• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.33-53
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• 2021

In the crossroads of social change caused by the spread of the Fourth Industrial Revolution and the prolonged COVID-19, the Korean government announced the Digital New Deal policy on July 14, 2020. The Digital New Deal policy's primary goal is to create new businesses by accelerating digital transformation in the public sector and industries around data, networks, and artificial intelligence technologies. However, in a rapidly changing social environment, information asymmetry of the future benefits of technology can cause differences in the public's ability to analyze the direction and effectiveness of policies, resulting in uncertainty about the practical effects of policies. On the other hand, the media leads the formation of discourse through communicators' role to disseminate government policies to the public and provides knowledge about specific issues through the news. In other words, as the media coverage of a particular policy increases, the issue concentration increases, which also affects public decision-making. Therefore, the purpose of this study is to verify the dynamic relationship between the media coverage and the stock market on the Korean government's digital New Deal policy using Granger causality, impulse response functions, and variance decomposition analysis. To this end, the daily stock turnover ratio, daily price-earnings ratio, and EWMA volatility of digital technology-based companies related to the digital new deal policy among KOSDAQ listed companies were set as variables. As a result, keyword search volume, daily stock turnover ratio, EWMA volatility have a bi-directional Granger causal relationship with media coverage. And an increase in media coverage has a high impact on keyword search volume on digital new deal policies. Also, the impulse response analysis on media coverage showed a sharp drop in EWMA volatility. The influence gradually increased over time and played a role in mitigating stock market volatility. Based on this study's findings, the amount of media coverage of digital new deals policy has a significant dynamic relationship with the stock market.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.111-136
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• 2012

The global recession has made it more difficult for companies to invest in IT, and they are increasingly aware of the environmental costs of so doing. In these circumstances, cloud computing has emerged as a new paradigm in the business IT sector. Governments, institutes and companies around the world, as well as specifically in Korea since 2009, have turned to this model of providing IT resources. This study is concerned to identify those characteristics of cloud computing that affect its introduction on a company's part; it offers a theoretical framework describing cloud services and seeks to establish causal linkages between antecedent factors and a company's introduction and application of this form of IT provision. The features of cloud computing in particular contexts that the study selected for analysis were its scalability, speed, security, potential compatibility with existing services, efficiency, economic feasibility, dependency and credibility. The study thus related these to whether or not cloud computing was adopted, verifying adjustment effects for cloud services. On the basis of a survey of enterprise IT decision-makers, it emerged through a statistical analysis of correlations that cloud computing's efficiency, economic feasibility and credibility had an effect on its introduction. This study's results should be of use to vendors and potential purchasers of cloud computing services. It is one of the first pieces of research on cloud computing from the customer perspective, based on the perceived characteristics of cloud services as they are seen and valued by users.

• The Journal of Society for e-Business Studies
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• v.8 no.3
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• pp.177-195
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• 2003

In a traditional customer support environment, mainly call centers or service centers are responsible for receiving inquiries from their customers via telephone calls. Due to the rapid growth of Internet with its widespread acceptance and accessibility, means of communication with customers in the traditional customer support center, such as telephones, letters, and direct-visiting, have been replaced by e-mails and bulletin board systems (BBSs) using the Internet constantly. BBSs are basically question and answer systems, they require some lead time to get answer from administrator. To reduce lead time, BBSs enable remote customers or users to log on and tap into a knowledge database that is generally formatted in the form of Frequently Asked Questions (FAQs) that provide answers and solutions to the common problems. And, many different types of the questions are mixed on the BBS. It is a burden to administrator. To build FAQs and to support BBS adminstrator, a supporting tool which is to categorize questions is helpful. In this research, we suggest an interactive question categorizing methodology which consists of steps to present question using keywords, identifying keywords' affinity, computing similarity among questions, and clustering questions. This methodology allows users to interact iteratively for clear manifestation of ambiguous questions. We also developed a prototype system, IQC (interactive question categorizer) and evaluated its performance using the comparison experiments with other systems. IQC is not a general purposed system, but it produces a good result in a given specific domain.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.209-225
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• 2015

Research and development projects in railroad domain are different from those in other domains in terms of their close relationship with laws. Some cases are reported that new technologies from R&D projects could not be industrialized because of relevant laws restricting them. This problem comes from the fact that researchers don't know exactly what laws can affect the result of R&D projects. To deal with this problem, we suggest a model for law retrieval system that can be used by researchers of railroad R&D projects to find related legislation. Input of this system is a research plan describing the main contents of projects. After laws related to the R&D project is provided with their rankings, which are assigned by scores we developed. A ranking of a law means its order of priority to be checked. By using this system, researchers can search the laws that may affect R&D projects throughout all the stages of project cycle. So, using our system model, researchers can get a list of laws to be considered before the project they participate ends. As a result, they can adjust their project direction by checking the law list, avoiding their elaborate projects being useless.

