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Shipping is a major source of air pollution, causing severe impacts on the environment and human health, greatly contributing to the creation of greenhouse gases and influencing climate change. The research was investigated to provide a better insight into the emission inventories in the Red River in Hanoi (Vietnam) that is often heavily occupied as the primary route for inner-city waterway traffic.

The total emissions of seven different pollutants (PM₁₀, PM_2.5, SO_x, CO, CO₂, NO_x and HC) were estimated using the SPD-GIZ emission calculation model.

The results show that CO₂ has the most significant contribution to the gas volume emitted: 103.21 tons/day. Remarkably, bulk carriers are the largest emission vehicle, accounting for more than 97% of total emissions, due to their superior number and large capacity.

The result to have a roadmap for making efforts to fulfil its commitment so that it could achieve its net-zero climate target by 2050 in Vietnam as committed at COP26.

In this research, the number of vehicles and types of vessels travelling on the Red River flowing within Hanoi territory and other activity data are reported. The tally data will be used to estimate emissions of seven different pollutants (PM₁₀, PM_2.5, SO_x, CO, CO₂, NO_x and HC) using a method combining both top-down and bottom-up approaches.

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.

In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.

To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.

The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.

This research has not been published anywhere else.

Customer reviews on online platforms after their service experience not only provide useful information to help other customers make reasonable decisions about the hotel, but also provide a great opportunity for scholars to refresh the research directions on customer experience and satisfaction in tourism services. This paper aims to discover the key driver of international tourist satisfaction in the hospitality service and the way to effectively improve this factor, starting with the abundant online customer reviews.

A multi-perspective approach was used to compare the differences in service providers and service user’s interpretation of the factors that shape customer satisfaction. In addition to content analysis of nearly 2,500 online reviews of international tourists for 21 high-class hotels in Vietnam on Booking.com in 2019, the authors conducted in-depth interviews with the managers of 5-star hotels to show a comprehensive picture of customer satisfaction drivers, especially the staff factor.

The research results have clarified the main aspects of the staff – the most important service factor among the seven hotel service factors investigated from the customer’s perspective. On the other hand, the study also emphasized the gap between customers’ perception of the staff and the enterprise’s efforts and implementation of this factor. These findings allowed to identify aspects of staff that could be further improved to more effectively satisfy customers and provide a superior experience.

The study suggested a potential research direction using a multi-perspective approach to better understand trends and shifts in customer experience and satisfaction. Further studies could overcome the limitation of the research scope of this paper by examining different destinations or expanding the exploration of both mid-range and budget hotels.

The findings offer implications for managers to improve tourist satisfaction by developing organizational culture and mindfulness-related training programs for employees.

This study has enriched the literature of tourism and hospitality services by providing empirical evidence on the exploitation of big data sources and deepening the insights into international tourist satisfaction with hotel services.

This study aims to explore the mediating roles of self-efficacy and learning orientation in the relationship between entrepreneurship education and entrepreneurial intentions of university students in Vietnam.

The data were collected from an online survey of 1,021 university students in Vietnam. The authors conducted a hierarchical regression analysis to test the hypotheses.

The results of hierarchical regression analysis reveal that entrepreneurship education positively affects entrepreneurial intentions, and this relationship is mediated by both learning orientation and self-efficacy.

This study confirms the importance of entrepreneurship education in encouraging university students' entrepreneurial intentions.

This study offers practical implications for universities and policy makers.

This study is one of the first to empirically examine the concept of entrepreneurship education and entrepreneurial intentions in an Asia-Pacific context.

This study emphasises the significance of entrepreneurship education and its effects on university students' entrepreneurial intentions. Furthermore, the findings confirm that self-efficacy and learning orientation play an important part in explaining how entrepreneurship education relates to entrepreneurial intentions.

COVID-19 hits every country’s health-care system and economy. There is a trend toward using automation technology in response to the COVID-19 crisis not only in developed countries but also in those with lower levels of technology development. However, current studies mainly focus on the world level, and only a few ones report deployments at the country level. The purpose of this paper is to investigate the use of automation solutions in Vietnam with locally available materials mainly in the first wave from January to July 2020.

The authors collected COVID-related automation solutions during the first wave of COVID-19 in Vietnam from January to July 2020 through a search process. The analysis and insights of a panel consisting of various disciplines (i.e. academia, health care, government, entrepreneur and media) aim at providing a clear picture of how and to what extent these solutions have been deployed.

The authors found seven groups of solutions from low to high research and development (R&D) levels deployed across the country with various funding sources. Low R&D solutions were widely spread owing to simplicity and affordability. High R&D solutions were mainly deployed in big cities. Most of the solutions were deployed during the first phases when international supply chains were limited with a significant contribution of the media. Higher R&D solutions have opportunities to be deployed in the reopening phase. However, challenges can be listed as limited interdisciplinary research teams, market demand, the local supporting industry, end-user validation and social-ethical issues.

