Abstract
Today, the variety of complex products, low volume and decreasing life cycles require a combination of multiple skills that, often, do not exist in a single organization. This raises the need to extend the traditional organization towards the extended virtual enterprise. During the last decade several research projects developed concepts, methods and tools to support the design and operation of the virtual enterprises. However, the impact in industry remains low mainly due to the lack of vertical and horizontal integration, both at business and technical level. Industry 4.0 may be the missing enabler for effective virtual enterprises, once it integrates both business entities and technical entities into a single concept - the Industry 4.0 component - thus enabling enhanced interoperability. This paper presents innovative Industry 4.0 approaches, concepts, methods and tools applied to real manufacturing environments, showing how they enable the creation of cyber-physical production systems leading to a flexible, efficient and seamlessly virtual enterprise.

Abstract
Considering the many significant challenges faced by higher education in contemporary society, gamification and game-based approaches to Education have been gaining protagonism in research as well as in practice. Application of games can encourage-or require-students to apply deeper levels of knowledge and skills, focusing their knowledge acquisition in more than simple memorization and repetition in tests, allowing them to use their new-found knowledge, skills and abilities in problem solving-even if simulated and fairly accessible ones. Unlike traditional assessments, which typically require students to recall or demonstrate basic levels of skills, games and simulations can present students with more authentic environments to demonstrate strategic and critical thinking, which is highly compatible with the "competency model". Through games, learning can also be made more of a social and collaborative activity, which are important 21st century skills. Hence, a model was developed for applying gamification in a course of Human Resources Management of a Masters in Engineering. This model was based on a state of the art research of gamification in higher education, as well as some guidelines and main features of a gamification framework. This paper presents the game system, platform and strategies implemented by the teaching team, comparing the original project with the one actually implemented. Teacher and student reflections on this experience are presented, and guidelines for future practice are brought out, including the biggest blunders and the best features of the game-based approach used in this experience, their causes and consequences. We believe this work can contribute to further game-based approaches in higher education, stimulating reflection and insight for other researchers and practitioners.

Abstract
The organizational struck of the companies in the biomass energy sector, regarding the supply chain management, services, can be greatly improved through the use of software decision support. tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. to particular, this work presents the modelling a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided.

Abstract

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
Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail supply chains. For profitable retail businesses, accurate sales forecasting is crucial in organizing and planning purchasing, production, transportation and labor force. Retail sales series belong to a special type of time series that typically contain strong trend and seasonal patterns, presenting challenges in developing effective forecasting models. This paper compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. An approach based on cross-validation is used to identify automatically appropriate state space and ARIMA models. The forecasting performance of these models is also compared by examining the out-of-sample forecasts. The results indicate that the overall out-of-sample forecasting performance of ARIMA models evaluated via RMSE, MAE and MAPE is better than state space models. The performance of both forecasting methodologies in producing forecast intervals was also evaluated and the results indicate that ARIMA produces slightly better coverage probabilities than state space models for the nominal 95% forecast intervals. For the nominal 80% forecast intervals the performance of state space models is slightly better.