Search results

The purpose of this paper is to examine the effects of share repurchase announcements on the stock price of rival firms in the same industry in Vietnam during 2010–2017.

Both event study and t-test are employed to test the effects of share repurchase announcements on rival firms. In addition, cross-sectional analysis by ordinary least square regression is also applied for investigating the heterogeneous effects due to information transfer.

The finding shows that stock repurchase announcements result in a positive and significant valuation effect for both announcing firms and rival firms in Vietnam. Furthermore, the degree of signal to the industry is conditional on the degree of signal about the announcing firms as a contagious effect. Intra-industry effects are more favorable when profit performance of rival firms is good and when leverage of rival firms is low.

Rival firms can seize opportunities surrounding share repurchase announcements in the same industry in Vietnam. However, due to firm characteristics, intra-industry effects of stock repurchases differ among industries.

By examining different methods, the paper attributes valuable results to investigate the stock price behavior of rival firms in the same industry when firms announce stock repurchase in Vietnam.

This paper aims to offer an empirical study of the impact of institutional quality on the banking system risk and credit risk.

Applying cross-sectional dependent tests and stationary tests to check the property of our sample, the panel corrected standard errors model is recruited as the main estimator, while feasible generalized least squares, pool ordinary least squares (OLS), robust pool OLS and other estimators are used as a robustness check for an unbalanced panel data for 56 economies divided into three subsamples between 2002 and 2015.

The empirical results show several significant contributions. First, an improvement in institutional quality is an important factor to reduce the banking system risk. This effect of the institutions is less important in well-capitalized, highly profitable and in high-economic growth countries. This effect is also stronger in highly liquid banking systems. Notably, a better institutional quality helps to reduce the banking system risk in the highly concentrated banking system. Second, institutional quality has a significant negative relationship with the banking credit risk, especially in highly concentrated banking systems and in high-growth countries. This influence is weaker in highly liquid and well-capitalized banking systems. Finally, better institutions reduce the positive effect of trade openness, but it induces a higher credit risk for the banking system from the trade openness. Notably, a better institutional quality enhances the negative effect of foreign direct investment (FDI) inflow on both banking system risk and credit risk. These findings are documented for a global sample and three subsamples: low and lower-middle-income economies, upper-middle-income economies and high-income economies.

This study provides some recommendations, for policymakers, on the roles of institutions in the banking system and financial stability.

Shipping is a major source of air pollution, causing severe impacts on the environment and human health, greatly contributing to the creation of greenhouse gases and influencing climate change. The research was investigated to provide a better insight into the emission inventories in the Red River in Hanoi (Vietnam) that is often heavily occupied as the primary route for inner-city waterway traffic.

The total emissions of seven different pollutants (PM₁₀, PM_2.5, SO_x, CO, CO₂, NO_x and HC) were estimated using the SPD-GIZ emission calculation model.

The results show that CO₂ has the most significant contribution to the gas volume emitted: 103.21 tons/day. Remarkably, bulk carriers are the largest emission vehicle, accounting for more than 97% of total emissions, due to their superior number and large capacity.

The result to have a roadmap for making efforts to fulfil its commitment so that it could achieve its net-zero climate target by 2050 in Vietnam as committed at COP26.

In this research, the number of vehicles and types of vessels travelling on the Red River flowing within Hanoi territory and other activity data are reported. The tally data will be used to estimate emissions of seven different pollutants (PM₁₀, PM_2.5, SO_x, CO, CO₂, NO_x and HC) using a method combining both top-down and bottom-up approaches.

This study aims to evaluate the impact of climate change on some specific areas of agricultural production in Quang Nam Province, including assessing the possibility of losing agricultural land owing to sea level rise; assessing the impact on rice productivity; and, assessing the impact on crop water demand.

This study used the method of collecting and processing statistics data; method of analysis, comparison and evaluation; method of geographic information system; method of using mathematical model; and method of professional solution, to assess the impacts of climate change.

Evaluation results in Quang Nam Province show that, by the end of the 21st century, winter–spring rice productivity may decrease by 33%, while summer–autumn rice productivity may decrease by 49%. Under representative concentration pathway (RCP) 4.5 scenario, water demand increases by 31.1% compared to the baseline period, of which the winter–spring crop increases by 28.4%, and the summer–autumn crop increased by 34.3%. Under RCP 8.5 scenario, water demand increases by 54.1% compared to the baseline period, of which the winter–spring crop increases by 46.7%, and the summer–autumn crop increased by 63.1%. The area of agricultural land likely to be inundated by sea level rise at 50 cm is 418.32 ha, and at 80 cm, it is 637.07 ha.

