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The purpose of this study is to assess the extent of Sustainable Development Goals (SDGs) disclosures among Vietnamese listed firms and identify key influencing factors.

The authors analyse SDG-related disclosures of the top 100 listed firms by market capitalisation on the Hanoi and Ho Chi Minh stock exchanges as of December 31, 2023, using an established reporting methodology. Data were sourced from annual, corporate governance, ESG, financial and sustainability reports. A regression model was used to examine factors influencing SDG disclosure.

SDG disclosure among Vietnamese firms is relatively low. Corporate governance, firm size, government ownership, industry and Global Reporting Initiative (GRI) usage positively influence disclosure levels, while auditing firm type and firm age show a negative association. Financial firms tend to use sustainable development reports and GRI indicators more frequently.

Practically, strengthening governance frameworks and promoting GRI adoption can improve the quality and extent of sustainability reporting among Vietnamese firms. Socially, enhanced SDG disclosure supports improved corporate practices that align with the United Nations SDGs, fostering a more sustainable and transparent economy in Vietnam.

To the best of the authors’ knowledge, this is the first study examining SDG disclosure and influencing factors in Vietnamese listed (2021–2023), using the GRI (2016) standard. This study contributes to transparency in Vietnam’s financial markets and sustainability practices, offering insights for preparers and policymakers.

Poor mental health is a well-recognized issue in the construction sector. However, there is still little understanding of factors affecting construction employees’ awareness of mental health problems (MHP). This study aims to investigate the awareness of MHP among construction employees using the Health Belief Model (HBM). The research explores how various factors, such as perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action and self-efficacy, shape MHP awareness within the construction sector.

A structured four-step research methodology was employed. First, a literature review and expert validation identified 28 variables relevant to MHP awareness. A questionnaire was then developed and distributed to construction employees in Vietnam, with 238 valid responses collected. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were employed to validate the evaluation model. After that, fuzzy synthetic evaluation (FSE) was used to assess the importance of each dimension of MHP awareness.

The results indicate that perceived barriers and perceived benefits were the two most significant factors in MHP awareness. The remaining dimensions – perceived susceptibility, perceived severity, cues to action and self-efficacy – were found to have a lesser but notable impact on MHP awareness.

This research comprehensively analyzes MHP awareness among construction employees using the HBM framework. The findings suggested that Vietnamese firms should focus on increasing cues to action and self-efficacy to improve MHP awareness among construction employees. This study also proposed that construction firms should provide more stress-reduction activities and training programs suitable to the Vietnamese context for their employees.

This paper investigates the key determinants affecting household spending for university degree in Vietnam. This paper serves as empirical evidence for policymakers to select appropriate factors to estimate financial needs for university students in Vietnam.

We employ an innovative variable selection approach with adaptive LASSO for Tobit Regression Model.

The results suggest income, region and ethnicity play significant roles in determining higher education expenditure at Vietnamese households. Gender-related indicators (such as gender of household head, student’s gender), distance to school, occupations, etc. are empirically insignificant.

This study proposes a data-driven method by interfering regulation and Tobit regression to understand the divergence in higher education spending. Especially, adaptive LASSO was first introduced to identify key determinants of higher education expenditure at household level in Vietnam. It hopes to tackle over-fitting problems of traditional OLS regression in previous literature.