Search results

Adopting digital transformation is changing the methods through which companies' function, generating novel possibilities and difficulties that force firms to adjust to remain competitive in the digital era. It is critical for firms to embrace this change and utilize technology to develop a more flexible, proactive and effective approach as digital transformation continues to advance at an accelerating pace. Vietnam has been placed at the forefront of these changes in attracting investments and becoming a hub of international trade. As a result, Vietnamese firms have been implementing restructuring and adopting digital transformation to remain competitive with the flow of foreign investment. This paper aims to examine the effects of digital transformation on corporate restructuring in Vietnam. The authors then investigate the moderating role of corporate governance in the digital transformation – corporate restructuring nexus.

The authors employ content analysis to extract information from the annual reports of 747 Vietnamese listed companies, where the authors focus on specific phrases, such as “digitalization”, “big data”, “cloud computing”, “blockchain” and “information technology” over a period of 11 years, from 2011 to 2021. The frequency count of these keywords is calculated to represent the level of digital transformation for the Vietnamese listed firms. A final sample of 118 Vietnamese listed firms with sufficient data is selected for the analysis using the generalized method of moments (GMM) approach.

The results indicate that digital transformation and corporate governance negatively impact corporate restructuring when their effect on corporate restructuring is examined independently. However, corporate governance strengthens the effect of digital transformation on corporate restructuring.

This paper is one of the first to investigate the moderating role of corporate governance on the effect of digital transformation on corporate restructuring in Vietnam. The findings inspire listed firms in Vietnam to implement digital transformation during their corporate restructuring to enhance performance.

The financial system has witnessed the substantial growth of financial technology (fintech) firms. One of the strategies that banks have adopted to cope with this emergence is to cooperate with fintech firms. This study empirically investigated whether cooperation between banks and fintech companies would improve banks’ risk-adjusted returns.

We developed a novel index of bank–fintech cooperation across various fintech sectors. A system generalized method of moments (GMM) was used to examine this relationship using a sample of Vietnamese banks from 2007 to 2019.

The findings show that the diversity of bank–fintech cooperation across seven sectors tends to enhance banks’ risk-adjusted returns. The results also highlight that this relationship may depend on the types of fintech sectors and bank ownership. More specifically, the positive association between this cooperation and banks’ risk-adjusted returns only holds in the comparison sector of fintech, whereas there is a negative relationship between them in the payments and mobile wallets sector. Furthermore, state-owned commercial banks that engage in more bank–fintech cooperation tend to generate greater earnings. If we look at listed banks, the positive effect of bank–fintech partnerships on risk-adjusted returns still holds. A similar result was also found in the case of large banks.

Our empirical evidence provides motivations for incumbent banks to implement appropriate strategies toward diversity in bank–fintech partnerships when fintech firms have engaged in various financial segments.

This study adds more evidence to the existing literature on the relationship between bank–fintech cooperation and bank performance.

Financial integration has played an essential role in achieving economic growth in the members of the Association of Southeast Asian Nations (ASEAN). However, its effects on economic growth in the region in the long run have been underexamined. This paper examines these effects for the ASEAN member countries.

A fully modified ordinary least squares (FMOLS) estimation is used to take into account two critical econometric issues in panel data analysis, including (1) cross-sectional dependence and (2) slope heterogeneity. The dynamic ordinary least squares estimation is also used for robustness analysis. The authors use the generalized least squares estimation to examine the effects in the short run.

This study’s empirical results confirm the important role of financial integration to economic growth in the ASEAN countries in the short term. However, the effects appear to disappear in the long term. The authors also find capital, labor, and human development positively contribute to economic growth in the region. International trade plays a significant role in supporting economic growth in the ASEAN in the short run. However, its effect seems to weaken in the long run.

The growth effects of financial integration in the ASEAN region in the long term have largely been neglected. As such, the authors examine these effects using updated data on financial integration. The authors extend this study’s analysis by considering foreign direct investment and financial depth as the alternative proxies for financial integration. Other estimation technique is also used as the robustness check.

Since financial sector plays a critical economic role in Hong Kong, the current research aims to comprehensively analyze the association between financial development and economic growth in the country to draw correct conclusions about the impact that financial sector's development has on the growth of the economy. This requires both using of more comprehensive data that includes all or nearly all elements of the country's financial sector and utilizing advanced econometrics techniques to provide more reliable evidence based on the findings. In the study, both issues have been addressed more academically to aid the relevant authorities better.

This study empirically examines the financial development-economic growth nexus in Hong Kong employing data covering 1980–2019. The quantile-on-quantile (QQ) approach of Sim and Zhou (2015) is utilized to investigate certain subtle aspects of the association linking financial development and economic growth. In addition, the authors benefit from applying the nonlinear Granger causality test of Diks and Panchenko (2006) to assess the variables' nexus in a nonlinear manner.

