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Ho Chi Minh City (HCMC), Vietnam's largest urban center, is home to over 9 million people and faces significant challenges due to rapid urbanization and the heavy reliance on personal vehicles. Over 95% of urban passenger transport in HCMC relies on high-emission cars, contributing to severe air pollution and slowing progress toward the United Nations Sustainable Development Goals (SDGs). Greening HCMC's transport system is essential to reducing emissions and achieving SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action). Despite ongoing efforts, many barriers continue to hinder this transition. This paper aims to identify and prioritize these barriers using the fuzzy TOPSIS method. The results highlight limited infrastructure investment, a lack of charging stations, and unclear policies as the top obstacles. Other challenges include poor service quality, dependence on private vehicles, low community awareness, high fuel prices, and the cost of green vehicles. These findings offer a foundation for proposing solutions and prioritizing actions to build an eco-friendly transport system. This would directly support the SDGs related to sustainable cities, climate action, and public health. A thorough analysis of these barriers and their impact is vital to expedite and enhance the "greening" process by focusing on factors with significant and decisive influence. [ABSTRACT FROM AUTHOR]

Urbanization is often considered a manifestation of social development, but at the same time, it can be a factor that erodes the distinctive values of a particular area. Urban studies suggest that many factors beyond physical appearance shape a city's appeal, including a combination of cultural, economic, social, environmental, and historical values. Our previous research identified a comprehensive conceptual framework of factors contributing to urban staycation identity, encompassing 141 specific elements within nine dimensions. In this study, we apply environmental behavior studies theory to explore human perceptions of these factors, using residents' perception questionnaires and statistical analysis to gather and analyze data. Through these approaches, this research identified 94 elements in 22 categories within eight dimensions that significantly contribute to the appeal of urban areas for different demographic groups. These findings provide concrete evidence that Ho Chi Minh City's allure is closely intertwined with broader processes of urbanization. The study also offers actionable insights for urban planners, policymakers, and designers seeking to enhance the attractiveness of urban environments, with a particular focus on Ho Chi Minh City. [ABSTRACT FROM AUTHOR]

The application of machine learning and deep learning in air pollution management is becoming increasingly crucial, as these technologies enhance the accuracy of pollution prediction models, facilitating timely interventions and policy adjustments. They also facilitate the analysis of large datasets to identify pollution sources and trends, ultimately contributing to more effective and targeted environmental protection strategies. Ho Chi Minh City (HCMC), a major metropolitan area in southern Vietnam, has experienced a significant rise in air pollution levels, particularly PM2.5, in recent years, creating substantial risks to both public health and the environment. Given the challenges posed by air quality issues, it is essential to develop robust methodologies for predicting PM2.5 concentrations in HCMC. This study seeks to develop and evaluate multiple machine learning and deep learning models for predicting PM2.5 concentrations in HCMC, Vietnam, utilizing PM2.5 and meteorological data over 911 days, from 1 January 2021 to 30 June 2023. Six algorithms were applied: random forest (RF), extreme gradient boosting (XGB), support vector regression (SVR), artificial neural network (ANN), generalized regression neural network (GRNN), and convolutional neural network (CNN). The results indicated that the ANN is the most effective algorithm for predicting PM2.5 concentrations, with an index of agreement (IOA) value of 0.736 and the lowest prediction errors during the testing phase. These findings imply that the ANN algorithm could serve as an effective tool for predicting PM2.5 concentrations in urban environments, particularly in HCMC. This study provides valuable insights into the factors that affect PM2.5 concentrations in HCMC and emphasizes the capacity of AI methodologies in reducing atmospheric pollution. Additionally, it offers valuable insights for policymakers and health officials to implement targeted interventions aimed at reducing air pollution and improving public health. [ABSTRACT FROM AUTHOR]

This study surveys the actual situation of vocabulary development for 5–6-yearolds children in some preschools in Ho Chi Minh city. The results revealed main issues such as: Preschool teachers' awareness of the importance of using games for vocabulary development; Methods for teachers to design and organize vocabulary development games and evaluate their effectiveness; Difficulties in creating engaging games for this age group. Additionally, the study explores teachers' perspectives on game design and assesses children's vocabulary development levels. This study provides valuable practical insights to assist preschool teachers in designing vocabulary development games for 5-6- year-olds, thereby promoting overall language development.

