Technology clustering based on evolutionary patterns: The case of information and communications technologies

Hyoung joo Lee, Sungjoo Lee, Byungun Yoon

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

Technology trend analysis anticipates the direction and rate of technology changes, and thus supports strategic decision-making for innovation. As technological convergence and diversification are regarded as emerging trends, it is important to compare the growth patterns of various technologies in a particular industry to help understand the industry characteristics and analyse the technology innovation process. However, despite the potential value of this approach, conventional approaches have focused on individual technologies and paid little attention to synthesising and comparing multiple technologies. We therefore propose a new approach for clustering technologies based on their growth patterns. After technologies with similar patterns are identified, the underlying factors that lead to the patterns can be analysed. For that purpose, we analysed patent data using a Hidden Markov model, followed by clustering analysis, and tested the validity of the proposed approach by applying it to the ICT industry. Our approach provides insights into the basic nature of technologies in an industry, and facilitates the analysis and forecasting of their evolution.

Original languageEnglish
Pages (from-to)953-967
Number of pages15
JournalTechnological Forecasting and Social Change
Volume78
Issue number6
DOIs
StatePublished - Jul 2011

Keywords

  • Evolutionary patterns
  • Information and communications technology
  • Patent analysis
  • Technology clustering
  • Trend analysis

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