Hyo Shin Choi
Papers
1
Total Citations
13
H-Index
1
About
Hyo Shin Choi is a leading researcher in technology forecasting and innovation diffusion, with a focus on integrating diverse data sources to predict market adoption of new products. Her most-cited work, "Forecasting new product diffusion using both patent citation and web search traffic" (2018, 13 citations), introduces a novel framework that combines technology diffusion signals from patent citations with consumer interest signals from web search traffic. This dual-diffusion approach addresses a critical challenge in business strategy—accurately forecasting demand for emerging technologies before they reach the market. By bridging the gap between technical innovation and consumer behavior, Choi’s research provides actionable insights for firms navigating uncertain product launches. Her work stands out for its interdisciplinary methodology, merging patent analytics with digital trace data to enhance predictive accuracy. With growing recognition in the field of innovation management, Choi’s contributions continue to influence how researchers and practitioners leverage big data for strategic decision-making in technology commercialization.
Research Focus
Key Achievements
Top Papers
- 1