Good transport infrastructure and services improve the well-being of all groups of the population, including women, men, children, the elderly and people with disabilities. However, they are often incorrectly considered 'gender-neutral'. Mobility is socially determined by gender roles related to reproduction, production and community. This research investigates the cohesive relationship of urban transportation, including mobility, gender and care, by studying the case of Ho Chi Minh City (HCMC). The differences between women's and men's participation in transportation are identified and connected to gender-role activities. The findings show a clear relationship between urban mobility and gender roles. There is clear evidence of women's trade-off between travelling less than men and carrying more unpaid work in the family, which is more pronounced for married women who live with their families. Differences in women's traffic experiences compared to men's reveal the disadvantages that women face in traffic. The findings of this research will assist the HCMC transport sector and project executive agencies in designing gender-inclusive projects. The dissemination of this research will draw attention to the gender dimension of transport and encourage gender mainstreaming across the transport sector to promote and support equality and women's empowerment. [ABSTRACT FROM AUTHOR]

According to the greenhouse gas (GHG) protocol for cities, GHGs are responsible for an estimated 75 per cent of global energy-related carbon dioxide emissions. This represents a key opportunity to tackle climate change. With the year 2023 and, in particular, the month of July delivering record-breaking temperatures, this demonstrates a clear need to accelerate decarbonisation and, in this context, to reduce the carbon footprint of cities. Further, acting on urban development addresses a number of key United Nations Sustainable Development Goals (UNSDGs). Many cities, however, are struggling to break away from a reliance on carbon and some are economically dependent on it. This paper seeks to investigate, through an energy justice lens, some first considerations of how to secure just and sustainable urban regeneration. It posits that energy justice, and its five core principles, is a useful analytical tool for considering the justice and development concerns related to the transition to a low-carbon world. The cities examined in brief in this comparative study are Bordeaux in France, Venice in Italy, Ho Chi Minh City in Vietnam and Bangkok in Thailand. The research posits that despite different trajectories, cities can play a leading role in ensuring justice and sustainability in our low-carbon world. [ABSTRACT FROM AUTHOR]

This research investigates the novel design and implementation of a relational mapping of city spaces, based on research conducted in Ho Chi Minh City, Vietnam. The experimental mapping employs relational methods of exploration to document and understand the city. A special Memefest mapping workshop used food as a key medium for some of the relationships that underpin the culture, community, and the city itself. This paper outlines the design of a sensory based exploration and creative mapping of food culture in Ho Chi Minh City and puts special emphasis in the atmospheres that are created through the relations between food, community, and the structures that underlie these. Lastly the paper shows an example of installations and explains how they work as (post) representational maps of relations and atmospheres. [ABSTRACT FROM AUTHOR]

AbstractThe main aim of this research is to examine the extent to which specific personal values are used for explaining employee engagement at work. Data was collected by survey questionnaires from 255 respondents working for firms located in Ho Chi Minh City during the covid-19 panamic and processed by Smart PLS. The findings indicate that self-enhancemen higher-order value (Power – Stimulation), openness to change higher-order value (Hedonism – Self-direction – Achievement), and conformity basic personal vaule impact on employee engagement significantly at the 5% and 1% level, respectively. The research findings inferred that employee engagement is influenced by the basic personal values (Conformity) or the convergence of personal values such as Power and Stimulation values, and Hedonism, Self-direction, and Achievement values. Therefore, engaged employees can be detected based on identifying their personal values. These personal values explain 37.7% of the variance of employee engagement at work in the Vietnam context.

