• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.851-860
• /
• 2021

The Knowledge Transfer (KT) for higher education institutions (HEIs) is boundless. Still and all, the members of the staff affiliated with these institutions do recognize an array of hitches in relation to KT practices. The study in question underscores social interactions, training, and Information and Communication Technology (ICT) as the primary barriers and treats them as the independent variables of the study. The study posits that inadequate management of the above-mentioned barriers would impact effective KT unfavorably. Besides, putting forth some striking solutions needed to fix the obstructions that hamper the adequate management of the KT exercises is another aim of the study. For data collection purposes, the study picks out higher education institutions (public) of the Quetta district. The reckoned sample size is 317 subjects. The research type that has been used is cross-sectional research and, in this context, the cross-sectional explanatory sequential design has been used. Concerning the findings of the paper, the results of PLS-SEM show positive and significant relationships of social interaction and training with knowledge transfer, while ICT shows an insignificant positive relationship with the knowledge transfer. The most influencing factor for the knowledge transfer is social interaction as suggested by social interaction theory.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.10
• /
• pp.159-168
• /
• 2022

The time series of foreign trade turnover is complex and variable and contains linear and nonlinear information. This paper proposes preprocessing the dataset by the EMD algorithm and combining the linear prediction advantage of the SARIMA model with the nonlinear prediction advantage of the EMD-LSTM model to construct the SARIMA-EMD-LSTM hybrid model by the weight assignment method. The forecast performance of the single models is compared with that of the hybrid models by using MAPE and RMSE metrics. Furthermore, it is confirmed that the weight assignment approach can benefit from the hybrid models. The results show that the SARIMA model can capture the fluctuation pattern of the time series, but it cannot effectively predict the sudden drop in foreign trade turnover caused by special reasons and has the lowest accuracy in long-term forecasting. The EMD-LSTM model successfully resolves the hysteresis phenomenon and has the highest forecast accuracy of all models, with a MAPE of 7.4304%. Therefore, it can be effectively used to forecast the Sino-Russia foreign trade turnover time series post-epidemic. Hybrid models cannot take advantage of SARIMA linear and LSTM nonlinear forecasting, so weight assignment is not the best method to construct hybrid models.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.10
• /
• pp.1201-1208
• /
• 2019

The government has operated financing fund under the National Finance Act for the smooth conduct of national policy. But, It is exposed to problems such as the possibility of abuse of fund and the lack of after-loan management. In this paper, It uses fintech such as the blockchain and machine learning to solve these problems. The fund operation procedure is designed as a consortium blockchain, and it suggests the application of PBFT negotiation algorithm and the smart contract. In case of the fund management, it suggests utilizing multilayer artificial neural network model of machine learning and a module of result interpretation. The introduction of this research approach will improve the transparency and efficiency of the financing fund, ensure the credibility and also contribute to the improvement of the fund management and the establishment of the fund policy.

• Asia-Pacific Journal of Business
• /
• v.11 no.2
• /
• pp.159-172
• /
• 2020

Purpose - The purpose of this study is to investigate economic variables which have impact on the prices and returns of preferred stocks and to provide investors, underwriters, and policy makers with information regarding correlations and causal relations between them. Design/methodology/approach - This study collected 98 monthly data from Korea Exchange and Bank of Korea. The Granger causal relation analysis, unit-root test and the multiple regression analysis were hired in order to analyze the data. Findings - First, our study derives the economic variables affecting the prices and returns of preferred stocks and their implications, while previous studies focused mainly on the differential characteristics and related economic factors between common and preferred stocks. Empirical results show that the significant variables influencing the prices and returns of preffered stocks are consumer sentiment index, consumer price index, industrial production index, KOSPI volatility index, and exchange rate between Korean won and US dollar. Second, consumer sentiment index, consumer price index, and industrial production index have significant casual relations with the returns of preferred stocks, providing market participants with important information regarding investment in preferred stocks. Research implications or Originality - This study is different from previous studies in that preferred stocks themselves are investigated rather than the gap between common stocks and preferred stocks. In addition, we derive the major macro variables affecting the prices and returns of preferred stocks and find some useful causal relations between the macro variables and returns of preferred stocks. These findings give important implications to market participants, including stock investors, underwriters, and policy makers.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.8
• /
• pp.67-74
• /
• 2021

