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This study aims to examine the relationships among fear of COVID-19, job stress, job commitment and intention to quit. It also investigates the boundary conditions of the impact of fear of COVID-19 on job stress and intention to quit, a research gap that has not been addressed yet.

This research focused on full-time frontline hotel employees who have been working in four- and five-star hotels in Ho Chi Minh City, Vietnam. A pilot test was performed before collecting formal data. The survey was conducted face-to-face on site so that any potential confusion could be clarified right away. 487 valid responses were analyzed using SPSS 28 and SmartPLS 4.

The majority of hypotheses were supported, with the results suggested that supervisor support contributes to reducing the tendency of hotel employees to quit their job and their job stress. Besides, government support is necessary to make staff feel secure during the pandemic.

This study contributes to pointing out central priorities in making decisions by hotel managers when facing crises. Managers need to focus more on measures to help their employees feel secure and should be available for guidance and feedback when nedeed. Additionally, supportive policies from the government, especially financial support, can provide hotel employees with resources they need to maintain a basic level of living in the face of a severe drop in their income. The study provides the hotel industry not only in Vietnam but also in countries with comparable settings with strategies to cope with unexpected events.

Research on intention to quit a job has mainly focused on a complex interplay of internal factors. However, the influence of fear of COVID-19 on intention to quit a job has not been studied in the context of Vietnamese hotel industry yet. During the COVID-19 pandemic, a number of hotels in Vietnam had to close due to a lack of visitors, which had a negative impact on human resources. Accordingly, fear, stress, commitment and intention to quit a job are the issues faced by staff.

This study examines the effects of employer attractiveness (EA) on employee engagement (EE) and employee performance (EP).

Mixed method. The analytical technique is the Partial Least Squares Structural Equation Modeling through survey questionnaires collected from 937 respondents as employees from 37 enterprises in Vietnam.

EA has a positive impact on EE and EP factors. However, EE has no statistically significant impact on EP.

This study helps managers build solutions toward retaining talent and improving EP through the strategy of building EA. Concurrently, this study guides the important factors to build an effective EA.

This study explores the relationship between three factors: EA, EE and EP. This has added a new research direction of EA to existing employees. In addition, the study results provide a new perspective on the relationship between EE and EP.

The purpose of this study is to assess the factors that motivate young people’s intention to undergo cosmetic surgery in Vietnam.

This study applies Ajzen’s theory of planned behavior as a research model. The study is based on a quantitative method that applied exploratory factor analysis.

In total, 412 valid responses are used for the statistical analysis. The results confirm that subjective norm (SN), attitude toward cosmetic surgery and perceived behavioral control (PBC) are the main factors that motivate young people’s intention to undergo cosmetic surgery.

The results show the positive relationship between attitude toward cosmetic surgery, SN, PBC and intention to undergo cosmetic surgery in Vietnam.

This study aims to investigate the influence of external factors identified by the Political, Economic, Social, Technological, Environmental and Legal (PESTEL) framework on corporate social responsibility (CSR) performance in Vietnamese construction firms.

The snowball sampling method was employed to gather 182 validated responses. Employing Partial Least Squares Structural Equation Modeling (PLS-SEM), the research analyzed how these factors correlate with CSR practices under institutional theory.

Results indicated that social, economic, environmental, legal and technological factors positively impacted CSR performance. Among these, social factors had the most significant effect, followed sequentially by economic, environmental, legal and technological influences. Intriguingly, political factors demonstrated no significant association with CSR performance.

The strong impact of social factors confirms that societal norms and cultural values are critical in shaping corporate behavior in Vietnam. Firms can leverage this insight by intensifying their community engagement and social investment. Additionally, the negligible role of political factors in shaping CSR suggests that firms might not need to focus heavily on political engagement in Vietnam. However, firms should remain aware of legal changes as legal factors influence CSR outcomes.

Despite CSR’s growing importance, there remains a notable research gap regarding how external macro-environmental factors influence CSR performance, particularly within the construction industry. The findings emphasize the importance of aligning business strategies with socioeconomic and environmental aspects.

