Speaker
Description
Impact assessment often requires comparing alternatives whose consequences differ across criteria, stakeholders, and time horizons. Although multi-criteria decision analysis (MCDA) is widely used to structure such problems, temporal assumptions are often treated only implicitly, despite their potential influence on final rankings. This paper proposes an outranking-based framework for incorporating temporal preferences into multi-criteria impact assessment. The approach constructs period-specific outranking matrices and aggregates them using normalized discount factors, thereby preserving pairwise preference information until the final temporal aggregation step. Combined with semantic-distance-based comparisons, the framework can handle heterogeneous score types, including quantitative, qualitative, fuzzy, and stochastic information. The contribution is a discount-factor-based temporal aggregation layer that operates on complete period-specific outranking matrices before the final ranking is derived. We also propose local and global sensitivity analyses to assess how rankings respond to alternative assumptions about the relative importance of future periods. An illustrative electricity-sector application based on NREL ATB data shows that temporal assumptions can induce rank reversals between alternatives. Our findings highlight the importance of making intertemporal value judgements explicit in multi-dimensional impact assessment, particularly when policy-relevant alternatives differ in their short-term performance and long-term sustainability implications.
| Keywords | Multi-criteria decision analysis; Impact assessment; Temporal weighting; Discounting; Outranking; Sensitivity analysis; Semantic distance |
|---|---|
| Participation in the SNSF Early-Stage Researcher Support and Award Scheme | I am submitting a regular presentation but do not wish to participate in the scheme. |