Factors Affecting Decision to Adopt Artificial Intelligence During COVID-19 Pandemic Period: Evidence from PLS-SEM and fsQCA

The study investigated the factors influencing the demand for Artificial Intelligence (AI) applications in Vietnam from the perspective of Accounting and Auditing. The data was gathered using a quantitative technique based on questionnaires to study a total of 206 accountants and auditors, and was analysed using the PLS-SEM method to determine influential factors and their relationships. In addition, we compare the PLS-SEM results with a recently established approach of panel data fuzzy-set qualitative comparative analysis (fsQCA). The results reveal that the components of finance, tasks, technology, epidemics, knowledge readiness and trust all have a favourable impact on the use of AI in Accounting and Auditing in Vietnam. Besides, the fsQCA results are consistent with the PLS-SEM method, which means that our findings are robust and valid. This study adds empirical evidence to the scientific literature on AI in Accounting and Auditing, which will be immensely beneficial for legislators and businesses looking to improve company efficiency. Besides, applying the fsQCA approach contributes significantly to the existing literature about the research method. © 2023 MDI.

Interlinkages of cryptocurrency and stock markets during the COVID-19 pandemic by applying a QVAR model

Purpose: This paper aims to study the interlinkages between cryptocurrency and the stock market by characterizing their connectedness and the effects of the COVID-19 crisis on their relations. Design/methodology/approach: The author employs a quantile vector autoregression (QVAR) to identify the connectedness of nine indicators from January 1, 2018, to December 31, 2021, in an effort to examine the relationships between cryptocurrency and stock markets. Findings: The results demonstrate that the pandemic shocks appear to have influences on the system-wide dynamic connectedness. Dynamic net total directional connectedness implies that Bitcoin (BTC) is a net short-duration shock transmitter during the sample. BTC is a long-duration net receiver of shocks during the 2018–2020 period and turns into a long-duration net transmitter of shocks in late 2021. Ethereum is a net shock transmitter in both durations. Binance turns into a net short-duration shock transmitter during the COVID-19 outbreak before receiving net shocks in 2021. The stock market in different areas plays various roles in the short run and long run. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the most severe impact at the beginning of 2020. Practical implications: Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets. Originality/value: The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages between these two markets. © 2023, Nguyen Hong Yen and Le Thanh Ha.

An Wavelet analysis of connectedness between volatility of the energy and other markets during the COVID-19 crisis

By applying novel partial wavelet coherency, this paper investigates the transmission mechanism of the volatility from the oil, gold, and silver sector to the energy sector in the time and frequency dimensions as well as the influence of the COVID-19 health crisis on this linkage. The multiple coherencies suggest at least five multiple cycles, which are located at high frequencies (the 52 – 132-day frequency band). Among these cycles, the largest one occurs at the low frequency (the 120 – 132-day frequency band), and this cycle is persistently prolonged. Notably, the four sectors' remarkable interlinkages of the volatility are presented more clearly since the COVID-19 pandemic first appeared and hit the globe (from the end of 2019 to the middle of 2020). The partial coherency between the volatility of the energy sector and the volatility of the oil sector reveals that the relations between two sectors are relatively persistent, which changes in the energy sector's volatility cause the oil sector to become more volatile. The partial coherency between the volatility of the energy sector and the volatility of the gold and silver sector suggests their interlinkages are time-varying and can be divided into four phases. The relationships are either positive or negative, and the energy sector or the silver or gold sector could be an attendant of other market's rising volatility. During the time of the COVID-19 pandemic, the energy sector's volatility is in-phase with the oil and silver sector's volatility leading, whilst the gold sector's volatility leads to the energy sector's volatility, and the relation is negative. © 2023

An Application of a TVP-VAR Extended Joint Connected Approach to Investigate Dynamic Spillover Interrelations of Cryptocurrency and Stock Market in Vietnam

In this paper, we employ a time-varying parameter vector autoregression (TVP-VAR) in combination with an extended joint connectedness approach to study interlinkages between the cryptocurrency and Vietnam's stock market by characterizing their connectedness starting from January 1, 2018, to December 31, 2021. We report that the COVID-19 health shocks impact the system-wide dynamic connectedness, which reaches a peak during the COVID-19 pandemic. Net total directional connectedness suggests that the cryptocurrency market significantly impacts Vietnam's stock market, especially those with the largest market capitalization like Bitcoin and Ethereum. This market can be held accountable for Vietnam's stock market volatility. In encountering the COVID-19 pandemic, the effect of the three cryptocurrencies reduced before 2020, around the end of 2019 and the beginning of 2020. However, from the end of 2020-2021, while cryptocurrencies continued their roles as net transmitters for Vietnam's stock market. © 2023 World Scientific Publishing Company.