This study aims to examine and analyze the effect of Risk Profile, Good Corporate Governance (GCG), Earnings, Capital (RGEC), and Earnings per Share (EPS) on stock prices with financial distress as an intervening variable. The sampling technique used purposive sampling based on certain criteria and data used was secondary data, that is, annual reports of commercial banks in Indonesia for the period of 2012-2018 with a sample of 23 banks from a total population of 81 banks. This type of research is explanative with a quantitative descriptive approach to describe or explain quantitative data. The data obtained was analyzed using SEM (Structural Equation Model) with the AMOS Program. The results showed that RGEC, EPS, and financial distress affect stock prices. This is based on testing the direct effect as indicated by a p-value that is smaller than 0.05. Based on the mediation test, the results show that financial distress cannot mediate the effect of RGEC and EPS on stock prices as indicated by a p-value greater than 0.05. The implication of this research is very important for investors to analyze stock price changes based on RGEC, EPS, and financial distress to gain profits. In addition, there are various warning signs indicating that a company is experiencing financial distress or it is heading towards such a state. Being aware of these signs can help prevent failure.

• Journal of the Korea Convergence Society
• /
• v.13 no.3
• /
• pp.217-225
• /
• 2022

We analyzed efficiency and productivity of the Indian non-life insurance market affected by the COVID-19 pandemic from 2020. Using data envelopment analysis(DEA), we examined non-life insurance companies selling health insurance products in India from FY2013 to FY2019. We found the followings. First, average efficiency of the entire non-life insurance industry worsened in the beginning yet improved later. Second, analyzing the efficiency measures by group, we found that private insurance companies had the highest efficiency, followed by state-run insurance companies and pure health insurance companies. Third, average annual productivity growth rate of companies operating distance selling channels including telemarketing is higher than that of traditional face-to-face channels. During and after the COVID-19 pandemic, therefore, Indian non-life insurance companies should focus their resources and efforts on the development of distance selling channels when establishing business strategies. Besides, it would be interesting to extend our analysis to the post-coronavirus period and we leave this for future research.

• Journal of Information Science Theory and Practice
• /
• v.10 no.1
• /
• pp.1-17
• /
• 2022

The article reports the results of an investigation on the practice of providing digital scholarship services at Vietnam National University Ho Chi Minh City, Vietnam. This study is part of an ongoing research project entitled Developing a digital scholarship service framework for universities at Vietnam National University Ho Chi Minh City. It employed a qualitative research approach through in-depth interviews with 31 individuals who are university managers, library managers, lecturers, and postgraduate and undergraduate students from six member universities and Central Library of Vietnam National University Ho Chi Minh City. Research results show that some digital scholarship services have been provided at Vietnam National University Ho Chi Minh City. However, they have not been yet systematically implemented and have not met users' needs. Lack of needed resources such as space, technology infrastructure, human resources, finance, and stakeholder support are among major challenges in developing digital scholarship services. The management of existing digital scholarship services is fragmented without a clear policy for developing digital scholarship and supporting services. The study contributes to the existing knowledge by adding substantially to current understanding of the practice of providing digital scholarship services in Vietnam's universities in the transition period, from state control to autonomy, which has not been much addressed in previous research. Furthermore, this study can be a useful reference for higher education institutions in developing countries regarding implementation of digital scholarship services.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.2
• /
• pp.61-69
• /
• 2022

