Foresight methods for smart specialisation strategy development in Lithuania
Author(s) | |
---|---|
Paliokaitė, Agnė | Visionary analytics, UAB |
Martinaitis, Žilvinas | Visionary analytics, UAB |
Reimeris, Ramojus | Mokslo ir studijų stebėsenos ir analizės centras |
Elsevier |
Date Issued |
---|
2015 |
This paper presents the methodological approach and first results of the ongoing national level foresight process organised in Lithuania in the context of preparing the smart specialisation strategy and defining the national research and innovation priorities. The main objective is not to determine where to invest but how to help agents to discover where to invest in a decentralised and bottom-up logic. The methodology accepted in Lithuania departs from the traditional approach to priority setting focused on identification of research fields or economy sectors, and builds on the concepts of long term challenges and critical technologies. Choosing challenge-based priorities allows to better develop synergies and integrated policies, thus reducing fragmentation. A mixed qualitative and quantitative method approach is applied, including the expert panels, surveys, statistical and bibliometrical analysis, roadmaps, and analytical studies on the emerging trends and long term challenges.
Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
---|---|---|---|---|---|---|---|---|
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE | 2.678 | 1.749 | 1.566 | 1.932 | 2 | 1.488 | 2015 | Q1 |
Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
---|---|---|---|---|---|---|---|---|
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE | 2.678 | 1.749 | 1.749 | 1.932 | 2 | 1.488 | 2015 | Q1 |
Journal | Cite Score | SNIP | SJR | Year | Quartile |
---|---|---|---|---|---|
Technological Forecasting and Social Change | 4.6 | 1.865 | 1.286 | 2015 | Q1 |