• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.4
• /
• pp.275-286
• /
• 2020

The study explores factors that affect the performance of responsibility accounting at public universities in Vietnam. The study conducted a survey of 130, out of 154 public universities in Vietnam and uses regression analysis methods. The results identify eight groups of factors affecting the performance of responsibility accounting at these establishments of higher education: Division of the organization into responsibility centers, Estimation and Reality, Cost and income allocation, University autonomy, Management decentralization, Estimation, Reward, and Report. Costs and income allocation for responsibility centers, university autonomy, and the division of universities into responsibility centers are shown to significantly affect the performance of public universities in Vietnam. The results show that the performance of responsibility accounting at public universities in Vietnam is influenced by decentralization of management, division of the organization into responsibility centers, reward, cost and income allocation, estimation, evaluation of the results achieved between the estimation compared with reality, release of reports and university autonomy. Among the factors, cost and income allocation, university autonomy, division of the organization into responsibility centers, reward and evaluation of results achieved between estimation and reality have strong impacts. The study findings also indicate that the school council does not affect responsibility accounting at these universities.

• Asia Marketing Journal
• /
• v.11 no.1
• /
• pp.39-72
• /
• 2009

With the growing importance of accountability, it is getting necessary to test the impact of marketing expenditure on marketing performance. Including recent ROM, we can find a few researches about marketing accountability. But there are a few problems about definitions and metric of marketing expenditure and marketing performance. Therefore, by defining and analyzing the impact of marketing expenditure on marketing performance, we are going to set the classification scheme of marketing expenditure and marketing performance. Based on research findings, new definitions and metrics are proposed as follows. First, we suggest the classification scheme of marketing expenditure. Marketing expenditure is defined as expense accounts in the balance sheet for doing marketing tasks. Marketing expenditures includes many accounts, for example, marketing research, advertising, sales promotion, foreign market development, physical distribution, after services. Among these marketing investment, advertising expenses have a positive effect on marketing performance. Second, we suggest the classification scheme of marketing performance. Already, marketing performance has been defined as financial metrics, customer metrics, market metrics, and corporate social responsibility. But, in this study, we find that the process model is not relevant for explaining association between the performance metrics. The process model is a virtuous cycle: "customer metrics→market metrics→financial metrics→firm valuation metrics." But, in this study, it is not supported or a little significant association between these metrics. Based on these results, we suggest the balance model or flower model as the classification scheme of marketing performance.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.12
• /
• pp.863-867
• /
• 2020

This study was conducted on financial data of 38 economic groups listed on Vietnam's stock market for the period 2009 - 2019 and it aims to provide an empirical evidence on the impact of working capital management policy on performance in all phases of the economic cycle of Vietnamese economic groups. The study uses FGLS estimation method with 2 dependent variables ROA, GOP, independent variables including INV, AR, AP, CCC, dummy variable representing different phases of the economic cycle, variables Control includes CAT, CR, LEV, SZ, GR. Research shows that the greater the level of investment by companies in liquid assets corresponding to a certain level of activity (shown by average days of inventory (INV), average days of collection. (AR), cash flow cycle (CCC)) the lower the rate of return on assets. The study also provides additional evidence of the negative effects of economic crisis on the performance of economic groups. The study also shows that the number of short-term asset cycles has a positive impact on operational efficiency, and the level of debt use has a negative impact on operational efficiency. This result implies that the managers of economic groups can increase the efficiency of businesses through a reasonable working capital policy.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.5
• /
• pp.31-40
• /
• 2020