Could volatile cryptocurrency stimulate systemic risks in the energy sector? Evidence from novel connectedness models

By identifying the connectedness of seven indicators from January 1, 2019, to June 13, 2022, we choose an extended joint connectedness approach to a vector autoregression model with time-varying parameter (TVP-VAR) to analyze interlinkages between Crypto Volatility (CV) and Energy Volatility (EV). Our findings show that the COVID-19 outbreak seems to have an impact on the dynamic connectedness of the whole system, which peaks at about 60% toward the end of 2019. According to net total directional connectedness over a quantile, throughout the 2020–2022 timeframe, natural gas and crude oil are net shock transmitters, while the CV, clean energy, solar energy, and green bonds consistently receive all other indicators. Specifically, pairwise connectedness indicates that the CV appears to be a net transmitter of shocks to all energy indicators before the COVID-19 outbreak but acts as a net receiver of shocks from clean energy, wind energy, and green bonds in late 2020. The CV mostly has spillover effects on green bonds. The primary net transmitter of shocks to the Crypto market is crude oil. Our findings are critical in helping investors and authorities design the most effective policies to lessen the vulnerabilities of these indicators and reduce the spread of risk or uncertainty. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Interlinkages of cryptocurrency and stock markets during COVID-19 pandemic by applying a TVP-VAR extended joint connected approach

Purpose The purpose of this paper is to study the interlinkages between the cryptocurrency and stock market by characterizing their connectedness starting from January 1, 2018 to December 31, 2021. Design/methodology/approach The author employs a time-varying parameter vector autoregression (TVP-VAR) in combination with an extended joint connectedness approach. Findings The pandemic shocks appear to have influences on the system-wide dynamic connectedness, which reaches a peak during the COVID-19 pandemic. Net total directional connectedness suggests that each cryptocurrency and stock have a heterogeneous role, conditional on their internal characteristics and external shocks. In particular, Bitcoin and Binance Coin are reported as the net receiver of shocks, while the role of Ethereum shifts from receivers to transmitters. As for the stock market, the US stock market stays persistent as net transmitters of shocks, while the Asian stock market (including Hong Kong and Shanghai) are the two consistent net receivers. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the impact most severe at the beginning of 2020. Practical implications Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets. Originality/value The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages among these two markets. The author employs the TVP-VAR combined with an extended joint connectedness approach.

VIETNAM ECONOMY UNDER THE IMPACT OF COVID-19

The COVID-19 pandemic has already produced considerable changes in all aspects of an economy. Being an economy with a high degree of trade openness, Vietnam has maintained extensive trade relations with many partners. In the context of a global pandemic, Vietnam's economy has been severely affected. Therefore, this article focuses on analyzing the impact of the COVID-19 outbreak on the aspects such as gross domestic product (GDP) growth, foreign trade, tourism, unemployment rate, and enterprises' operation, and raising some prospects of Vietnam's economy.

Better Risk Management of Banks and Sustainability - A Case Study in Vietnam

Modern advanced bank risk management is a current and hot issue for all Vietnam banks, during the context of industry 4.0. Because of rapid economic growth under impacts of China-US commerce war and effects from Covid 19, as welll as industry 4.0, enhancing roles of banks in Vietnam economic development is becoming necessary. This paper also refers to new perspectives on corporate governance issues that can be applied into bank management. This study mainly use combination of quantitative methods and qualitative methods including synthesis, inductive and explanatory methods for a special case of big listed bank in Vietnam, Eximbank. The results show us that better management of bank need to forecast effects from GDP growth, Industrial manufacturing (IM) and Risk free rate (Rf) on both beta and stock price of Eximbank (EIB), in this case we found out there is positive relationship. Then, we can suggest suitable plans for risk management to enhance the bank roles and sustainable management strategies.

FACTORS PREDICTING INDIVIDUAL HEALTH BEHAVIORS DURING COVID-19 PANDEMIC

Background: Covid - 19 is a global pandemic, affecting all areas of social life in every country. In the current conditions of the Covid-19 pandemic, individual health behaviors are of primary importance. Each citizen consciously implements their health behaviors not only to prevent them from being infected, but also to help the country's prevention of Covid-19 effective. The study of factors predicting people's health behaviors in the community will help managers come up with appropriate measures to improve public health and to quickly repel the pandemic. Objectives: The research analyzes factors predicting personal health behaviors during the Covid-19 pandemic in Vietnam, including: pandemic awareness, self-assessment of the possibility of becoming infected, fear of disease, quality of life, and mental health (anxiety). Methods: This was a cross-sectional quantitative study. Data were collected from a convenient sample of 572 people in Vietnam (118 males, 451 females;M age =27.0 (sd = 10.0)) by a means of an online questionnaire survey. The questionnaire was constructed based on the YouGov Behavior Change questionnaire;the Fear of Coronavirus-19 Scale (FCV-19), WHOQOL-BREF, the Moral Foundation Questionnaire, and Knowledge of Covid-19. This study performed multivariate regression analysis to explore effects of moral, quality of life, knowledge and fear of Coronavirus-19 on health behaviors of participants. Result: The result showed that fear and sex factors explain 4% (R2-adj = 4%) of health behavior change in the Covid-19 pandemic. In addition, there is a significant relationship between health behaviors and fear, age, gender, and occupation. Conclusion: People's health behaviors are particularly concerned during the Covid-19 pandemic. Community healthcare activities for the people should be tailored to suit different population groups such as gender, age or emotional experiences. More indepth studies are needed to find out the causes of these differences, thereby proposing practical solutions to help people practice more effective health behaviors, contributing to preventing and combating the outbreak.