Abstract
Serious Games apply game strategies to a training environment to encourage participants to make decisions and face challenges - the more interactive, the greater the participants' involvement with the content. Moreover, the best way to train is to simulate and identify scenarios for decision making, recreating situations, and strategies for learning. The Serious Games for training have this purpose. A Serious Game for training can be refined with a game narrative, a methodology centered on group experience defining problems and giving solutions through the game story. The challenge is how to diversify a unique narrative according to the individual player's experience. The present study aims to answer, using Design Science Research, whether a personalized narrative can improve the design of serious games for training. The specific goal is to design, develop and evaluate an artifact based on Design Thinking to design a personalized narrative method for Serious Games.

Abstract
Due to the value and diversity of data that organizations use and produce in their activity, it is extremely important to protect this asset. Security flaws can arise due to several factors and whenever it is difficult to access the desired information because of technological barriers. In this case, attacks are redirected to the exploitation of human beings vulnerabilities through various techniques. The objective of this work focuses on literature review, studying the underlying theme of Social Engineering, as it uses human trust, convincing someone of something fake, using various interactions and different vectors to gain access to private information. Design Science Research will support the research work due to the possibility of construction, evaluation, and subsequent validation of the artefact. The contribution of a framework proposal for preventing social engineering attacks in organizations and providing the best recommendations, guiding, and supporting the stakeholders in the selection and definition of controls that guarantee the security of organizational information and avoid possible attacks by Social Engineering. It is expected that the practical effects of the future work will result in a reduction in the number of attacks using Social Engineering, greater individual and collective preparation to deal with this problem and, over time, the incentive to the continued expansion of the adoption of these artefacts at the organizational level.

Abstract
For some years now, master data has become extremely relevant to business success and continuity in an increasingly competitive and global business environment. The banking sector is one example of how the implementation of well-structured and designed master data management policies and initiatives is crucial for reaching positive results. One of the areas in which banks need to ensure extremely fruitful master data management approaches and data governance procedures is when dealing with risk-related data, as it not only ensures accurate and well-supported management and decision-making, but also because banks are required to do so by imposed regulations, such as the BCBS 239. Drawing on a DSR methodology supported research project, where banking and IS-related expertise was continuously merged with existing theoretical knowledge on MDM and BCBS 239 related topics, and a permanent focus on the technical and functional complexity associated with implementing master data management and well-established data governance procedures that ensure regulatory compliance, we propose a novel, six-phase action plan that will allow banks to ensure compliance with BCBS 239 and, consequently, ensure efficient and effective risk data management and reporting.

Abstract

The role of the digital economy is undoubtful these days, with new digital services and technologies appearing regularly, creating new products, and digitalizing others. With the technology exploring new limits, the growth tendency of this economy is clear, and more incumbents will face serious competition, which can’t be ignored. Several of these startups have untapped markets that are not being addressed, exploring that disruption leads to more innovative solutions that will likely lead to better services for people and organizations. Those startups might, though, move up the ladder and take away the market from those incumbents; with this work, we aim to analyze the role of digital economies in market disruption through the lenses of a case study and understand to what extent that case is looking at disrupt an existing market

Abstract
To transform an organization, it isn't possible to ignore the people aspect and the significant impact of talent development in any transformation process. While in larger organizations, there is often access to more resources that ultimately could bring the needed competencies to successfully run such a complex program, in small or medium enterprises, the resources are more limited and the access to talent more difficult, forcing a potential more aggressive strategy in developing the digital skills needed to enable their transformation. This work aims to review some of the literature and better comprehend the role of learning analytics as a practice that could potentially be used to enhance the learning process within Small and Medium Enterprises and support the improvement of digital literacy within these companies.

Abstract
IoT devices that perform translation are often closed proprietary systems which offer no, or very limited, possibilities of being freely integrated with other IoT devices or systems/platforms and cannot be easily updated. The objective of this paper is to offer a Systematic Literature Review (SLR) approach to find and synthesise articles on IoT applications in machine translation and potential integration and interoperability functionalities, along with challenges that arise from it. This research identified IoT based projects/devices that implemented machine translation solutions, including ones that resorted to low-cost devices such as the raspberry pi, as well as challenges faced by IoT devices when it comes to integration/interoperability. The findings in this paper provide a way to become more familiar with IoT based machine translation devices/projects and IoT integration/interoperability challenges, as well as proposing new paths for research.