“The world needs science, science needs women” is the message given by UNESCO in the program for the development of women in science” (UNESCO, 2017). In Vietnam, women’s participation and achievements in scientific research is considered a great and important resource for industrialization and modernization. Even so, are there gender differences in scientific achievement in the social science research institutes in Vietnam? What factors influence the scientific achievement of female social researchers? The answers will be based on data from a 2017 survey with a sample of 756 researchers, of which 77.6% were female. The survey was conducted by the Vietnam Academy of Social Sciences, a leading, ministry-level national center for the social sciences in Vietnam. This chapter analyzed the scientific achievements of researchers through their position as principal investigators of research projects and their publications, and factors that may impact this. Bivariate and multivariate analyses of factors that may affect the scientific achievement of researchers found that gender differences in academic achievement in the social sciences in Vietnam was still prevalent. Female researchers’ scientific achievements were lower than those of their male counterparts. The contribution to science of Vietnamese female researchers was limited by many different factors; the most important were the academic rank of the researchers and gender stereotype that considered housework the responsibility of women.

This paper aims to propose a dynamic stochastic general equilibrium (DSGE) model for the State Bank of Vietnam (SBV) to assess the response from the household sector to monetary policy shocks through the consumption function. Moreover, the transmission from monetary policy to household consumption and income distribution is experimented with through the vector autoregression (VAR) model.

In this study, the authors used the maximum likelihood estimation to estimate the DSGE and VAR models with the sample from 1996Q1 to the end of 2021Q4 (104 observations).

The DSGE model’s results show that the response of the household sector is as expected in the theory: a monetary policy shock occurs that increases the policy interest rate by 0.29%, leading to a decrease in consumer spending of about 0.041%, the shock fades after one year. Estimates from the VAR model give similar results: a monetary policy shock narrows income inequality after about 2–3 quarters and this process tends to slow down in the long run.

Based on the research results, the authors propose policy implications for the SBV to achieve the goal of price stability, and stabilizing the macro-economic environment in Vietnam.

The findings of the study have theoretical contributions and empirical scientific evidence showing the effectiveness of the implementation of the SBV’s monetary policy in the context of macro-instability, namely: flexibility, caution and coordination of different measures promptly.

The purpose of this paper is to expand and analyze deeply customer emotions, concretize the levels of positive or negative emotions with the aim of using machine learning methods, and build a model to identify customer emotions.

The study proposed a customer emotion detection model and data mining method based on the collected dataset, including 80,593 online reviews on agoda.com and booking.com from 2009 to 2022.

By discerning specific emotions expressed in customers' comments, emotion detection, which refers to the process of identifying users' emotional states, assumes a crucial role in evaluating the brand value of a product. The research capitalizes on the vast and diverse data sources available on hotel booking websites, which, despite their richness, remain largely unexplored and unanalyzed. The outcomes of the model, pertaining to the detection and classification of customer emotions based on ratings and reviews into four distinct emotional states, offer a means to address the challenge of determining customer satisfaction regarding their actual service experiences. These findings hold substantial value for businesses operating in this domain, as the findings facilitate the evaluation and formulation of improvement strategies within their business models. The experimental study reveals that the proposed model attains an exact match ratio, precision, and recall rates of up to 81%, 90% and 90%, respectively.

The study has yet to mine real-time data. Prediction results may be influenced because the amount of data collected from the web is insufficient and preprocessing is not completely suppressed. Furthermore, the model in the study was not tested using all algorithms and multi-label classifiers. Future research should build databases to mine data in real-time and collect more data and enhance the current model.

The study's results suggest that the emotion detection models can be applied to the real world to quickly analyze customer feedback. The proposed models enable the identification of customers' emotions, the discovery of customer demand, the enhancement of service, and the general customer experience. The established models can be used by many service sectors to learn more about customer satisfaction with the offered goods and services from customer reviews.

The research paper helps businesses in the hospitality area analyze customer emotions in each specific aspect to ensure customer satisfaction. In addition, managers can come up with appropriate strategies to bring better products and services to society and people. Subsequently, fostering the growth of the hotel tourism sector within the nation, thereby facilitating sustainable economic development on a national scale.