To the authors’ best knowledge, this is the first study analyzing the use of automation technology in response to COVID-19 in Vietnam and also in a country in Southeast Asia. Lessons learned from these current deployments are useful for future emerging infectious diseases. The reality of Vietnam’s automation solutions in response to COVID-19 might be a reference for other developing countries with similar social-economic circumstances and contributes to the global picture of how different countries adopt technology to combat COVID-19.

This paper aims to assess the economic impacts of the European Union’s Carbon Border Adjustment Mechanism (CBAM) on Vietnam.

We constructed a general equilibrium model to assess the economic impacts of the CBAM on the macroeconomic indicators of Vietnam. We also constructed a generic partial equilibrium model to provide a zoomed-in view of the impact on each group of CBAM-targeted commodities, which is not possible in the general equilibrium model. Both the general equilibrium and the partial equilibrium models were calibrated with publicly available data and a high number of value sets of hyperparameters to estimate the variations of the estimated impacts.

The results suggest that the current form of the EU’s CBAM is unlikely to produce substantial effects on the overall economy of Vietnam, mainly because the commodities affected by it represent a small portion of Vietnam’s exports. However, at the sectoral level, the CBAM can reduce production outputs and export values of steel, aluminium, and cement.

The CBAM by itself may not lead to significant decreases in greenhouse gas emissions, but it could provide a rationale for implementing carbon pricing strategies, which might result in more significant economic effects and help in reducing greenhouse gas emissions. This highlights the necessity of supplementary policies to tackle global climate change.

We constructed economic models to evaluate the impacts of the European Union’s Carbon Border Adjustment Mechanism on Vietnam, both at the macroeconomic level and zooming in on directly impacted groups of commodities.

Official development assistance (ODA) education projects have played a crucial role in improving education and training fields in developing countries, but are often facing several considerable challenges (e.g. long implementation time). Thus, this study aims to identify critical success factors (CSFs) in ODA education projects and investigate the influences of CSFs on ODA project performance measured by 11 nonprofit outcomes (NPOs).

A comprehensive literature review and expert interviews were conducted to compile a list of 35 potential success factors for ODA education projects. Using a survey questionnaire, 143 valid responses were collected from practitioners joining ODA projects in Vietnam. Various statistical methods (e.g. mean score method, Spearman rank correlation test, analysis of variance test, factor analysis and regression analysis) were used to analyze the collected data.

This research identified seven CSFs for ODA education projects in Vietnam: comprehensive project management competency (C1), clarity and compliance in project execution (C2), transparency and committed funding (C3), external context conditions (C4), well-controlled design and project management procedures (C5), preparations in equipment and complexity insight (C6) and punctual site delivery (C7). Furthermore, the results of regression analysis indicated that comprehensive project management competency (C1) and transparency and committed funding (C3) could significantly affect various NPOs.

This study offers significant insights for practitioners (e.g. project managers) to improve ODA projects’ performance and effectiveness in the education and training sector of a developing country context (like Vietnam).

The current review aims to examine the growth trajectory, most influential documents, intellectual and conceptual structure of the literature regarding gender issues in family business research.

The bibliometric analysis was performed using 224 documents from 1991 to 2020 extracted from the Web of Science database.

The review finds that this field's knowledge grew exponentially during the last three decades, mainly after 2003 and the last several years. Based on the co-citation analysis, three major research lines are identified: “Women's challenges and opportunities in the family business”, “Gender diversity in the family business corporate board”, and “Gender and family SMEs management.” The temporal co-word analysis reveals that “Gender diversity in the family business corporate board” is the latest research line.

By reviewing prominent cited references and documents that cited them, the authors provide the landscapes and research gaps of three major research lines for further development.

Using a substantial sample of U.S.-listed firms’ Seasoned Equity Offerings (SEOs) spanning the period from 2012 to 2017, we examine the relationship between hierarchical complexity and the selection of SEO methods.

We employ multinomial logistic regression to examine the influence of hierarchical complexity on the choice among various SEO techniques. To strengthen the robustness of our results, we employ a two-stage-least-squares (2SLS) analysis and utilize propensity score matching to address potential endogeneity issues and mitigate self-selection bias, respectively.

The research indicates that companies characterized by high levels of hierarchical complexity tend to steer clear of accelerated offerings but exhibit a preference for rights offerings over firm commitment offerings. This tendency is plausibly attributed to the impact of hierarchical complexity, which diminishes information transparency and heightens information asymmetry. Furthermore, the study highlights a negative association between hierarchical complexity and firm value following SEOs.

While an expanding body of evidence establishes a connection between hierarchical complexity and various firm- or market-specific activities, to the best of our knowledge, there are no specific empirical studies that have investigated how hierarchical complexity impacts equity offering strategies. Building on the established correlation in previous research between hierarchical complexity, information transparency, and asymmetric information, and recognizing the critical role of information in the selection of SEO methods, our study reveals that hierarchical complexity may diminish information transparency, heighten information asymmetry, and hinder outside investors from fully grasping a firm’s actions and outcomes. Consequently, this influence extends to the methods of offerings chosen by listed companies.