2026
Autores
Gonçalves, N; Oliveira, HP; Sánchez, JA;
Publicação
IbPRIA (2)
Abstract
2026
Autores
da Fonseca, MJS; Martins, L; Rodrigues, HS; Cardoso, PR; Andrade, JG; Cairrão, A; Garcia, JE;
Publicação
WorldCIST (5)
Abstract
Marketing communication has changed a lot in recent decades, mainly due to new technologies and shifts in how consumers behave. Generation Alpha, born from 2010 onwards, is the first to grow up fully surrounded by digital media, but traditional advertising is still part of their everyday lives. This makes it important to understand how they see and react to both online and offline marketing. This study looks at Generation Alpha’s attitudes toward marketing communication, focusing on how they perceive, prefer, and respond to different advertising formats. It uses a qualitative approach with focus groups involving children aged 6 to 13, allowing a closer look at their experiences and emotional reactions to ads on digital platforms, social media, television, and outdoor media. The results show a clear preference for digital communication, especially formats that are interactive, audiovisual, and entertaining. Online advertising tends to be viewed as more appealing and relevant when it includes storytelling, strong visual elements, and chances to interact. Even so, offline advertising still plays a role, particularly in family contexts, where exposure often happens with parents or in shared viewing moments. In both online and offline environments, aspects such as transparency, credibility, and the perceived honesty of the message are central to whether advertising is accepted or rejected. Overall, the study helps clarify how younger consumers relate to marketing communication and points to practical paths for brands that want to build strategies that are ethical, credible, and effective for a digital-native generation.
2026
Autores
Gonçalves, N; Oliveira, HP; Sánchez, JA;
Publicação
IbPRIA (1)
Abstract
2026
Autores
Prata Lima, MD; Giraldi, GA; Cardoso, JS;
Publicação
CoRR
Abstract
2026
Autores
Temporão, B; Garcia, JE; Rodrigues, HS; da Fonseca, MJS;
Publicação
WorldCIST (5)
Abstract
The rapid evolution of artificial intelligence (AI) has transformed customer service environments, with chatbots emerging as key tools for improving efficiency, responsiveness and personalization. Despite their growing adoption across sectors such as retail, finance, healthcare and education, uncertainty persists regarding how users perceive these systems and which factors shape their satisfaction. Existing research points to clear advantages of chatbots but also highlights limitations related to trust, empathy and the handling of complex interactions.? This paper examines how AI-based chatbots influence user satisfaction in customer service contexts and identifies the interactional factors that most strongly shape users’ evaluations. A quantitative, cross-sectional survey was conducted using a questionnaire that explored perceived interaction quality, trust in AI systems, social presence, usefulness, responsiveness and limitations experienced during automated service. Statistical analysis was used to identify relationships between chatbot use, user satisfaction and the variables contributing most strongly to positive or negative evaluations.? The results show that although most respondents had previous experience with chatbots, their assessments varied across performance dimensions. Ease of use received the most favourable ratings, while problem resolution showed the greatest variability, suggesting that chatbots remain more effective for simple requests than for complex issues. Trust and clarity of information were generally positive but displayed substantial dispersion, reflecting heterogeneous user experiences. More than half of users required human assistance after chatbot interaction, and barriers such as lack of need, privacy concerns and perceived inconsistencies were frequently reported. Despite these challenges, overall satisfaction and recommendation levels were positive, indicating that effectiveness in resolving issues is central to user acceptance.
2026
Autores
Wang, B; Cardoso, JS; Wu, L;
Publicação
CoRR
Abstract
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