A Technology-Based Classification of Firms: Can We Learn Something Looking Beyond Industry Classifications?

Area of Science:

• Economics
• Innovation Studies
• Data Science

Background:

• The structure of industries and firm competition is constantly evolving due to technological advancements.
• Existing industry classifications may not accurately reflect firms' true technological similarities and competitive landscapes.
• A dynamic and data-driven approach is needed to keep pace with technological change.

Purpose of the Study:

• To develop a novel method for classifying firms based on their technological capabilities.
• To create a Technologically Driven Classification (TDC) that adapts to the changing technological landscape.
• To validate the TDC's effectiveness in capturing technological similarities and market competition.

Main Methods:

• Utilized clustering techniques on patent data to identify firms with similar technological market focus.
• Employed information theory to assess the explanatory power of the TDC and its relationship with industrial classifications.
• Developed a data-driven approach for firm classification, differentiating from traditional methods.

Main Results:

• The clustering successfully identified groups of firms competing in similar technological markets, often transcending traditional industrial sectors.
• The Technologically Driven Classification (TDC) effectively groups firms based on their technological capabilities, as validated by information theory.
• The TDC demonstrates a strong ability to characterize competition within technological markets.

Conclusions:

• The proposed Technologically Driven Classification (TDC) offers a robust and adaptive method for grouping firms by technological competencies.
• This approach provides a valuable tool for comparing firms in the technological space and understanding market dynamics.
• The TDC represents an attractive alternative to traditional industry classifications for analyzing innovation and competition.