• Journal of Korea Trade
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• v.27 no.5
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• pp.1-22
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• 2023

Purpose - Southeast Asia has been the focus of Korea's foreign investment. Korea has been helping developing countries in Southeast Asia achieve economic growth and win-win cooperation through capital exports. FDI is an important channel for technology diffusion. However, the impact of FDI on the bias of technological progress in the host country is dependent on the host country's own endowment structure and capital-labor factor substitution elasticity. Therefore, the central issue of this paper is to accurately evaluate the impact of Korea's FDI to the four Southeast Asian countries in various industries on their bias of technological progress. Design/methodology - The paper uses macroeconomic data for Korea and four East Asian countries to estimate capital-labor factor elasticities of substitution using nonlinear, seemingly uncorrelated regressions (NLSUR). Then, the biased technological change index (BTCI) is calculated for each country. Finally, panel data analysis is used to explore the impact of Korean FDI in various industries in the four Southeast Asian countries on their own directed technological progress, and a robustness test is conducted. Findings - There is a substitution relationship between capital and labor factors based on their elasticity in Korea, Singapore and the Philippines. There is a complementary relationship between capital and labor factors in Indonesia and Malaysia. According to the BTCI, there is a trend toward labor-biased technological progress in all countries. Korean investments in manufacturing, wholesale and retail trade in the host country trigger capital-biased technological change in the host country; investments in the finance, insurance and information and communication sectors trigger labor-biased technological change. In addition, this paper also confirms that directed technological progress can enable cross-country transmission. Originality/value - The innovation of this paper lies in three aspects. First, we estimate the BTCI for five countries and explore the trend and situation of directed technological progress in each country from each country's own perspective. Second, we explore the impact of Korean FDI in the host country on the bias to its technological progress at the industry level. Second, we explore the impact of Korean FDI in various industries in the four Southeast Asian countries on the four countries' own directed technological progress from a national perspective. Finally, we propose corresponding countermeasures for technological progress from the perspective of inverse factor endowment. These innovative points not only expand the understanding of technological progress and cross-country technology transfer in East Asia but also provide practical references for policy-makers and business operators.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.767-783
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• 2013

Generalized Method of Moment(GMM) is a popular estimation method to estimate model parameters in empirical financial studies. GMM is frequently applied to estimate diffusion models that are basic techniques of modern financial engineering. However, recent research showed that GMM had poor properties to estimate the parameters that pertain to the diffusion coefficient in diffusion models. This research corrects the weakness of GMM and suggests alternatives to improve the statistical properties of GMM estimators. In this study, a simulation method is adopted to compare estimation methods. Out of compared alternatives, NGMM-Y, a version of improved GMM that adopts the NLL idea of Shoji and Ozaki (1998), showed the best properties. Especially NGMM-Y estimator is superior to other versions of GMM estimators for the estimation of diffusion coefficient parameters.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.765-774
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• 2008

Korean financial markets are rapidly integrating into the world financial markets as they are getting to open more widely. The Korean government enacted new law about financial investments. The environment of domestic financial markets are expected to be more competitive. As a result, the learning demand for financial engineering has been increased. However, the current state of education of financial engineering is in a beginning stage. The financial engineering consists of an appropriate mix of mathematics, statistics, finance and engineering. So interdisciplinary property of financial engineering requires lecturers to be cooperative to operate education of financial engineering. Another element of this education is cooperation of both academia and industry.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.755-767
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• 2014

Recently, many firms have introduced information and communication technology (ICT) into supply chain. However, existing studies have not yet insisted definite conclusion with respect to ICT impact on supply chain. Thus, this study subdivides supply chain performance which previous researchers have studied comprehensively while suggesting perspective of the use of firm's ICT capabilities. We classify ICT capabilities into four types of group and then analyze the difference between groups regarding each factor of supply chain performance by ANOVA analysis and Tukey method. As a result of analysis, the group in which all ICT capabilities are high shows the highest level of integration and flexibility performance among supply chain performances. On the other hand, the group in which all ICT capabilities are low presents the lowest level of integration and flexibility performance. We also provide more precise and specific information with practitioners by analyzing the difference between groups with regard to detailed measurements on integration and flexibility variables.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1861-1885
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• 2020

Test Case Prioritization (TCP) involves the rearrangement of test cases on a prioritized basis for various services. This research work focuses on TCP in web services, as it has been a growing challenge for researchers. Web services continuously evolve and hence require reforming and re-execution of test cases to ensure the accurate working of web services. This study aims to investigate gaps, issues, and existing solutions related to test case prioritization. This study examines research publications within popular selected databases. We perform a meticulous screening of research publications and selected 65 papers through which to answer the proposed research questions. The results show that criteria-based test case prioritization techniques are reported mainly in 41 primary studies. Test case prioritization models, frameworks, and related algorithms are also reported in primary studies. In addition, there are eight issues related to TCP techniques. Among these eight issues, optimization and high effectiveness are most discussed within primary studies. This systematic review has identified that a significant proportion of primary studies are not involved in the use of statistical methods in measuring or comparing the effectiveness of TCP techniques. However, a large number of primary studies use 'Average Percentage of Faults Detected' (APFD) or extended APFD metrics to compute the performance of techniques for web services.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.799-812
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• 2010