This study aims to predict fine particulate matter (PM2.5) pollution in Ho Chi Minh City, Vietnam, using autoregressive integrated moving average (ARIMA), linear regression (LR), random forest (RF), long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), and convolutional neural network (CNN) combining Bi-LSTM (CNN+Bi-LSTM). Two experiments were set up: the first one used data from 2018–2020 and 2021 as training and test data, respectively. Data from 2018–2021 and 2022 were used as training and test data for the second experiment, respectively. Consequently, ARIMA showed the worst performance, while CNN+Bi-LSTM achieved the best accuracy, with an R² of 0.70 and MAE, MSE, RMSE, and MAPE of 5.37, 65.4, 8.08 µg/m³, and 29%, respectively. Additionally, predicted air quality indexes (AQIs) of PM2.5 were matched the observed ones up to 96%, reflecting the application of predicted concentrations for AQI computation. Our study highlights the effectiveness of machine learning model in monitoring of air pollution.

This study assesses the increasing flood risks in Ho Chi Minh City due to climate change and urbanization, and proposes the implementation of the sponge city concept as a solution to enhance flood resilience. Through a comprehensive analysis of literature, data, and models, coupled with GIS techniques, the study reveals the escalating flood risks in the city, both from inland and from the coast. The sponge city concept, which integrates nature-based solutions such as green spaces and water storage facilities, is presented as a means to improve flood resilience. The study analyzes the opportunities and constraints in the application process, provides recommendations to utilize opportunities and overcome constraints, and suggests some potential locations for implementation. The findings highlight the importance of incorporating nature-based solutions into urban planning and development strategies to create sustainable and resilient cities. While focusing on Ho Chi Minh City, the study's recommendations can be applicable to other urban areas facing similar flood challenges. Further research and feasibility studies are recommended to fully implement the sponge city concept.

Academic, government, and industry researchers have attempted to build some theoretical and empirical ways to understanding how to innovate and interact in data- driven contexts in recent years. However, it does not appear to go above and beyond our expectations in terms of offering fresh views and resources to investigate this trend in terms of measurement. In this brief study, I show how Dimensions.ai, a new academic big data resource, can be used to assess knowledge-based innovation processes in emerging and transitional countries like Vietnam. This article investigates creativity and collaboration in Ho Chi Minh City using a "n-tuple helix" framework based on Loet Leydesdorff's sociological theory of communication. From a social network standpoint, I argued that a city's innovation system is inextricably linked to its position in intercity and global co-authorship networks. This shows how the helix model and applications can be utilized to discover a data-driven society. [ABSTRACT FROM AUTHOR]

BackgroundA baseline of hepatitis C virus (HCV) burden and other HCV epidemiological profiles is necessary for HCV micro-elimination in Ho Chi Minh City (HCMC), Viet Nam. This study aimed to determine HCV exposure and prevalence of HCV viremia as well as the proportion of HCV testing and treatment uptake among participants.MethodsFrom 2019 to 2020, the probability proportionate to size sampling method was deployed to representatively invite approximately 20,000 adults (18 or older) throughout HCMC to free screening and linkage to care for HCV.FindingsIn HCMC, the weighted prevalence of anti-HCV was 1·3% (95% CI, 1·1%-1·6%). Individuals born from 1945 to 1964 had the anti-HCV prevalence of 3·6% (95% CI, 3·0%-4·2%) and represented 40·4% of all HCV cases. There were wide variations in anti-HCV prevalence in HCMC, including variations between districts, risk factors, and socioeconomic statuses. A baseline HCV continuum of care for the city demonstrated that only 28·5% (85/298, 95%CI 23·4-33·7%) of persons with anti-HCV (+) were aware of their HCV status, with 77.6% (66/85, 95%CI 68·8-86·5%) diagnosing HCV incidentally, 82·7% (62/75, 95%CI 74·1-91·2%) initiating anti-HCV therapy, and 53.6% (30/56, 95%CI 40·5-66·6%) achieving HCV cures.InterpretationThere remains a considerable disease burden of HCV in HCMC of which a significant proportion was in the age group born between 1945 to 1964. Additionally, there were significant gaps in HCV awareness, screening, and access to care in the community in Viet Nam. Thus, future interventions must have pragmatic targets, be tailored to the local needs, and emphasise screening.FundingThis work was supported by investigator-sponsored research grants from Gilead Sciences Inc. (Grant No: IN-US-987-5382); Roche Diagnostic International Ltd. (Grant No. SUB-000196); and in-kind donations from Abbott Diagnostic Viet Nam; Hepatitis B Foundation; Medic Medical Center, Viet Nam; Johns Hopkins University School of Medicine's Center of Excellence for Liver Disease in Viet Nam; and the Board of Directors, Viet Nam Viral Hepatitis Alliance (V-VHA).

