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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.

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.

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.

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.

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.

本學術論文擬透過找出加密貨幣與股票市場兩者相互關聯之特徵,來探討這個聯繫;文章亦擬探究2019冠狀病毒病全球大流行對這相互關聯的影響。

作者以分量向量自我迴歸法、來找出2018年1月1日至2021年12月31日期間九個指標的關聯,藉此探討加密貨幣與股票市場之間的關係。

研究結果顯示,全球大流行的驚愕,似對全系統動態關聯產生了影響。動態總淨值定向關聯暗示了就我們的樣本而言,比特幣是一個純短期衝擊發送器。比特幣在2018年至 2020年期間是一個衝擊的長期純接收器,並進而於2021年年底成為一個衝擊的長期純發送器。以太坊則為短期以及長期之純衝擊發送器。幣安在2019冠狀病毒病爆發期間,在2021年接收純衝擊前、成為一個純短期衝擊發送器。位於不同地區的股票市場,無論在短期抑或長期而言均扮演各種不同的角色。在2019冠狀病毒病全球大流行的驚愕期間,成對的關聯顯示了加密貨幣可以以2020年年初最嚴重的影響去解釋和說明股票市場的波動。

研究結果使我們能深入認識有關的市場之間不同情緒和看法的蔓延所帶來的影響的主要先例,這些知識、亦能幫助決策者制定適當的政策,以減少有關的市場的弱點,並把這些市場間的風險和不確定性的散播減到最低。

作者是首位研究加密貨幣與股票市場之間的相互關聯的學者,亦是首位學者、去評估像2019冠狀病毒病健康危機的不確定事件,會如何影響有關的兩個市場之間的動態相互關聯。

The development of financial markets as well as a country’s overall financial system plays a crucial role in the evolution of the world’s real economy. In developed countries like the USA, UK, Japan, and European nations, the world’s financial centers are located for exchanging huge capital flows with well-established functioning. However, laying the foundation for a financial center can be a big challenge to developing markets whose financial systems are still in the early stages, since the formation of financial centers is determined by multiple factors. Motivated by that reason, this book chapter provides a comprehensive review of critical determinants in the formation of international financial centers, including (i) economic growth; (ii) governance and business environment; (iii) financial development; (iv) labor force; (v) infrastructure accessibility; and (vi) the country’s reputation and stability. In line with the reviewed literature, the study particularly highlights the recent political and technological developments in the world and their impacts on the future of different financial centers worldwide.

Although there are many efforts within organisations to improve the financial performance of business processes, the results of studies on the impact of internal factors on the financial performance of business processes in an organisation are inconsistent, even contradictory. Therefore, this paper aims to examine the extent and trends of the impact of factors inside companies on the financial performance of business processes and discover lessons learned to improve the financial performance of business processes.

This analysis was done through a quantitative study of listed companies in Vietnam. Pooled OLS regression, REM, FEM and robust regression were performed on 566 companies.

The results provide four main findings. First, firm size and operational efficiency strongly correlate with financial performance. Second, financial leverage has a negative, significant connection with financial performance. Third, net working capital has a positive and meaningful relationship with EPS and a negative association with ROE. Fourth, liquidity does not have any significant association with financial performance.

This study only restricts the internal factors affecting the financial performance of business processes without mentioning the external factors. Furthermore, this study is limited to one emerging country and has not been compared with companies in different countries.

The findings of this study may help inform users inside and outside the organisation to understand the factors that affect the financial performance of business processes. As a result, information users will focus more on aspects that can improve their financial performance to make informed decisions.

This study has many differences compared to previous studies. First, it focuses on the internal factors affecting the financial performance of business processes in non-financial listed companies in Vietnam, which has an emerging economy. First, it focuses on the internal factors affecting the financial performance of business processes in non-financial listed companies in Vietnam, which has an emerging economy. Second, this study analyses data in companies' financial statements for the ten years from 2012 to 2021, when the Vietnamese economy, in particular, and the world economy experienced many fluctuations due to the impact of the post-financial crisis 2007–2008 and the COVID-19 pandemic. Third, this study provides empirical evidence to support RBV, RDT theories and the trade-off theory of capital structure.

