Search results

The study aims to examine the association between virtual communication effectiveness (VCE), leadership effectiveness (LE) and the role of emotional intelligence (EI) in the post-pandemic era.

A survey was conducted among 305 employees in the Indian IT sector using an online questionnaire. Data were analyzed using reliability, validity and moderated regression analysis.

The findings reveal that VCE is a significant predictor of LE. EI plays a significant moderating role between VCE and LE.

This study establishes the role of EI in pre-empting LE. Furthermore, it results in the advancement of improved tools for the selection, training and development of leadership talent. Research on virtual communication (VC) and EI enhances our understanding of effective leadership. To the best of the authors’ knowledge, the present research is one of the first to link and standardize various practices of VC, and EI to increase LE in the post-pandemic era.

This study aims to investigate whether the changes in gender composition of bank board affects Vietnamese bank stability efficiency.

This research covers a panel of 27 commercial banks in Vietnam over a 14-year period from 2007 to 2020. The two-step system generalized method of moments is used to estimate the gender diversity–Vietnamese bank stability efficiency nexus.

The authors find that a greater degree of board gender diversification enhances bank stability efficiency and reduces bank risk-taking in Vietnam. The relationship between gender diversity and the stability efficiency of Vietnamese banks is still valid under the influence of regulatory capital sufficiency and during the financial crisis. These findings are robust to alternative proxies for risk indicators and consistent with the perspectives of stakeholder and behavior theory.

Although this research revisits the relationship between gender diversity and bank risk-taking, it is the first attempt to explore the role of women on board in enhancing the stability efficiency of banks, using the stochastic frontier approach. These findings shed light on the function of gender diversity as a governance instrument for mitigating risk in an emerging market context.

This study explores the effect of local budget retention rate changes (RER) on total factor productivity (TFP) and its components in Vietnam.

The study employs a two-system generalized method of moments (GMM) estimator and data from 2012 to 2019 across all 63 provinces/cities of Vietnam.

The study finds that local budget retention rates significantly influence public investment, affecting scale and allocation efficiency. The reallocation of budgets between regions and from the central government to local levels incurs certain costs, often resulting in economically robust provinces experiencing reductions in their retention rates.

Recognizing the challenges of immediate structural budget changes due to cultural and historical factors, the study suggests a more gradual policy approach. It emphasizes the importance of policy predictability, as abrupt reductions in the retention rate lead to higher costs than gradual reductions, thus implementing budget policies with a clearer timeline. This study provides insight into local budget allocation regimes and their impact on productivity in transitioning countries.

First, the study provides fresh evidence of the impact of retention rate changes on TFP and its components in Vietnam. Second, the study provides insights into the mechanisms of the nexus of increased budget spending, capital efficiency and, most importantly, attaining improvement in education. We also offer further insights into inefficient budget allocation agents in Vietnam, especially in large cities, which should alert scholars to explore this topic further in the future.

The study aims to uncover the relationship between rising temperatures, increased greenhouse gas emissions and the prevalence of lethal violence, encompassing suicides and homicides. It also sought to identify how climate change affects different economic strata in countries, notably in high and middle-income nations, and across Asia and Africa.

This study rigorously explored the link between global climate change and lethal violence across 201 countries from 1970 to 2020. Climate change was measured using annual surface temperature fluctuations and greenhouse gas emissions, while lethal violence was estimated using data on suicides and homicides.

The analysis revealed significant positive associations between escalating temperatures, heightened greenhouse gas emissions and lethal violence. These connections were evident across different economic levels and geographic regions in Asia and Africa.

This study emphasizes the urgent need for comprehensive interventions to combat human-induced climate change and mitigate its extensive negative impacts on society, particularly its association with increased violent behavior.

This study aims to deeply understand customer experiences toward Internet of Things (IoT) applications in retail by developing machine learning models for aspect-based sentiment analysis (SA). It includes creating a related terms dictionary and proposing implications for retail businesses in Vietnam based on these analyses. The ultimate goal is to gain insights into customer opinions and assist administrators in formulating effective digital transformation and business strategies within the Vietnamese market.

Initially, this research uses qualitative methods to identify different aspects of customer experience at stores equipped with IoT applications. Then, quantitative methods were applied through classification machine learning models which were trained on the annotated data set to classify comments into aspects and sentiments. Finally, the classification results were analyzed and visualized to draw implications about customer opinions of these stores.

This study collected 77,042 customers’ comment from potential and actual customers who have ever shopped at retail stores with IoT applications deployed worldwide, identified ten new aspects of customer experience in this field and built a dictionary of related terms. Furthermore, this study contributed two efficient ensemble models with an accuracy of 81% and 89% for analyzing aspects and customer sentiments, respectively. This study also proposes implications for managers regarding the use of IoT technology in retail stores to improve shopping experiences for customers.

This study’s findings help managers develop appropriate digital transformation and business strategies for integrating IoT technology into retail stores, especially for retail businesses in the Vietnamese market based on the analysis results and proposed model.