The knowledge relatedness of potential entrants to the target industry is often cited as one of the main drivers of entry. However, empirical evidence shows that the relationship between relatedness and the probability to enter often varies across industry and time, suggesting therefore that industry characteristics may act as moderators in this relationship. This study provides a theoretical framework to identify these moderators, focusing on modularity and concentration of innovative activity across different types of entrants. It then empirically tests this framework using a dataset of firms active in the US electronics industry between 1960 and 1990. The results of this paper show that modularity and concentration of innovative activity moderate the relationship between knowledge relatedness and entry, but in different ways depending on the type of entrant.
