2026
Autores
Kurowska, A; Barbosa, B;
Publicação
INTERNATIONAL REVIEW ON PUBLIC AND NONPROFIT MARKETING
Abstract
Femvertising, a marketing approach that uses advertising to promote female empowerment, has been recognized for its positive impact on women. Although research acknowledges that femvertising elicits positive and negative emotions among consumers, it still discusses these emotions in broad terms and largely disregards male perspectives. To address this gap, this article explores and compares emotions elicited by femvertising in women and men. This research employed a qualitative approach, comprising five focus groups with 36 participants aged 20-35 (women and men). Transcripts were subject to thematic analysis in NVivo. Results show that femvertising triggers a wide range of positive, negative, and mixed emotions. Positive emotions (e.g., happiness, gratitude) were mostly reported by women, while men more frequently expressed indifference, boredom, and irritation. Both genders showed scepticism, but for different reasons: women pointed to the misappropriation of feminist values by advertising, whereas men emphasized a lack of novelty and perceived overexposure. Emotions were shaped by viewers' perceptions of authenticity and realism in portrayals, gender imbalance, lack of novelty, repetition, misappropriation or overuse of feminist themes, and the personal relevance of these themes. As a result, five consumer profiles were identified: Proud Supporter, Saturated Sceptic, Curious Spectator, Disengaged Outsider, and Excluded Critic. By translating discrete emotions into a five-segment typology, the study specifies emotions beyond simple positive-negative valence, integrates male perspectives, and enables direct gender comparison. It also helps marketers calibrate femvertising to enhance emotions across viewer segments.
2026
Autores
Torres, A; Beirao, G;
Publicação
PROCEEDINGS OF 19TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES, CISTI 2024, VOL 5
Abstract
Education 5.0 is a new paradigm in education posing many challenges and opportunities. This paper uses qualitative methods to explore students' and teachers' experiences with online learning to understand the challenges, benefits, and vision for a successful blended learning model, proposing a dynamic framework for blended learning. Results of in-depth interviews show the three main challenges of blended learning: pedagogical design, technological design, and environment/ setup design. Finally, the study discusses insights into future directions for developing Education 5.0, including the need for ongoing research, collaboration communities, curricula personalization, and innovation in the field.
2026
Autores
Inácio, R; Cerqueira, V; Barandas, M; Soares, C;
Publicação
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. APPLIED DATA SCIENCE TRACK AND DEMO TRACK, ECML PKDD 2025, PT X
Abstract
Time series forecasting is pivotal across industries, as it fosters data-driven decision-making, increasing the chances of successful outcomes. Yet, certain instances that feature adverse characteristics, may lead models to manifest stress through decreases in performance (e.g., large errors). Hence, the ability to preemptively identify such cases, while establishing their root causes, would be advantageous to elevate the understanding of forecasting processes, informing users about the trustworthiness of predictions. Hence, we propose MASTFM, a method based on meta-learning that leverages statistical characteristics of input time series, and estimations of forecasting performance from model outputs, to build a metamodel that learns conditions for stress. Given that such occurrences are naturally rare, data augmentation is employed to ensure balance during training. Moreover, SHapley Additive exPlanations (SHAP) are used to explain how features impact forecasting behaviour.
2026
Autores
Campos, R; Jatowt, A; Lan, Y; Aliannejadi, M; Bauer, C; MacAvaney, S; Anand, A; Ren, Z; Verberne, S; Bai, N; Mansoury, M;
Publicação
Lecture Notes in Computer Science
Abstract
[No abstract available]
2026
Autores
Barbosa, B; Santos, AF;
Publicação
EUROPEAN JOURNAL OF INNOVATION MANAGEMENT
Abstract
PurposeThis study explores gamification as a tool to foster employee involvement in innovation. While previous research has demonstrated the benefits of incorporating game elements in the workplace, the mechanisms and domains through which gamification impacts innovation remain unclear.Design/methodology/approachThis study employed a qualitative approach within the retail sector, conducting semi-structured interviews with Innovation and R&D managers to obtain nuanced insights into the application of gamification in practice.FindingsThe findings indicate that even when applied through short-term or one-off initiatives, gamification generates hedonic, social, and utilitarian outcomes. The employees' sense of ownership of projects and career progression were particularly relevant outcomes. Key factors for successful implementation included a structured and continuous process, transparent metrics to measure impact, alignment with company culture, and leadership support.Originality/valueThis study identifies a comprehensive range of hedonic, social, and utilitarian outcomes of gamification in the open innovation context, as well as the conditions that enable it to foster employee involvement.
2026
Autores
Penelas, G; Nunes, R; Barbosa, L; Reis, A; Barroso, J; Pinto, T;
Publicação
ADVANCES IN PRACTICAL APPLICATIONS OF AGENTS, MULTI-AGENT SYSTEMS, AND COMPUTATIONAL SOCIAL SCIENCE: THE PAAMS COLLECTION, PAAMS 2025
Abstract
This paper presents a game-simulated environment that mimics real-world conditions, with a focus on autonomous vehicle navigation. Despite significant advances in the field of games and simulations, there are still a number of challenges to overcome, in particular, the ability to accurately transfer what has been learned in virtual environments to the real world. This project recreates an agent (a motorcycle), modeled with complex physics, navigating autonomously on a detailed map based on the urban geography of Vila Real, Portugal, recreated from real data, implemented in the Unity game engine. In this paper, we provide a detailed overview of the environment and agent creation processes, highlighting the integration of realistic road networks, obstacles, and interaction mechanics that enhance the fidelity of the simulation. The experimental phase demonstrates the motorcycles ability to navigate efficiently, adapting to road layouts, avoiding obstacles, and adjusting to dynamic conditions. The insights from this study can be applied and transferred to real-world application scenarios, particularly in optimizing route planning and driving behaviour for electric motorcycles.
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