Search results

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).

This chapter provides information on the development of Vietnamese education under the influence of global forces based on the analysis of relevant education research and policies using Wolhuter’s frameworks. In the process of coming up with ways to develop education in the face of different influences of globalization, besides having reactions with patterns commonly found in countries around the world, Vietnam also has responses that reflect its own political, sociocultural and economic characteristics. The state still plays a controlling role in education at all levels and many culture-related features that have existed throughout the country’s history have hardly changed, namely aspects related to teachers, learners and teaching and learning methods. To sustain its education in the globalized era, Vietnam must make more efforts in various aspects such as the link between education and employment, the logic of education objectives, the feasibility and appropriateness of curricula, quality of education, especially of higher education and equality in education for underprivileged groups.

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.

This paper aims to identify the disproportionate impacts of the COVID-19 pandemic on labor markets.

The authors conduct a large-scale survey on 16,000 firms from 82 industries in Ho Chi Minh City, Vietnam, and analyze the data set by using different machine-learning methods.

First, job loss and reduction in state-owned enterprises have been significantly larger than in other types of organizations. Second, employees of foreign direct investment enterprises suffer a significantly lower labor income than those of other groups. Third, the adverse effects of the COVID-19 pandemic on the labor market are heterogeneous across industries and geographies. Finally, firms with high revenue in 2019 are more likely to adopt preventive measures, including the reduction of labor forces. The authors also find a significant correlation between firms' revenue and labor reduction as traditional econometrics and machine-learning techniques suggest.

This study has two main policy implications. First, although government support through taxes has been provided, the authors highlight evidence that there may be some additional benefit from targeting firms that have characteristics associated with layoffs or other negative labor responses. Second, the authors provide information that shows which firm characteristics are associated with particular labor market responses such as layoffs, which may help target stimulus packages. Although the COVID-19 pandemic affects most industries and occupations, heterogeneous firm responses suggest that there could be several varieties of targeted policies-targeting firms that are likely to reduce labor forces or firms likely to face reduced revenue. In this paper, the authors outline several industries and firm characteristics which appear to more directly be reducing employee counts or having negative labor responses which may lead to more cost–effect stimulus.

Unsustainable logging and illegal logging for domestic and international trade and trafficking continue to lead to deforestation. It is crucial that Sustainable Development Goal 15 ‘Sustainably manage forests, combat desertification, halt and reverse land degradation, halt biodiversity loss’ is achieved to maintain the livelihoods of people and protect the planet. This is the case in Vietnam as well, where many people, including indigenous groups, rely on the forest for their survival. Drawing on semistructured interviews in Vietnam and a literature review, we investigate how the abuse of forest policies leads to human insecurity. From this, we propose solutions to (1) end unsustainable harvesting and illegal logging (SDG 15.7), (2) integrate the value of forests (culturally and economically) into national and local planning, the development process and poverty elimination strategies (SDG 15.9) and (3) improve the use of forest protection funding provided by international donors.

The purpose of this paper is to trace the way in which a popular ritual became one of Vietnam’s most important festivals, elevated as a celebration of national heroism and charts its gradual transformation in modern society.

This research focuses on the combination of a fertility rite and narratives of St Gióng based on nationalism or heroism created a special festival reflecting many traditional cultural characteristics of Vietnam and the Việt people and the transformation of St Gióng from a mythological to a national symbol of heroism in anti-invader history was recorded in texts.

The paper casts light on the mythologization and historicization of St Gióng in Vietnam’s particular historical context by decoding the Gióng symbol as a core element of the folktales and myths about St Gióng to understand the formation and development of St Gióng in the cultural history of Vietnam.

The paper is not exploring the Gióng symbol within a larger cultural context of nationalism and ethnosymbolic approach in a comparison of national symbolism and heroism.

The paper includes implications for advised scholars to conduct further exploration of the symbol and myth of not only St Gióng in Vietnam but also Kubera in India and Vaisravana in China to connect Kubera, Vaisravana and St Gióng under the connection of literal myth and heroic symbol.

The paper shows how processes of historicizing myth and mythologizing history are important features of Vietnamese socio-historical research.

The paper shows how a fertility rite became a historical festival and the figure of St Gióng became a symbol of patriotic heroism.

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.

This study investigates the interactions between the US daily public debt and currency power under impacts of the Covid-19 crisis.

The authors employ the multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) modeling to explore the interactions between daily changes in the US Debt to the Penny and the US Dollar Index. The data sets are from April 01, 1993, to May 27, 2022, in which noticeable points include the Covid-19 outbreak (January 01, 2020) and the US vaccination campaign commencement (December 14, 2020).

The authors find that the daily change in public debt positively affects the USD index return, and the past performance of currency power significantly mitigates the Debt to the Penny. Due to the Covid-19 outbreak, the impact of public debt on currency power becomes negative. This effect remains unchanged after the pandemic. These findings indicate that policy-makers could feasibly obtain both the budget stability and currency power objectives in pursuit of either public debt sustainability or power of currency. However, such policies should be considered that public debt could be a negative influencer during crisis periods.

The authors propose a pioneering approach to explore the relationship between leading and lagging indicators of an economy as characterized by their daily data sets. In accordance, empirical findings of this study inspire future research in relation to public debt and its connections with several economic indicators.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2022-0581

This study aims to investigate the impact of AI chatbots on customer trust in AI chatbots for hotel services.

The probability sampling method was employed to develop a research sample. The research uses correlation analysis and structural equation modeling to analyze the data of 413 valid observations collected in the structured questionnaire survey in Vietnam.

The paper reports that empathy response, anonymity and customization significantly impact interaction. Empathy response is found to be the strongest influence on interaction. Meanwhile, empathy response and anonymity were revealed to indirectly affect customer trust. This paper also contributes several implications for hotel providers in emerging economies.

To the best of the authors’ knowledge, this is the first study to shed light on the role of AI chatbots in explaining customers’ behavior. The results provide an enhanced understanding of how the AI chatbot system influences customers’ decision-making. It has been used to plan the chatbot application and highlight which implementation issues need the most attention in the hospitality industry.