title: A comparison of partial order technique with three methods of multi-criteria analysis for ranking of chemical substances.
abstract: An alternative to the often cumbersome and time-consuming risk assessments of chemical substances could be more reliable and advanced priority setting methods. An elaboration of the simple scoring methods is provided by Hasse Diagram Technique (HDT) and/or Multi-Criteria Analysis (MCA). The present study provides an in depth evaluation of HDT relative to three MCA techniques. The new and main methodological step in the comparison is the use of probability concepts based on mathematical tools such as linear extensions of partially ordered sets and Monte Carlo simulations. A data set consisting of 12 High Production Volume Chemicals (HPVCs) is used for illustration. It is a paradigm in this investigation to claim that the need of external input (often subjective weightings of criteria) should be minimized and that the transparency should be maximized in any multicriteria prioritisation. The study illustrates that the Hasse diagram technique (HDT) needs least external input, is most transparent and is least subjective. However, HDT has some weaknesses if there are criteria which exclude each other. Then weighting is needed. Multi-Criteria Analysis (i.e. Utility Function approach, PROMETHEE and concordance analysis) can deal with such mutual exclusions because their formalisms to quantify preferences allow participation e.g. weighting of criteria. Consequently MCA include more subjectivity and loose transparency. The recommendation which arises from this study is that the first step in decision making is to run HDT and as the second step possibly is to run one of the MCA algorithms.
authors.affiliation: Department of Chemistry, The HC Ørsted Institute, Copenhagen University, Universitetsparken 5, DK-2100 Copenhagen Ø, Denmark.
authors.forename: Dorte
authors.initials: D
authors.lastname: Lerche
authors.forename: Rainer
authors.initials: R
authors.lastname: Brüggemann
authors.forename: Peter
authors.initials: P
authors.lastname: Sørensen
authors.forename: Lars
authors.initials: L
authors.lastname: Carlsen
authors.forename: Ole John
authors.initials: OJ
authors.lastname: Nielsen
mesh_terms: D002617:Chemical Industry; D003198:Computer Simulation; D064420:Drug-Related Side Effects and Adverse Reactions; D005060:Europe; D006801:Humans; D008956:Models, Chemical; D009010:Monte Carlo Method; D011336:Probability; D018570:Risk Assessment; D012308:Risk Management