To propose adaptation solution to avoid the impacts of climate change on agriculture, it is necessary to consider about the impact on losing land for agriculture, the impact on rice productivity, assess the impact on crop water demand and other. The result of this assessment is useful for policymakers for forming the agriculture development plan.

This paper analyzes the effects of the monetary stance on the media's favorable (or otherwise) attitude to the State Bank of Vietnam's (SBV) monetary policy using monthly data from 2011 to 2021. Monetary stance is a multivariate index based on the growth rates of money supply and domestic credit. A large set of articles published in five Vietnam daily newspapers are utilized to construct a view of the media's favorableness to the monetary policy.

This paper uses hand-collected data from 211 articles published in five newspapers from December 2011 to September 2021 in order to examine the relationship between the monetary stance and the media's favorableness to monetary policy. Following the studies of He and Pauwels (2008) and Xiong (2012), the authors constructed a multivariate stance index to capture most of the important changes in the SBV's monetary policy stance.

The study's main findings are that a change in monetary stance from easing to neutral/tightening, or from neutral to tightening, is greatly appreciated by the media. The study's findings are robust, especially in terms of alternative measures of the media's favorableness and monetary policy variables.

These findings have important policy implications for implementing SBV's monetary policy.

The main contribution of this paper is that the authors are the first to study the nexus of multivariate monetary stance and the media's favorableness to a central bank's non-inflation-targeting mandate. In particular, the study’s findings confirm that the SBV's multivariate monetary stance affects the media's favorableness, whereas the effect of inflation is statistically insignificant.

This study aims to investigate the relationship between corporate governance (CG) and financial performance in the case of publicly listed companies in Vietnam for the period from 2019 to 2021. The topic is crucial in understanding how effective governance practices can influence the financial outcomes of companies. The study sheds light on the link between CG practice and firm financial performance. It also provides insights for policymakers and practitioners to improve CG practices.

Due to the potential dynamic endogeneity in CG research, this study uses the generalized system methods of moments to effectively address the endogeneity problem. Financial performance is measured by Tobin’s Q, return on equity (ROE) and return on assets (ROA). Based on organization for economic cooperation and development (OECD) standards, these indices were calculated to assess the influence of CG practices on corporate financial performance, namely, for accounting information (ROA and ROE) and market performance (Tobin’s Q and service à resglement différé (SRD) – stock price volatility) for the period 2019–2021. In addition, the study examines the relationship between changes in the CG index and changes in financial performance.

The study’s main objective is to determine the relationship between CG performance scores and financial performance. The study found a positive relationship between transparency disclosure and financial performance and a positive correlation between CG and company size. The COVID-19 pandemic caused a decrease in transparency and information index scores in 2021 compared to 2019 and 2020 due to delayed General Meetings of Shareholders. The study failed to find a relationship between shareholder rights index (“cg_rosh”) and board responsibility (“cg_reob”) and financial performance, concerning which the findings of this study differ from those of previous studies. Reasons are put forward for these anomalies.

Policymakers need to develop a set of criteria for assessing CG practices. They also need to promulgate specific regulations for mandatory and voluntary information disclosure and designate a competent authority to certify the transparency of company information. The study also suggests that companies should develop CG regulations and focus on regulations relating to the business culture or ethics, as well as implementing a system to ensure equal treatment among shareholders. The study found that good CG practices can positively contribute to a company’s financial performance, which is crucial for investors to evaluate the quality of CG practices for each listed company so that investment risks can be limited.

The paper aims to propose a practical model for market segment selection and evaluation. The paper carries out a technique of order preference similarity to the ideal solution (TOPSIS) approach to make an operation systematic dealing with multi-criteria decision- making problem.

Introducing a multi-criteria decision-making problem based on TOPSIS approach. A new entropy and new similarity measure under neutrosopic environment are proposed to evaluate the weights of criteria and the relative closeness coefficient in TOPSIS model.

The outcomes show that the TOPSIS model based on new entropy and similarity measure is effective for evaluation and selection market segment. Profitability, growth of the market, the likelihood of sustainable differential advantages are the most important insights of criteria.

This paper put forward an effective multi-criteria decision-making dealing with uncertain information.

While many factors contribute to peace, economic and governmental factors are considered essential litmus tests for determining peace levels. This study aims to examine the impacts of World Governance Index (WGI) variables on the Global Peace Index (GPI) which ranges from 0 (very high) to 5 (very low).

The GPI serves as a key indicator of peace levels. Valid data from two databases covering 161 countries from 2008 to 2022 were collected and analyzed by using a logarithmic panel data regression model. This approach ensures robust results, particularly when endogenous and exogenous variables have different measurement units.

