Manuel Au-Yong Oliveira

Abstract
Digital marketing has become an integral part of the modern business landscape, revolutionizing the way companies promote their products and interact with their customers. In this essay, we aim to demonstrate how it can be related to an increased tendency for mental health problems and other societal complications, as well as developing insights into its evolution using the latest breakthroughs in technology. This study will provide an overview of the impacts of digital marketing on companies, and in society, resorting to classical literature, as well as recent studies and articles conducted on the matter. An online survey was developed to support our research, reaching 112 Portuguese participants. The scientific methodology used was the Chi-Square test, with a confidence margin of 95% targeting two focus groups, one with their ages comprised within 16-25 years old and the other from 35 to 50 years old. We perceived that there would be behavioral differences between people who were born in the digital marketing age and those who had to adapt to it. We also provided some possible solutions to the problems raised by digital marketing and explained how these issues could be exacerbated with the renaissance technology is facing recently.

Abstract
Corporate Social Responsibility (CSR) is increasingly shaping the pathways of Small Medium-sized Enterprises (SMEs). This study presents an entity-relationship diagram (ERD) approach to 184 determinants of SME internationalization success, in order to provide structured inputs for Deep Learning (DL) Recommenders that can support CSR-aligned internationalization strategies. Employing Visual Paradigm 17.2 Professional software for modeling, the research synthesizes state-of-the-art findings on foreign market entry, and export performance, into ERDs. Then the market adoption drivers for such a DL tool are explored through semi-structured interviews with twelve stakeholders. The results reveal a propensity to adopt the DL recommender, with experts highlighting essential features for engagement, pricing, and implementation. The discussion contextualizes these findings, while the conclusion addresses gaps and future directions. The study's focus in Portugal/Germany may limit worldwide extrapolation, yet it advances knowledge by consolidating success determinants, validating platform requirements, exposing gaps, and suggesting research in both CSR, AI and SME internationalization.

Abstract
This study examines the factors that motivate viewers to financially support streamers on the Twitch digital platform. It proposes a conceptual framework that combines the uses and gratifications theory (UGT) with Michel Foucault's concept of the practice of freedom (PF). Using a cross-sectional quantitative survey of 560 Portuguese Twitch users, the model investigates how three core constructs from UGT-entertainment, socialization, and informativeness-affect the intention to donate, with PF acting as a mediating variable. Structural equation modeling confirms that all three UGT-based motivations significantly influence donation intentions, with socialization exhibiting the strongest mediated effect through PF. The findings reveal that Twitch donations go beyond mere instrumental or playful actions; they serve as performative expressions of identity, autonomy, and ethical subjectivity. By framing PF as a link between interpersonal engagement and financial support, this study provides a contribution to media motivation research. The theoretical integration enhances our understanding of pro-social behavior in live streaming environments, challenging simplistic, transactional interpretations of viewer contributions vis-& agrave;-vis more political ones and the desire to freely dispose of what is ours to give. Additionally, this study may lay the groundwork for future inquiries into how ethical self-formation is intertwined with monetized online participation, offering useful insights for academics, platform designers, and content creators seeking to promote meaningful digital interactions.

Abstract
This study aimed to investigate the effect of organizational culture on employee-perceived performance and whether this relationship is mediated by perceived organizational support and moderated by employee motivation. Three hundred individuals working in organizations located in Portugal and Angola participated in this study. This is a quantitative, exploratory, correlational, and cross-sectional study. The results indicate that only goal culture, rule culture, affective organizational support perception, and identified motivation have a positive and significant effect on perceived performance. Supportive culture and goal culture have a positive and significant effect on affective organizational support perception. All dimensions of organizational culture have a significant effect on cognitive organizational support perception, with the effects of the supportive culture and the goal culture being positive and significant, while the effects of the innovative culture and the rule culture are negative and significant. The perception of affective organizational support has a total mediating effect on the relationship between goal culture and perceived performance. Intrinsic motivation and identified motivation have a moderating effect on the relationship between all dimensions of organizational culture and perceived performance. This study is expected to help human resource managers understand the importance of the type of organizational culture that prevails in their organization to enhance employees' perception of organizational support and performance.

Abstract
This study introduces the concept of DEEPEIA, a novel deep learning (DL) platform designed to recommend the optimal export market, and its ideal foreign champion, for any product or service offered by a small and medium-sized enterprise (SME). Drawing on expertise in SME internationalization and leveraging recent advances in generative artificial intelligence (AI), this research addresses key challenges faced by SMEs in global expansion. A systematic review of existing platforms was conducted to identify current gaps and inform the conceptualization of an advanced generative DL recommender system. The Discussion section proposes the conceptual framework for such a decision optimizer within the context of contemporary technological advancements and actionable insights. The conclusion outlines future research directions, practical implementation strategies, and expected obstacles. By mapping the current landscape and presenting an original forecasting tool, this work advances the field of AI-enabled SME internationalization while still acknowledging that more empirical validation remains a necessary next step.