The study intends to investigate a short-run and a long-run causality among money, income, and prices in the Keynesian and Monetarists framework. This study emphasizes the importance of unrecorded money, which exists alongside legal monetary assets and plays a dual function in determining economic prosperity. The underground economy, which is a hidden component of aggregate economic activity, is determined using Tanzi's monetary approach (Tanzi, 1980). This research uses a time series of annual data from 1990 to 2019 for this purpose. The data is extracted from the World Bank database for the monetary and development indicators. The study keeping in view the trending nature in data follows a unit root testing followed by the Autoregressive Distributive Lag Model (ARDL) to assess the long and short-run dynamics of causality among the variables. In both the pricing and income equations, the study finds a significant level link among the variables; however, there is no evidence of the presence of a level association in the money equation. The short-run causal relationship provides evidence of bi-directional causation between the supply of money and national income. The outcome of this study advise that though the view point of both the Monetarist and Keynesian school holds in both short and long run, however, in Pakistan only the Monetarists' role of money supply and income holds in Pakistan. This evidence would be of precise interest to the policy-makers.

• Asia-Pacific Journal of Business
• /
• v.13 no.3
• /
• pp.183-208
• /
• 2022

Purpose - The main purpose of this study is to widely investigate the impact of recent pandemic crises on the synchronization of the world capital markets through 25 stock indices from major developed countries. Design/methodology/approach - This study collects 25 stock indices from major developed countries and the time period is between January 5, 2001 and February 24, 2022. The data sets used in the study include finance.yahoo.com and Investing.com.. The Granger causality analysis, unit-root test, VAR analysis, and forecasting error variance decomposition were hired in order to analyze the data. Findings - First, there are significant inter-relations among 25 countries around recent major pandemic crises(such as SARS, A(H1N1), MERS, and COVID19), which is consistent result with previous literature. Second, COVID19 shows much stronger impact on the world-wide synchronization than other pandemics. Third, the return volatility of each stock market varies, unit root tests show that daily stock index data are unstable while daily stock index returns are stable, and VAR(Vector Auto Regression) analyses presents significant inter-relations among 25 capital markets. Fourth, from the impulse response function analyses, we find that each market affects the other markets for short term periods, about 2~4 days, and no long term effect was not found. Fifth, Granger causality tests show one-side or two-sides synchronization between capital markets and we estimate, through forecasting error variance decomposition method, that the explanatory portions of each capital market on other markets vary from 10 to 80%. Research implications or Originality - The above results all together show that pandemic crises have strong effects on the synchronization of world capital markets and imply that these synchronizations should be carefully considered both in the investment decisions by individual investors and in the financial and economic policies by governments.

• Asia-Pacific Journal of Business
• /
• v.13 no.3
• /
• pp.261-279
• /
• 2022

Purpose - The purpose of this study was to examine the effect of regulatory focus on proactive behavior and to examine the mediating effect of work hope between superior's regulatory focus and subordinate's proactive behavior. In addition, the purpose of this study was to investigate the moderating effect of interpersonal justice between regulatory focus and work hope, and the moderated mediating effect of work hope and interpersonal justice in the relationship between regulatory focus and proactive behavior. Design/methodology/approach - This study used data 255pairs(510people) collected from Public organizations such as gu office and private organizations that perform various tasks such as human resources, finance, accounting, marketing, and R&D. The Confirmatory Factor Analysis (CFA) and the multiple regression analysis were used in order to analyze the data. Findings - The result showed that promotion focus was positively related to proactive behavior. In addition, this study found that the relationship between promotion focus and proactive behavior was mediated by work hope. Regarding the moderating roles of perceived interpersonal justice, the results showed that perceived interpersonal justice significantly interacted with promotion focus in influencing work hope. Finally, the moderated mediation analysis showed that the indirect effect of promotion focus on proactive behavior through work hope was valid only for subordinates with high perceived interpersonal justice. Research implications or Originality - In order to increase proactive behavior, it is necessary to focus on promotion focus and to increase the positive psychology such as hope. In addition, it is necessary to increase perception of interpersonal justice.