Abstract
This paper focuses on the spare parts inventory management of a maintenance provider of the health sector, where the commitment to ensure the agreed customer service level and the guarantee of maximum availability of the devices are relevant issues. Spare parts inventory management means handling with unpredictable consumption, since in most cases, it is impossible to know in advance when a specific spare part will be necessary or the needed amount. Determining an adequate inventory management policy for spare parts, specifically for unplanned maintenance operations is essential to provide the contracted service level. Considering that the criticality of a spare part has consequences regarding the availability of an equipment and service level agreement, the spare parts were classified in terms of quantity, value of usage and criticality. Based on this classification, differentiated service levels and inventory management policies were adopted for each group.

Abstract
This paper intends to give some insights on the performance comparison of two main conversion system technologies from a set of wind farms from two major promoters in the Portuguese wind energy sector. Conversion system technologies under analysis are based on the generator type, synchronous and asynchronous, which are the basis of the dominant technological trends in actual market. The performance assessment is accomplished using Data Envelopment Analysis (DEA) methodology, by computing the Malmquist index for group's comparison. From the obtained results, it is possible to conclude that farms with conversion systems based on synchronous generators have a better performance than the ones using conversion systems based on asynchronous generators. These conclusions may support the decision makers in repowering and overpowering processes.

Abstract
This study proposes a Data Envelopment Analysis (DEA) framework to assess the technical efficiency of 26 European countries in the last five years, under the ongoing 2020 energy policy. DEA is used to estimate efficiency which is complemented by bootstrapping to obtain statistical inferences. Further, we explore the relationship between the targets regarding energy efficiency, renewable energy share and the greenhouse gas emissions and, in addition, the electricity prices derived from the energy system on the efficiency levels of European countries through a panel data truncated regression with bootstrapping. It is observed that the bias-corrected efficiency of the economies increased approximately 13%, on average, since 2009. Therefore, the efforts regarding the energy policies developed in each country, to follow 20-20-20 targets, have not threatened the improvement of their efficiency.

Abstract
This study proposes an integrated methodology to provide insights regarding the efficiency of wind farms of two major promoters in the Portuguese energy sector. The focus of the wind farms performance assessment is on the operating stage which corresponds to the electrical energy production process. In a first stage, Data Envelopment Analysis is used to measure the efficiency of wind farms in producing electrical energy from the resources available and exogenous variables. This method is complemented by bootstrapping to refine the efficiency estimates. In a second stage, the factors which may influence the performance of wind farms are investigated by using truncated regression with bootstrapping. The methodology proposed may be used by promoters in management of wind farms and may also be useful to regulator agents on the supervision of the energy market.

Abstract
This study develops a framework to provide insights regarding the performance of the farms of an energy player in the Portuguese wind sector. The focus of the wind farm performance assessment is on the operating stage which corresponds to the electrical energy generation process, during 2010 and 2011. In a first stage, Data Envelopment Analysis is used to measure the efficiency of wind farms in generating electrical energy from the resources available and non-discretionary variables. This analysis enables the identification of the best practices of the efficient farms which can be emulated by inefficient ones. In a second stage, changes in wind farms productivity are investigated using Malmquist index. Bootstrap procedures are applied to obtain statistical inference on the efficiency estimates. We conclude that almost all farms decreased overall productivity levels, mainly due to the decline in the productivity levels of the frontier, which is in accordance with the decrease in wind availability observed in 2011.

Abstract
This study purposes a Data Envelopment Analysis (DEA) framework to assess the performance of Non-Profit Organizations that look after children and young people. The DEA method is used to assess the managerial efficiency of eight institutions from Bragança district, since 2010 to 2013. The model evaluates each institution concerning the reduction of operational and staff costs incurred in providing social services to the number of users observed in each unit. A fair policy for the allocation of subsidies is designed according to the performance of institutions in order to support the regulator.