The use of foresight to anticipate and prioritise innovation system failures
The case of machine learning in broadcasting in South Korea
Bibliographic Data
| ID | 9845623 |
|---|---|
| Authors | Jong-Seok KIM (0000-0002-4560-2553, Chungnam National University, corresponding author), Kieron Flanagan (0000-0002-7299-3158, University of Manchester) |
| Year | 2024 |
| Volume | 163 |
| Pages | 103454 |
| Publication date | 2024-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Futures (JOURNAL) |
| Journal identifiers | ISSN: 0016-3287 • E-ISSN: 1873-6378 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.futures.2024.103454 |
| OpenAlex | W4401418951 |
| Language | EN |
| Citations received | 1 |
| References cited | 35 |
Broadcasting (networking · Business · Computer security · Economics · Economy · Futures studies · Industrial organization · Innovation system · National innovation system · Process (computing · Artificial Intelligence · Computer Science · Economic and Technological Innovation · Innovation and Knowledge Management · Innovation Diffusion and Forecasting
How are foresight methods selected?
Sectoral systems of innovation and production
Why does renewable energy diffuse so slowly? A review of innovation system problems
A system failure framework for innovation policy design
Legitimizing research, technology and innovation policies for transformative change
Policies for science, technology and innovation
The diffusion of renewable energy technology
Artificial intelligence and corporate innovation
The Oxford Handbook of Innovation
Innovation, Science and Institutional Change
Sectoral innovation system foresight in practice
In search of sectoral foresight methodology
Innovation system analyses and sustainability transitions
Path dependence and path break-out in the electricity sector
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |