• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3196-3203
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• 2010

The regional strategic industry support has been increasingly developed due to the change of environmental and political conditions for the last 10 years. As the paradigm changed from the central government-sponsored system to regional government-sponsored system, the policy has been diversified into various support systems such as regional strategic industry, specialized industry, supporting technology, supporting business, etc. It is crucial to establish the overall development plans and project strategies for the regional industry in terms of effectiveness and efficiency which will generate an integrated strategic frame to adjust overlapped supporting policies and offer a consumer-oriented service. Not only does the study focus on performance-based outcome regarding to a regional business (supporting policy) portfolio, but it also analyzes and proves an empirical decision-making model to draw out the priority and relative importance according to the regional strategic industry and support cases by analyzing the case of Chungnam area's strategic industry support in 2009. Following a priority list of 20 support cases selected from this research model by the Analytic Hierarchy Process (AHP), the result shows that the diverse support plans are needed according to the different strategic industries or the size of enterprise due to the fact that priority of project type varies upon the characteristics of strategic industry. Thus, the support project needs to generate various strategic industries and develop differentiated support policy to consolidate competitiveness of regional enterprises and revitalize the regional economy.

• Journal of Technology Innovation
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• v.27 no.3
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• pp.27-52
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• 2019

This research studied the determinants of private R&D investment by examining the innovation strategies of 481 small and medium enterprises (SMEs, their employee size is 5 or more and less than 300) in Busan, South Korea. The data is derived from the Technology Survey of Small and Medium Enterprises in 2001 and 2003. Three explanatory variables for the innovation strategies are the R&D portfolio, the organization (personnel) for R&D, and the strategic role of CEO for innovation. The technological levels of industries are controlled in the linear regression model. The dependent variable is the total private R&D investment of a firm in the given fiscal year. The empirical results indicate that the private R&D investment positively correlates with the complexity of the R&D portfolio, the formal organization for R&D team, and the increase of R&D personnel. The formal organization for R&D team and the number of R&D personnel are correlated with the increase of private R&D investment across the four groups in the manufacturing sector but not in the service sector. These findings suggest that the innovation policy needs to target firms who have complex R&D portfolios, the formal organization of R&D teams, and sufficient R&D personnel in order to increase the private R&D investment of SMEs in regions, with consideration of industrial characteristics.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.5
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• pp.353-358
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• 2018

We herein analyze the service traffic characteristics and spectrum of the 5G mobile communication and suggest the effective 5G network deployment method for 5G mobile communication services. The data rates of the 5G mobile communication are from several kbps (voice and IoT) up to 1 Gbps (hologram, among others). The 5G mobile communication services show the diverse cell coverage environments owing to the use of diverse service data rates and multiple spectrum bands. To effectively support the 5G mobile communication services, the network deployment requires the optimization of the service coverages for new service environments and multiple spectrum bands. Considering the 5G spectrum bandwidth debated at present, if the 5G services of 100 Mbps can be supported in the 200 m cell edge using the 3.5 GHz spectrum bands, the 5G services of the 1 Gbps hologram and 500-Mbps 4k UHD can be supported in the cell edges of 50 m and 100 m using the 28 GHz spectrum bands. Therefore, the 5G services can be supported effectively by the 5G network deployment using spectrum portfolio configurations to match the diverse 5G services and multiple bands.

• IE interfaces
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• v.19 no.2
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• pp.140-152
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• 2006

Today, many companies realize that the effort to develop new products / services faster that customers want and continue to purchase is crucial for their survival. As the service sector is rapidly growing, one of the challenges faced by the service industries is the lack of effective methodologies for new service development. This paper proposes a systematic framework for developing new service concepts, with an emphasis on generating innovative, convergence-type service concepts from the customer‘s perspective. The framework consists of three phases-identification of customer needs (Phase I), extraction of new service opportunities (Phase II), and generation of new service concepts (Phase III). The proposed framework is demonstrated through a case study in the telecommunications industry. In the case study, a survey was conducted on ten customers to identify the latent customer needs; 61 new service opportunities were extracted; and 129 new service concepts were generated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.1-14
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• 2023

As markets and industries continue to evolve rapidly, technology opportunity discovery (TOD) has become critical to a firm's survival. From a common consensus that TOD based on a firm's capabilities is a valuable method for small and medium-sized enterprises (SMEs) and reduces the risk of failure in technology development, studies for TOD based on a firm's capabilities have been actively conducted. However, previous studies mainly focused on a firm's technological capabilities and rarely on business capabilities. Since discovered technologies can create market value when utilized in a firm's business, a firm's current business capabilities should be considered in discovering technology opportunities. In this context, this study proposes a TOD method that considers both a firm's business and technological capabilities. To this end, this study uses patent data, which represents the firm's technological capabilities, and trademark data, which represents the firm's business capabilities. The proposed method comprises four steps: 1) Constructing firm technology and business capability matrices using patent classification codes and trademark similarity group codes; 2) Transforming the capability matrices to preference matrices using the fuzzy function; 3) Identifying a target firm's candidate technology opportunities using the collaborative filtering algorithm; 4) Recommending technology opportunities using a portfolio map constructed based on technology similarity and applicability indices. A case study is conducted on a security firm to determine the validity of the proposed method. The proposed method can assist SMEs that face resource constraints in identifying technology opportunities. Further, it can be used by firms that do not possess patents since the proposed method uncovers technology opportunities based on business capabilities.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.125-162
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• 2003

This paper investigates the short- and long- run relationship among Korean, U.S. and Japanese construction indices. We conducted the Johansen's cointegration tests on the hypotheses that the construction indices of three countries we related in the long-run as well as in the short-run. The test results show that there exists no long-run relationship among three countrie's construction indices. In addition, the cointegrating relation did not exist for three countrie's stock market indices and five major Korean construction firms. It fumed out that the U.S. indices Granger-causes Japanese and Korean indices. This finding implies that there may exist international diversification benefit through forming a portfolio from these indices.

• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.103-119
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• 2021

Ports in Korea have been increasing in terms of volume while they have performed functions and roles such as industrial ports in promoting industries of their hinterlands as well as commercial ports supporting imports and exports. Nevertheless, specialization degree is different from port to port by cargo type and the changes in cargo volume. This study aims to analyze the structural changes and the degree of concentration and specialization by cargo type and port between 2001 and 2020. Top 10 ports were analyzed in terms of traffic volume by categorizing liquid, dry, general cargo and containers. HHI(Herfindahl-Hirschman Index), LQ(Location Coefficient), and shift-share analysis were employed in order to identify the degree of concentration, specialization and changes in cargo volume by port and cargo type. As a result of the analysis, the degree of port concentration and specialization for each cargo of 4 categories have maintained a high level, and no significant difference were found in fluctuations over the past 20 years. As a result of calculating the flucation of cargo volume through the shift-share analysis, the growth rate of liquid cargo was high in Yeosu Gwangyang Port, Pyeongtaek Dangjin Port in dry cargo, and Busan Port in general cargo and container ports. The result implies that it is not expected that the structural changes including degree of cargo concentration, specialization and relative fluctuation of cargo volume is significant in Korean ports in the future since the effects of economies of scale and clustering were achieved to the great degree.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.473-484
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• 2017

This study analyzed collaborative R&D projects funded by the Korean government from 2013-2015. For this analysis, input and output variables of projects were considered, and a combination of those variables was itemized. The output-oriented variable return to scale (VRS) model extended from the DEA methodology was adopted to evaluate the cooperation efficiency of the types of R&D collaboration, which were classified according to the project leader's organizations. In addition, hierarchical cluster analysis was conducted using the efficiency results of the scientific, technical, and economical outcome models. The results showed that cooperation efficiency between large companies and public research institutions was relatively high. Conversely, cooperation among medium-sized companies, small businesses and universities was particularly inefficient. The clustering results demonstrated the various strengths and weaknesses of the types depending on publications, patents, technical loyalties and the number of commercialization. In conclusion, this study suggests differentiated investment portfolios and strategies based on the efficiency results of diverse cooperation types among industries, universities and public research institutions.

• Environmental and Resource Economics Review
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• v.18 no.4
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• pp.587-635
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• 2009

The purpose of this study is to develop the Global Dynamic Computable General Equilibrium Model (Global CGE Model) in order to produce an economic impact analysis, including prospective obligations for the Post-2012 regime. This model explores the impact of an international emissions trading market and macroeconomic variables such as GNP, consumption, investment, imports and exports, in accordance with potential increased obligations on the Republic of Korea. Distinguishing it from existing studies, this Global CGE Model divides the global community into major economic groups, and in the capacity of the analyzed global model, reflecting the principle nations' macroeconomic indicators through the theoretical approach of endogenous growth theory. Policies such as an emissions trading scheme and carbon tax are reflected in the model. Also, in particular, the model reflects exogenous technological advances. According to this analysis, the stronger the greenhouse gas reductions, the greater the adverse effects on the economy; among macroeconomic indicators that appear, a significant decline is realized in the balance of trade, along with a significant decrease in investment and consumption. Energy dependence, in particular, plays a large role-varying in degree by industry type-, as greenhouse gas reductions would have a greater impact on energy-intensive industries. Furthermore, if Korea, currently recognized as a developing country, is given the obligation to reduce greenhouse gas emissions, competing countries such as China and other developing countries will be given an advantage.