investment theories. Contingency factors, including firm characteristics, industry dynamics, and economic conditions, significantly influence investment strategies. By integrating these contingencies into agent-based models, researchers can analyse their interactions and understand how they shape investment behaviour, leading to a deeper understanding of the dynamic nature of corporate investment decisions.