Publicações

This study explores how AI chatbot experiences on travel websites influence consumer engagement, with satisfaction from using AI chatbots as a mediating factor. Grounded in the Stimulus-Organism-Response (S-O-R) framework, the research shifts the focus from utilitarian models to examine how chatbot attributes—e.g., ease of use, information quality, security, anthropomorphism, and omnipresence—affect satisfaction of using AI chatbots and subsequent consumer engagement behaviours. Survey data from 519 Portuguese travellers were analysed using partial least squares structural equation modelling (PLS-SEM). The study contributes to theory by (1) demonstrating S-O-R’s advantages over utilitarian models in capturing relational and emotional dimensions of AI interactions, (2) identifying satisfaction with using AI chatbots as a pivotal mediator between AI chatbot experience and consumer engagement, and (3) revealing generational disparities in drivers of engagement. Notably, satisfaction strongly influences engagement for Generation X, while direct experience matters more for Generation Z. Millennials exhibit a distinct preference for hybrid human–AI service handoffs. The practical implications include prioritizing natural language processing for ease of use, implementing generational customization (e.g., gamification for Gen Z, reliability assurances for Gen X), and ensuring seamless human escalation for Millennials. These insights equip travel businesses to design AI chatbots that foster long-term loyalty and competitive differentiation.

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 environ- ments, challenging simplistic, transactional interpretations of viewer contributions vis-à-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.

This study identifies key attributes shaping the perceived image of accessible tourist destinations (ATDs) from the perspectives of various demand segments, including people with disabilities, individuals with health condition and their companions, and tourists without accessibility needs. It also compares these perceived attributes with those projected by destination management organizations (DMOs), as identified in previous research. A survey of 1052 Portuguese participants, employing quota sampling, supported a two-factor model of ATDs’ perceived image, with accessibility as a transversal dimension encompassing structural and environmental features. Accessible infrastructure and safety were identified as essential, while price and inclusive messaging were not significant in the confirmatory factor analysis. Attribute prioritization varies across segments, the results revealing substantial gaps between perceived and projected images, pointing to the need for closer alignment in destination branding strategies.

The fashion industry’s environmental crisis demands urgent shifts toward sustainable consumption models, such as capsule wardrobes. While prior research has examined ethical fashion adoption through conventional behavioral lenses, this study innovatively integrates heterodox economic theories, including the Theory of Subjective Value (TSV) and Bounded Rationality, with the Theory of Reasoned Action (TRA) to analyze discrepancies between attitudes and actions. Using a sample of 776 Portuguese consumers, we examine a mediation model where attitude links personal shopping values, fashion involvement, and socially responsible behavior to adoption intentions. Results reveal socially responsible behavior’s strong indirect effect via attitude, while personal shopping values and fashion involvement show paradoxical relationships, underscoring cognitive and market barriers. Gender and generational analyses highlight women’s higher sustainability engagement and Generation Z’s intention-action gap. The study advances sustainable fashion literature by exposing how subjective valuations and structural constraints interact, calling for coordinated stakeholder interventions beyond individual behavior change.

Research on corporate bankruptcy prediction has garnered renewed interest due to economic crises and regulatory changes. Most studies focus on large enterprises, leaving a gap in understanding bankruptcy prediction in small and medium-sized enterprises (SMEs). This study carries out a systematic literature review to examine the evolution of this topic, focusing on SMEs. Using a structured methodology based on PRISMA, we analysed 541 academic papers, categorising them into two groups: (i) SMEs and (ii) non-SMEs. Our findings reveal key distinctions between the two groups, particularly regarding the definition of bankruptcy, financial and non-financial predictive factors, and the types of models applied. While statistical models, such as logistic regression and discriminant analysis, remain dominant in SME-focused research, artificial intelligence-based techniques are gaining traction. The study also identifies a lack of comparative studies assessing model effectiveness for SMEs across different economic contexts. Based on these insights, we propose a framework to enhance future research in corporate bankruptcy prediction, emphasising the need for models that integrate macroeconomic variables, governance factors, and alternative risk assessment techniques tailored to SMEs. Our findings contribute to bridging the gap between theory and empirical research, offering practical implications for financial institutions, auditors, policymakers, and SME managers in mitigating bankruptcy risks.