TY - JOUR
T1 - Technology clustering based on evolutionary patterns
T2 - The case of information and communications technologies
AU - Lee, Hyoung joo
AU - Lee, Sungjoo
AU - Yoon, Byungun
PY - 2011/7
Y1 - 2011/7
N2 - 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.
AB - 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.
KW - Evolutionary patterns
KW - Information and communications technology
KW - Patent analysis
KW - Technology clustering
KW - Trend analysis
UR - http://www.scopus.com/inward/record.url?scp=79957517233&partnerID=8YFLogxK
U2 - 10.1016/j.techfore.2011.02.002
DO - 10.1016/j.techfore.2011.02.002
M3 - Article
AN - SCOPUS:79957517233
SN - 0040-1625
VL - 78
SP - 953
EP - 967
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
IS - 6
ER -