Abstract
This paper proposes an innovative composite indicator to evaluate Corporate Social Responsibility (CSR). The methodology proposed involves two stages. The first stage specifies an optimization model, based on Directional Distance Functions, to obtain a relative measure of CSR at the firm level that can guide performance improvements. This model allows distinguishing the firms with best practices from those with potential for improvement and can suggest targets for future achievements. In the second stage, a goal programming model is proposed to identify a common set of weights for the key performance indicators, enabling the evaluation of all firms on common grounds. These weights are used to construct an industry ranking, which is based on the distance of firms to a common frontier of technology that respects the trade-offs determined for the industry. An illustrative application of the method proposed is presented at the end of the paper. The indicators considered in the evaluation were selected according to international standards and guidelines applicable to mining firms. All dimensions of the Triple Bottom Line (economic, environmental and social) were taken into account. The results and their managerial implications are discussed with the objective of promoting the awareness of CSR levels in the mining activity, supporting the sustainable development of industrial activities.

Abstract
Electric power systems are facing significant challenges regarding their organization and structure. Energy infrastructures are crucial to ensure a transition to low-carbon societies, contributing to sustainable development. This paper uses Data Envelopment Analysis to compare the performance of the power systems in 16 European countries using data available to the public. Three perspectives were considered, focusing on technical aspects affecting quality of service, network costs and environmental impact. It is proposed a new formulation of the DEA model that estimates a composite indicator (CI) aggregating individual indicators which should be minimized. The benchmarking results can give insights to electric operators, regulators and decision-makers on the strengths and weakness of national power systems and disclose the potential for performance improvements. Based on the outcomes from the CI model, Austria, Croatia, Denmark, Germany, Greece, Ireland, Italy and Netherlands are identified as the benchmarks for the power systems in the Europe. The discussion of the results is intended to raise public awareness on the performance of the European power systems and contribute to the definition of public policies for the promotion of continuous improvement. © 2019, Springer Nature Switzerland AG.

Abstract
The performance evaluation of education systems is at the top of the agenda of governments and education authorities worldwide. However, research involving cross-country comparisons of the performance of education systems is still incipient. This paper proposes a new composite indicator to summarise the performance of education systems, enabling benchmarking comparisons and the definition of objectives for improvement. The research analyses different modelling alternatives for the construction of composite indicators, with varying degrees of weight flexibility. Our study uses annual data of 29 European countries, collected from Eurostat and the Organisation for Economic Co-operation and Development databases. The results obtained in terms of performance scores and country rankings are presented and their managerial implications are discussed. We conclude that composite indicators estimated using frontier techniques can support the transition from the paradigm of performance assessment (control) to performance management (improvement).

Abstract
The search for logistics best-practices in international trade has led to the appearance of the Berth Allocation Problem. If the vessels have release dates, the problem is proved to be NP-hard and the performance of exact algorithms is not satisfactory, leading to the use of metaheuristics. This paper develops a Hybrid Evolutionary Algorithm for the discrete and dynamic Berth Allocation Problem. A challenge of using Genetic Algorithms is the identification of the best approach to model a specific problem. This paper proposes the use of frontier techniques (Data Envelopment Analysis and Free Disposal Hull models) to compare the performances of alternative specifications of the parameters for the algorithm proposed and to identify efficient solutions.

Abstract
Backrooms are an important echelon of the retail supply chain. However, research focus has been mostly targeted to optimise both distribution centres and stores' sales area. In this paper, we propose two mathematical programming formulations to solve the grocery backroom sizing problem. This problem consists of determining the dimension of each storage department in the backroom area to optimise its overall efficiency. The first formulation is a bottom-up approach that aims to reduce the backroom life-cycle costs by determining the optimum floor space and storage height for each department. The second is a top-down approach based on Data Envelopment Analysis (DEA), which determines the efficient level of storage floor space for each backroom department, based on a comparison with the benchmarks observed among existing stores. Each approach has distinct characteristics that turn the models suitable for different retail contexts. We also describe the application of the proposed approaches to a case study of a European retailer. The application of this methodology in the design process demonstrated substantial potential for space savings (6% for the bottom-up model and 16% for the top-down model). This space reduction should either allow higher revenues in the sales area and/or lower backroom-related costs.

Abstract
The performance of secondary schools is usually assessed based on students' results on national exams at the end of secondary education. This research uses data on academic achievements by first-year university students to benchmark secondary schools on their ability to lead students to success in higher education. The analysis is conducted using data of University of Porto and Catholic University of Porto, Portugal, for a three-year period, corresponding to more than 10.000 students from 65 degrees, for which the school of origin is known. A number of variables representing students' success in Higher education were constructed for each school in our sample and aggregated through a Benefit of the Doubt indicator. Results suggest that the schools' ranking based on schools' ability to prepare students for university success is quite different from the ranking based on results on national exams. Given these findings, we propose complementing schools' performance assessments (traditionally based on national exam results or indicators of value added) with indicators that account for the preparation of students for success in future challenges, which is indisputably a key objective of secondary education. We propose a composite indicator for the analysis of these complementary aims as well, and results show that frontier units indeed exhibit trade offs between traditional measures of performance and our new measure of performance.