Abstract
This paper describes the assessment of performance of educational services recurring to benchmarking. We adopted two perspectives for the evaluation of secondary schools, aligned with the objectives of different stakeholders. In the society perspective schools are viewed as promoting students achievement ( ideally including not only academic results but also interpersonal capacities) given the students characteristics in terms of academic abilities and socio-economic backgrounds. In the educational authorities perspective schools are viewed as transforming a set of resources ( including students with given characteristics in terms of academic abilities and socioeconomic backgrounds and also school resources, such as teachers) into students achievement. The relative performance assessment was carried out using Data Envelopment Analysis models, followed by an exploratory analysis of contextual indicators that potentially affect schools' performance, in order to understand their impact on the educational process.

Abstract
Purpose - In a context of international economic crisis the improvement in the efficiency and productivity of public services is seen as a way to maintain high-quality levels at lower costs. Increased productivity can be promoted through benchmarking exercises, where key performance indicators (KPIs), individually or aggregated, are used to compare health units. The purpose of this paper is to describe a benchmarking platform, called Hospital Benchmarking (HOBE), where hospital's services are used as the unit of analysis. Design/methodology/approach - HOBE platform includes a set of managerial indicators through which hospital services' are compared. The platform also benchmarks services through aggregate service indicators, and provides an aggregate measure of hospital's performance based on a composite indicator of the service's performances. These aggregate indicators were obtained through data envelopment analysis (DEA). Findings - Some results are presented for Portuguese hospitals for the trial years of 2008 and 2009, for which data is publicly available. Details for the service-level analysis are provided for a sample hospital, as well as details on the aggregate performance resulting from services performances. Practical implications - HOBE's features and outcomes show that the platform can be used to guide management actions and to support the design of health policies by administrative authorities, provided that good quality and timely data are available, and that hospitals are involved in the design of the KPIs. Originality/value - The platform is innovative in the sense that it bases its analysis on hospital's services, which are in general more comparable among hospitals than indicators of hospital overall performance. In addition, it makes use of DEA to aggregate performance indicators, allowing for user choice in the inputs and outputs to be aggregated, and it proposes a novel model to aggregate service's efficiencies into a single measure of hospital performance.

Abstract
Spatial analyses and competition assessments can be used by firms to identify target geographic markets for entry. By integrating these two kinds of analysis, this paper presents an innovative method that identifies target geographic markets for health care providers. In these target markets, supply is potentially insufficient to satisfy demand and competition problems that make entry unsuccessful are not expected to occur. Considering the Portuguese hospital health care market, an application of the method in a case study illustrates how the method works in practice.

Abstract

Abstract
Recent advances in telecommunications created new opportunities for monitoring public transport operations in real-time. This paper presents an automatic control framework to mitigate the Bus Bunching phenomenon in real-time. The framework depicts a powerful combination of distinct Machine Learning principles and methods to extract valuable information from raw location-based data. State-of-the-art tools and methodologies such as Regression Analysis, Probabilistic Reasoning and Perceptron's learning with Stochastic Gradient Descent constitute building blocks of this predictive methodology. The prediction's output is then used to select and deploy a corrective action to automatically prevent Bus Bunching. The performance of the proposed method is evaluated using data collected from 18 bus routes in Porto, Portugal over a period of one year. Simulation results demonstrate that the proposed method can potentially reduce bunching by 68% and decrease average passenger waiting times by 4.5%, without prolonging in-vehicle times. The proposed system could be embedded in a decision support system to improve control room operations. (C) 2016 Published by Elsevier B.V.

Abstract
In this paper the authors present a meta-model aiming to support decision-makers that wish to know more about how to use systems models to cope with the integration of environmental concerns into the company strategy. This is made by using a General Morphological Analysis (GMA) to bridge the gap between Operations Research (OR) analysts, decision-makers and stake-holders, making all of them part of the problem structuring and formulation process, particularly in societal issues like the environmental ones. The novelty of this approach is two-fold: (i) there are no examples in literature of a GMA research that address a linkage between environmental practices, strategic objectives, and the integration of stakeholders in the decision-making process at the level of a company; (ii) there is no GMA that had covered all the phases of a decision-making problem (problem definition, problem analysis and problem solving) in such a context.