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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.08488 |
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| _version_ | 1866908446055464960 |
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| author | Straub, Daniel Betz, Wolfgang Ruf, Mara Hoffmann, Amelie Landgraf, Angela Friedli, Lea Papaioannou, Iason |
| author_facet | Straub, Daniel Betz, Wolfgang Ruf, Mara Hoffmann, Amelie Landgraf, Angela Friedli, Lea Papaioannou, Iason |
| contents | Information value, a measure for decision sensitivity, can provide essential information in engineering and environmental assessments. It quantifies the potential for improved decision-making when reducing uncertainty in specific inputs. By contrast to other sensitivity measures, it admits not only a relative ranking of input factors but also an absolute interpretation through statements like ''Eliminating the uncertainty in factor $A$ has an expected value of $5000$ Euro''. In this paper, we present a comprehensive overview of the information value by presenting the theory and methods in view of their application to engineering and environmental assessments. We show how one should differentiate between aleatory and epistemic uncertainty in the analysis. Furthermore, we introduce the evaluation of the information value in applications where the decision is described by a continuous parameter. The paper concludes with two real-life applications of the information value to highlight its power in supporting decision-making in engineering and environmental applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_08488 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Sensitivity measures for engineering and environmental decision support Straub, Daniel Betz, Wolfgang Ruf, Mara Hoffmann, Amelie Landgraf, Angela Friedli, Lea Papaioannou, Iason Applications Information value, a measure for decision sensitivity, can provide essential information in engineering and environmental assessments. It quantifies the potential for improved decision-making when reducing uncertainty in specific inputs. By contrast to other sensitivity measures, it admits not only a relative ranking of input factors but also an absolute interpretation through statements like ''Eliminating the uncertainty in factor $A$ has an expected value of $5000$ Euro''. In this paper, we present a comprehensive overview of the information value by presenting the theory and methods in view of their application to engineering and environmental assessments. We show how one should differentiate between aleatory and epistemic uncertainty in the analysis. Furthermore, we introduce the evaluation of the information value in applications where the decision is described by a continuous parameter. The paper concludes with two real-life applications of the information value to highlight its power in supporting decision-making in engineering and environmental applications. |
| title | Sensitivity measures for engineering and environmental decision support |
| topic | Applications |
| url | https://arxiv.org/abs/2507.08488 |