03 Nov, 2026
Amid volatility in global markets, the studies clarify the internal barriers to digital transformation and how uncertainty in the international environment affects the investment decisions of Vietnamese firms.
- Systemic challenges in digital transformation: The study examines digital transformation in Vietnamese higher education, from theoretical perspectives to implementation in practice. It identifies the systemic challenges institutions face, including misaligned strategies, workforce gaps, governance limitations, resistance rooted in organizational culture and infrastructure barriers. Digital transformation is thus viewed as a comprehensive change in strategy and organizational capability, rather than merely an investment in technology.
- International ESG uncertainty and investment decisions: The study analyzes how sustainability-related uncertainty from the United States and China – two of Vietnam’s major trading partners – affects the investment decisions of domestic firms. The results show that uncertainty originating in the United States has a positive effect on corporate investment, while uncertainty from China has a negative effect. Investment irreversibility is also examined as a moderating factor, and the study identifies possible nonlinear relationships between uncertainty and investment decisions.
Publications in computer science, data science and engineering continue to expand applied research capacity, addressing challenges in data security, environmental forecasting and the optimization of industrial resources.
- Federated Learning – distributed machine learning: The FedEnergy study tackles the challenge of non-identically distributed (non-IID) data in distributed machine learning. The proposed method aims to improve model aggregation across devices or organizations with different data distributions, supporting collaborative training without the need to centralize sensitive data.
- Multi-source PM2.5 monitoring and forecasting: Rather than relying solely on time-series data or meteorological indicators, the study proposes a multimodal CNN-LSTM model that combines environmental images with data from multiple sensors. This approach draws on additional visual cues from the urban environment to improve PM2.5 forecasting, supporting air quality monitoring and the protection of public health.
- SAERS energy recovery technology: In mechanical engineering, the study introduces a Single Accumulator Energy Recovery System (SAERS) for the boom cylinder of a hydraulic excavator. By integrating a hydraulic accumulator, the system aims to recover and reuse energy, thereby improving the energy efficiency of industrial equipment.
- Smart contract security in DeFi: The study applies Inductive Behavioral Graph Learning to detect vulnerabilities in smart contracts within decentralized finance (DeFi) ecosystems. Focusing on common attack types such as reentrancy and arithmetic overflow, it aims to strengthen risk detection and protect Blockchain-based financial infrastructure.
The studies continue to place people at the center of technological and managerial transformation, from innovating teaching methods to enhancing psychological well-being and improving the work environment.
- GenAI in language education: The study reviews current trends and prospects for applying generative AI in language education, clarifying the changes GenAI brings to pedagogy and learning environments. In doing so, it broadens the discussion from the use of AI tools to their potential to reshape teaching and learning amid rapid technological development.
- Work–family conflict and psychological well-being: The study analyzes the relationship between work–family conflict and employees’ psychological well-being through two mediating mechanisms: workplace mindfulness and burnout. Segmentation preference – the preference for keeping work and personal life separate – is examined as a boundary condition, helping explain differences in employees’ psychological experiences.
- Illegitimate tasks and citizen-oriented behavior: In public management, the study on illegitimate tasks examines how tasks that public servants perceive as unnecessary or inappropriate can affect their citizen-oriented boundary-spanning behaviors. The findings help identify job design factors that may influence the quality of public service delivery.
- Human capital and the intention to work overtime: Beyond psychological well-being, the study draws on data from the Vietnam Labor Force Survey to analyze the relationship between human capital, including educational attainment and work experience, and the intention to work extra hours. The results offer further insight into how worker characteristics relate to decisions on allocating working time, given that overtime is common in developing economies.
Studies on sustainable development continue to highlight the role of perceptions, beliefs and behavioral characteristics in encouraging environmentally friendly choices.
- Low-carbon tourism and perceived tourist effectiveness: Integrating the Theory of Planned Behavior (TPB) with the Cognition–Affect–Conation perspective, the study analyzes how tourists’ perceived effectiveness of their individual actions shapes attitudes, subjective norms and perceived behavioral control. In doing so, it clarifies the mechanisms that drive intentions to choose low-carbon tourism in tourism cities.
- Urban mobility transition in Ho Chi Minh City: The study examines the factors influencing urban residents’ intention to use electric motorcycles in Ho Chi Minh City, based on an extended model combining the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM). As motorcycles remain central to daily travel, the study provides a scientific basis for understanding what motivates residents to switch to low-emission vehicles, helping to reduce urban air pollution.
The publications from Week 5 of October 2026 reveal connections among three prominent research directions: strengthening organizational adaptability, developing technological solutions and advancing a green transition grounded in human behavior. From distributed machine learning, air quality forecasting and energy recovery in industrial equipment to human resource management, low-carbon tourism and electric mobility, the studies demonstrate diverse approaches and the applied potential of interdisciplinary knowledge.
In doing so, UEH continues to affirm its direction as a multidisciplinary research university, connecting academic foundations with real-world problems and contributing to digital transformation, the green transition and sustainable development in Vietnam and the region.
Publications of the Week
View the Week 5 - October 2026 publication list at:
https://news.ueh.edu.vn/2026/scientist/W5Oct.html
View the full 2026 New UEH Publications Alert at:
https://news.ueh.edu.vn/en/scientist
The New UEH Publications Alert series will continue to bring weekly updates on UEH’s latest international publications. We warmly invite faculty members, alumni and learners to follow the series and help spread the spirit of “Research Contribution for All”.
Pillar: Research
News, photos: Department of Research - Development and Global Engagement, Department of Communications and Partnerships