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DecisionSupport 7uses numerical values (e.g. as in the scale below)to conduct the pairwise comparisons,constructing a set of pairwise comparisonmatrices. Several matrices are produced tocompare the alternatives (e.g. adaptationoptions) with respect to each criteria, and thecriteria with respect to the goal.4. Calculate relative priorities. This can be doneusing a spreadsheet, or software, such asExpertChoice. 1 The values in Step 3 areprocessed to obtain numerical priorities orweights for the criteria and alternatives.Depending on the problem at hand, a priority orweight can refer to importance, preference orlikelihood.5. Aggregate priorities. The final step is toaggregate relative priorities to produce overallpriorities (final evaluation metrics) which sum to1.0.The Application to AdaptationAHP has been used in a wide variety of fieldsincluding engineering, business strategicmanagement, education and quality assessment.The approach has high relevance for the analysisof climate adaptation related decisions, given itis useful where a range of stakeholders aredealing with issues that have a high degree ofcomplexity, that involve uncertainty and risk, andinclude subjectivity, i.e. human perceptions andjudgments. It is also potentially useful when theoutcomes have possible long-termconsequences (Bhushan, 2004).The tool has a particular relevance whereimportant elements of the decision are difficult toquantify or compare, or where different expertise,goals, and world-views are a barrier toconsensus-building and communication.In the context of climate adaptation, the methodcan be used to compare a set of adaptationoptions against a set of defined criteria usingparticipants’ experience and judgment about theissues of concern. It allows the comparison ofdiverse elements that are often difficult tomeasure in a structured and systematic wayusing a scale. This makes it particularly relevantfor sectors or key criteria where quantification ischallenging.The first applications of the approach to climatechange were in the context of the globalnegotiations on climate change (Ramanathan,1998) and later in mitigation policy instruments(Konidari and Mavrakis, 2007). AHP is nowincreasingly being applied in the area of climatechange adaptation. It was applied using aparticipatory approach for the integration ofindigenous knowledge within adaptationstrategies in the Tabasco Plains of Mexico(Ponce-Hernandez and Patel, forthcoming), inthe evaluation of adaptation options for humansettlements in South East Queensland (Choy etal., 2012), in the integration of GIS modelling tolook at crop impacts in Australia (Sposito, 2006)and to explore the impacts of storm surge andsea level rise in Canada and Caribbean (Laneand Watson, 2010). Yin et al (2008) applied AHPto evaluate adaptation options for the watersector in the Heihe River Basin in north-westernChina, resulting in a higher preference forinstitutional options for managing water demand(imposing constraints on large consumers, waterconservation initiatives through water userassociations, and transferrable water allocationpermits), rather than ‘hard’ engineering optionsfor increasing water supply.1http://expertchoice.com/2
Analytic Hierarchy ProcessThe AHP method can evaluate adaptationoptions against a range of different criteria in thecontext of an overarching climate adaptationgoal by comparing them to one another, two at atime (pairwise comparison). These comparisonsare made using a scale that represents howmuch more one element is preferential to anothergiven the criteria and options chosen are asmutually exclusive as possible.Strengths and WeaknessesA key part of the MEDIATION project has been toidentify the strengths and weaknesses ofdifferent approaches. A summary of some of thestrengths and weakness is outlined below.The main strength of AHP is the ability to directlycompare tangible and intangible elements, takinginto account the opinions and preferences of awide range of people in the analysis of complexproblems. This allows it to be used in contexts inwhich other decision tools cannot be used. Theapproach also provides results in a simpleranking that is easy to communicate. As well asthe application in areas where quantification orvaluation is difficult, it can also compare optionsagainst qualitative criteria, even in areas whichare not directly comparable using conventionaldecision support techniques.The potential weaknesses relate to the increasedcomplexity of application and time taken to applythe approach if many criteria, sub-criteria andoptions are considered, and the somewhatsubjective nature of the results (athough aninconsistency index can be calculated. The useof software can also conceal conflicting valuejudgments.Case StudiesThe MEDIATION study has reviewed existingliterature examples that have applied AHP toadaptation. The project has also undertaken twocase study applications, summarised in theboxes belowKey strengths• Can be applied to complex problems wheredecision elements are difficult to quantify ornot directly comparable.• Relatively simple approach and producessimple rankings that are easy to communicate.• Does not require information on economicbenefits and monetary valuation, and so it isapplicable to areas that are difficult to value(e.g. ecosystems), difficult to quantify (e.g.equity) or that are contentious.• Can accommodate a wide range of disciplines,opinions and groups of people who do notnormally interact.Potential weaknesses• Results change as new options / alternativesare considered in the analysis.• Becomes complicated if many criteria andoptions are considered. Some criteria are notindependent so this can bias or complicate theway in which they are assessed.• Subjective scale can lead to biases and it issubject to human error.• The use of software can conceal conflictingvalue judgments.• Linked to the previous point, trans-disciplinarycapacity building can be undermined at thecost of the expediency (Cartwright et al., 2012)3
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Key Messages• There is increasing
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DecisionSupport 1Stage three relate
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Method OverviewAs a result there is
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Iterative Risk AssessmentMethod Ove
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Method Overviewhttp://reports.eea.e
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Further informationThe research lea
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Key Messages• There is increasing
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DecisionSupport 2Box 2. Comparing M
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DecisionSupport 2location and techn
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DecisionSupport 2Discussion and App
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DecisionSupport 2ReferencesBoyd, R
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