Modelling the Structural Dynamics of Business Networks : Two Agent-based Models of Supply Networks

This thesis aims at describing and analysing the structural changes of business networks that emerge as a result of change triggers. Despite previous studies, our understanding of the evolution of the network structure and its influencing factors is still limited. Specifically, the literature falls short in explicit consideration of the aggregate outcomes of various actors’ responses for the structure of the network. The methodological challenges have contributed to these shortcomings. The Industrial Networks Approach and Complexity Perspective are the theoretical points of departure in this thesis. As a consequence of viewing business networks as Complex Adaptive Systems, Agent-based modelling (ABM) and simulation is the specific methodology adopted. In this thesis, two ABMs are designed and implemented. In the first one, the strategic initiative of a railway operator gives rise to various customer responses. In the second one, a supply network with various supply chains is modelled. The pressure from end-customers triggers responses from business actors in terms of re-arranging their supply chains. The consequent structural changes in both networks and mechanisms involved are systematically explored through various computational experiments. The results contribute to the literature on business network dynamics by showing the influence of a set of Perceptual-Intentional factors as well as Contextual factors. A contribution of the adopted methodology is the ability to analyse the aggregate outcomes of the actor-level responses. The potential of ABM approach to be combined with case studies is illustrated. Opportunities for systematic experimentation and the formalization of theoretical concepts in ABMs contribute to better theory development. With ABM, more actors, interdependencies and larger time scales can be explored