Identifying technological opportunities using enhanced tech mining
The case of the E-health industry
Bibliographic Data
| ID | 21402912 |
|---|---|
| Authors | Seungyeon Moon (0000-0002-5131-1007, Sungkyunkwan University), Heesang Lee (0000-0002-2796-6126, Sungkyunkwan University, corresponding author) |
| Year | 2024 |
| Volume | 206 |
| Pages | 123561 |
| Publication date | 2024-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Technological Forecasting and Social Change (JOURNAL) |
| Journal identifiers | ISSN: 0040-1625 • E-ISSN: 1873-5509 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.techfore.2024.123561 |
| OpenAlex | W4400333024 |
| Language | EN |
| Citations received | 1 |
| References cited | 38 |
Business · Data science · High tech · Industrial organization · Mining engineering · Mining industry · Political science · Big Data and Business Intelligence · Computer Science · Engineering
The Sage Encyclopedia of Qualitative Research Methods
The Coding Manual for Qualitative Researchers
Latent Dirichlet allocation (LDA) and topic modeling
Manual or electronic? The role of coding in qualitative data analysis
Topic Modeling in Management Research
Two-stage technology opportunity discovery for firm-level decision making
Discovering technological opportunities by identifying dynamic structure-coupling patterns and lead-lag distance between science and technology
Opportunity-driven technology roadmapping
Combining topic modeling and SAO semantic analysis to identify technological opportunities of emerging technologies
Identifying technology opportunity using SAO semantic mining and outlier detection method
Topic modeling, long texts and the best number of topics. Some Problems and solutions
Deep learning and medical image processing for coronavirus (Covid-19) pandemic
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |