Abstract
Promotional tools such as cross-market discounts have been increasingly used as a means to increase customer satisfaction and sales. This paper aims to assess whether the implementation of a cross-market discount campaign by a retailing company encouraged customers to increase their purchases level. It contributes to the literature by using neural networks to detect novelties in a real context involving cross-market discounts. Besides the computation of point predictions, the methodology proposed involves the estimation of neural networks prediction intervals. Sales predictions are compared with the observed values in order to detect significant changes in customers' spending. The use of neural networks is validated through the comparison with the forecasting estimates of support vector regression, regression trees, and linear regression. The results reveal that the promotional campaign under analysis did not significantly impact the sales of the rewarded customers.

Abstract
The synchronization of Public Transportation (PT) systems usually considers a simplified network to optimize the flows of passengers at the principal axes of the network. This work aims to identify the most relevant transfer-connections in a PT network. This goal is pursued with the development of a methodology to identify relevant transfer-connections from entry-only Automatic Fare Collection (AFC) data. The methodology has three main steps: the implementation of the Trip-Chaining-Method (TCM) to estimate the alighting stops of each AFC record, the identification of transfers, and finally, the selection of relevant transfer-connections. The adequacy of the methodology was demonstrated with its implementation to the case study of Porto. This methodology can also be applied to PT systems using entry-exit AFC data, and in that case, the TCM would not be required.

Abstract
This study presents an innovative procedure to assess the evolution of the social performance of firms over time using a Benefit-of-the-Doubt Composite indicator specified with a Directional Distance Function and the Malmquist index. In recent years, the social indicators of large corporations are increasingly being used to evaluate corporate performance. Reputation issues associated with the firms’ impact on society, including local employment and contribution to local economic development are considered critical. This paper develops a composite indicator of social performance that can be used both for benchmarking comparisons among firms within an industry and to monitor the evolution of performance over time. Both desirable and undesirable factors can be taken into account in the performance evaluation. An illustrative application involving the assessment of 24 large mining firms in the years 2011 and 2012 is discussed. The specification of indicators reflecting social burdens and benefits of mining firms is based on international standards and guidelines for large corporations. The managerial implications of the results obtained are discussed. © 2020 Elsevier Ltd

Abstract
130In the majority of European countries, the evaluation of schools is at the heart of the educational system as a means to guarantee the quality of education. Every year, in most countries around the world, students perform national exams. Their results are analyzed by several stakeholders, including governmental agencies, the media, and researchers on educational issues. At present, advances in information and communication technology (ICT) and data analysis techniques allow schools to make use of massive amounts of data in their daily management. This chapter focuses in particular on the use of students’? data to benchmark schools. It illustrates the potential contribution of the information gathered and analyzed through data analytics to promote the continuous improvement of schools’? educational processes. © 2018 by Taylor & Francis Group, LLC.

Abstract
In recent decades, the concept of urban metabolism has been widely applied at different scales. This paper proposes an optimization model, based on Data Envelopment Analysis, for the evaluation and benchmarking of countries' metabolism. The EU-28 countries are analyzed based on economic and environmental indicators, including the resources consumed (energy and materials) and environmental pressures (GHG emissions and waste) associated with the value-added from the economic activities. The empirical results produced a ranking of countries' based on their metabolic performance underlying the creation of wealth, along with the targets for the countries with lower metabolic performance. This new metabolic approach is a contribution to the design of policies for the promotion of sustainable and resilient services.

Abstract
This paper develops a benchmarking framework to support performance-based sunshine regulation in the water sector. It uses benefit-of-the-doubt composite indicators formulated with a directional distance function. Weight restrictions are incorporated in the model to account for different perspectives in the performance assessment. The framework is tested using data of the Portuguese regulation authority concerning the activity of wastewater operators. The information obtained using this framework reflects overall performance at the firm level and complements traditional evaluations of regulatory authorities based on the analysis of individual indicators. The results can be used to disseminate best practices, motivate continuous improvement, and foster enhancements in the governance of regulated utilities.