A1 Refereed original research article in a scientific journal
Generating sets of diverse and plausible scenarios through approximated multivariate normal distributions
Authors: Aalto, Eljas; Kuosa, Tuomo; Stucki, Max
Publisher: Elsevier
Publication year: 2025
Journal: European Journal of Operational Research
Volume: 320
Issue: 1
First page : 160
Last page: 174
ISSN: 0377-2217
eISSN: 1872-6860
DOI: https://doi.org/10.1016/j.ejor.2024.08.003
Web address : https://doi.org/10.1016/j.ejor.2024.08.003
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/457803857
This article presents a novel and broadly generalizable framework for generating diverse and plausible sets of scenarios. Potential future outcomes are decomposed using a set of uncertainties which are assumed to be multivariate normally distributed, regardless of whether the uncertainties actually present numerically quantifiable phenomena. The optimal scenarios are then chosen along the principal components of the distribution, and the results can be easily interpreted and visualized. Notably, our approach requires a relatively small number of numerical assessments, offering an efficient and practical solution for decision-makers. The framework also provides a testable setting for evaluating its performance and allows users to iteratively improve future-related assumptions and predictions. These findings are relevant for all fields that aim to understand potential future developments, such as, but not limited to, foresight, economics, business strategy and strategic intelligence analysis.
Downloadable publication This is an electronic reprint of the original article. |  |
