4.6 Article

An integrated sustainability decision-support framework - Part II: Problem analysis

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SAPIENS PUBLISHING
DOI: 10.1080/13504500509469623

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sustainable development; decision-making; multiple criteria decision analysis; multi-attribute decision analysis; problem analysis

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One of the main goals in decision-making for sustainable development is to identify and choose the most sustainable option among different alternatives. This process usually involves a large number of stakeholders with multiple, often conflicting objectives. Facilitating and resolving such difficult decision situations can be complex, so that a more formal and systematic approach to decision-making may be necessary. This paper proposes an integrated multiple criteria decision-support framework specifically developed to provide a systematic, step-by-step guidance to decision-makers. The framework, which is suitable for both corporate and public policy-making in the context of sustainable development, comprises three steps: problem structuring, problem analysis and problem resolution. This paper concentrates on problem analysis and resolution, where decision-makers articulate their preferences for different decision criteria. A suitable Multiple Criteria Decision Analysis (MCDA) technique, such as multi-objective optimisation, goal programming, value-based and outranking approaches, is then used to model the preferences. These techniques are discussed here in some detail, to provide guidance oil the choice of the most appropriate MCDA method. Based on the Outcome of preference modelling, which estimates the overall 'value' of each alternative being considered, decision-makers can then choose the 'best' or most sustainable option. Such an integrated decision-support framework is useful for providing structure to the debate, ensuring dialogue among decision-makers and showing trade-offs between conflicting objectives. In this way, it may be possible to create shared understanding about the issues, generate a sense of common purpose and, often, resolve 'difficult' decision problems.

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