Abstract
Electric vehicles (EVs) are to play an important role in electricity markets, since their energy storage capability can be beneficial to power systems operation. Electric vehicle aggregators will consequently develop adequate offering strategies to participate in energy and reserve markets, accounting for the market rules and operational capabilities of EVs aggregators (e.g., fleet of EVs). In this paper, we propose an offering strategy model for an EV aggregator to participate in the frequency-controlled normal operation reserve service (FCR-N) in Eastern Denmark. The aim is to maximize the expected revenue of the aggregator, accounting for potential penalties for missing the provision of both upward and downward reserves. The methodology has been modeled and tested under the scope of the PARKER project, which considers a case study based on real data from a small fleet of electric vehicles. An important conclusion relates to the availability patterns of the EVs that significantly changes the strategical participation of the EV aggregator in the service.

Abstract
In an increasingly competitive and dynamic world where globalization, information and technology are commonly accepted as influential and determining factors of organizational culture and performance, it becomes imperative for organizations to stand out and gain an advantage over their competitors. This scenario transformation created a greater and more exquisite demand as concerns the average customer and it is now understood that a competitive advantage gained does not necessarily prevail over time. Therefore, organizations must be flexible and learn to adapt easily and rapidly to changes in order to create a sustainable position. Furthermore, the ability to be different, to be innovative, and to create unique products, services, experiences, or a combination of all three, may be viewed as a booster of competitive advantages. In this context: 1. When does innovation begin or should it begin? 2. Is innovation an organizational goal or a philosophy? 3. What makes an organization innovative? This study focuses on innovation as a precursor and defining agent in the development of a business model. First, a brainstorming session was conducted as an exploratory qualitative research effort, with eighteen participants studying innovation and technology management in Portugal (the participants were probed for their views on the three questions above). Additionally, a questionnaire was administered to Portuguese millennials (171 valid responses), with the goal of perceiving potential changes in the national culture that could impact the national innovation mindset. The results were quite surprising and reveal a significant change since the original questionnaire (led by Hofstede) was administered in Portugal.

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Immersion is a state of altered consciousness-not the prim suspension of disbelief, but its joyous capsizing. Since approximately 2012, a new ecosystem of immersive virtual reality technologies and experiments has emerged. In this emerging ecosystem, journalism is still a minor component. Nevertheless, media outlets such as The New York Times, BBC or ABC News have been producing virtual reality news stories. This led to the advent of immersive journalism, not only as a media phenomenon, but also as an academic concept. Drawing on some notions and concepts like the definitions of immersive journalism, immersion and presence, as well as some examples of the relation between journalism practices and visual media, we analyse, reflect and provide a general overview about the main concepts, uses, opportunities and limits of immersive journalism. Thus, the main goal of this article is to provide a theoretical and conceptual gateway that serves as a starting point for immersive journalism future academic and industry endeavours.

Abstract
Forecasting enterprise bankruptcy is a critical area for Business Intelligence. It is a major concern for investors and credit institutions on risk analysis. It may also enable the sustainability assessment of critical suppliers and clients, as well as competitors and the business environment. Data Mining may deliver a faster and more precise insight about this issue. Widespread software tools offer a broad spectrum of Artificial Intelligence algorithms and the most difficult task may be the decision of selecting that algorithm. Trying to find an answer for this decision in the relatively large amount of available literature in this area with so many options, advantages, and pitfalls may be as informative as distracting. In this chapter, the authors present an empirical study with a comprehensive Knowledge Discovery and Data Mining (KDD) workflow. The proposed classifier selection automation selects an algorithm that has better prediction performance than the most widely documented in the literature.