How to develop data-driven technology roadmaps:The integration of topic modeling and link prediction

Junhan Kim and Youngjung Geum

Technological Forecasting and Social Change, 2021, vol. 171, issue C

Abstract: 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.

Keywords: Technology roadmap; Topic model; Latent dirichlet allocation; LDA; Link prediction; Data-analytics (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:171:y:2021:i:c:s0040162521004042

DOI: 10.1016/j.techfore.2021.120972

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