Three single-authored papers in this thesis will explore the role of knowledge and information in industrial clusters; and specifically, how knowledge plays a role inthe emergence and persistence of clusters. This thesis places a major emphasis on spinoff firms.

The first paper uses a computational model to describe how patterns of industrial clustering arise with respect to the size of an initial firm when measured in terms of innovation. Technology is qualitatively described using a code set mapped on a cognitive space. Assuming inheritability of networking skills, I seek to model how the size of an initial firm influences future patterns of cluster formation through a model of technical cognition and a mimicking of creativity. Replicating the stylized facts of entrepreneurial cluster formation, we find initial firm size has a lasting impact on clustering patterns through its influence on the level of cognitive distance of the underlying agents.

The second paper turns to networks as a tool of analysis to explore the relationship between a spinoff’s network and its geographical location within an industrial cluster. Although recent literature infers that the transmission of organizational attributes in industrial clusters is accomplished via passive network ties, this has not been directly measured. After controlling for firm size, parent size and age, we find that there a statistically significant and negative relationship between network efficiency and geographic distance to a cluster’s core.

The third and final paper extends the use of networks to examine how knowledge flows, as conduits for routines and skills, affect the survival prospects for firms in industrial clusters. We consider knowledge transmission via two channels: those from inherited linkages and those from geographic proximity. It is found that a firm’s historical links formed through parent-spinoff networks have a significant impact on survival, which differ depending on the motivations of the entrepreneur. Moreover, the gains with respect to location are found to be nonlinear.