Developing Agent-Based Models of Business Relations and Networks as Complex Adaptive Systems

Business relationships are dynamic, embedded in a larger network of interconnected relationships and they change over time. Current research and theory in marketing give very limited attention the issue of dynamics and change in marketing systems. The dom-inant variance-based and cross-sectional approaches cannot capture the development of relationships over time; narrative and longitudinal research are usually so data intensive that they have to focus on the development of one relationship, or the interactions between a very small number of them. From the perspective of complexity theory, business relations and networks can be seen as examples of complex adaptive systems in which the structure and patterns observed on the aggregated, collective level emerge from local, micro interactions over time in a self-organizing manner. Such systems can be modelled and studied using agent-based modelling methods. In order to advance our understanding of the dynamics of business relationships and networks, I propose to build computer models of the key mechanisms that drive the systems ’ development