This study developed a customer emotions detection model for detecting and classifying customer ratings and reviews as 4 specific emotions: happy, angry, depressed and hopeful based on online booking hotel websites agoda.com and booking.com that contains 80,593 reviews in Vietnamese. The research results help businesses check and evaluate the quality of their services, thereby offering appropriate improvement strategies to increase customers' satisfaction and demand more effectively.

Reconstruction of old buildings is often necessary after prolonged usage, but these projects encounter various complexities, leading to their failure. However, there is a lack of studies that focus on investigating the complexity of old building reconstruction initiatives. Thus, this study aims to examine the complexity of reconstruction projects for old buildings in Vietnamese urban areas.

Through a literature review and discussions with experienced practitioners, 12 significant complexity factors were identified. The study then utilized the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to analyze the interrelationships among these complexity factors.

The findings revealed intricate interdependencies among the complexity factors, visualized in a complexity map. The map highlighted the critical complexities of site compensation, clearance and the long project duration. Furthermore, a causal diagram categorized the complexity factors into net-effect and net-cause groups.

By examining the relationships and interactions among these factors, the study emphasizes the interconnected nature of complex systems and the influence of one factor on others. Therefore, decision-makers and stakeholders involved in reconstructing old buildings are suggested to possess a comprehensive understanding of these interdependencies to ensure effective decision-making.

In recent years, climate for innovation has attracted wide attention from industry and academia. It is perceived as a critical component of innovation performance in the built environment sector, especially in architectural design firms (ADFs). This study attempts to assess the degree of climate for innovation in the Vietnamese ADFs under the organizational climate theory.

A list of 13 innovation climate variables was found by reviewing previous studies and discussions with industry practitioners. These variables were then categorized into three principal factors (personal commitment, tolerance of difference, and support for creativity), forming the inputs of the fuzzy synthetic evaluation (FSE) analysis.

The results showed that the overall level of innovation in the climate is moderate, implying that it is still necessary for more improvements to the Vietnamese ADFs. The fuzzy analysis revealed that support for creativity was the most critical factor, followed by tolerance of difference and personal commitment.

The proposed climate for innovation model is practical and reliable for architectural professionals and can be applied to assess other research areas. Few studies have emphasized the innovation climate in the construction sector, so this research may broaden the knowledge and literature on the industry, especially for the ADFs.

In this paper, the authors examine the association between conditional conservatism and deviations of the first digits of financial statement items from what are expected by Benford's Law.

This research uses data of companies listed on the London Stock Exchange. The authors measure deviations of first digits from Benford's Law following Amiram et al. (2015) and firm-year conditional conservatism following previous studies (Basu, 1997; Khan and Watts, 2009; García Lara et al., 2016). The authors use multiple regressions to provide evidence for their hypothesis.

The results show that conditional conservatism is positively associated with deviations from Benford's Law. The findings are robust across different measures of deviations and conditional conservatism. Also, the authors find that the relationship between deviations from Benford's Law and conditional conservatism is more pronounced for firms with debt issuance, and for leveraged firms facing financial distress. Next, the authors’ analyses confirm previous evidence by showing that the first digits of financial statement items of UK listed companies conform to Benford's Law at the firm-specific level and the market level, and deviations of income statements are larger than those of balance sheets and cash flow statements.

The research makes significant contributions to the literature. First, this is the first study that provides empirical evidence suggesting that conditional conservatism may be a source of deviations from Benford’s Law. Second, the authors provide evidence confirming previous US findings (e.g. Amiram et al., 2015) showing that the distributions of first digits of financial statement items of UK listed companies also conform to Benford's Law.

The authors’ findings have implications for auditors. Auditors should be aware of “false positive” for material misstatements when using Benford's Law as a risk assessment procedure. While both conditional conservatism and earnings management are related to deviations from Benford's Law, conservatism-related biases could indicate less audit risks.

The authors provide new and original evidence suggesting that conditional conservatism is related to deviations from Benford's Law.