Structuring the Core Competencies of a Major Car Manufacturer in a Technology Field: Applying Semantic Anchor Points to General Motors’ Gearing Technology

Abstract

In order to stay competitive, companies develop a set of core competencies, many of which are based on technological know-how. This technological know-how, along with the efforts of R&D-projects, is displayed in those companies’ patent portfolios. Large companies often have a large patent portfolio, comprising various technologies. In order to understand a company’s position within a technology, it seems helpful to structure its core competencies. For a similar purpose, several authors developed a method based on semantic anchor points. While this method works well for smaller companies with a limited number of patents in one field, the question arises, whether and how this method can be applied to a major manufacturer with a comparatively large number of patents. In this paper, General Motors and their patents in the technology field of gearings are used to test the method. We have to divide the data set of General Motors due to their special patenting strategy. Using the cluster-specific semantic anchor points, specific technological know-how of General Motors is identified, and the competencies are analyzed in the course of time. For instance, three clusters of competencies could be identified. Two clusters describe the core competence of General Motors - the application of planetary gear sets. One cluster comprises a basic set of diverse competencies, which we call the follower-cluster.