The article mentions the migration factor associated with the movement of labor in Ho Chi Minh City, specifically the number of workers by urban and rural areas by economic sector and enterprise sector. There have been both positive and negative impacts, especially on immigrant workers. Research methods of dialectical materialism, historical materialism along with the approach of historical science were used. In addition, data collection methods and data analysis methods combined with sociological approaches are also applied. The research results reconstruct the overall migration process in Ho Chi Minh City and its impacts. Simultaneously, the article offers a number of ecommendations to improve policies for this group with the purpose of advising the government to promote migrant workers in the coming years.

Applying STEM education to primary schools leads to many practical benefits, in line with the trend of general education innovation. The Ministry of Education and Training deployed Official Dispatch 3089/BGDDT-GDTrH dated August 14, 2020 on implementing STEM education in schools at 3 levels: STEM lessons, STEM experiences, STEM scientific and technical research. However, in current reality, the quality of STEM education in primary schools still has many limitations from teachers and administrators. This article reviews and analyzes the current status of STEM education in primary schools in Ho Chi Minh City, thereby developing measures to manage STEM education capacity development activities for primary school teachers to meet the 2018 General Education Program.

Abstract The emission sources of fine particulate matter (PM2.5) have not yet been fully identified in Ho Chi Minh City (HCMC), Vietnam, presenting difficulties to authorities in controlling air pollution efficiently. To address this issue, this study explores the source apportionment of PM2.5 by the positive matrix factorization (PMF) model and identifies potential regional sources through the weighted concentration-weighted trajectory (WCWT) model based on the field observation data of PM2.5 in HCMC. 24-h PM2.5 samples were collected in central HCMC for a year (September 2019–August 2020). Herein, inductively coupled plasma mass spectroscopy was used to analyze trace elements, in addition to identifying PM2.5 mass and other chemical species, such as water-soluble ions and carbonaceous species, reported in our former study. The PMF results showed that PM2.5 in HCMC was dominated by anthropogenic-rich sources comprising biomass burning, coal combustion, transportation, and crustal origins (36.4% of PM2.5 mass), followed by secondary ammonium sulfate (18.4%), sea salt (13.7%), road dust (9.6%), and coal and crude oil combustion (9.4%). WCWT results suggested that the geological sources of PM2.5 were mainly from local areas and scattered to the northeast/southwest of HCMC. In addition, the long-range transport of PM2.5 from surrounding countries was revealed during the assembly restriction and lockdown period in 2020. Graphical Abstract

This paper contributes to the understanding of the recent urban development of Ho Chi Minh City, Vietnam. Previous studies have aimed at quantifying the city's spatial growth yet have disregarded its inherent morphological and socio-economic heterogeneity. To overcome this knowledge gap, we employ an urban structure type approach for the spatially explicit quantification of urbanisation patterns for the period 2010–⁠2020, categorising 77,000 blocks across the entire administrative area of 2095 km2. The approach allows us to understand the basic underlying processes of urbanisation, both quantitatively and qualitatively, and the main growth corridors along the rural–urban gradient. By contextualizing and combining our findings within current literature and official planning reports, we discern between traditional urban growth and the contemporary new town development patterns, highlighting their driving forces and policy implications. Incremental plot-by-plot development along the northwest development corridor is observed as the principal mode of urban development, whilst bypass urbanisation is seen along both the eastern and southern development corridors. Our block-based results highlight the city's key growth challenges and provide insights on a scale that is meaningful for official spatial and infrastructure planning, and periodic analysis and monitoring. As far as the authors are aware, this is the first time that an urban structure type approach was applied to understand the rapid urban growth dynamics of an emerging megacity in Southeast Asia. [ABSTRACT FROM AUTHOR]

The emission sources of fine particulate matter (PM2.5) have not yet been fully identified in Ho Chi Minh City (HCMC), Vietnam, presenting difficulties to authorities in controlling air pollution efficiently. To address this issue, this study explores the source apportionment of PM2.5 by the positive matrix factorization (PMF) model and identifies potential regional sources through the weighted concentration-weighted trajectory (WCWT) model based on the field observation data of PM2.5 in HCMC. 24-h PM2.5 samples were collected in central HCMC for a year (September 2019–August 2020). Herein, inductively coupled plasma mass spectroscopy was used to analyze trace elements, in addition to identifying PM2.5 mass and other chemical species, such as water-soluble ions and carbonaceous species, reported in our former study. The PMF results showed that PM2.5 in HCMC was dominated by anthropogenic-rich sources comprising biomass burning, coal combustion, transportation, and crustal origins (36.4% of PM2.5 mass), followed by secondary ammonium sulfate (18.4%), sea salt (13.7%), road dust (9.6%), and coal and crude oil combustion (9.4%). WCWT results suggested that the geological sources of PM2.5 were mainly from local areas and scattered to the northeast/southwest of HCMC. In addition, the long-range transport of PM2.5 from surrounding countries was revealed during the assembly restriction and lockdown period in 2020. [ABSTRACT FROM AUTHOR]

The impact of the COVID-19 pandemic on global tourism meant local communities in tourist destinations had to act to minimise detrimental influences. Researching the perceptions of locals towards tourism operations could provide insights into what communities might do to address the restrictions preventing the coronovirus imposed on international tourism operations. This research in Ho Chi Minh City assessed risk perception when residents participate in tourism activities. The findings reveal that: local participation levels are associated with risk perceptions in collaborations between communities and organisations and with attitudes towards taking vacations at home (referred to as "staycation"); there is a discernible relationship between collaboration and attitudes about staycation during the pandemic; and ideas of staycation and collaboration can have a positive impact in local tourism development. These results help us tackle the challenges of sustainable development, strategic planning, local management and future resilience in tourism operations during and after the pandemic. [ABSTRACT FROM AUTHOR]

After 1975, Vietnam experienced a series of dramatic changes in social class structure, and these changes continue to have strong impacts in the present period. A significant change is the emergence of a growing middle-class, and this class tends to have an essential role in economic development, as seen in many countries around the world (ADB, 2011). However, studies of the theoretical significance of the middle-class exploring practical applications of the concept in Vietnam are still quite limited. By integrating quantitative and qualitative research, this article analyses the characteristics and factors affecting the occupation of middle-class groups in Ho Chi Minh City (Vietnam). [ABSTRACT FROM AUTHOR]

This study contributes to the diversity of Vietnamese lichens with four new records for the country, including Nigrovothelium bullatum and Pyrenula confinis in urban areas and Leptogium phyllocarpum and Gabura fascicularis in central highlands. Amongst these, G. fascicularis is the first record of Arctomiaceae in Vietnam. The morphology, distribution, ecology and illustrations of all four species are provided. [ABSTRACT FROM AUTHOR]

