The requirement for congruence in normalization
By Gregory A. Norris. 2001
102 citations recorded by the source corpus.
Subfields: Building and Construction, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/6736e7bd1c07f40b9e4af0a5092e539b063b88b7
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Building and Construction
- Jeroen B. Guinée
- Masanobu Ishikawa
- J. Seppälä
- Thomas P. Seager
- Reinout Heijungs
- Pekka Leskinen
- Tanja Myllyviita
- Gjalt Huppes
In Environmental Engineering
- Reinout Heijungs
- Jeroen B. Guinée
- Gjalt Huppes
- V. Rovers
- Masanobu Ishikawa
- R. Kleijn
- J. Seppälä
- Thomas P. Seager
Citations in the corpus
- A Framework for Quantified Eco‐efficiency Analysis (2005, methodology): “Placing the eco-efficiency analysis in a broader societal efficiency context requires a case-independent specification of the axes (see work by Heijungs et al. 1992 and Norris 2001).”
- Bias in normalization: Causes, consequences, detection and remedies (2007, background): “For instance, when there are 5 product alternatives, all impact scores are normalized in a way that they fall between 0 and 1. As observed by Norris (2001) , internal normalization does not allow for an assessment of relative significance, whereas external normalization, of which the use of a regio”
- Impact of normalisation, elicitation technique and background information on panel weighting results in life cycle assessment (2014, methodology): “External normalisation relates to a magnitude of impacts caused by a studied product system on a certain reference value (Finnveden et al. 2002; Norris 2001).”
- Stochastic multi-attribute analysis (SMAA) as an interpretation method for comparative life-cycle assessment (LCA) (2014, background): “Although internal normalization approaches in the absence of preference and indifference thresholds may result in “absurd” conclusions (Norris 2001), outranking avoids these pitfalls by distinguishing between negligible and significant differences (Prado et al.”