This study investigates whether other comprehensive income (OCI) reported in the statement of comprehensive income (one of the main financial statements after the adoption of K-IFRS) predicts a firm's future performance. Using the quarterly data of Korean listed companies, we examine the association between OCI estimates and future earnings. First of all, we find that OCI is positively associated with earnings in both 1- and 2-quarter ahead, supporting the predictive value of OCI. When we break down OCI into its individual components, our results suggest that the net unrealized gains/losses on available-for-sale (AFS) investment securities are positively associated with future earnings, while the other components (e.g., net unrealized gains/losses on valuation of cash flow hedge derivatives) present insignificant results. In addition, we investigate whether the reliability in OCI estimates enhances the predictive value of OCI to predict future performance. We find that the predictive ability of OCI, in particular the net unrealized gains/losses on available-for-sale (AFS) investment securities, becomes more pronounced when firms are audited by the Big 4 audit firms. Overall, our study suggests that information content embedded in OCI can provide decision-useful information that is helpful for the prediction of future firm performance.

• Smart Media Journal
• /
• v.11 no.3
• /
• pp.9-17
• /
• 2022

Algorithmic trading, which uses algorithms to trade financial products, has a problem in that the results are not stable due to many factors in the market. To alleviate this problem, ensemble techniques that combine trading algorithms have been proposed. However, there are several problems with this ensemble method. First, the trading algorithm may not be selected so as to satisfy the minimum performance requirement (more than random) of the algorithm included in the ensemble, which is a necessary requirement of the ensemble. Second, there is no guarantee that an ensemble model that performed well in the past will perform well in the future. In order to solve these problems, a method for selecting trading algorithms included in the ensemble model is proposed as follows. Based on past data, we measure the contribution of the trading algorithms included in the ensemble models with high performance. However, for contributions based only on this historical data, since there are not enough past data and the uncertainty of the past data is not reflected, the contribution distribution is approximated using the Dirichlet distribution, and the contribution values are sampled from the contribution distribution to reflect the uncertainty. Based on the contribution distribution of the trading algorithm obtained from the past data, the Transformer is trained to predict the future contribution. Trading algorithms with high predicted future contribution are selected and included in the ensemble model. Through experiments, it was proved that the proposed ensemble method showed superior performance compared to the existing ensemble methods.

• Korea Trade Review
• /
• v.48 no.1
• /
• pp.83-126
• /
• 2023

The revenue histogram of venture businesses is shifting from bell-shaped normal distribution to power-law distribution, which implies that the fitness landscape of the venture businesses ecosystem is changing to be more rugged terrain. We argue that the firm should adopt both exploitation (fast follower) and exploration (or first mover) strategies not to get stuck in local maxima in the rugged fitness landscape from the complex system perspective. By designing and performing agent-based modeling simulation experiments which consist of three types of agents (new technologies, entrepreneurs, and consumers), we demonstrated that the ambidexterity strategy showed the highest performance score in three of four different environment except 'Fast Widening' case where the exploitation strategy showed the highest performance score under low technology appropriation and fast disruptive technology development speed. By investigating the financial and other statistics of 617 top venture businesses who have earned 100B won or higher annual revenue, we concluded that 82% and 9% of firms are bent on the exploitation and exploration strategy.

• The Journal of Industrial Distribution & Business
• /
• v.11 no.4
• /
• pp.31-38
• /
• 2020

Purpose: At a time when the distribution industry is dominated by capital and technology, win-win growth among businesses groups (BGs) in wholesale market is becoming a social issue. Therefore, through analysis of market growth, market concentration (MC) and market power (MP), we want to identify the structure of the wholesale market and the competitiveness of the BGs in terms of market share (MS), sales-profit ratio (SPR), and labor productivity (LP) to explore the possibility of win-win growth. Market situation: Wholesale and Retail sales ratio (W/S) continues to increase, which also means inefficiency in distribution channels or opportunities in wholesale markets. Wholesale sales have grown 8.3 percent annually over the past 15 years, while the number of companies and workers has declined since 2017, which is why some restructuring is believed to begin in the wholesale industry. In terms of MC and MP, the growth potential of SBG can be found in FCB, ARM, FBT and CME BTs. Methodology and data: Through ANOVA and Regression Analysis, the 2015 Economic Census Data of KOSTAT was analyzed. Results: The results of ANOVA show that statistically significant SBG has a larger MS than LBG. The SPR was not different among BGs. LP is higher for LBG than for other BGs. Regression results show that the employment weight (EW) and the company size (SC) have positive effects on the MS, but the company weight (CW) and employment size (SE) have negative effects. In the case of SPR, the CW is positive and the EW is negative. In addition, LP appears to be more positive as SC in the BGs is larger. Conclusions: Although there is sufficient potential for SBG in the wholesale market, there is a problem that needs to increase LP. Therefore, the SBG needs to restructure in terms of number of companies and SC to improve the efficiency of employment. In terms of MC and MP, the SBG looks for possibilities in FCB, ARM, FBT and CME BTs. In addition, SBG that seeks higher returns with human services rather than simple sales is found to be competitive in the HHG, MES and CME BTs.

