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This study aims to investigate the antecedents and outcomes of excessive use of personal social media at work. The prevalence of personal social media in the work environment can easily lead to excessive use and negative consequences. Understanding the predictive factors and negative consequences of employees' excessive use of personal social media at work is important to develop their appropriate use of social media and improve their job performance.

Based on dual-system theory and the person-environment fit model, this study develops a research model to examine the effect of habit and self-regulation on excessive use of personal social media at work and that of the outcomes of excessive use on employee job performance through strain. This study conducts a questionnaire survey on 408 employees to test the research model and hypotheses empirically.

Results suggest that the imbalance between habit and self-regulation drives excessive personal social media use of employees at work. Furthermore, excessive use of personal social media has a strong impact on employee strain, which can significantly decrease job performance.

First, this study considers excessive use of personal social media at work as a result of two different cognitive systems, that is, an automatic system and a controlled system, thereby extending the dual-system theory to explain excessive use of personal social media in the work context. Second, unlike previous studies that focused on the outcomes or explored the antecedents of excessive social media use at work respectively, the study employs the person-environment fit model and examines the systematic influence of excessive social media use at work from a broad perspective by linking its antecedents and outcomes.

This research takes the transfer behavior of users from Tencent QQ to WeChat as an example to discuss the wider transfer behavior of social media users on the Internet.

This paper collects data through a combination of offline interviews and online questionnaire surveys, and utilizes data analysis tools to construct structural equation modeling (SEM). Using Statistical Product and Service Solutions (SPSS) Statistics 22.0 and Analysis of Moment Structures (AMOS) 22.0 software with SEM, this study was carried out to provide reasonable statistical support for relevant proposed hypotheses based on 368 effective samples acquired through the questionnaire.

The findings of this study show that subjective norm, transfer experience, social communication, and knowledge acquisition all have significant associations with transfer intention and switching behavior. To be specific, transfer intention exerts a positive association on switching behavior; function setting, privacy protection and personal innovation have a favorable association with transfer intention; transfer cost has a significantly negative relationship with transfer intention and switching behavior; function setting has no important relationship on switching behavior.

The research results provide a reference for improving the viscosity and loyalty of social media users in the new era and resolving the problem of user churn.

It is difficult to argue against the fact that research has focussed on artificial intelligence (AI) and robotisation over the past few decades. Additionally, during the past several years, it has taken off and is now extensively used in numerous businesses across various industries. Most of the time, AI has been associated with some industrial sector process automation. Still, recently, the authors have noticed more positive technology uses, especially in the financial services industry. Due to several factors, the financial sector needs to adopt AI and recognise its potential. The industry has historically been concerned about unpredictability, legislation, stronger cybersecurity, technological limitations and disruption of established lucrative operations.

Never before has there been more discussion about AI due to the advantages it provides to businesses that are providing financial services. That may explain why this change is referred to as the fourth industrial revolution. Both positively and negatively, it is quite disruptive. The effectiveness, accuracy and cost-effectiveness of solutions greatly increase. However, immense power also entails great responsibility.

Precautions and security are more crucial than ever for businesses since the financial sector is changing significantly and quickly. The various benefits and drawbacks of this technology are yet unknown to humans. Although AI was first shown to us in the 1950s, it has recently gained new prominence as processing power, and the available quantity of data has increased dramatically.

This analysis examines the relationship between corruption and firm productivity in Vietnam.

The authors apply the system generalized method of moments estimation approach on a panel dataset constructed from comprehensive enterprise surveys covering all the sectors over the 2011–2020 period.

The results confirm a non-linear relationship between corruption and firm productivity. Where corruption is severe, leaving corruption alone tends to benefit firm productivity because efforts to control corruption are likely to cause greater delays. In less corrupt provinces, corruption appears to harm firm productivity while efforts to control corruption provide significant productivity gains. This U-shaped relationship is confirmed for small firms and those in the private sector sub-samples. Intriguingly, this study reveals that the U-shaped relationship does not apply to micro, medium, large firms, state-owned firms and foreign-invested firms because corruption is found to have no significant impact on productivity among these sub-samples. Changes in regulations after 2014 toward promoting a transparent business environment are shown to foster the positive impact of lowering corruption on firm productivity.

This study suggests that lowering corruption is beneficial for firm productivity at the micro level. However, where corruption is severe, monitoring corruption alone is likely to cause adverse effects on productivity due to increased bureaucratic delays. Institutional reforms might play an important role in leveraging the effects of lowering corruption on productivity in highly corrupt areas.

This paper sheds new light on the relationship between corruption and firm productivity in the broad existing literature and especially in the limited number of studies for Vietnam.

The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).

The lockdown of schools to control the spread of Coronavirus Disease 2019 (COVID-19) has adversely affected elementary and secondary school students in China. However, little evidence is available that documents their perceptions toward the use of e-learning under the pandemic context. This study aims to explore (1) the underlying determinants influencing the students' intentions to continue e-learning and (2) the role that the COVID-19 pandemic plays in this decision. This study extends the expectation–confirmation model (ECM) through a mixed-methods study.

