Accurate prediction of US Treasury bond yields is crucial for investment strategies and economic policymaking. This paper explores the application of advanced machine learning techniques, specifically Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models, in forecasting these yields. By integrating key economic indicators and policy changes, our approach seeks to enhance the precision of yield predictions. Our study demonstrates the superiority of LSTM models over traditional RNNs in capturing the temporal dependencies and complexities inherent in financial data. The inclusion of macroeconomic and policy variables significantly improves the models’ predictive accuracy. This research underscores a pioneering movement for the legacy banking industry to adopt artificial intelligence (AI) in financial market prediction. In addition to considering the conventional economic indicator that drives the fluctuation of the bond market, this paper also optimizes the LSTM to handle situations when rate hike expectations have already been priced-in by market sentiment.

Artificial Intelligence (AI) has become a pivotal force in transforming the retail industry, particularly in the online shopping environment. This study investigates the impact of various AI applications—such as personalized recommendations, chatbots, predictive analytics, and social media engagement—on consumer buying behaviors. Employing a quantitative research design, data was collected from 760 respondents through a structured online survey. The snowball sampling technique facilitated the recruitment of participants, focusing on diverse demographics and their interactions with AI technologies in online retail. The findings reveal that AI-driven personalization significantly enhances consumer purchase intentions and satisfaction. Multiple regression analysis shows that AI personalization (β = 0.35, p < 0.001) has the most substantial impact on purchase intention, followed by chatbot effectiveness (β = 0.25, p < 0.001), predictive analytics (β = 0.20, p < 0.001), and social media engagement (β = 0.15, p < 0.01). Similarly, AI personalization (β = 0.30, p < 0.001), predictive analytics (β = 0.25, p < 0.001), and chatbot effectiveness (β = 0.20, p < 0.001) significantly influence consumer satisfaction. The hierarchical regression analysis underscores the importance of ethical considerations, showing that ethical and transparent use of AI increases consumer trust and engagement. Model 1 explains 45% of the variance in consumer behavior (R² = 0.45, F = 154.75, p < 0.001), while Model 2, incorporating ethical concerns, explains an additional 10% (R² = 0.55, F = 98.25, p < 0.001). This study highlights the necessity for retailers to leverage AI technologies ethically and effectively to gain a competitive edge, improve customer satisfaction, and drive long-term success. Future research should explore the long-term impacts of AI on consumer behavior and the integration of emerging technologies such as augmented reality and the Internet of Things (IoT) in retail.

This study aimed to explore the influence of entrepreneurial skills development on entrepreneurial confidence in university students. Using an empirical approach, a structured questionnaire was administered to 322 students at a university in Lima, Peru, to assess participants’ perceptions of self-awareness and self-assessment, problem solving, communication and presentation of ideas, as well as their entrepreneurial confidence. The data collected were analysed using structural equation modelling (SEM), which allowed for the identification of significant relationships between the variables. The results revealed that self-awareness, problem solving and effective communication have a positive and determinant influence on the development of entrepreneurial skills, which in turn significantly strengthen students’ entrepreneurial confidence. These findings highlight the importance of incorporating the promotion of entrepreneurial skills in university education, as this can increase students’ readiness and willingness to successfully start and manage their own entrepreneurial projects.

This systematic literature review (SLR) delves into the realm of Artificial Intelligence (AI)-powered virtual influencers (VIs) in social media, examining trust factors, engagement strategies, VI efficacy compared to human influencers, ethical considerations, and future trends. Analyzing 60 academic articles from 2012 to 2024, drawn from reputable databases, the study applies specific inclusion and exclusion criteria. Both automated and manual searches ensure a comprehensive review. Findings reveal a surge in VI research post-2012, primarily in journals, with quantitative methods prevailing. Geographically, research focuses on Europe, Asia Pacific, and North America, indicating gaps in representation from other regions. Key themes highlight trust and engagement’s critical role in VI marketing, navigating the balance between consistency and authenticity. Challenges persist regarding artificiality and accountability, managed through brand alignment and transparent communication. VIs offers advantages, including control and cost efficiencies, yet grapple with authenticity issues, addressed through human-like features. Ethically, VI emergence demands stringent guidelines and industry cooperation to safeguard consumer well-being. Looking ahead, VIs promises transformative storytelling, necessitating vigilance in ethical considerations. This study advocates for continued scholarly inquiry and industry reflection to navigate VI marketing evolution responsibly, shaping the future influencer marketing landscape.

The increasing domains of digital technology in educational settings urgently require digital leadership (DL) to ensure the sustainability of school improvement initiatives in the digital era and to facilitate the digital transformation of educational institutions. DL emerges as an urgent and evolving topic of significant public interest. However, there is a notable lack of consensus persists regarding its definition and constructs within educational settings, hindering the advancement of DL theory. To address this gap, a systematic literature review was conceived, employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The primary aim was to enhance comprehension of the geographical and temporal distribution of relevant publications, as well as to elucidate prevalent definitions and constructs of digital leadership in educational contexts. This article endeavors to synthesize the extant scientific literature on DL, focusing on studies published between 2019 and 2024. Inclusion criteria encompassed scientific research publications sourced from Scopus and the Web of Science (WoS) databases, available in English, and centered on educational settings. Initial database queries yielded 578 papers, subsequently refined to 35 studies through meticulous screening for duplicity and adherence to inclusion criteria. Notably, the reviewed publications predominantly characterize DL as a multifaceted process, amalgamation, or integration, with a predominant emphasis on functional aspects of leadership. Noteworthy constructs frequently encountered include digital age learning culture, visionary leadership, excellence in professional practice, systemic improvement, and digital citizenship. This review contributes to the enrichment of theoretical conceptualizations surrounding DL. It underscores the imperative for future research to explore into the measurement of DL, thereby presenting promising avenues for evaluating principal DL within educational institutions.

This study investigates the dynamic landscape of agritourism in Thailand, emphasizing innovations, challenges, and policy implications in the post-COVID-19 era. Employing a qualitative approach, including a comprehensive literature review and semi-structured interviews with stakeholders, the research identifies key agritourism models, such as immersive learning experiences, technology-driven agritourism, and unconventional practices like salt and coconut plantations. Findings reveal that agritourism has adapted to shifting market demands through diversification, technological integration, and a heightened focus on sustainability. Notably, technology adoption in precision farming and hydroponics enhances resource efficiency and visitor engagement, while initiatives like rice paddy field tourism and highland agritourism showcase the cultural and ecological richness of rural landscapes. The study underscores the critical role of policy frameworks, infrastructure development, and community empowerment in fostering sustainable agritourism practices. Key policy recommendations include targeted subsidies, capacity-building programs, and harmonized regulatory frameworks to address challenges such as financial constraints, regulatory ambiguities, and inadequate infrastructure. This research contributes to the broader discourse on sustainable tourism and rural development, aligning agritourism with the United Nations Sustainable Development Goals (SDGs). By synthesizing insights on innovation, resilience, and sustainability, this study offers a comprehensive roadmap for policymakers, practitioners, and academics to leverage agritourism as a vehicle for rural revitalization and global sustainability. Future research directions are proposed to explore the long-term impacts of technological integration, community empowerment, and resilience strategies in agritourism.