Tạp chí Nghiên cứu Tài chính - Marketing

Factors affecting bank competitiveness during non-economic crises: A study in ASEAN countries

Vo Thi Thu Hang — 2024-11-25

This investigation examines the essential elements that have shaped the competitive landscape of banks in ASEAN nations during non-economic crises, covering the years from 2010 to 2023. The S.GMM method and necessary tests are used to control regression results. We found empirical evidence that positive influencing factors included: the previous year's competitiveness had an impact of 0,27; the size of banks has an impact of 0,11; the size of equity has an impact at f 1,78; the profitability rate has an impact at 1,22; the growth rate of total assets has an impact of 0,014 on the competitiveness of banks. On the contrary, negative factors include factors such as the ratio of loans to total assets have an impact of -0,049; income diversification has an impact of-2,34; technological innovation or non-economic crisis to competitiveness. The authors also address the interaction between income diversification and technological innovation. Results show that these factors have a negative impact on the dependent variable during the research period. Based on the research results, we propose several implications with the expectation that they will provide useful strategies for enhancing competitiveness in the future, as well as add reliable empirical evidence to upcoming research.

Effects of economic growth, foreign direct investment, energy consumption, and urbanization on the ecological footprint in Vietnam

Bui Thi Thu Thao — 2024-11-25

This research examines the impacts of economic growth, foreign direct investment, energy consumption, and urbanization on the ecological footprint in Vietnam from 1992 to 2022. The Wavelet Coherence analysis method is employed to evaluate the correlation levels between variables across various periods and frequencies, providing insights into the mechanisms and extent to which these factors influence the environment amidst urbanization and economic development. The research results indicate a robust in-phase relationship among energy consumption, urbanization, and the ecological footprint. Meanwhile, the interaction between economic growth, foreign direct investment, and the ecological footprint is observed to be more intricate and fluctuates over time. Drawing from these insights, the authors recommend adopting targeted sustainable development policies, promoting clean energy usage, and implementing effective urban management strategies to mitigate the adverse environmental impacts of economic growth in Vietnam.

How government expenditure and trade openness affect foreign direct investment: Evidence from dynamic panel estimations

Pham Nhat Tuan — 2024-11-25

The main objective of this study is to examine the effects of government expenditure and trade openness on foreign direct investments. Our sample includes 992 annual observations from 32 high and middle-income countries from 1990 to 2020. We employ the dynamic system Generalized Method of Moments to overcome heteroskedasticity and endogeneity issues. Our findings suggest that trade openness and government expenditures positively affect FDI inflows. The study recommends that the implementation of reasonable macroeconomic policy, along with the planning of investment strategies and some government interventions, will improve the efficiency of receiving foreign investment flows into the country.

The impact of digital financial inclusion on economic growth in ASEAN countries – Policy implications for Vietnam

To Thi Hong Gam — 2024-11-25

Applying the Bayesian approach, this paper examines how digital financial inclusion affects economic growth in ASEAN nations between 2015 and 2022. The findings demonstrate that digital financial inclusion has a detrimental effect on economic growth. This is a significantly different conclusion from earlier research. This can be explained by the fact that digital financial services are still expensive and require a while to mature or adapt to current development paradigms. On the part of control factors, while unemployment (UNE) negatively affects economic growth, others including population growth (POP), inflation (INF), and foreign direct investment (FDI) have a positive effect. The authors used the research results on the data range of ASEAN countries as prior information to regress the model with the data range of Vietnam. The research model’s findings in Vietnam are quite similar to those of the research model in ASEAN countries in general except for the POP variable, which assumes that economic growth (GDP) will decrease when POP increases. Consequently, to stimulate economic growth, ASEAN nations, particularly Vietnam, must identify strategies to lower the cost of accessing digital finance, decrease the unemployment rate, attract more foreign direct investment, and sustain a moderate inflation rate. To reduce the cost of accessing digital finance, policymakers should encourage financial institutions to provide services at lower costs and in remote areas. Additionally, FinTech providers can be leveraged to provide digital financial services.

Bitcoin price movement prediction by news sentiment using machine learning approach

Phan Huy Tam — 2024-11-25

This study investigates the potential of news sentiment, derived from Google News, in predicting Bitcoin price movements. It explores the correlation between sentiment in news headlines and Bitcoin's market behavior. Employing a data set of news headlines related to Bitcoin from Google News, this research applies sentiment analysis and various machine learning algorithms, including Decision Tree, Random Forest, Logistic Regression, Support Vector Machine, Naïve Bayes, and KNN. The approach involves extracting sentiment scores and correlating these with historical Bitcoin price data. The analysis revealed that Decision Tree and Random Forest algorithms provide a balanced prediction for Bitcoin price movements. Logistic Regression and Support Vector Machine showed high AUC scores but with unbalanced class predictions. Naïve Bayes and KNN were less effective. Overall, sentiment analysis of news headlines can predict short-term Bitcoin price movements to a reasonable degree. This research offers a novel tool for investors and market analysts, enhancing understanding of the impact of news sentiment on cryptocurrency prices. It provides a predictive model to assist in investment decision-making and market analysis. This study contributes to the literature on financial forecasting by integrating sentiment analysis with machine learning for cryptocurrency price prediction. It's one of the few studies to analyze the impact of news sentiment on Bitcoin price, offering a new perspective in the realm of financial technology and digital currencies.

