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Groundwater plays a critical part in both natural and human existence. When surface water is scarce in arid climates, groundwater becomes an immensely valuable resource. Dak Lak is an area that frequently lacks water resources for everyday living and production, and the scarcity of water resources is exacerbated during the dry season. As a result, it is critical to do study and understand about groundwater to meet the region's water demand. This study aims to extend the use of the MODFLOW model for groundwater simulation and assess the overall groundwater reserves and water demand in the highland province Dak Lak.

The MODFLOW model is used in this work to compute and analyze the flow, prospective reserves of groundwater from which to plan extraction and estimate groundwater variation in the future.

The application of the MODFLOW model to Dak Lak province demonstrates that, despite limited data, particularly drilling hole data for subterranean water research, the model's calculation results have demonstrated its reliability and great potential for use in other similar places. The use of the model in conjunction with other data extraction modules is a useful input for creating underground flow module maps for various time periods. The large impact of recharge and evaporation on groundwater supplies and water balance in the research area is demonstrated by simulations of climate change scenarios RCP4.5 and RCP8.5.

None of the studies has been done previously to analyze water resources of Dak Lak and the scarcity of water resources is exacerbated during the dry season. Therefore, this study will provide useful insights in the water resource management and the conservation of Dak Lak. The groundwater in Dak Lak can meet the area's water demand, according to the results obtained and water balance in the study area. However, the management of water resources and rigorous monitoring of groundwater extraction activities in the area should receive more attention.

This study combines the TAM and UGT frameworks to investigate how Vietnamese students' views of ChatGPT and intrinsic needs affect their intentions to use it for education (via variables including perceived ease of use, perceived usefulness, novelty, information seeking and academic content creation). We will employ TAM theory (Davis, 1989) and UGT theory to elucidate university students' motivations for utilising ChatGPT in Vietnam. Simultaneously, we aim to address the limitation stemming from data uniformity. Our research will make a substantial contribution to the understanding of researchers regarding the use of ChatGPT and its varied consequences as it grows and develops.

This study was conducted at a private university in Vietnam with an estimated population of 15,000 students. One of Vietnam’s top private information technology institutions requires its students to use a variety of information and communication technologies (ICTs) on a regular basis to facilitate and enjoy their academic pursuits (Ngo, 2024; Nguyen). Students who are familiar with ChatGPT and have access to it for educational purposes are the ones that were chosen. This research is a quantitative study that utilises primary data through a survey method. Participants answered a questionnaire online through the Google Form platform sharing via social media platforms from October to December 2023. The questionnaire was divided into two sections: the first contained screening questions and demographic information and the second had five-point Likert-scale questions that measured the study’s components. Two screening questions are used to separate out the intended responders. (i.e. “I have heard the name ChatGPT” and “I know about ChatGPT”) were set to find whether the participants had any knowledge of ChatGPT. If participants were unaware of ChatGPT, their responses were not included in the study. A total of 283 responses were received. The participant’s demographic information is shown in Table 1. It is believed that a sample size of more than 200 provides adequate statistical power for data analysis in structural equation modelling. It is evident that the 283-sample size in this study is adequate to evaluate the research hypothesis and the fitting model. 42.9% of the 283 research samples were made up of men, while 57.1% were women. Business administration accounted for 40.1% of survey respondents, followed by information technology (25.2%) and English language (14.5%). The average ChatGPT usage time of respondents was 56 min in a single use. The study sample’s average age is 20–72 years old.

The present study contributes to the existing AI chatbot literature in the educational industry in several ways. First, this study addresses a gap in the literature by investigating the factors that influence students’ ITU ChatGPT for educational purposes in Vietnam. Using the extended model, we investigated factors influencing students’ intentions to use ChatGPT. It integrates three motive factors of the UGT (ACT, IS and N) with the core factors of TAM (PeoU and PU). The integrated framework’s findings indicate that in a Vietnamese educational setting, ChatGPT is a novel technology that should be considered in conjunction with PU and PEoU.

First, only Vietnamese students make up the research sample. To increase the relevance of the findings, it is advised that future research look at the study model in various geographic regions. Second, the present investigation’s constraints arise from the lack of clarity about the Chat GPT version utilised by the respondents, specifically whether it was the free or premium edition. Furthermore, the limited duration of the survey presents an obstacle to gathering thorough data. Due to their reliance on the particular features and functionalities of the Chat GPT version used, these restrictions may have an effect on the researcher’s objectivity. Furthermore, the limited survey time may curtail the coverage of the collected answers, particularly considering that our survey predominantly focuses on business administration students, thus limiting the diversity and richness of the gathered data. We recommend that future studies should conduct comparative research between different versions of GPT Chat, including free and paid variants that can provide valuable insights into potential differences in performance and results. Such analysis can provide a deeper understanding of the strengths and limitations of different GPT Chat versions. Third, because the study focused on behavioural intention, actual usage and post-usage behaviour may not be covered by the findings. To gain a deeper understanding of users' actual behaviour, we suggest doing research on their usage and post-usage behaviours.

