The clustering of firms in related fields has a positive impact on economic performance and innovative behaviour. The cluster lifecycle model provides a framework in order to add a temporal dimension to this ongoing debate. This model conjectures that clusters undergo various phases, in each of which they exhibit distinct characteristics in terms of size, economic performance and knowledge sourcing pattern. While there is strong evidence of a dynamic interplay between knowledge networks and clusters, we know little about how the structural configurations of a knowledge network engender cluster transition, and how these dynamics can be captured and integrated into policies. First, this paper contributes to this debate by providing a conceptual framework that accounts for cluster evolution based on endogenous micro-forces that are immanent in a knowledge sourcing structure. Secondly, this article underlines the failures of recent network-related cluster policies and discusses how the developed framework alleviates these issues.