TY - JOUR
T1 - How to develop data-driven technology roadmaps:The integration of topic modeling and link prediction
AU - Kim, Junhan
AU - Geum, Youngjung
N1 - Publisher Copyright:
© 2021
PY - 2021/10
Y1 - 2021/10
N2 - Technology roadmaps have been used as an important tool in strategic technology planning, due to their strong advantages in linking technologies and markets. With the rise of big data analytics, several studies have been suggested regarding data-driven technology roadmapping. However, literatures on providing a systematic method for developing data-driven technology roadmaps is surprisingly sparse. In response, this study suggests a systematic and concrete framework to develop data-driven technology roadmaps. The data-driven roadmapping is consist of three phase: layer mapping, contents mapping, and opportunity finding. The first phase, layer mapping, deals with identifying sub-layers for the technology roadmap using topic modeling. Then, contents mapping is conducted using the keyword network analysis. Third, opportunity finding is conducted to anticipate future possible innovation chances, with the help of link prediction. Our study contributes to the field by suggesting a systematic method for data-driven roadmapping, and provides data-driven evidence that helps experts to make more reasonable decision-making.
AB - Technology roadmaps have been used as an important tool in strategic technology planning, due to their strong advantages in linking technologies and markets. With the rise of big data analytics, several studies have been suggested regarding data-driven technology roadmapping. However, literatures on providing a systematic method for developing data-driven technology roadmaps is surprisingly sparse. In response, this study suggests a systematic and concrete framework to develop data-driven technology roadmaps. The data-driven roadmapping is consist of three phase: layer mapping, contents mapping, and opportunity finding. The first phase, layer mapping, deals with identifying sub-layers for the technology roadmap using topic modeling. Then, contents mapping is conducted using the keyword network analysis. Third, opportunity finding is conducted to anticipate future possible innovation chances, with the help of link prediction. Our study contributes to the field by suggesting a systematic method for data-driven roadmapping, and provides data-driven evidence that helps experts to make more reasonable decision-making.
KW - Data-analytics
KW - LDA
KW - Latent dirichlet allocation
KW - Link prediction
KW - Technology roadmap
KW - Topic model
UR - https://www.scopus.com/pages/publications/85111033918
U2 - 10.1016/j.techfore.2021.120972
DO - 10.1016/j.techfore.2021.120972
M3 - Article
AN - SCOPUS:85111033918
SN - 0040-1625
VL - 171
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
M1 - 120972
ER -