Tag: FIP
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Generating Competitive Technical Intelligence Using Topical Analysis, Patent Citation Analysis, and Term Clumping Analysis
Because of the flexibility and complexity of Newly Emerging Science and Technologies (NESTs), traditional statistical analysis fails to capture technology evolution in detail. Tracking technology evolution pathways supports industrial, governmental, and academic decisions to guide future development trends. Patents are one of the most important NESTs data sources and are pertinent to developmental paths. This…
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Advancing the forecasting innovation pathways approach: hybrid and electric vehicles case
The forecasting innovation pathways (FIP) approach combines empirical tech mining with expert opinion. To date, FIP has been devised for relatively immature emerging technologies. This study extends the FIP methodology to work for a more advanced and complicated technology. It does so through a case analysis of hybrid and electric vehicles (HEVs). We retain the…
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Green Energy Prospects: Trends and Challenges
The transition of energy systems moving from non-renewable fossil-nuclear to renewable sources is a key challenge of climate mitigation and sustainable development. Green energy technologies can contribute to solutions of global problems such as climate change, growth of energy consumption, depletion of natural resources, negative environmental impacts, and energy security. In this article the prospective…
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Tech Mining to Generate Indicators of Future National Technological Competitiveness: Nano-enhanced Drug Delivery (NEDD) in the US and China
“Global technological competitiveness” is widely acknowledged, but the challenge is to go beyond this recognition to develop empirical indicators of important transitions. These may concern particular technologies, the competitive position of particular organizations, or national/regional shifts. For decades, the US has been the world leader in biomedical technologies, with attendant implications for organizational priorities in…
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Text mining of information resources to inform Forecasting Innovation Pathways
Highly uncertain dynamics of New and Emerging Science and Technologies (NEST) pose special challenges to traditional forecasting tools. This paper explores the systematisation of the ‘Forecasting Innovation Pathways’ analytical approach through the application of Tech Mining.
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Identifying innovation risk path for a newly emerging science & technology: Dye-sensitized solar cells
For “Newly Emerging Science & Technologies” (“NESTs”), uncertainty is the major challenge. Technological innovation for NESTs faces many kinds of risks that dramatically affect their development paths. This chapter combines methods of risk utility theory and technology path research and explores a new innovation risk path modeling method for NEST development.