Background: User-Generated Content (UGC) videos have received considerable attention in recent years thanks to their great potential for buyers and sellers. However, the effect of this content on consumer behavior remains unclear, especially in the context of developing countries (e.g., Vietnam). By applying the Stimulus-Organism-Response model (S-O-R model), this paper examines the effect of UGC videos on online purchase intention. Moreover, the mediating role of cognitive responses, consisting of perceived credibility, perceived diagnosticity, and mental imagery, is also examined to offer valuable insights to businesses, enabling them to leverage and effectively promote the trends of UGC videos. Method: A convenience sampling method was employed to collect the data. A total of 318 valid respondents participated in this survey. The data was analyzed with the Partial Least Squares Structural Equation Modeling method (PLS-SEM). Results: The findings show that UGC videos have a direct impact on online purchase intention. This paper also verified that cognitive states mediate the relationship between stimuli and subsequent behavioral intentions. Conclusion: Our research findings enrich the literature on consumer's online purchase intentions by applying the S-O-R framework by highlighting the role of cognitive responses, and improving generalizability by contributing additional consumer behavior findings in developing Asian nations. Moreover, this paper offers businesses insights into the formation of customers' purchase intentions while watching UGC videos. Based on that, this paper raises practical recommendations regarding promoting the UGC video trend and creating UGC videos effectively to improve the cognitive states perceived by customers, including credibility, diagnostic value, and mental imagery. [ABSTRACT FROM AUTHOR]

Background: Socioeconomic development and population growth have led to canal pollution, a challenge in Ho Chi Minh City (HCMC), Vietnam. In HCMC, diffuse pollution of rivers and canals makes applying pollution control measures at the source challenging. Poor sanitation, insufficient safe drinking water, and poor hygiene practices are the leading causes of the emergence of waterborne diseases. Methods: A cross-sectional survey was done to investigate the knowledge, behavior, and factors associated with sanitation and hygiene of residents living along the side of canals in HCMC. This study also investigated the pollution of canal water in the primary canal systems in HCMC. Results: The canal water systems at Ho Chi Minh City exceeded the permissible thresholds of Vietnam's discharge limit standards of total coliforms and E. coli. Among the 640 households interviewed, 60% of residents perceived that the polluted canal environment affected their lives. Most residents (99%) used tap water for daily activities, but 25% of households did not filter water before drinking. The hygiene behavior is uneven; more than 30% of households discharged wastewater into the canal, and nearly 60% of children have the conditions to contact flood water on the street. The causes of water pollution in canals are people's low awareness, with only 38.4% of respondents interested in canal-environmental protection activities, inadequate infrastructure (59%), and the ineffective management of surface water resources (57.8%). Conclusion: The study indicated incorrect knowledge and behavior toward sanitation and protecting the canal environment of the local people caused increasing pollution of canal water. Hence, measures must be implemented to protect the canal water environment and the community's health, such as training about sanitation and hygiene for local people.

The application of machine learning and deep learning in air pollution management is becoming increasingly crucial, as these technologies enhance the accuracy of pollution prediction models, facilitating timely interventions and policy adjustments. They also facilitate the analysis of large datasets to identify pollution sources and trends, ultimately contributing to more effective and targeted environmental protection strategies. Ho Chi Minh City (HCMC), a major metropolitan area in southern Vietnam, has experienced a significant rise in air pollution levels, particularly PM2.5, in recent years, creating substantial risks to both public health and the environment. Given the challenges posed by air quality issues, it is essential to develop robust methodologies for predicting PM2.5 concentrations in HCMC. This study seeks to develop and evaluate multiple machine learning and deep learning models for predicting PM2.5 concentrations in HCMC, Vietnam, utilizing PM2.5 and meteorological data over 911 days, from 1 January 2021 to 30 June 2023. Six algorithms were applied: random forest (RF), extreme gradient boosting (XGB), support vector regression (SVR), artificial neural network (ANN), generalized regression neural network (GRNN), and convolutional neural network (CNN). The results indicated that the ANN is the most effective algorithm for predicting PM2.5 concentrations, with an index of agreement (IOA) value of 0.736 and the lowest prediction errors during the testing phase. These findings imply that the ANN algorithm could serve as an effective tool for predicting PM2.5 concentrations in urban environments, particularly in HCMC. This study provides valuable insights into the factors that affect PM2.5 concentrations in HCMC and emphasizes the capacity of AI methodologies in reducing atmospheric pollution. Additionally, it offers valuable insights for policymakers and health officials to implement targeted interventions aimed at reducing air pollution and improving public health.

