By switching to dark mode you can reduce the energy consumption of our digital service.

Multi-criteria analysis (MCA)

MCA is a well-known method (or more accurately, family of methods) for evaluation of alternatives according to multiple decision criteria.
mca image


MCA is a well-known method (or more accurately, family of methods) for evaluation of alternatives according to multiple decision criteria. An evaluation is based on the selection of one or more algorithms, which support different interpretations of what inputs and analytical processes are important to a decision, and their application to produce rankings and/or scorings of these alternatives.

MCA has the following characteristics that make it well-suited to support analysis of environmental problem domains and as a management tool to support decision-making:

  • multiple impacts can be explicitly considered and can be cross-examined in terms of impacts on different stakeholders
  • it does not require the monetary evaluation of decision outcomes, such as those involving environmental resources which are difficult to value in such terms (they also have non-use values)
  • a strong participatory component, (i.e. expert judgement) can be included to produce a jointly defined set of criteria, and in this way different points of view can be incorporated
  • such participation also necessitates the different stakeholders to articulate their preferences

MCA is often implemented with the use of a computer-aided support tool for the application of algorithms in the evaluation phase. These tools, which make use of MCA methods, are often also described as Decision Support Systems (DSSs)

Application to adaptation decision-making

MCA is a popular approach in environmental decision-making and has provided a basis for decision support tools applied notably in the sectors of water resources management (such as mDSS) and in agriculture (such as NAIADE).

In terms of IVA (Impacts, Vulnerability and Adaptation) models, methods and metrics it has also been identified and used for many years. This is particularly notable in vulnerability assessment, where MCA has been mandated as a tool in the NAPAs (see this page and the main programme website) although its use in decision analysis remains uncertain in the gap between full economic appraisal and deliberative techniques that do not seek to solve the ‘what is best’ question.

In a recent review of the ‘toolbox of IVA’ the Mediation project has highlighted several areas for improvement in the provision of advanced tools for implementation and assessment of climate change adaptation:

  • More emphasis on uncertainty within models and methods
  • Greater access to tools
  • More novel means of conveying information about tools

A closely related technique is the Analytic Hierarchy Process (AHP). It similarly takes into consideration multiple criteria, however it is based solely on eliciting individuals’ preferences rather than requiring additional input data. It uses pairwise comparison to score alternative options relative to a well-specified goal.

Case studies

As part of the Yemen NCAP project, priority adaptation options were studied in three sites in Yemen using an MCA analysis among local stakeholders.

The Ghanan NCAP project used MCA to explore the multi-objective decision space of cross-sector project planning and produce a prioritized list of adaptation options.

Further Reading

Mysiak, J., Giupponi, C., & Rosato, P., (2005), ‘Towards the development of a decision support system for water resource management’, Environmental Modelling and Software, 20(2), 203-214. see the paper on Science Direct

Giupponi, C., (2007), ‘Decision Support Systems for Implementing the European Water Framework Directive: the MULINO approach’, Environmental Modelling and Software, 22(2), 248-258. see the paper on Science Direct

Download mDSS software here:

Decision Support Systems that use the MCA approach

Other related pages

Add your project

Exchange your climate change adaptation projects and lessons learned with the global community.