Adopting and improving a new forecasting paradigm
Bibliographic Data
| ID | 21502433 |
|---|---|
| Authors | Ian Speigel (North-West State Technical University, corresponding author) |
| Year | 2021 |
| Volume | 36 |
| Issue | 7 |
| Pages | 961-977 |
| Publication date | 2021-11-10 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Intelligence & National Security (JOURNAL) |
| Journal identifiers | ISSN: 0268-4527 • E-ISSN: 1743-9019 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/02684527.2021.1946955 |
| OpenAlex | W3182966114 |
| Language | EN |
| Citations received | 2 |
| References cited | 59 |
A large and growing body of research suggests that when it comes to forecasting, the process-oriented paradigm prevalent in the Allied intelligence community (IC) acts as a drag on forecasting accuracy. A new verification-oriented paradigm has been developed over the past decades, which produces more accurate forecasts and therefore should be put into practice. However, the accuracy achievable by the new verification paradigm does not yet satisfy the needs of the clients of IC practitioners. IC scholars should improve the verification paradigm by recognizing that IC forecasts typically pertain to complex situations, and therefore require the tools, methods and concepts found in complexity science
Data science · Epistemology · Management science · Paradigm shift · Competitive and Knowledge Intelligence · Computer Science · Engineering · Artificial Intelligence
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| Citations per year | 1 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |