Wikis > Formulation Tools > Multicriteria Analysis (MCA)
Primary Source: Armines, P. (2006) Multicriteria Analysis in Report on the SWOT analysis of concepts, methods, and models potentially supporting LCA. Eds. Schepelmann, Ritthoff & Santman (Wuppertal Institute for Climate and Energy) & Jeswani and Azapagic (University of Manchester), pp 149-152

Level of analysis: Micro, meso and macro

Assessed aspects of sustainability: environmental, economic

Main purpose of the assessment:

Choose among different proposed actions (e.g. environmental directive, choice of technology, environmental policy, …) if there are criteria that have not been evaluated in monetary terms.

Description of the methodology:

Multi-Criteria Analysis (MCA) (often called Multi- Criteria Decision Analysis – MCDA) provides the methodological tools to help decision makers to effectively handle complex decision situations in which the level of conflict between criteria is such that intuitive solutions cannot be satisfactory. There are several different MCA methods. Some involve asking the participants in an MCA to indicate weighting factors for the various criteria under consideration; others involve the elicitation of preference rankings between each pair of alternative choices.

Detailed Description

Multi-Criteria Analysis (MCA) (often called Multi-Criteria Decision Analysis – MCDA) provides the methodological tools to help decision makers to effectively handle complex decision situations in which the level of conflict between criteria is such that intuitive solutions cannot be satisfactory [see e.g. Zeleny 1982]. MCA can support comparison of different policy/project options, using and weighting multidimensional and not homogeneous sets of criteria and identifying the effects of these options and the trade-offs among the different involved aspects; as consequence MCA can be used as alternative or in combination with methods using monetary comparison, as CBA. In addition, MCA can help in resolving disagreement if stakeholders have different views on the relative importance of the considered criteria. It is important to stress that MCA is not a tool providing the right solution in a decision problem, simply because no such solution exists. Instead, it is an aid to decision making that helps stakeholders organize the available information, think on the consequences, explore their own wishes and tolerances and minimize the possibility for a post-decision disappointment [Belton and Stewart, 2002].

In the last 30 years, MCA methods have undergone remarkable progress in the framework of Operational Research and Decision Sciences. This progress is manifest not only in the impressive number of communications in scientific journals and conferences, but also in the increasing use of MCA approaches in real-life problems in the public or private sector. Because of its capacity to handle conflicting decision situations, MCA is particularly suited for sustainability problems where the aim is the integration of economic, environmental and social values.

MCA relies on preference elicitation methods aiming at gradually constructing values for unfamiliar goods, rather than revealing some ‘true’ values hidden in the human mind. More specifically, the following advantages of MCDA methods are emphasized in the literature:

–          MCA methods can consider a large variety of criteria independently of the type of data (quantitative or qualitative) and the measurement scale. Hence, it allows for a comprehensive analysis including all various aspects of sustainability and not only marketed goods or monetized costs and benefits [Omann, 2000].

–          MCA directly involves the stakeholders facing a particular decision problem in order to detect their own preferences and values regarding the decision criteria. Hence, the extracted values better reflect the concerns and priorities of the people concerned.

–          MCA acts as an interactive learning procedure that motivates stakeholders to think harder about the conflicts addressed by taking into account other points of view and opposing arguments [Martinez-Alier et al., 1998, Omann, 2000]. Such a transparent and constructive procedure enables stakeholders to better understand the problem at hand and eventually arrive at a better and commonly accepted solution [Faucheux and Froger, 1995; Lahdelma et al. 2000].

–          MCA is a multi-disciplinary approach that is capable of better capturing the complexity of natural systems, the plurality of values associated with environmental goods and the variant perceptions of sustainable development [Toman, 1997]. The stakeholders participating in a MCDA procedure have the possibility and the responsibility to go beyond their own discipline and to take into account perspectives and information that are possibly fields from other disciplines.

A multiplicity of MCA methods is currently available for use in a wide variety of situations. These methods distinguish themselves through the used decision rules (compensatory, partial compensatory and not compensatory, where compensability refers to the possibility of compensating the different criteria among them) and through the type of data (quantitative, qualitative or mixed). Furthermore, several weighting techniques have been developed to help stakeholders involved in a MCA procedure understand and articulate their preferences concerning the relative importance of the examined criteria. Sensitivity analysis is used to check the robustness of the result for changes in scores or weights.

In terms of the theoretical background and the key assumptions adopted in the modelling procedure and in the aggregation of the performances and/or preferences regarding the decision criteria, MCDA methods can be divided into two broad categories, as follows:

Multi-Attribute Value Theory methods (MAVT) try to associate a unique number (‘value’) representing the overall strength of each alternative if all criteria are taken into account

Outranking methods trying to associate a preference index to each pair of alternatives that is further exploited to rank alternatives in a descending order of preference.