According to the Feasible Generalized Least Squares (FGLS) estimators, five WGI components exhibit inverse relationships with the GPI (increasing WGI components leads to a decline in GPI, indicating an enhancement in peace quality). The most significant factor influencing peace is “Political Stability and Absence of Violence/Terrorism”, while the effects of “Voice and Accountability” and “Control of Corruption” are also noted.

Extant studies have largely overlooked the interaction between governance and peace, often relying on regional data (with neighboring countries) or case studies on local solutions. This paper, based on data from 161 countries, evaluates governance quality and its dimensions in relation to peace conditions on a global scale, providing more generalizable results for policymakers and scholars.

The authors investigate the impact of standards compliance on the participation in the global value chain and labour value-added of Vietnam’s small and medium-sized enterprises (SMEs).

The authors use a three-period panel dataset of SMEs combined with Vietnam’s Provincial Competitiveness Index. The authors also use multiple econometric models; and with each model, the authors include all independent variables that are available from the study's data and that are suggested by the literature.

The authors find that standards compliance by Vietnam’s SMEs improved their participation in the global value chain via subcontracts with FDI multinational firms. The authors also find that standards compliance improved the value-added of labour in Vietnam’s SMEs, which is robust to the choice of econometric models.

The study's results suggest that better outcomes for firms and society will be possible if standards are recognised and respected.

This paper complements scant literature on the impact of standards compliance on global value chain participation via subcontracting work and labour value-added, especially in developing countries.

Terrestrial laser scanning (TLS) point clouds have been widely used in deformation measurement for structures. However, reliability and accuracy of resulting deformation estimation strongly depends on quality of each step of a workflow, which are not fully addressed. This study aims to give insight error of these steps, and results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. Thus, the main contributions of the paper are investigating point cloud registration error affecting resulting deformation estimation, identifying an appropriate segmentation method used to extract data points of a deformed surface, investigating a methodology to determine an un-deformed or a reference surface for estimating deformation, and proposing a methodology to minimize the impact of outlier, noisy data and/or mixed pixels on deformation estimation.

In practice, the quality of data point clouds and of surface extraction strongly impacts on resulting deformation estimation based on laser scanning point clouds, which can cause an incorrect decision on the state of the structure if uncertainty is available. In an effort to have more comprehensive insight into those impacts, this study addresses four issues: data errors due to data registration from multiple scanning stations (Issue 1), methods used to extract point clouds of structure surfaces (Issue 2), selection of the reference surface S_ref to measure deformation (Issue 3), and available outlier and/or mixed pixels (Issue 4). This investigation demonstrates through estimating deformation of the bridge abutment, building and an oil storage tank.

The study shows that both random sample consensus (RANSAC) and region growing–based methods [a cell-based/voxel-based region growing (CRG/VRG)] can be extracted data points of surfaces, but RANSAC is only applicable for a primary primitive surface (e.g. a plane in this study) subjected to a small deformation (case study 2 and 3) and cannot eliminate mixed pixels. On another hand, CRG and VRG impose a suitable method applied for deformed, free-form surfaces. In addition, in practice, a reference surface of a structure is mostly not available. The use of a fitting plane based on a point cloud of a current surface would cause unrealistic and inaccurate deformation because outlier data points and data points of damaged areas affect an accuracy of the fitting plane. This study would recommend the use of a reference surface determined based on a design concept/specification. A smoothing method with a spatial interval can be effectively minimize, negative impact of outlier, noisy data and/or mixed pixels on deformation estimation.

Due to difficulty in logistics, an independent measurement cannot be established to assess the deformation accuracy based on TLS data point cloud in the case studies of this research. However, common laser scanners using the time-of-flight or phase-shift principle provide point clouds with accuracy in the order of 1–6 mm, while the point clouds of triangulation scanners have sub-millimetre accuracy.

This study aims to give insight error of these steps, and the results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds.

The results of this study would provide guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. A low-cost method can be applied for deformation analysis of the structure.

Although a large amount of the studies used laser scanning to measure structure deformation in the last two decades, the methods mainly applied were to measure change between two states (or epochs) of the structure surface and focused on quantifying deformation-based TLS point clouds. Those studies proved that a laser scanner could be an alternative unit to acquire spatial information for deformation monitoring. However, there are still challenges in establishing an appropriate procedure to collect a high quality of point clouds and develop methods to interpret the point clouds to obtain reliable and accurate deformation, when uncertainty, including data quality and reference information, is available. Therefore, this study demonstrates the impact of data quality in a term of point cloud registration error, selected methods for extracting point clouds of surfaces, identifying reference information, and available outlier, noisy data and/or mixed pixels on deformation estimation.