The public banking market (the main eld of the second banking sector) faces increased competition du to the expansion of the rst banking sector. In this situation, Customer Satisfaction Management(CSM is emerging as a core business factor to create continuous growth without competitive exclusion because it is possible to churn management and draw an advocate customer. In this pa- per, with Suhyup mutuality bank as a sample for research, I have looked for necessary Customer Satisfaction(CS) factors and deduced a Customer Satisfaction Index(CSI), Customer Loyalty and Net Promoter Score(NPS) of detail factors in CS through a survey. Based on these result, the strategic factors required to improve CS were found and strategic directions for CS were proposed through a CS portfolio analysis.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.1049-1057
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• 2020

The shift from elite education to mass education in Vietnam has met the demand for education for everybody as well as for quality human resource talent for an emerging nation. Under the resource constraint, understanding the quality dimensions of education and its priority level is important for effective and efficient policies. This study was carried out using both qualitative and quantitative methodologies to develop quality criteria and a ranking model. Two rounds of in-depth interviews were conducted with fifteen experts in the field, who were rectors, employers, and recruitment specialists to develop the quality framework applied in Vietnamese universities under total quality management (TQM), starting from the input of the senior secondary school leavers, through a teaching process to the output. The first round of interviews were unstructured questionnaires designed to explore the main factors in quality assessment model. The second round affirmed the experts' agreement on the assessment model. Then, fuzzy logic was applied to rank eight criteria in the quality assessment model into priority order: cost, teaching and administrative staff, leadership, curriculum, student-related factors, internationalization, admissions, and campus. The results are critical for identifying the necessary actions to enhance the education quality and to further research on the optimal quality model.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.183-192
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• 2020

The purpose of this paper is to investigate the determinants of the Operational Self-Sustainability (OSS) of Vietnamese microfinance institutions (MFIs). This research uses both qualitative and quantitative research methods: (i) qualitative research was via in-depth interviews with ten microfinance practitioners, policymakers and researchers; (ii) quantitative research was conducted by using panel data of 34 MFIs in the period 2011-2015 with binary logistics and OLS regressions. Results are as follows: (i) MFIs' OSS in Vietnam are mainly determined by five key factors: portfolio at risk (PAR>30), capital structure, gross loan portfolio, scope of activities and legal form; (ii) OSS are most affected by legal status (social organizations have better OSS than formal MFIs or programs/projects), location (MFIs focus in one province have higher OSS than working nationwide or just in one district), capital structure (MFIs with more equity proportion have higher OSS); (iii) surprisingly, average loan size per borrower and age of MFIs do not have statistically significant correlation with OSS. The key recommendations are: (i) MFIs should focus on its professionality and increase its equity; (ii) related stakeholders such as State Bank of Vietnam should promote the enabling ecosystem for microfinance development to enhance poverty reduction and economic development.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.101-111
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• 2020

Companies struggle to make their best products with high quality and service at a competitive price in global markets. However, customer needs and requirements keep changing with a variety of situations. Companies that face the changes can not stay the same and make an effort to adapt themselves to new circumstances. They would probably review the overall management system that is currently implementing to improve management efficiency. Among other things, quality might be considered to be a crucial element if they are manufacturing industries to be sustained in global markets. KSA (Korean Standards Association) is a government-affiliated organization under the Ministry of Trade, Infrastructure, and Energy. It is a Korean standards provider for quality and service industry. KSA confers national commendations for organizations, quality circles, artisans, QCEC (Quality Competitive Excellent Company), and the most honorable KNQA (Korean National Quality Award) every year. KSA established KNQA on the basis of Malcom Baldrige National Quality Award, Deming Prize, and European Quality Award. Research on quality awards shows that there are many similarities in the framework. Although KSA summarizes two factors for 13 evaluation indicators in the quality competitive excellent model of QCEC, the categorization is ambiguous to explain them according to earlier studies. We performed a deep analysis of foreign quality awards and background for KNQA and QCEC. We conducted a content analysis of KNQA and QCEC and matched evaluation items that were closely related. We proposed a quality competitiveness model with three factors, Technology, System, and Tools, summarizing 13 evaluation indicators in QCEC. Based on audit data for six years from 2012 to 2017 we carried out a confirmatory factor analysis for the proposed model by examining the model validity and fitness.