Firms as Influencers: Shaping Industries through Search and Collaboration

Abstract

Firms often engage in shaping the various dimensions of an industry's competitive landscape. While the actions by which firms are able to shape an industry has received increased attention, research has yet to examine the knowledge antecedents of firms’ shaping behavior; that is the knowledge that allows firms to create a persistent change to the competitive landscape. This paper takes a first step at quantitatively examining the information processing antecedents of industry shaping by employing a novel methodology using computational linguistic tools to provide evidence on how firms can engage in industry shaping. Specifically, I examine how a firm’s shaping of the positioning space depends on its depth and breadth knowledge search and the extent to which they collaborate with other firms. I study this question using machine learning techniques in combination with 2.4 million USPTO patents and 585,133 firm descriptions. The results show that search breadth and depth are positively associated with industry shaping while the effect of collaboration is contingent on a firm's level of breadth and depth. Overall, the findings suggest that depth enables a structural understanding of the environment allowing other firms to learn from the focal firm in collaborative relationships, enhancing their credibility. Meanwhile, breadth lowers the level of expertise, decreasing the amount of useful knowledge that other firms learn from collaboration.