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Using energy economically and efficiently is essential to ensure national energy security, reduce greenhouse gas emissions, and preventing climate change. Household appliances consume considerable energy, so choosing energy-efficient is to consuming energy economically and efficiently. The research applies the extended theory of planned behavior (TPB) to empirically investigate factors affecting consumers’ purchase intention toward energy-efficient household appliances (EEHA) in Ho Chi Minh City (HCM). The chapter develops both qualitative and quantitative methods. The qualitative method is conducted with five in-depth interviews to get more consumer insight, verify the research model, and elaborate the questionnaire. The quantitative method with 300 consumers living in HCM is used to address the research question. The primary data are collected via a web-based questionnaire and analyzed by IBM SPSS Statistics 20 and Amos 20. The research indicates that attitude, subjective norm (SN), perceived behavioral control (PBC), past purchase experience (PPE), and economic benefit (EB) have significant positive impacts on consumers’ purchase intention. EB has the most significant impact. Nonetheless, consumers’ purchase intention is not significantly impacted by their level of environmental knowledge (EK). Besides, PPE and EBs positively impact attitude and indirectly affect purchase intention, while EK does not. Based on the empirical results, some recommendations are drawn for policymakers to promote energy-efficient household appliance consumption by citizens, thereby ensuring national energy security and promoting environmental protection. Implications to help manufacturers improve products in the right direction and make wise investment decisions and distributors/retailers to understand consumers in HCM are also suggested.

This study aims to investigate whether the changes in gender composition of bank board affects Vietnamese bank stability efficiency.

This research covers a panel of 27 commercial banks in Vietnam over a 14-year period from 2007 to 2020. The two-step system generalized method of moments is used to estimate the gender diversity–Vietnamese bank stability efficiency nexus.

The authors find that a greater degree of board gender diversification enhances bank stability efficiency and reduces bank risk-taking in Vietnam. The relationship between gender diversity and the stability efficiency of Vietnamese banks is still valid under the influence of regulatory capital sufficiency and during the financial crisis. These findings are robust to alternative proxies for risk indicators and consistent with the perspectives of stakeholder and behavior theory.

Although this research revisits the relationship between gender diversity and bank risk-taking, it is the first attempt to explore the role of women on board in enhancing the stability efficiency of banks, using the stochastic frontier approach. These findings shed light on the function of gender diversity as a governance instrument for mitigating risk in an emerging market context.

Mental ill health is prevalent among construction workers due to high job demands and unsafe working conditions. Psychological safety climate (PSC) has emerged as a potential solution for improving workplace mental health. However, there is still limited understanding of how different dimensions of PSC influence mental ill health. Thus, this study aims to explore the impact of PSC on the mental ill health of construction employees in the Vietnamese context.

Data were collected from 238 construction professionals using a non-probability sampling method. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the relationships between various PSC dimensions and mental ill health.

The findings revealed that management commitment and management priority have the most significant influence on reducing mental ill health in the Vietnamese construction sector. While organizational communication and participation contribute, their impact is less pronounced but crucial in promoting employee well-being.

Firms should actively promote mental well-being by visibly prioritizing psychological health alongside productivity and providing resources for stress prevention. For policymakers, these findings suggest the need for regulations that encourage or mandate mental health programs. Additionally, the study highlights the need for employees to engage with mental health initiatives to reduce the stigma surrounding mental health discussions in the workplace.

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 study aims to analyze online responses to gain insights into public attitudes and concerns regarding traditional Chinese medicine (TCM) among Hong Kong residents. By addressing gaps in understanding public sentiment, this study contributes to the development of effective health-care policies.

Responses were collected from Baby-Kingdom.com using Python, gathering 17,568 TCM-related comments from 2016 to 2023. Analysis involved an eight-theme codebook and sentiment and semantic network analyses with DiVoMiner.

Most responses expressed positive sentiments and attitudes toward TCM. The analysis revealed recurring topics related to conditioning and specific diseases, including gynecological problems. Clinic service quality, fair pricing and convenient locations were also highlighted.

This study examines the networked public sphere and the Theory of Planned Behavior regarding TCM, emphasizing online forums’ impact on attitudes and highlighting gaps in service access, using big data and an interdisciplinary approach.

The findings of this study from Baby-Kingdom.com emphasize the need to improve the accessibility of TCM-related discussions. An official platform for professionals is proposed, with government support for reliable information and partnerships with local universities to expand services.

This study provides valuable insights into the popularity of TCM in Hong Kong, which may encourage uptake and use of TCM services in the health-care sector in not only Hong Kong but also the Greater Bay Area, China and potentially other countries in the future.

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.