This study uses a mixed-methods approach. Phase 1 draws conclusions and extracts significant elements related to e-learning during the pandemic by analyzing students' user reviews from platforms. Based on the findings, the authors identify the relevant variables and develop an extended ECM by integrating attitudes and the perceived threat of COVID-19. In Phase 2, the research model is empirically validated using data collected from 36,920 elementary and secondary school students in China. This study uses a mixed-methods approach. Phase 1 draws conclusions and extracts significant elements related to e-learning during the pandemic by analyzing students' user reviews from platforms. Based on the findings, the authors identify the relevant variables and develop an extended ECM by integrating attitudes and the perceived threat of COVID-19. In Phase 2, the research model is empirically validated using data collected from 36,920 elementary and secondary school students in China.

In Phase 1, the results reveal that students' most concern elements in the COVID-19 pandemic are user perceptions toward e-learning and threat perceptions of COVID-19. In Phase 2, the results reveal that perceived usefulness and attitude are the most significant factors in students' intention to continue. The perceived threat of COVID-19 indirectly influences their intention to continue.

The study extends the ECM with a mixed-methods study to understand students' perceptions toward e-learning during the COVID-19 pandemic. This study can be helpful in related studies in the context of COVID-19-related diseases or other novel scenarios.

This study aims to investigate the influence of corporate social responsibility (CSR) on corporate sustainable performance (CSP) of small- and medium-sized enterprises (SMEs) by looking into the significance of mediating factors, namely, brand image (BI) and brand loyalty (BL), within the context of an emerging economy.

The authors conduct an extensive literature study on the subjects of CSR, BI and BL to assess their influence on the sustainable performance of SMEs in an emerging market. The study adopts a quantitative methodology. A total of 438 answers were obtained from a sample size of 513. The data of the SMEs in Vietnam was analyzed using the smart partial least squares structural equation modeling software, specifically version 3.3.2.

The results of the authors demonstrate notable and favorable correlations between CSR and CSP, CSR and BI and CSR and BL. Importantly, the findings contribute to existing knowledge by looking into the mediating influence of BI and BL in the relationship between CSR and CSP.

According to the authors’ understanding, a number of research have investigated the correlation between CSR and CSP within the realm of SMEs. Nevertheless, there is a scarcity of scholarly research examining the mediating function of BI and BL in this association. The study’s findings have important implications for entrepreneurs and senior management in effectively guiding their enterprises and improving their business strategies with an emphasis on sustainability in emerging markets. The outcome of this study has the potential to significantly contribute to SMEs in Vietnam as well as other emerging countries.

The purpose of this study is to analyze the short-term development pattern and long-term development trend of the digital supply chain.

This study uses the combination of short-term game and long-term evolutionary game theory.

Findings of this study suggest that irrational decisions can make the evolutionary path of the digital supply chain complex and unpredictable.

This study proposes an evolutionary game model for the digital supply chain that can provide good guidance for the digitalization process of enterprises.

This paper aims to examine the relationship between social presence and consumer purchase intention in the context of livestreaming commerce and test the mediating role of immersive experience and the moderating role of positive emotions.

The authors used a convenience sampling method to select 408 college students from a university in Ganzhou as the participants. They employed structural equation modeling to test the hypotheses, as well as Hayes' PROCESS to test the mediation and moderation effects.

The authors found that immersion experiences partially mediate the relationship between social presence and consumers' purchase intentions and positive emotions moderate the “social presence–immersion experience–consumer purchase intentions” path. Therefore, social presence constitutes a moderating mediating effect on consumer purchase intentions.

This study offers meaningful insights into how livestreamers and e-retailers can stimulate consumers' buying behavior in livestreaming environments. E-commerce platforms should strengthen consumer interactions and increase consumers' perceptions of social presence. In addition, companies should meet the social and psychological needs of consumers and generate positive emotional resonance.

This research sheds light on the effect of social presence on consumer purchase intentions in livestreaming commerce and extends the social presence literature by investigating the mediation mechanism of immersive experience.

This study examines the mediation effects of leaders' communication competency in the link between leadership styles (i.e. servant and transactional leadership) and employees' work engagement.

Cross-sectional survey data from 392 employees in 33 hotels in Bangladesh were collected. To analyze the data, structural equation modeling was adopted, and partial least squares (PLS) analysis was used.

Results of PLS analysis revealed that servant leaders and leaders' communication competency positively influence employees' work engagement. In boosting employees' work engagement, communication competency is an important tool for servant leadership but not for transactional leadership.

Hoteliers and managers may want to adopt a servant leadership style and develop effective leadership communication skills to increase employees' engagement at work.

This study introduces communication competency as a mediating mechanism between leadership styles and work engagement in the hospitality industry.