• The Journal of Society for e-Business Studies
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• v.15 no.2
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• pp.137-166
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• 2010

A virtual team is defined a group of people that use electronic communications for some or all of their interactions with other team members. Because team members of a virtual team are physically and temporally distributed, a team's transactive memory system(TMS) is considered to be crucial for the team's effectiveness and performance. TMS refers to a set of individual memory systems which integrate knowledge possessed by particular members through a shared awareness of who knows what. This paper seeks to understand (1) how a virtual team's TMS influences team performance, and (2) what factors contribute to developing the team's TMS. Given these purposes, through the extensive literature review, we first identified components and antecedents to develop a theoretical model that predicts a virtual team's performance. Using the survey data gathered from 172 virtual teams, this study found that expertise location, coordination, and cognition-based trust which were proposed as three components of TMS positively influenced a virtual team's performance. Furthermore, this study uncovered that perceived media richness, network tie strength, and shared norms significantly influenced the components of TMS, while geographical dispersion did not exert any significant influence on TMS.

• The Journal of Society for e-Business Studies
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• v.22 no.3
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• pp.1-28
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• 2017

Today, according to the increased importance of industry-university cooperation in the knowledge-based economy, support and the number of researches involved in industry-university cooperation has also steadily increased. But it is true that profits from the outcome of patents resulting from such cooperation, such as technology transfer and royalty fees, are lower than they are supposed to be, because of excessive patents applications, although some of them have little commercial potential. Therefore, this research aims to suggest a way to analyze and recognize patents, which enable efficient industry-university cooperation and technology transfer. For the analysis, data on 1,061 patents was collected from 4 different universities. With the data, a quality-strategy matrix was arranged targeting the industry-university cooperation foundations', US patents owned by universities, text mining, and social network analysis were carried out, particularly focusing on the patents in the advanced quality technology section of the matrix. Then core key words and IPC codes were obtained and key patents were analyzed by universities. As a result of the analysis, it was found that 4 key patents, 2 key IPC codes were drawn for University H, 4 key patents, 2 key IPC codes for University K, 6 key patents, 1 key IPC code for University Y, 14 key patents, and 2 key IPC codes for University S. This research is expected to have a great significance in contributing to the invigoration of industry-university cooperation based on the analysis result on patents and IPC codes, which enable efficient industry-university cooperation and technology transfer.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.109-130
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• 2020

Recently, the importance of research and development for technological innovation is increasing. The rapid development of research and development has a number of positive effects, but at the same time there are also negative effects that accelerate crimes of information and technology leakage. In this study, a research security level measurement model was developed that can safely protect the R&D environment conducted at the organizational level in order to prepare for the increasingly serious R&D result leakage accident. First, by analyzing and synthesizing security policies related to domestic and overseas R&D, 10 research security level evaluation items (Research Security Promotion System, Research Facility and Equipment Security, Electronic Information Security, Major Research Information Security Management, Research Note Security Management, Patent/Intellectual Property Security Management, Technology Commercialization Security Management, Internal Researcher Security Management, Authorized Third Party Researcher Security Management, External Researcher Security Management) were derived through expert interviews. Next, the research security level evaluation model was designed so that the derived research security level evaluation items can be applied to the organization's research and development environment from a multidimensional perspective. Finally, the validity of the model was verified, and the level of research security was evaluated by applying a pilot target to the organizations that actually conduct R&D. The research security level evaluation model developed in this study is expected to be useful for appropriately measuring the security level of organizations and projects that are actually conducting R&D. It is believed that it will be helpful in establishing a research security system and preparing security management measures. In addition, it is expected that stable and effective results of R&D investments can be achieved by safely carrying out R&D at the project level as well as improving the security of the organization performing R&D.

• International Commerce and Information Review
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• v.18 no.3
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• pp.23-43
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• 2016

Many customers of individual countries are interested in overseas direct purchase. B2C is not limited in a domestic market anymore. There are giant online shopping sites such as Amazon and eBay around the world. Many local and overseas customers can access and purchase products via B2C sites. Market size of overseas direct purchase has been dramatically increased. Overseas direct purchase can be closely associated with trade or international commerce due to the massive increase. This study aims at gaining a better understanding of overseas direct purchase in the country-level not customer-level. Specifically, this study examines relationships between overseas direct purchase and customer determinants including openness, innovativeness, and strategic confirmity to normative institution. Also, moderating effect with external environments such as logistics infrastructure and market uncertainty. Relying on RBV, TCA, Institutional theory, and OSAM model, this study justifies how internal and external determinants can increase or decrease consumer awareness on overseas direct purchase.