The increasing number of students intending to drop out of universities in Vietnam has raised concerns. While previous studies have addressed factors influencing dropout intentions, several aspects still need to be explored, particularly in developing countries like Vietnam. This research provides an overview of the factors influencing students’ dropout intention in Ho Chi Minh City. The study employs the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach with a survey sample of 804 students from universities in Ho Chi Minh City. The research findings reveal that factors such as Lack of university commitment (LUC), degree and course commitment (DCC), ineffective time management (ITM), curriculum design (CD), Ineffective adaptation to learning environment (IALE), low classroom participation (LCP) and personal circumstances (PC) significantly influence students’ dropout intentions. Additionally, factors including skills and attitudes of instructors (SAI), instructor support (IS), positive instructor feedback (PIF), university facilities (UF), cultural and social environment (CSE), and access to support from academic advisors (ASA) do not show statistically significant relationships with students’ dropout intention. Furthermore, the study finds no significant differences in dropout intention based on gender, area, and type of university, except for ASA has a differential impact on students’ dropout intentions based on the type of university. The research results provide valuable insights for researchers and educational experts to understand better the factors contributing to students’ dropout intentions. Moreover, the findings assist educational managers and instructors in developing appropriate support measures and interventions to enhance student engagement throughout their academic journey. Finally, the study discusses limitations and suggests future research directions. [ABSTRACT FROM AUTHOR]

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The Vietnamese government has advocated developing an export-based economy. In fact, the Prime Minister issued Decision No. 2471/QD-TTg dated December 28, 2011, approving the strategy of import and export of goods for the period 2011 to 2020, with a vision to 2030 formulating policies on development of logistics services, credit, and investment to develop export production, and customs clearance places for import and export goods. That fact prompted us to conduct the research investigating the impact of export support policies on export performance of firms locating in Ho Chi Minh City. The combination of qualitative and quantitative research method was applied. The netnography method and in-depth interview were used to explore support policies influencing export performance, and found Tax Incentives, Credit Incentives, Trade Promotion Support, and Custom Procedures Reform are four policies significantly explaining firms' export performance. To measure the impact of these policies on export performance, we surveyed 141 firms in HCMC. The quantitative study confirmed that four policies impact positively significantly on export performance. The best explanatory factor is Trade Promotion Support, the second is Customs Procedure Reforms, followed by Tax Incentives. Credit incentives have the lowest effect on export performance. The findings asserted the positive effectiveness of policies promoting export performance implementing in Vietnam, and provided empirical evidence to support institutional theory. [ABSTRACT FROM AUTHOR]

In the current 4.0 context, digital transformation is a particularly necessary thing for retail businesses in particular or most businesses in general. That’s why a sense of privacy is so important to retailers. This paper focuses on the factors affecting the privacy perception of customers in the digital transformation period in Ho Chi Minh City. 452 Ho Chi Minh City people who have experience with the digital revolution participated in quantitative research to evaluate and examine this correlation. The results of the study show that privacy impression is influenced by privacy worries, retailer vs. consumer advantage, privacy-intrusive experience, and retailer credibility. The association between customer benefit and privacy perception and between technology hedonism and privacy perception is unaffected by the role of store trustworthiness moderators.

