This paper presents a systemic review of the contributions that stochastic actor‐oriented
models (SAOMs) and exponential random graph models (ERGMs) have made to the study …

Drawing on the 'local buzz and global pipeline'perspective on the geographies of production
in knowledge‐intensive industries, our analysis associates observed network patterns with …

This study investigates the usefulness of exponential random graph models (ERGM) to
analyze the determinants of cross-regional R&D collaboration networks. Using spatial …

The analysis of spatial networks' evolution has predominantly concentrated on the formation
process of links. However, the evolution of networks is similarly shaped by the dissolution of …

This chapter aims at reviewing complex network models and methods that were either
developed for or applied to socioeconomic issues, and pertinent to the theme of New …

In recent years, industrial clusters have received considerable attention from economists,
because they are seen as the main reason for the economic success of certain region and …

A key question raised in recent years is what factors determine the structure of inter-
organizational networks. Most research so far has focused on different forms of proximity …

The exponential random graph model (ERGM) is an increasingly popular method for the
statistical analysis of networks that can be used to flexibly analyze the processes by which …

The importance of network structures for the transmission of knowledge and the diffusion of
technological change has been recently emphasized in economic geography. Since …

We define a general class of network formation models, Statistical Exponential Random
Graph Models (SERGMs), that nest standard exponential random graph models (ERGMs) as …