Publicações

In 2014, the Banco Espírito Santo (BES) conglomerate collapsed, marking the first
bank resolution inspired by the European Union’s Bank Recovery and Resolution
Directive (BRRD). Explanations for these events range from the aftermath of the
2008 financial meltdown to last-minute regulatory failures or capture. In this arti-
cle, we offer empirical findings supporting a different perspective. The 2014 debacle
stemmed from structural issues dating back to the Espírito Santo family’s reacquisi-
tion of BES in the early 1990s and the business strategy pursued over the subse-
quent two decades. While the financial meltdown post-2008 may have accelerated
the events of 2014, it was not the root cause but rather an immediate trigger. Regula-
tory failures were evident but began well before the 2010s. This case carries broader
implications for banking regulation in the European Union and beyond.

This study develops and tests an association-based model explaining how consumers interpret AI-enabled personalization in fashion e-commerce and how these interpretations relate to behavioral intentions. Integrating perspectives from Social Exchange Theory, the Antecedents of Trust Model, Self-Determination Theory, Psychological Contract Breach Theory, and Surveillance Capitalism, we examine the joint associations of perceived personalization, transparency, data control, and privacy concerns with brand trust, perceived surveillance, privacy violation perceptions, and purchase intention. Using PLS-SEM with data from 664 online shoppers, we find that personalization, transparency, and data control are each positively associated with brand trust, while personalization and privacy concerns are positively associated with surveillance perceptions. Brand trust is negatively associated with both surveillance and privacy violation perceptions, and privacy violation is negatively associated with purchase intention. Data control is directly associated with lower surveillance perceptions, whereas transparency operates indirectly through brand trust. Mediation analysis reveals that surveillance is associated with lower purchase intention only indirectly through privacy violation (full mediation), identifying perceived privacy violation as the central psychological pathway in the personalization-privacy paradox. Multi-group analysis identifies segment-level variations by gender and education: personalization is a stronger trust cue for men, while transparency is a stronger trust cue for women; trust buffers violation more strongly for higher-educated consumers. The results highlight a trust-first personalization strategy in which relevance must be paired with meaningful transparency and data-control features to mitigate surveillance and violation appraisals, supporting positive consumer outcomes in fashion e-commerce.

Short-form destination videos often rely on music to carry cultural meaning. This paper links Cognitive Metaphor Theory with the circumplex dyad of pleasure and arousal to explain how music–image pairings build destination brand resonance (DBR). Three experiments show that pleasure is the stable route to DBR, arousal helps only under favorable tone, and their effects are additive. A Meaning-Access Prime (MAP) raises both emotions under identical clips and, in Bayesian structural models, also exerts a direct path to DBR, strongest when pleasant tone is low. DBR then predicts destination brand identification and destination consumption intention. We also show a useful state view: Resonant versus Emergent DBR. The framework provides design rules for co-tuning tone, activation, and cultural cues in creator-made clips that improve resonance, identification, and intention.

This study investigates the potential of Artificial Intelligence (AI) to foster sustainable tourism practices that align with the Sustainable Development Goals (SDGs). It employs the SPAR-4-SLR protocol to conduct a systematic literature review (SLR) of 76 Q1 peer-reviewed articles identified in Web of Science and Scopus to determine the contribution of AI to environmental, social and economic sustainability. Four thematic areas emerged: (1) co-creation of value and sustainability in supply chains; (2) AI, service innovation and sustainable transitions; (3) AI, experience and governance in sustainable tourism; and (4) technology, nature and emerging frontiers. Results indicate that AI improves the sustainability process by making operations more efficient and sustainable and promotes ethical governance, inclusivity and innovation. A framework presents the interaction of AI-driven transformation, governance and ethical practices to foster a sustainable environment, contribute to SDGs 8, 9, 11, 12 and 13, and help improve SDGs 5, 7, 10, 14, 15 and 17. The study’s research agenda includes evaluating the long-term purposes of AI adoption, adoption barriers, implementation in less developed destinations and the enhancement of AI-oriented forecasting models. It provides original insights into the intersection of AI and sustainable development within tourism, providing actionable knowledge for academics, policymakers and practitioners seeking to harness AI for advancing sustainable tourism.

Retail practice shows that augmented-reality shopping applications with similar technical quality can elicit widely different consumer reactions. This study proposes a dual-pathway Stimulus–Organism–Response model: a technical pathway linking augmented realism, information richness, and personalization to interaction satisfaction, and an emotion-priming pathway where anticipated emotions shape immersion, telepresence, and pleasure without technical appraisal. Both converge at inspiration, the sole System-2 construct converting experience into behavior. Data from quasi-experimental participants were analyzed using PLS-SEM, SHAP-interpreted gradient boosting, and K-Means robustness checks. Information richness showed the strongest technical effect, while anticipated emotions most strongly affected immediate experiences. Inspiration predicted purchase and cross-buying intentions. Machine-learning diagnostics supported the framework and revealed non-linear thresholds in key pathways, clarifying inconsistent AR outcomes and positioning inspiration as the cognitive bridge to purchase.