Between these two categories, MAVT methods offer the advantage of greater simplicity and transparency. In addition, they are more compatible with cost-benefit analysis because they use a similar utilitarian background where decisions result from explicit or implicit trade-offs between conflicting interests or points of view. Although trade-offs are not acceptable under a strong sustainability perspective, they represent the most realistic approach for implementing the sustainability concept in practice.

For an interesting example of the use of MCA for environmental choices, see the SusTools project of the EC DG Research [Rabl et al 2004]. In this project two environmental problems were addressed in an MCA workshop with stakeholders: the treatment of waste, and the use of nitrogen fertilizer.


Compared to CBA (cost benefit analysis) the strength of MCA is the ability to include qualitative criteria. This is a crucial advantage for certain sustainability problems because not all impacts can be quantified in terms of monetary values, for example the risks of nuclear proliferation. For some impact categories, such as ecosystem impacts, reliable monetary values are not yet available, and the damage cost of greenhouse gases is still very uncertain and controversial. Furthermore, many decisions will involve additional considerations beyond economics, for instance equity. For choices that involve non-quantified impacts or considerations, one needs MCA.


Compared to CBA, MCA has a serious problem with the representativeness of its results because in practice it is notoriously difficult to achieve the participation of a representative sample of all the concerned stakeholders in any MCA exercise: most of the stakeholders who are invited refuse because they are too busy, and the ones who end up participating are rarely representative enough.

By contrast, the methods used by economists to determine monetary values for such impacts as health and mortality, reduced visibility, noise, global warming etc (see e.g. the Methodology2005 Update of ExternE [2005]) are designed to yield representative results. In particular the contingent valuation method, now very mature and frequently used for valuing environmental goods [Mitchell and Carson 1989], involves interviewing large representative samples of the concerned population (at least several hundred, usually on the order of a thousand). For many impact types the literature contains several valuation studies that can be compared. In any case, standardized and generally accepted monetary values based on economic analysis are necessary to make policy decisions consistent with the preferences of the population as expressed in the transactions of the market.

Opportunities for broadening and deepening LCA

The main advantage of MCA, compared to CBA, is the ability to deal with criteria or impacts that are too difficult to express in monetary terms, for example the risks of nuclear proliferation for nuclear power. In particular, social impacts are practically impossible to reduce to monetary values, and therefore MCA is necessary for broadening LCA to social impacts.

Another advantage, at least in principle, is the possibility of involving the stakeholders directly in the decision process. However, in practice it is notoriously difficult to achieve theparticipation of a representative sample of all the concerned stakeholders: most of thestakeholders who are invited refuse because they are too busy, and the ones who end upparticipating are rarely representative enough.

The most promising approach is to combine CBA and MCA, i.e. use monetary values as much as possible and then proceed to MCA to account for impacts and criteria which can be expressed only in qualitative terms. In any case, decision makers always use some kind of informal assessment of multiple criteria, however subjective it may be in a particular case. A more rigorous formal MCA approach can only improve the quality of the decisions.

Threats for broadening and deepening LCA

The main threat to the use of MCA for broadening LCA lies in the cost and difficulty of carrying out an MCA exercise with a sufficiently representative sample of stakeholders to yield representative results.

Literature/Internet links

Belton, V. and Stewart, T. J., (2002), Multiple Criteria Decision Analysis: An integrated approach. Kluwer Academic Publishers, Dordrecht.

ExternE 2005. ExternE – Externalities Of Energy: Methodology 2005 Update. Available at

Faucheux, S., and Froger, G., (1995), Decision making under environmental uncertainty. Ecological Economics, 15, 29-42

Lahdelma, R., Salminen, P., Hokkanen, J., (2000), Using Multicriteria Methods in Environmental Planning and Management. Environmental Management, 26 (6), 595-605.

Martinez–Alier J., Munda G., O’Neill J., (1998), Weak comparability of values as a foundation for ecological economics. Ecological Economics, 26, 277-286.

Omann, I., (2000), How can Multi-criteria Decision Analysis contribute to environmental policy making? A case study on macro-sustainability in Germany. Paper for the Third International Conference of the European Society for Ecological Economics, Vienna.

Rabl A, Zoughaib A, von Blottnitz H, Holland M, Torfs R, van der Linden A, Diakoulaki D, Taylor T, Arnold S, Scasny M, Havranek M, Kovanda J & Boyadjiev D. 2004. “Tools for sustainability: Development and application of an integrated framework”. Final Technical Report, contract N° EVG3-CT-2002-80010. EC DG Research. Available at

Toman, M., (1998), “Sustainable Decision Making: The state of the art from an economic perspective”. Discussion Paper 98–39, Resources for the Future, Washington DC.

Zeleny M., (1982), Multiple Criteria Decision Making, McGraw-Hill, NY.