In contrast to the evidence of a unidirectional linkage documented in many related studies, the empirical findings suggest that a bi-directional relationship exists between financial development and economic growth for Hong Kong. This is a helpful input for the relevant policymakers and implies that they can set appropriate policies and regulations to balance financial development and economic growth in this country.

The originality of this study can be divided into two parts. Methodologically, unlike past studies that utilized mostly linear and parametric methods, the paper contributes to the literature by applying the more robust nonparametric and nonlinear methodologies. Theoretically, most researchers have used various financial development indicators, which led to very different conclusions. Therefore, this study attempts to resolve this deficiency in the literature by using a more comprehensive index for financial development.

Professional touching behavior (PTB), defined as intentional touching behavior that occurs between organizational members and that falls within the boundaries of appropriateness and professionalism in the workplace, is prevalent in organizations. Scholars from multiple disciplines, including human resources researchers, have acknowledged the importance of physical contact for facilitating interpersonal communication and relationship-building. However, PTB may not only elicit positive reactions from those who receive it but also negative reactions as well, with implications for social dynamics in organizations. PTB can, on the one hand, fulfill employees’ desires for interpersonal connection; at the same time, such physical contact at work can represent a threat to employees’ health. To explain the nature and implications of these divergent effects of receiving PTB, the authors draw upon sociometer theory and behavioral immune system (BIS) theory to model the emotional, cognitive, and physiological processes via which, and the conditions under which, receiving such behavior will result in socially functional responses and prompt subsequent prosocial behavior, and when PTB will be perceived as a health risk and prompt withdrawal behavior. The theoretical framework of this chapter expands our conceptual understanding of the consequences of interpersonal physical contact at work and has important human resources management (HRM) implications for organizational managers.

Coronavirus disease 2019 (COVID-19) has shifted purchase behavior and accelerated the diffusion of modern retail channels via mobile application (or m-application). This work aims to frame a mechanism of m-application-based behavioral intentions in the COVID-19 context.

The authors designed a web-based survey to retrieve empirical data from 478 Vietnamese users. Quantitative approach and structural equation modeling (SEM) were employed to test a research model.

Findings reveal that antecedents of Unified Theory of Acceptance and Use of Technology (UTAUT) (i.e. performance expectancy and facilitating conditions), external influences (i.e. perceived imitation), m-application-related factors (i.e. additive value and alternative attractiveness) and COVID-19-related factors of Protective Motivation Theory (PMT) (i.e. perceived contraction threat, fear and social distancing) are determinants of use intention. Moreover, COVID-19-related dimensions and use intention have direct and indirect positive influences on purchase intention.

Practitioners should stay agile and focus greater attention on a mechanism in which consumer adoption and purchase intention are formulated in the pandemic.

This work narrows the gap by simultaneously identifying the importance of the dimensions from UTAUT and COVID-19-related factors from PMT, especially social distancing, integrated with additive value and alternative attractiveness of m-applications in forming the behavioral intention model in a disease context.

Mobile location-based service (m-LBS) seems like a new class of personalized service due to location positioning technologies. This work aims to investigate consumer readiness (RED) toward m-LBS based on integrating pull effect- and push effect-related factors into the technology acceptance model (TAM).

An online survey collected data from 423 participants, and the research framework was analyzed using structural equation modeling (SEM).

The results divulge that consumer RED is determined by TAM antecedents, including usefulness (USE) and ease of use (EOU). EOU motivates USE in m-LBS. Regarding pull effect-related factors, absorptive capacity (ABC) is the strongest positive factor influencing consumer RED to use m-LBS, followed by technology willingness (TWI) and innovativeness (INN). Moreover, INN, trust (TRU) and perceived risk (RIS) significantly influence USE and EOU.

This work endeavors to explicate customer RED toward m-LBS by incorporating some meaningful pull effect-related dimensions (i.e. ABC, TWI and INN) and pushing effect-related dimensions (i.e. RIS) into crucial antecedents rooted in TAM. Thus, the findings assist practitioners in developing marketing strategies by boosting pull effects and controlling push effects on customer engagement in m-LBS.

This paper aims to investigate the impact of relationship quality among team members in the project team on knowledge transfer effectiveness and analyze the role of organizational structure in the influencing process.

The hypotheses are verified by the Structural Equation Modeling (SEM) analysis using Smart PLS 3 software with the data collected from 236 questionnaire samples in Chinese construction industry.

The results indicate that relationship quality has a direct impact on knowledge transfer in project teams and centralization has a negative impact on relationship quality. Moreover, relationship quality plays a mediating role between centralization and knowledge transfer effectiveness and formalization plays a negative moderating role in the effect of relationship quality on knowledge transfer effectiveness.

This paper studies intra-project knowledge transfer from the perspective of relationship quality of project teams and explores the antecedent and moderating role of organizational structure in the influence of relationship quality on knowledge transfer.

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.

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.