Playing exergames may resemble doing conventional exercise and thus has the potential to enhance users’ health. However, no study has yet examined whether and how a need for exercise impacts users’ intention to continuously play exergames, i.e. continuance intention and its antecedents. We developed a model grounded in the uses and gratifications theory (UGT) to address this issue.

We recruited 583 participants to play exergames and collected their psychological responses and physical information. Structural equation modeling (SEM) was used to test the hypotheses.

We found that health consciousness and perceived exercise benefits are positively related to a need for exercise, which is, in turn, positively related to continuance intention. Moreover, perceived exergame similarity with exercise strengthens the positive link between the need for exercise and continuance intention.

This is the first study using the UGT to explain the underlying mechanism linking health consciousness to continuance intention in the playing of exergames. In addition, we introduced the need for exercise as a novel construct in this study. Our findings provide insights to managers on incorporating health-related features into their exergame products to motivate users' engagement in playing exergames.

The purpose of this paper is to expand and analyze deeply customer emotions, concretize the levels of positive or negative emotions with the aim of using machine learning methods, and build a model to identify customer emotions.

The study proposed a customer emotion detection model and data mining method based on the collected dataset, including 80,593 online reviews on agoda.com and booking.com from 2009 to 2022.

By discerning specific emotions expressed in customers' comments, emotion detection, which refers to the process of identifying users' emotional states, assumes a crucial role in evaluating the brand value of a product. The research capitalizes on the vast and diverse data sources available on hotel booking websites, which, despite their richness, remain largely unexplored and unanalyzed. The outcomes of the model, pertaining to the detection and classification of customer emotions based on ratings and reviews into four distinct emotional states, offer a means to address the challenge of determining customer satisfaction regarding their actual service experiences. These findings hold substantial value for businesses operating in this domain, as the findings facilitate the evaluation and formulation of improvement strategies within their business models. The experimental study reveals that the proposed model attains an exact match ratio, precision, and recall rates of up to 81%, 90% and 90%, respectively.

The study has yet to mine real-time data. Prediction results may be influenced because the amount of data collected from the web is insufficient and preprocessing is not completely suppressed. Furthermore, the model in the study was not tested using all algorithms and multi-label classifiers. Future research should build databases to mine data in real-time and collect more data and enhance the current model.

The study's results suggest that the emotion detection models can be applied to the real world to quickly analyze customer feedback. The proposed models enable the identification of customers' emotions, the discovery of customer demand, the enhancement of service, and the general customer experience. The established models can be used by many service sectors to learn more about customer satisfaction with the offered goods and services from customer reviews.

The research paper helps businesses in the hospitality area analyze customer emotions in each specific aspect to ensure customer satisfaction. In addition, managers can come up with appropriate strategies to bring better products and services to society and people. Subsequently, fostering the growth of the hotel tourism sector within the nation, thereby facilitating sustainable economic development on a national scale.

This study developed a customer emotions detection model for detecting and classifying customer ratings and reviews as 4 specific emotions: happy, angry, depressed and hopeful based on online booking hotel websites agoda.com and booking.com that contains 80,593 reviews in Vietnamese. The research results help businesses check and evaluate the quality of their services, thereby offering appropriate improvement strategies to increase customers' satisfaction and demand more effectively.

In recent years, agricultural activities in the Mekong Delta have frequently faced the potential risks of drought, saline intrusion and unusually heavy rainfall because of climate change, leading to a decline in crop yield. Therefore, this study aimed to establish rice planting seasons in An Giang, an upper-located province in the Mekong Delta.

The impacts of seasonal variation on the key rice seasons were simulated using the Food and Agriculture Organization-crop model for the OM6976 rice variety grown in the study area. For the simulation, the model combined crop, soil, weather and crop management data.

The results show that seasonal variation because of changes in weather factors leads to alternation in crop yields across the study area. Specifically, the spring and summer rice planting seasons are advanced by one to two weeks compared with the baseline, and crop yield increased by 5.9% and 4.2%, respectively. Additionally, planting for the autumn–winter rice season on 3 August increased crop yield by up to 8.1%.

In general, rice planting seasons that account for weather factor changes effectively reduce production costs and optimise production.

This research extends the theory of planned behaviour (TPB) and aims to study the underlying factors that influence Chinese consumers' purchase intentions towards green products. The conceptual model encompasses four elements (subjective norms, perceived behaviour control, moral norms and attitude) and one consumer response (purchase intention).

