The rapid growth of wealth-tech platforms has intensified the importance of digital trust, particularly among Generation Z investors who rely heavily on social media–driven information sources when making investment-related decisions. While prior studies have examined influencer marketing, electronic word-of-mouth (e-WOM), and social media engagement in fintech contexts, empirical research that integrates these persuasion mechanisms into a unified trust-based model of wealth-tech adoption intention remains limited. Drawing on Source Credibility Theory, Trust Transfer Theory, and digital engagement frameworks, this study proposes and tests an integrative model in which influencer credibility, e-WOM, and social media engagement simultaneously influence wealth-tech adoption Intention through the mediating role of digital trust. Using survey data collected from 255 Generation Z actual users of wealth-tech platforms in Indonesia, this study employs Structural Equation Modelling (SEM) to simultaneously test the measurement model and the proposed trust-based structural relationships, including the mediating role of digital trust. A purposive sampling approach was adopted to ensure respondents possessed direct experience with wealth-tech applications, thereby enhancing construct validity in this specialized digital investment context. The results indicate that influencer credibility, e-WOM, and social media engagement each exert a significant positive effect on digital trust, which in turn strongly influences wealth-tech adoption Intention. Digital trust is found to play a critical mediating role, reinforcing its central importance in investment-oriented digital platforms characterized by heightened perceived risk. This study contributes to the literature by extending digital trust and fintech adoption research in three ways: (1) by integrating multiple digital persuasion mechanisms into a single trust-centered framework, (2) by empirically validating digital trust as a key mediating mechanism in a wealth-tech investment context, and (3) by providing contextual insights from an emerging market characterized by rapid digital adoption and persistent trust challenges. Practically, the findings offer guidance for wealth-tech platforms and digital marketers in designing trust-enhancing strategies targeting Generation Z investors.

The diffusion of contactless payment technologies has become a critical component of digital transformation strategies aimed at enhancing SME competitiveness in developing economies. Among these technologies, Quick Response (QR) Code Payment offers a low-cost and infrastructure-light solution, yet its adoption among SMEs remains uneven. This study investigates the determinants of QR Code Payment adoption and its subsequent effects on SMEs’ sustainability performance. Anchored in the Technology Acceptance Model (TAM) and the Resource-Based View (RBV), the proposed framework incorporates perceived usefulness, perceived ease of use, digital literacy, QR Code Payment adoption, and sustainability performance as core constructs. Integrating TAM and RBV is essential because belief-based perceptions translate into actual adoption only when supported by adequate organizational resources and capabilities, making adoption decisions the product of an interaction between what users believe and what the firm is able to execute. Survey data from 326 SMEs in the Special Region of Yogyakarta, Indonesia, were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that perceived usefulness and digital literacy significantly drive QR Code Payment adoption, whereas perceived ease of use does not, suggesting that performance-oriented beliefs and capability endowments outweigh perceptions of simplicity in shaping adoption behavior. Furthermore, QR Code Payment adoption positively influences economic, social, and environmental aspects of sustainability performance. These findings highlight the strategic value of digital payment integration for advancing SME sustainability and underscore the need to strengthen digital capabilities to accelerate technological uptake. The study extends the literature by jointly applying TAM and RBV to elucidate how belief structures and firm-level capabilities interact to shape adoption outcomes and their performance implications within resource-constrained contexts. For ecosystem coordinators, aligning merchant education with simple analytics dashboards can help SMEs turn payment data into insights—underscoring the need for policy support from government, financial institutions, and payment providers to ensure QR payment adoption translates into real performance gains.

In the context of the digital transformation of cultural institutions, there exists an imperative for interactive AR/VR systems that leverage the capabilities of artificial intelligence for the personalized presentation of cultural content and the management of cognitive interaction scenarios. In light of the above, the purpose of this study was to develop and empirically evaluate the efficacy of an interactive AI model (CurioMind) for AR/VR experiences, which tailors information input to align with user requests and behaviors. Within the framework of the study, an experiment was conducted with two groups of participants (n = 60), which involved comparing the measures of attraction, memorization and subjective evaluation of the experience. Furthermore, NASA-TLX cognitive load assessments were conducted alongside semi-structured interviews to qualitatively evaluate interface perception and content. Participants engaging with the CurioMind model demonstrated significantly higher levels of information retention (mean score of 9.1 compared to 7.2 in the control group) and longer exposure time. Moreover, their ratings on the parameters of emotional engagement, personalization, and interface attractiveness were markedly higher. The findings substantiate the study’s hypothesis: the integration of an adaptive AI agent within AR/VR experiences augments the efficacy of informal cultural learning and elevates the quality of the user experience. The CurioMind model introduces a novel approach to digital museum storytelling based on behavioral personalization. Future research may encompass the scaling of the system to authentic museum environments, adding multimodal input (gestures, gaze).

The trend of applying artificial intelligence (AI)-based personalization to e-commerce platforms is becoming increasingly popular to attract customers to buy products and services. To contribute to explaining this, this study was conducted to analyze the impact of artificial intelligence-based personalization on customers’ purchase intention when shopping on e-commerce platforms in Vietnam. Based on the PLS-SEM analysis method with valid data collected from 400 survey questionnaires for people who have shopped on e-commerce platforms. The results show that innovation, system quality, and information quality positively affect perceived usefulness and trust, thereby promoting purchase intentions. In addition, immersive experiences also positively affect purchase intentions. On that basis, the authors propose some management implications to help businesses operating on e-commerce platforms better understand the impact of AI-based personalization on purchase intentions, thereby being able to build strategies to improve operational efficiency and increase profits.