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This study addresses the problem of finding the range of efficiency for each Decision Making Unit (DMU) considering uncertain data. Uncertainty in the DMU coefficients in each factor (input or output) is captured through interval coefficients (i.e., these are uncertain but bounded). A twophase additive Data Envelopment Analysis (DEA) model for performance evaluation is used, which is adapted to include the concept of super-efficiency to provide a robustness analysis of the DMUs in face of uncertain information, assessing whether each DMU is surely efficient, potentially efficient, or surely inefficient for the uncertainty intervals specified. Another contribution is to present how a maximal stability hyper-rectangle can be computed for each DMU such that its efficiency status does not change when the coefficients vary within that interval.

Benchmarking of electricity distribution utilities has been widely used as a means to contribute for the adoption or reinforcement of enhanced competitiveness and innovation practices to optimize costs, increase customer satisfaction, improve corporate image and maximize profits. The purpose of this paper is to present a benchmarking study for the maintenance and outage repair activity carried out by a Portuguese electricity distribution company, EDP Distribuição (EDP-D), using the Value-Based DEA method, which builds on links between Data Envelopment Analysis (DEA) and Multiple Criteria Decision Analysis (MCDA). This study illustrates the impact of the incorporation of managerial preferences in the classification and ranking of 40 network areas served by EDP-D, confronting the results with a previous study based on a BCC DEA model. In order to deal with the underlying uncertainty, the Value-Based DEA method for performance evaluation is adapted to include the concept of super-efficiency. Besides identifying best practices, sources of inefficiency, gaps relatively to best practices and opportunities for improvement, this analysis supports the introduction of corrective measures and informs decisions about future goals.

The research interest in bank profitability and efficiency is linked to the economic situation and an important issue for policymakers is to ensure economic stability. Nevertheless, managerial decisions and the environment could play a critical role in ensuring proper and efficient allocation of the resources. The purpose of this study is to understand which are the main factors that can influence the performance and efficiency of 94 commercial listed banks from Eurozone countries through a dynamic evaluation, in the period between 2011 and 2016. To achieve this aim, the generalized method of moments estimator technique is used to analyze the influence of some bank-specific characteristics, controlled by management, on the profitability as a measure of bank performance. After that, through the value-based data envelopment analysis (DEA) methodology, those factors are considered in determining the efficient banks. The results show that banking efficiency depends on set bank-specific characteristics and that the effect of determinants on efficiency differs, considering the macroeconomic conditions.

ABSTRACT. In 2005 a new phase for Primary Health Care (PHC) in Portugal began, leading to the voluntary and independent creation of Family Health Units. The impact of this reform is now being witnessed, which justifies the need to evaluate its results as far as best practices in PHC are concerned.This work uses a Value-Based Data Envelopment Analysis (DEA) method, which combines an additive DEA model with Multi-Criteria Decision Analysis (MCDA) concepts, to allow incorporating managerial preferences in the performance assessment of 12 health centres in a Portuguese region. Two models are presented for evaluating access to PHC, which resulted from discussions with a group of decision makers.This analysis helped the decision makers in the identification of best practices, sources of inefficiency and gaps relatively to the best practices, thus leading to shape opportunities for improvement.

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The increased volatility in capital markets since the outbreak of the 2008 global financial crisis and the investor´s lack of confidence in the banking sector represented significant challenges to portfolio fund managers. The current study assesses the performance of Portuguese mutual fund portfolios considering the period 2007-2014 using the Value-Based DEA method. This approach combines Data Envelopment Analysis (DEA) with Multiple Criteria Decision Aiding (MCDA). A dynamic evaluation including value judgements is carried out using data from 15 Portuguese equity funds. The results unveil the impact of the global crisis in the Portuguese investment funds industry. They show that Portuguese investment funds performed better between 2011 and 2013; this suggests that equity funds investors became more confident in these vehicles due to political measures reinforcing financial markets. The methodology followed in this study contributes to help investors in the identification of the funds with the best practices according to their judgments.

The European Regional Development Fund devoted around 66 billion Euros to the financial support of innovation and productivity in European enterprises over the 2014–2020 programming period. In this framework, we assessed the implementation of the Operational Programmes dedicated to fostering research and innovation, particularly in small and medium-sized enterprises. With this aim, we used a network slack-based data envelopment analysis model paired with cluster analysis that encompasses a multitude of performance framework indicators to assess 53 Operational Programmes from 19 countries. Our findings suggest that compared to transition and less developed regions, more developed regions present a higher room for improvement. Also, less developed regions present a better performance when they employ their funding against more developed regions, suggesting that further funding should be channelled for leveraging research and innovation in the former regions. Finally, Operational Programme managers should focus on solving the problems both inherent to the poor outcomes in terms of enhancing the number of researchers working in improved research infrastructures and promoting the technology transfer between research institutions and enterprises.