The current research employs a questionnaire survey and two experiments. In Study 1, the hypotheses were tested using structural equation modelling with 485 consumers in China. Study 2 employed a single-factor, two-condition (morally engaged vs control), between-subject design.

The findings reveal that the morally extended TPB framework is more applicable in predicting Chinese consumers' green purchase intentions than the original TPB model. Attitude plays the most significant role in predicting purchase intentions, and moral norms prove to be a mediator of the relationship between the original construct of subjective norms and purchase intentions. The findings further revealed that moral norms comprise the underlying mechanism of the relationship between subjective norms and attitude.

This study therefore expands the TPB theory by including moral norms. Moreover, it contributes to the literature by clarifying the direct, indirect and total effects of each TPB element on the purchase intentions towards green products. Finally, managerial implications are given.

Recently, traditional financial institutions are facing strong competition from disruptive innovators (Fintech firms) forcing them to increasingly invest in new IT solutions to maintain their competitive edge. However, there are still advantages that traditional financial institutions enjoy, of which the primary one may be reputation. Surprisingly, the firm reputation link to use intention has not received much attention in the literature, prompting this research. The purpose of this study is to examine the firm reputation link to use intention in the context of mobile banking.

The results are based on a survey of 783 participants in Vietnam.

The study confirmed that reputation plays an important role in promoting use intention for mobile banking. Additionally, perceived risk and trust are also linked to perceived usefulness (PU) and perceived ease-of-use (PEOU).

This study is among the first to link perceived risk and trust to PU and PEOU in a mobile banking context. Based on the Theory of Reasoned Action, the study adds to the literature by connecting two separated research themes: technology adoption and reputation. It also suggests avenues for both traditional banks and Fintech firms to set their business strategies to enhance their reputation or collaborate for mutual benefits.

Drought and salinity intrusion aggravated by climate change threaten agricultural livelihoods in Viet Nan's Mekong Delta. In response, authorities have built water management infrastructure for irrigation and salinity protection. This study assessed the impact of one such project, the Ba Lai dam in Ben Tre province, on the livelihoods of aquaculture farmers.

This study uses the Sustainable Livelihoods Framework to assess the impact of the Ba Lai dam on the livelihood capitals of 18 farming households in four communes, located both upstream and downstream of the dam.

The authors find that, apart from some positive effects, the dam has also brought negative environmental consequences, such as increased water pollution. The authors also find that farmers have responded to the changes by adapting their livelihood practices.

The samples were relatively small, encompassing four communes in Ben Tre province. On the other hand, this case study is instructive to the many ongoing infrastructure projects in the Vietnamese Mekong Delta.

The project have caused an increase in water-related social conflict.

The case of the Ba Lai dam provides a cautionary example for infrastructure-based water management plans, both in Viet Nam and more broadly. The study suggests the need to strengthen community participation and prioritize impacts of farmers' capital assets when constructing water management infrastructure for climate change adaptation.

There is limited research on consumer intention and credit card adoption in the transitional economies of Southeast Asia. The purpose of this paper is to investigate the key elements that influence an individual’s intention of adopting credit cards in the transitional economy Vietnam.

A questionnaire was developed based on the technology adoption literature. After data cleaning, 595 responses were deemed valid. Factor analysis (EFA and CFA) was utilized on split samples, and a structural equation model developed to identify the influential technology adoption factors.

The analysis found strong support for the hypotheses theoretically developed. In the transitional economy of Vietnam, consumer’s intention to adopt credit cards was influenced by “Perceived usefulness (PU),” “Perceived ease of use (PEOU),” “subjective norm (SN),” “perceived self-efficacy (PSE)” and “Anxiety”. However, “perceived financial cost (PFC)” was not a significant factor.

The use of cross-sectional data does not enable the analysis of time sequence of the determinants of consumer intention.

This research provides a body of knowledge on modern banking payment systems and credit card utilization factors in the transitional economy of Vietnam which has relevance for other transitional as well as developing economies of Southeast Asia, and is a good reference source for foreign investors, banks and card service companies.

To date, there are no studies that explore the interaction between “PU,” “PEOU,” “PFC,” “SN,” “PSE,” “Anxiety” and “Behavioral Intention” in the context of the Vietnamese credit card market, nor other transitional markets in Southeast Asia.