• KDI Journal of Economic Policy
• /
• v.32 no.3
• /
• pp.71-99
• /
• 2010

The concept of CoVaR introduced by Adrian and Brunnermeier (2009) is a useful tool to measure the risk spillover effect. It can capture the risk contribution of each institution to overall systemic risk. While Adrian and Brunnermeier rely on the quantile regression method in the estimation of CoVaR, we propose a new estimation method using parametric distribution functions such as bivariate normal and $S_U$-normal distribution functions. Based on our estimates of CoVaR for Korean banking industry, we investigate the practical usefulness of CoVaR for a systemic risk measure, and compare the estimation performance of each model. Empirical results show that bank makes a positive contribution to system risk. We also find that quantile regression and normal distribution models tend to considerably underestimate the CoVaR (in absolute value) compared to $S_U$-normal distribution model, and this underestimation becomes serious when the crisis in a financial system is assumed.

• Journal of Korean Association for Spatial Structures
• /
• v.20 no.3
• /
• pp.71-79
• /
• 2020

In this paper, the hybrid prefabricated retrofit method that improve structural performance and reduce construction period was developed by using a finite element analysis. The hybrid prefabricated retrofit method consist of a Z-shaped side plate, a L-shaped lower plate, and a bottom plate containing an steel plate with openings. This shape has advantage that a retrofit method is possible regardless of the size of the beams and a follow-up process such as reinforcement bars placing are not required. The finite element analysis of hybrid Prefabricated retrofit method showed the most ideal stress distribution when the thickness of bottom plate was 10mm, the thickness of the L-shaped lower plate was 5mm, the thickness of the Z-shaped side plate was 2.5mm, and the bolt spacing was 200mm. The bending strength equation of Hybrid prefabricated retrofit method was proposed through the plastic stress distribution method in KDS 41 31 00. The result of Comparison the proposed equation with the finite element analysis, it is determined that the design of hybrid prefabricated retrofit method is possible through the KDS 41 31 00.

• Journal of Distribution Science
• /
• v.12 no.9
• /
• pp.73-82
• /
• 2014

Purpose - This study aims to illustrate the relationship between demographic factors and perceived risk types, supposing that Korean customers tend to postpone buying or hesitate to purchase the new version of hand sets, because of an early buying risk. Research design, data, and methodology - In addition to existing perceived risk types, the authors introduced an early buying risk. In order to measure each variable, also, the study has employed a five-point Liker-scale. To increase research reliability and validity, the research adopted an exploratory factor analysis, a confirmatory factor analysis, and one-way ANOVA. Results - First, there were statistically significant differences between financial risk and the group. Second, there weren't any statistically significant differences between the group means among the four perceived risk types (Performance Risk, Social Risk, Psychological Risk, and Physical Risk) and 4 factors (Gender, Age, Job, and Education). Lastly, job is apparently differentiated from others (Gender, Age, and Education). Conclusions - The authors found that customers regarded an early buying risk as one of the important perceived risk types, when purchasing a hand set.