The increasing number of students intending to drop out of universities in Vietnam has raised concerns. While previous studies have addressed factors influencing dropout intentions, several aspects still need to be explored, particularly in developing countries like Vietnam. This research provides an overview of the factors influencing students’ dropout intention in Ho Chi Minh City. The study employs the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach with a survey sample of 804 students from universities in Ho Chi Minh City. The research findings reveal that factors such as Lack of university commitment (LUC), degree and course commitment (DCC), ineffective time management (ITM), curriculum design (CD), Ineffective adaptation to learning environment (IALE), low classroom participation (LCP) and personal circumstances (PC) significantly influence students’ dropout intentions. Additionally, factors including skills and attitudes of instructors (SAI), instructor support (IS), positive instructor feedback (PIF), university facilities (UF), cultural and social environment (CSE), and access to support from academic advisors (ASA) do not show statistically significant relationships with students’ dropout intention. Furthermore, the study finds no significant differences in dropout intention based on gender, area, and type of university, except for ASA has a differential impact on students’ dropout intentions based on the type of university. The research results provide valuable insights for researchers and educational experts to understand better the factors contributing to students’ dropout intentions. Moreover, the findings assist educational managers and instructors in developing appropriate support measures and interventions to enhance student engagement throughout their academic journey. Finally, the study discusses limitations and suggests future research directions.

This study provides an exhaustive overview of the Virtual Learning Environment (VLE) system adopted by Ho Chi Minh City University of Education (HCMUE). The system, which caters to multiple forms of training and education, is detailed with descriptions of its interface, functionalities, and a selection of offered courses. While the VLE system has proven its mettle by enhancing the teacher-student interaction and overall learning experience, certain challenges persist, such as limited real-time interaction. The second part of the study delves into an empirical investigation conducted among Chinese language students. Using a structured questionnaire, the research examines five pivotal dimensions affecting online learning efficiency: student, teacher, curriculum, environment, and equipment factors. Data collected from 196 valid responses was processed to provide insights. The analysis aims to bridge the identified gaps and further bolster the effectiveness of online learning at the university. [ABSTRACT FROM AUTHOR]

In the underground lottery game—an illegal albeit prevalent gambling activity in Vietnam—players bet on two- or three-digit numbers and win money if their numbers appear in the results of the official lotteries. The predominant Vietnamese perception of the game as a problem of the lower class reveals that the underclass is conceptualized as a group with several moral shortcomings that have led to its members’ underdevelopment. However, this study shows that the game is perceived by its players as a moral reward for their responsiveness to the spiritual world around them, and for their sensibility, experience and attentiveness to daily events and dreams. [ABSTRACT FROM AUTHOR]

Mangroves play an important role in providing livelihoods, ecological services, and values to communities in Vietnam. However, mangrove forests are being significantly reduced due to socioeconomic development. This study assessed the awareness of mangrove forests and willingness to pay communities in the buffer zone of Can Gio Biosphere Reserve, Ho Chi Minh City for mangrove conservation. The model used was the contingent valuation method, through surveying 700 households in five communes in the buffer zone of the Biosphere Reserve. The results show that local people have a fairly good awareness of the values of mangroves and are willing to participate in conservation activities for the benefit of their families and future generations. The average WTP of a household is VND 529.6 thousand/year (USD 22) in the parametric model and VND 597.8 thousand/year in the non-parametric model (USD 25). Factors that significantly affect WTP include household income, number of people in the household, education and payment level. The study results provide implications for forest resource management activities in Vietnam, especially the financial mechanism for mangrove conservation with the participation of the community. [ABSTRACT FROM AUTHOR]

In this study, an evaluation model is developed to analyze the safety level of a street network in terms of accessibility for emergency services and evacuation risk for residents, especially for cities experiencing rapid urbanization and densification. The evaluation model is created based on the network geometry and street width using the Network Voronoi algorithm, and four evaluation variables are developed, namely the accessibility risk, unreachability risk, edge responsibility, and flow capacity. Next, the model is applied to an alleyway neighborhood in Ho Chi Minh City, characterized by a labyrinthine mesh and tree-shaped network, and narrow street widths. Finally, improvement interventions, such as adding new links and widening alleys, are implemented in three case studies, and the results are compared in terms of cost, social impact, and safety improvement. The results show that the most efficient improvement strategy is to target the weakest point in the network, except for the flow capacity, which, however, can detect intersections at risk on evacuation routes, which cannot be derived from the network topology. The developed evaluation model is not only useful to analyze the current risk level in the network but is also a powerful tool to evaluate future infrastructure improvement projects.