Modeling network growth with network theory and cellular automata

Purpose – Although the nonlinear growth of networks, e.g. the diffusion of innovations, is vital for strategic management, it is often treated implicitly in management theory and practice. Partial explanations of this discrepancy are the unintuitive nature and complexity of the required analytical tools. The goal of this research is to assess two possible approaches – the network theory and cellular automata (CA) – and to generate guidelines for their application. Design/methodology/approach – After having clarified the necessity for a network growth analysis, the network theory and CA are outlined and compared as alternative analytical approaches for its investigation. Findings – Results of the theoretical analysis indicate that the amount of the interacting agents and the complexity of the interaction rules are key determinants for choosing the optimal methodology. Originality/value – Given that sound research has addressed the implementation handles, the further application guidelines mentioned here can help corroborate and validate the concepts presented and contribute to a further diffusion of the underlying complex systems principles in management theory and practice.