Using Integrated Top-down and Bottom-up Dynamic Modeling for Triangulation and Interdisciplinary Theory Integration The Case of Long-term Firm Performance and Survival

摘要

System dynamics (SD) modeling has been classified as a "top-down" approach to modeling dynamic and complex systems, whereas agent-based (AB) modeling techniques are referred to as a "bottom-up" approach. Various papers have recently proposed the use of both approaches when studying complex, dynamic problems in the social; sciences, particularly, when hard data for important variables are hard to find. Furthermore, human and social dynamics typically have been studied through the lenses of various disciplines. When modeling those problems, insights from those various disciplines should be integrated. Dynamic modeling might provide an important instrument for such theory integration efforts. In this paper, the problem of long-term firm performance is taken as an illustration for such a research design, in which theory-integration is undertaken along with a design, in which top-down and bottom-up modeling are iteratively combined. It is concluded that besides arriving at deeper understanding of the problem through theory integration, cross-validation and dynamic triangulation may be among the potential benefits in such multi-disciplinary and multi-method research designs.