To support digital humanities research more effectively and efficiently, this study develops a novel Knowledge Graph Analysis Tool of People and Organizations (KGAT-PO) for the Digital Humanities Research Platform for Biographies of Chinese Malaysian Personalities (DHRP-BCMP) based on artificial intelligence (AI) technology that would not only allow humanities scholars to look at the relationships between people but also has the potential for aiding digital humanities research by identifying latent relationships between people via relationships between people and organizations.

To verify the effectiveness of KGAT-PO, a counterbalanced design was applied to compare research participants in two groups using DHRP-BCMP with and without KGAT-PO, respectively, to perform people relationship inquiry and to see if there were significant differences in the effectiveness and efficiency of exploring relationships between people, and the use of technology acceptance between the two groups. Interviews and Lag Sequential Analysis were also used to observe research participants’ perceptions and behaviors.

The results show that the DHRP-BCMP with KGAT-PO could help research participants improve the effectiveness of exploring relationships between people, and the research participants showed high technology acceptance towards using DHRP-BCMP with KGAT-PO. Moreover, the research participants who used DHRP-BCMP with KGAT-PO could identify helpful textual patterns to explore people’s relationships more quickly than DHRP-BCMP without KGAT-PO. The interviews revealed that most research participants agreed that the KGAT-PO is a good starting point for exploring relationships between people and improves the effectiveness and efficiency of exploring people’s relationship networks.

The research’s limitations encompass challenges related to data quality, complex people relationships, and privacy and ethics concerns. Currently, the KGAT-PO is limited to recognizing eight types of person-to-person relationships, including couple, sibling, parent-child, friend, teacher-student, relative, work, and others. These factors should be carefully considered to ensure the tool’s accuracy, usability, and ethical application in enhancing digital humanities research.

The study’s practical implications encompass enhanced research efficiency, aiding humanities scholars in uncovering latent interpersonal relationships within historical texts with high technology acceptance. Additionally, the tool’s applications can extend to social sciences, business and marketing, educational settings, and innovative research directions, ultimately contributing to data-driven insights in the field of digital humanities.

The research’s originality lies in creating a Knowledge Graph Analysis Tool of People and Organizations (KGAT-PO) using AI, bridging the gap between digital humanities research and AI technology. Its value is evident in its potential to efficiently uncover hidden people relationships, aiding digital humanities scholars in gaining new insights and perspectives, ultimately enhancing the depth and effectiveness of their research.

This paper aims to explore FinTech’s global impact in 40 countries, including the top 20 developing and developed nations, investigates FinTech’s complicated effects in emerging and mature economies, considering bank-specific characteristics, macroeconomic variables, market rivalry and technology.

Fixed effect regression is used to examine the baseline model before adding the efficient generalized method of moments (GMM) model to resolve endogeneity-induced biases. The panel regression model requires an efficient GMM estimate and a linear panel model with non-linear moment conditions. This research also uses a sequential test for multiple breaks at unknown breakpoints, comparing F-statistics to critical values at various significance levels.

The results show that NPL is substantially affected by prior NPL, with the preceding period’s greater NPL raising it and the two periods before decreasing it. Digital lending (DL) proportionally raises NPLs. Innovation-driven emerging countries have more NPLs and faster FinTech growth due to rapid adoption beyond restrictions. Rapid FinTech advances require stronger regulation for financial inclusion and economic progress in developing countries. Additionally, DL usage has remained steady due to gradual technology adoption, while digital capital raising has consistently grown, showing resilience to market shocks.

Due to FinTech’s quick innovation and legislative changes, conclusions should be applied cautiously. There may be gaps in the study on varied settings and long-term effects.

FinTech credit expansion globally drives central banks and authorities to monitor economic conditions, advise monetary policies and resolve competitive and regulatory arbitrage concerns. Studies show digital banking’s reach into underprivileged communities helps mortgage financing. Financial firms using FinTech for credit risk management show a dedication to risk assessment and decision-making. The practical effects show that FinTech adoption, credit risk and financial inclusion have pros and cons in different economic circumstances.

As central authorities use FinTech data for policy decisions, there’s potential for enhanced financial inclusion, fostering social equity and empowerment. In economies with high financial exclusion, FinTech development becomes a catalyst for broader access to financial services. However, concerns about FinTech’s correlation with traditional banks underscore the need for robust regulatory frameworks to ensure fair competition and consumer protection. Striking a balanced approach to FinTech adoption can lead to a more inclusive financial landscape, positively impacting individuals and communities traditionally underserved by conventional banking systems.

This research stands out in its comprehensive exploration of FinTech effect to the bank credit risk, delving into economic, regulatory and societal aspects. The focus on global FinTech credit expansion uniquely highlights the interconnected roles of central banks, regulatory authorities and financial institutions, outlining potential risks and benefits. The study’s nuanced analysis of FinTech’s impact on credit risk and financial inclusion provides distinctive insights, stressing the need for balanced adoption to foster inclusive economic growth. In essence, this research brings an original perspective to the intricate interplay between FinTech and global financial dynamics.