Abstract
With the global population crossing the 7 billion mark, the world is too crowded. The race for survival is not limited to food, water, shelter, and other basic needs; it also includes fierce competition in all industrial sectors across the world. These days, there are basically two patterns of uncontrolled industrial growth across the world. The first one is meant to fulfill the domestic demands and the common needs of the people. The second one is to exploit the present world situation to maximize profits. Of course, this is a race for supremacy that pushes nations to compete in all possible means to achieve the most from their resources.

Abstract
This article presents an integrated vision of the context of the residential real estate market in Portugal. It analyses the evolution of several macroeconomic indicators during the last decade. The article is complemented with the analysis of the house prices, where an evaluation of average prices of apartments in Portugal according to different typologies and regions have been done. Regarding the market environment, several indicators are assessed, such as the evolution of interest rates, the evolution of households' credit, the consumption and construction confidence indexes and the evolution of foreign direct investment in housing. The conclusion is that after a booming period, the future of the real estate market is somehow worrying.

Abstract
This paper analyzes the scientific literature produced recently about new product development (NPD) in order to identify and classify the major fields of knowledge, possible connections, as well as the nature of articles and analytics tools used. A review of the literature was implemented on 461 articles focused on NPD, published in three leading journals between 2000 and 2010. It was possible to create 13 main categories, in which innovation, research and development, NPD products and processes and NPD teams stand out. Results conclude that NPD is multifaceted, includes multiple concepts and interrelated categories. Moreover, future studies need to complement qualitative with quantitative research and to analyze how small and large firms differ.

Abstract
This paper estimates the relationships between bidding quantities, marginal cost and market power measures in the Spanish wholesale electricity market for two different regulatory periods: 2002-2005 and 2006-2007. Using panel econometric techniques we find differences in the impacts on bidding strategies for both periods. Hence, the marginal cost and the market power measures affect bid and net quantities. The market power measures also suggest that the coefficient is consistently positive and highly significant for both periods. Moreover, the market power and marginal costs have mixed effects according to the models proposed for both periods. In addition, our results point to the effectiveness of the different effects of mitigating the market power in the Spanish electricity market. For the 2006-2007 period, the proposed causal relationships are partially validated by the cointegration results, which assumes there is a significant causality between the Lerner Index and the marginal cost. (C) 2014 Published by Elsevier Ltd.

Abstract
E-government has become a priority for many governments around the world and one of the main change drivers in the provision of new services in the public administration context. As public services are part of a complex network in which citizens are the main players, public authorities are increasingly trying to identify and deploy programmes that promote the modernisation and simplification of public services based on knowledge management. This chapter aims to understand the impact of e-government initiatives on consumer behaviour, as well as the importance of knowledge management for value creation in the public administration context. The Simplex programme, the main initiative in Portugal to develop administrative simplification and e-government, is analysed within two contexts: the central administration and the local municipality of Oporto. This chapter highlights that e-government has been an important factor contributing to both the administrative simplification and the improvement in the quality of public services.

Abstract
To cope with today market challenges and guarantee adequate competitive performances, companies have been decreasing their products life cycles, as well as increasing the number of product varieties and respective services available on their portfolio. Consequently, it has been observed an increasing in complexity in all domains, from product and process development, factory and production planning to factory operation and management. This reality implies that organizations should be able to compile and analyze, in a more agile way, the immense quantity of data generated, as well as apply the suitable tools that, based on this knowledge, will supports stakeholders to take decision envisioning future performance scenarios. Aiming to pursuing this vision was developed a proactive performance management framework, composed by a performance thinking methodology and a performance estimation engine. While the methodology developed is an extension of the Systems Dynamics approach for complex systems' performance management, on the other hand, the performance estimation engine is an innovative IT solution responsible by capturing lagging indicators, as well as estimate future performance behaviors. As main outcome of this research work, it was demonstrated that following a systematic and formal approach, it is possible to identify the feedback loops and respective endogenous and exogenous variables responsible by hindering the systems behavior, in terms of a specific KPI. Moreover, based on this enhanced understanding about manufacturing systems behavior, it was proved to be possible to estimate with high levels of confidence not only the present but also future performance behavior. From the combination of both qualitative and quantitative approaches, it was explored an enhanced learning machine algorithm capable to specify the curve of behavior, characteristic from a specific manufacturing system, and thus estimate future behaviors based on a set of leading indicators. In order to achieve these objectives, both Neural Networks and Unscented Kalman Filter for nonlinear estimation were applied. Important results and conclusions were extracted from an application case performed within a real automotive plant, which demonstrated the feasibility of this research towards a more proactive management approach.