Bias in normalization: Causes, consequences, detection and remedies
By Reinout Heijungs, Jeroen B. Guinée, R. Kleijn, V. Rovers. 2007
129 citations recorded by the source corpus.
Subfields: Environmental Engineering, Management Science and Operations Research, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/063d0de978b5335470b8da205d8082ef97414330
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Environmental Engineering
- Jeroen B. Guinée
- Reinout Heijungs
- T. Ekvall
- Sangwon Suh
- Göran Finnveden
- Michel Hauschild
- A. Koehler
- S. Hellweg
In Management Science and Operations Research
- J. Seppälä
- Tanja Myllyviita
- Ben A. Wender
- Thomas P. Seager
- Pekka Leskinen
- Valentina Prado
- Bakhtiar Feizizadeh
- Thomas Blaschke
In Strategy and Management
- Reinout Heijungs
- Jeroen B. Guinée
- T. Ekvall
- Michel Hauschild
- Göran Finnveden
- S. Hellweg
- A. Koehler
- D. Pennington
Citations in the corpus
- Impact of normalisation, elicitation technique and background information on panel weighting results in life cycle assessment (2014, background): “However, the problem with external normalisation is that there are large uncertainties related to normalisation (Lautier et al. 2010; Heijungs et al. 2007), and normalisation factors related to less established impact categories may not be available.”
- Recent developments in Life Cycle Assessment. (2009, background): “complicated bias for a normalized score than for an unnormalized score (Heijungs et al., 2007).”
- Interpretation of comparative LCAs: external normalization and a method of mutual differences (2017, background): “tion of impacts of metals has been an issue in impact assessment that leads to an overestimation of ecotoxicity impacts as seen in CML-IA (Ligthart et al. 2004; Heijungs et al. 2007).”
- Stochastic multi-attribute analysis (SMAA) as an interpretation method for comparative life-cycle assessment (LCA) (2014, background): “However, it is now recognized that problems in existing external normalization approaches include reference data gaps (Heijungs et al. 2007), a lack of consensus in data compilation (Bare et al.”