Exact(4)
This paper makes proposals to improve the consideration of lifestyles in the quantitative foresight exercises.
In such context quantitative foresight methods, such as trend-extrapolation, often prove to be unreliable.
They claim that an optimal combination of qualitative and quantitative foresight methods' approaches is only limited by the ingenuity of the researchers themselves, not by the intrinsic characteristics of the approaches.
It is urgent to take full account of the insights that may be gained through the inclusion of interpretive qualitative approaches when doing quantitative foresight exercises, because the latter may tend to underestimate the contribution and need for triangulated approaches in practice and vice versa.
Similar(56)
Quantitative foresights, when done properly, provide a rigour, precision, and consistency that comes from their numerical and mathematical underpinnings.
Ideally, we look for the in-depth, contextualised, and natural but more time-consuming insights of qualitative foresight research, coupled with the more time-efficient but less rich or compelling predictive power of quantitative foresights.
Methodological links can be based on both quantitative and qualitative foresight methods.
Thirdly, stronger integration of qualitative and quantitative data in foresight is also called for as different methods have their strengths and weaknesses in different areas [16, 17, 18].
The authors applied a combined macro- & micro- scenario building approach, which provided an adequate way to make entrepreneurs familiar with both quantitative and qualitative Foresight methods.
Karlsen and Karlsen [3] investigated the inherent ontological and epistemic premises embedded in the application of quantitative and qualitative foresight methods and tools, offering taxonomies for the classification of the most commonly-used approaches according to criteria such as mobilisation, scope and complexity.
In doing so we relied methodologically on qualitative foresight tools combined at the end of the project with quantitative micro-simulation.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com