The findings will assist service providers and legislators in determining critical variables and influencing students' incentives to use ChatGPT in educational settings that use constructivist teaching methods. As a result, the information will assist service providers in creating AI chatbots that are more user-friendly, visually appealing, efficient, safe and convenient for education. Governments, in conjunction with service providers, have the potential to significantly accelerate the adoption of AI-based chatbots by highlighting their ethical and sustainable use. The findings demonstrate that students' ITU towards ChatGPT is substantially impacted by PU and PEoU. It is recommended that service providers emphasize the advantages and ease of use of AI chatbots in order to draw new clients. Additionally, in order to promote ChatGPT or related technologies, marketers should concentrate on raising the technology’s perceived novelty value. This is because people are open to new technologies as long as they believe they are interesting and innovative.

ChatGPT is an advanced AI-powered chatbot that has the potential to advance and revolutionize the learning and teaching process. This study attempted to look at the elements that lead students to want to use ChatGPT from an academic standpoint by combining the UGT and TAM. For practitioners, academics and educators, the findings provide a solid knowledge of and encouragement for the sustainable use of such AI tools. Despite having important practical consequences, the study contains a number of limitations that indicate possible research gaps that should be filled by further investigation.

In recent years, climate-smart agriculture (CSA) was introduced to Vietnam to enhance farmers’ resilience and adaptation to climate change. Among the climate-smart agricultural technologies (CSATs) introduced were water-saving techniques and improved stress tolerant varieties. This study aims to examine the determinants of farmers’ adoption of these technologies and the effects of their adoption on net rice income (NRI) in three provinces as follows: Thai Binh (North), Ha Tinh (Central) and Bac Lieu (South).

Determinants of adoption of CSATs and the adoption effects on NRI are analyzed by using a multinomial endogenous switching regression framework.

The results showed that gender, age, number of family workers, climate-related factors, farm characteristics, distance to markets, access to climate information, confidence on the know-how of extension workers, membership in social/agricultural groups and attitude toward risk were the major factors affecting the decision to adopt CSATs. However, the effects of these factors on the adoption of CSATs varied across three provinces. These technologies when adopted tend to increase NRI but the increase is much greater when these are combined.

It is important to consider first the appropriateness of the CSA packages to the specific conditions of the target areas before they are promoted. It is also necessary to enhance the technical capacity of local extension workers and provide farmers more training on CSATs.

This study is the first attempt to identify key determinants of adoption of CSATs either singly or in combination and the adoption effects on NRI in Vietnam.

The purpose of this paper is to estimate the effects of human resource management (HRM) practices on firm outcomes at the firm level in Vietnam.

The paper employs a fixed-effects framework for the estimation using a panel sample of manufacturing firms from small- and medium-sized enterprise surveys between 2009 and 2013.

The paper finds that, on average, a firm that provides the training for new workers gains roughly 13.7, 10 and 14.9 percent higher in output value per worker, value added per worker and gross profit per worker, respectively, than the counterpart. Moreover, an additional ten-day training duration for new employees on average leads to a 4.1 percent increase in output value per worker, a 3.0 percent rise in value added per worker and a 3.0 percent growth in gross profit per worker. The paper also uncovers that a marginal 10 percent of HRM spending results in about 2 and 1.6 percent rises in output value per worker and value added per worker, respectively.

Using the case of Vietnam, this paper shows the important roles of HRM practices in explaining firm outcomes.

Corruption has been evidenced as one of the major factors that drive a firm's dynamics and growth. This study examines the relationship between corruption and financing structure decisions of small and medium-sized enterprises (SMEs) in Vietnam.

The authors use a longitudinal data set from the Vietnam's SME Survey in the period 2007–2013 and adopt the two-stage least squares method to deal with endogeneity.

After controlling for endogeneity and firm heterogeneity, the authors find that, overall, corruption does significantly affect the decisions of financing sources. Given that, corruption increases the use of informal debt and decreases the levels of formal debt, owner's equity and retained earnings.

The findings suggest implications for corruption-combating actions and policies.

Different from previous studies that either provide evidence of government corruption and a firm's capital structure at the country level or focus on corruption and debt only, we deliver a more comprehensive analysis on the nexus between corruption and various financing sources.

