A group MCDA method for aiding decision-making of complex problems in public sector: The case of Belo Monte Dam
Socio-Economic Planning Sciences, ISSN: 0038-0121, Vol: 68, Page: 100625
2019
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
We review the applications of Multiple Criteria Decision Analysis (MCDA) methods in energy sector and in Environmental Impact Assessment (EIA), finding a gap on the non-use of specific methods that deal with divergent opinions, such as a group MCDA method. This way we suggest the application of a group MCDA method to demonstrate how it may be used for aiding group decision-making in public sector. Aiming at analyzing the aforementioned problem, we simulate the choosing of the construction alternatives of Belo Monte Dam. The power plant project was marked by several conflicts among stakeholders due to the generation of diversified environmental, social and economic impacts. The results show that a group MCDA method may be used to aid public sector in the analysis of complex problems, by dividing them into several parts, allowing, therefore, a transparent decision-making process, as well as to solve gaps in the EIA methods.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0038012117300253; http://dx.doi.org/10.1016/j.seps.2018.04.002; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85045438120&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0038012117300253; https://dx.doi.org/10.1016/j.seps.2018.04.002
Elsevier BV
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