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This study proposes an integrated qualitative and quantitative assessment of expert opinions aiming at ranking a set of five shantytowns (favelas) located in the city of Rio de Janeiro. These communities are candidates for investments in an energy efficiency program implemented by the local electric utility company. The city, state, and federal governments want to eliminate domination of these areas by organized criminal gangs and present the city as a peaceful metropolis while hosting two big sports events: the soccer World Cup in 2014 and the Olympic Games in 2016. In recent years, some favelas were chosen to be prototypes for an ambitious project to reshape Rio de Janeiro. This involves first sending in special tactics police to drive drug gangs out, then installing the Pacifying Police Unit in the favela. Once security has been established, it is possible to improve general living conditions in these areas, including by providing public services such as health clinics, formal electricity connections and cable television. The core of the energy efficiency program was to convert informal customers to formal ones, because such communities were responsible for approximately 40% of the commercial losses (stolen energy) in the city. The model specification presented in this paper was set up with ten relevant criteria for decision making, identified through an in-depth interview with the decision maker. The relative importance of the criteria and the performance of each favela regarding each criterion were measured by the Simos method. The preferences resulting from this method were translated into a nine-point scale. The imprecision of subjective judgment was partially compensated by using a fuzzy analytical hierarchy process. Some criteria were ordinal, such as 'Fair Relationship with the Community' and 'Complexity to Rebuild the Distribution Lines', whereas other were cardinal, like 'Percentage of Clients in Default' and 'Commercial Loss Due to Energy Theft'. At the end, the model was efficient in ranking the five favelas, therefore contributing to a rational and transparent approach for capital investment in social projects.

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This data article employs the Fuzzy Analytic Hierarchy Process (FAHP) to perform the project risk assessment in a phase of the construction of a large hydroelectric project. The list of service packs and risk events was extracted from in-depth interviews and content analysis with experts. Such qualitative data were used to identify the relevant service pack and risk event indicators for two groups – the owner's and the builder's representatives – required to specify the model. FAHP was used to calculate the relative importance of such indicators in two stages. First the relevance of the service packs was measured through paired comparisons and then weighted. Next, the relevance of the risk events associated with each service pack was assessed through the same method. A complete method of calculation for one of the respondents is presented. At the end, the average weights for the risk events of the two groups are calculated. For further information it is recommended to read the article entitled “Multi-criteria risk assessment: Case study of a large hydroelectric project” (Ribas et al., 2019).