Analyzing the time-frequency impact of digital transformation on the improvement of service trade in Vietnam

Ngo Thai Hung — 2024-11-25

This study investigates the dynamic influence of digitalization (DG), gross domestic product (GDP), population (PO), and broad money supply (M2) on service trade (ST) in Vietnam from 1996 to 2022 using wavelet analysis and spectral Granger causality models. The results indicate that there is a positive nexus between variables during the sample period. While the relationship between broad money supply, population, and service trade is significant across different times and frequencies, the cases of ST-DG and ST-GDP are weak and insignificant at low frequencies. Moreover, Granger causality tests reveal that there exist bidirectional associations between the selected indicators. These findings suggest that Vietnam should focus on investment to enhance digitalization and expand the broad money supply, which would improve the service trade, attract foreign direct investment, and strengthen ties with other economies.

Does “The Purchasing Managers' index” (PMI) affect the operational efficiency of commercial banks in Vietnam?

Do The Dan — 2024-11-25

This study investigates the impact of the Purchasing Managers' Index (PMI) on the operational efficiency of 17 commercial banks in Vietnam from 2013 to 2020. Utilizing the Generalized Method of Moments (GMM), the research analyzes how macroeconomic factors such as GDP growth and inflation, alongside internal bank metrics, influence bank performance. The findings reveal an inverse relationship between PMI and bank operational efficiency. Additionally, GDP growth and inflation positively affect ROE, while non-performing loans negatively impact it. These results provide valuable insights for bank managers to enhance bank performance by monitoring the PMI.

Factors affecting the effectiveness of internal audit at non–business units in Vietnam

Pham Huynh Lan Vi — 2024-11-25

The objective of this study is to determine the influence of factors on the effectiveness of internal audit at public non–business units in Vietnam. Using qualitative and quantitative research methods, the research sample includes 215 businesses, and data processing using SmartPLS software. Content of research on factors such as senior management support, internal audit independence, motivation of internal auditors, level of application of information technology, and Internal audit capacity to the effectiveness of internal audit at public non–business units in Vietnam. Research results show that senior management support, internal audit independence, motivation of internal auditors, level of information technology application, and Internal audit capacity has a positive impact on the effectiveness of internal auditing at public non–business units in Vietnam. Finally, the study concludes and suggests implications for improving the effectiveness of internal at public non–business units in Vietnam and overcoming weaknesses in the process of implementing internal audit by fully equipping auditors with professional knowledge, maintaining the independence of the audit department, and motivating them to work.

Vietnamese young consumers’ green purchase behavior: Does green trust matter?

Doan Bao Son — 2024-11-25

It is crucial to practice environmentally responsible purchasing since impulsive purchases can damage the environment. Green purchase behavior (GP) can help consumers lessen their environmental impact. An integrated structural model of GP was developed by drawing on postulates from the Protection Motivation Theory (PMT). A total of 302 Vietnamese university students were surveyed using the snowball sampling method. It was found through structural equation modeling (SEM) that there is a significant association between perceived severity (PS), perceived vulnerability (PV), and GP. The relationship between PS, PV, and GP is mediated by attitude toward green purchase (ATT). Also, green trust (GTR) plays a significant moderating role in the PV and GP relationship. The findings, including the correlations between the variables, provide credence to the suggested theoretical framework. Since studies on environmental problems and green purchasing behavior are still in their early stages, this work helps fill a gap in our understanding of the phenomenon in the context of Vietnam, a developing Southeast Asian economy. This research may help manufacturers and marketers of green products encourage the use of their products to improve environmentally friendly and sustainable behavior. The findings suggest marketers and manufacturers should emphasize environmental pollution's perceived severity and vulnerability. It is also critical to establish consumers' trust in green marketing.

Evaluating the quality of Kols’ reviews on fashion Via Tiktok

To Anh Tho — 2024-11-25

The Key Opinion Leader (KOL) phenomenon has swiftly gained popularity, especially in the context of product and service reviews. However, a noteworthy concern emerges as certain KOLs exploit consumers' trust and psychological predisposition. In parallel, consumers exhibit skepticism regarding the reliability and impartiality of information disseminated by KOLs. This study discusses the quality of KOL reviews of fashion products on TikTok. Using multiple regression analysis for a sample of 412 participants, the results show that expertise, trustworthiness, congruence of the KOL with the brand, the reputation of the KOL, and the content produced by the KOL positively impact the quality of KOL fashion product reviews. It underscores the affirmative impact of KOL reviews on consumers' purchase decisions. Therefore, KOLs play a vital role in shaping customers' purchasing decisions and should strive to maintain their authenticity and honesty while providing valuable insights to their viewers.

Evaluate learner satisfaction with the quality of training services of the University of Finance - Marketing

Ho Thanh Truc — 2024-11-25

The objective of this research is to investigate how learner satisfaction is affected by aspects of service quality. Quantitative and qualitative research methods are used in this study. Accordingly, with a qualitative method, the study conducted in-depth interviews with 20 experts in the field of higher education to evaluate the completeness and validity of the scale. Using the quantitative method, the study conducted a survey with 1,405 learners at the University of Finance and Marketing (UFM) for the purpose of evaluating the reliability of the scale and, at the same time, being used to test the research model and proposed research hypotheses. The findings of the study indicate that learner satisfaction is influenced by eight independent components. Specifically, the most important component is image, which is followed by reliability, training programs, facilities, assurance, empathy, responsiveness, and lecturers. The research findings lead the authors to suggest that the UFM should concentrate on enhancing the university's reputation so that students feel proud of them; they should also follow through on their initial promises to students; evaluate and enhance their curricula to bring them closer to international standards, make them appropriate for students, and satisfy societal demands; To better serve students, upgrade the facilities.