The study examines the impact of the preferential credit provided by the Vietnam Bank for Social Policies on poverty reduction in Ninh Binh province, Vietnam. It also identifies and ranks the barriers of accessing the credit.

The study applies fixed-effects method to handle the panel data to examine the impact of the credit on poverty reduction. It also uses face-to-face interviews and group discussions to identify and rank the barriers of accessing to the credit.

The results show that the credit (represented by loan volume) positively and significantly helps improve household income, but does not help to improve household consumption. The major barriers include the time spent to get to the nearest bank branch, banking support services provided to clients and the transparency of household poverty status assessment.

Data are collected in three years and the number of the observations is limited to 300 households.

The VBSP preferential credit may need to be modified to significantly help reduce poverty and the VBSP and involved parties may need to eliminate the barriers so that the poor can have a better access to the credit.

The VBSP preferential credit is one of the reasonable sources that can help eliminate poverty though increasing household income.

The VBSP preferential credit can help increase household income, but does not really help improve household consumption due to the small volume of loans. In addition, banking support services and the household poverty assessment are seen as barriers to the access of the poor.

This research aims to offers a new method for assessing geoeconomic risks in bilateral relations and evaluate the level of such risks from Vietnam’s economic dependency on China.

I apply descriptive analysis to identify asymmetrical dependency in Vietnam–China economic relations and propose a geoeconomic risk assessment framework to evaluate risk levels in bilateral economic linkages.

The proposed geoeconomic risk framework assesses risk levels, which are positively influenced by the degree of asymmetrical relations (vulnerabilities), the net impacts on the receiving economy (impacts) and the sending state’s ability to control economic tools (threats). In contrast, risk levels are negatively affected by the effectiveness of existing mitigation efforts. The framework employs ordinal likelihood scales to rank various risk levels. In the context of Vietnam–China relations, market access for agricultural products and control of the Mekong water emerge as the most risky areas for economic coercion, followed by Chinese official development finance in infrastructure and critical input imports. On the other hand, debt dependency and foreign direct investment in the energy sector are considered more secure areas—less likely targets for economic coercion. Hence, risk mitigation strategies should prioritize reducing asymmetry in vulnerable dependence areas while maintaining current practices in more secure areas.

Methodologically, it introduces a new approach for assessing bilateral geoeconomic risk. Empirically, it provides Vietnam’s policymakers with a comprehensive evaluation of the implications of economic interdependence with China.

This study aims to examine the premature deindustrialization risk in Vietnam.

This study uses a manufacturing–income relationship to conduct an empirical estimation. The latecomer index is adopted in the regression model to identify a downward shift of latecomer's relationship.

The empirical analysis indicates that there is a risk of premature deindustrialization in the Northern Midlands and Mountain Areas. The provinces with low trade openness or foreign direct investment may experience risk of premature deindustrialization.

This study proposes technology diffusion as a policy direction to prevent premature deindustrialization. Furthermore, the Vietnamese government should improve the business environment in the Northern Midlands and Mountain Areas by promoting and attracting export-oriented foreign direct investment.

This study is the first to examine premature deindustrialization in Vietnam based on provincial-level data.

Exclusive breastfeeding (EBF) rates continue to be low in Vietnam. This study aimed to determine the factors predicting 6-month EBF among mothers in Ho Chi Minh City, Vietnam.

A cross-sectional study was conducted with 259 mothers of infants aged between six to nine months at well-baby clinics in Ho Chi Minh City. The questionnaires used for data collection included personal background questionnaire, perceived benefits of breastfeeding scale, breastfeeding self-efficacy scale-short form, perceived barriers to breastfeeding scale and the family support of breastfeeding scale. Descriptive statistics, bivariate and multiple logistic regression were used for data analysis.

About 32% of the Vietnamese mothers practiced 6-month EBF. By increasing one unit of perceived benefits of breastfeeding, perceived self-efficacy in breastfeeding and family support, the mothers' likelihood to give 6-month EBF would increase 19% (AOR = 1.19, 95% CI = 1.08, 1.31), 12% (AOR = 1.12, 95% CI = 1.04, 1.19) and 10% (AOR = 1.10, 95% CI = 1.04, 1.16), while previous breastfeeding experience, maternal age and maternal education could not significantly contribute to the 6-month EBF.

This is the first study in Vietnam using a nursing model, the health promotion model, as a framework to identify factors predicting 6-month EBF. An effective program for promoting EBF could be developed by manipulating and tailoring the predicting factors to fit the Vietnamese mothers' needs through a mother class, lactation clinic or individual approach.