Search results

“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 study aimed to examine the impact of learning organization (LO) on job satisfaction and individual performance in Vietnamese enterprises. The study further explores the mediating effect of job satisfaction on the relationship between learning organization and employee performance.

Data were collected from 653 employees from various types of organizations in Vietnam. Structural equation modeling was implemented to test the hypotheses.

The results revealed that the proposed research model was supported. Results indicated that LOs positively influenced employees’ job satisfaction and the broader range of their individual performance. In addition, employees’ job satisfaction motivated them to achieve higher performance levels. The study also found a mediating effect of job satisfaction on the relationship between LO and employee performance. The results underscore the importance of implementing an LO culture for individual outcomes such as job satisfaction and employee performance in the Vietnamese cultural context, which is based on socialism and Confucianism.

To the best of the authors’ knowledge, this is the first study to examine the relationships among LO, job satisfaction and individual employee performance in the Vietnamese context. The results offer a deeper understanding of the LO concept in the Vietnamese cultural context and highlight the cultural impact on the LO concept and its effects. The results suggest how the LO concept is applied in the Vietnamese context.

The goal of the study is to offer important insights into the dynamics of the cryptocurrency market by analyzing pricing data for Bitcoin. Using quantitative analytic methods, the study makes use of a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and an Autoregressive Integrated Moving Average (ARIMA). The study looks at how predictable Bitcoin price swings and market volatility will be between 2021 and 2023.

The data used in this study are the daily closing prices of Bitcoin from Jan 17th, 2021 to Dec 17th, 2023, which corresponds to a total of 1065 observations. The estimation process is run using 3 years of data (2021–2023), while the remaining (Jan 1st 2024 to Jan 17th 2024) is used for forecasting. The ARIMA-GARCH method is a robust framework for forecasting time series data with non-seasonal components. The model was selected based on the Akaike Information Criteria corrected (AICc) minimum values and maximum log-likelihood. Model adequacy was checked using plots of residuals and the Ljung–Box test.

Using the Box–Jenkins method, various AR and MA lags were tested to determine the most optimal lags. ARIMA (12,1,12) is the most appropriate model obtained from the various models using AIC. As financial time series, such as Bitcoin returns, can be volatile, an attempt is made to model this volatility using GARCH (1,1).

The study used partially processed secondary data to fit for time series analysis using the ARIMA (12,1,12)-GARCH(1,1) model and hence reliable and conclusive results.

To delve further into the phenomenon of psychological pressure on single mothers, the purpose of this paper is to explore the factors that affect the psychological state of single mothers in Vietnam.

Interpretative phenomenological analysis (IPA) interviews were conducted and analysed with the aim of understanding the psychological state of single mothers sampled from a social group in Vietnam.

Single mothers lack direct support needed to improve their confidence, job opportunities, income levels and social status. The absence of interventions increases the psychological pressure on single mothers in Vietnam.

A future study can explore the psychological state of single mothers using a more expansive data set.

Understanding the psychosocial and socio-economic risk factors of postpartum psychological pressure in single mothers may have important implications on preventative and support measures, as well as laying the groundwork for social protection interventions and informing welfare policy-making at a national level.

Social constructs in Vietnam compound the effect of postnatal depression on Vietnamese single mothers (in contrast to their counterparts in developed Western nations). This means that researchers and policymakers need to reconstruct stigmas that cause psychological pressures on single motherhood, and in doing so, help to change the view held about single motherhood.

This study is the first to explore psychological state of mothers in Vietnam using IPA.

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.

The study estimates the willingness to pay for organic oranges and identifies its influencing factors among consumers in the Mekong Delta, Vietnam.

The study used survey data from 413 households in the Mekong Delta from March 2022 to July 2022. The choice experiment (CE) and contingent valuation method (CVM) were employed to analyze consumers’ willingness to pay (WTP). STATA 17 software was used to analyze research data in the logit model and mixed logit model.

The research results from the CVM approach show that a number of demographic characteristics have a direct impact on WTP, such as education, educational attainment, family size, the presence of children and the elderly in the household, food safety and environmental awareness. The CE model shows product attributes that influence consumers’ WTP, such as country of origin, traceability, quality grade, organic certification, ecolabel and organic content. Both approaches show that price is the main barrier to organic orange consumption.

The study surveyed four large cities in four provinces representing the Mekong Delta region.

Our study helps administrators have a deeper insight into consumer preferences and behavior, specifically the factors that affect consumers' WTP, an important indicator of demand for the success of manufacturers and marketers in developing as well as improving marketing strategies. Knowledge of a product’s WTP on behalf of (potential) customers plays an important role in many areas of marketing management, such as pricing decisions or new product development.

Furthermore, this understanding will inform policymakers about the future of agricultural markets in Vietnam and help them better prepare for the making of sustainable agricultural policies. Develop organic agriculture to both protect human health, protect the living environment and protect the soil from degradation, ensuring sustainable agricultural production. This is also one of the measures to help people stay away from diseases to limit the social burden.

The study confirms that both CVM and CE models can be used to estimate WTP. However, CVM fits the overall WTP estimate, while CE is more appropriate when estimating WTP for individual scenarios through combining attributes with different levels.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.