• Journal of Korea Technology Innovation Society
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• v.9 no.4
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• pp.842-864
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• 2006

This paper deals with an empirical study to statistically analyse various financial performances of the selected IPO firms using their investments on research and development(R&D) as an independent variables. The major results of statistical analyses have come up with the followings: 1) The regression analyses for change in average annual total market stock value/total assets over that of R&D expenditures showed the positive relationship, However, those of sales volume and net assets per share showed negative without statistical significances. 2) The statistical analyses in effect of the 3-year average total market stock value/total assets over the 3-year average R&D expenditures resulted in the positive coefficients what are statistically significant at 95% level. 3) Another statistical analysis showed that the financial performances of the IPO finns with deferred assets were better than those of the firms without them. In sum, the degree of investment on R&D by the IPO firms are expected to positively affect their financial performances except the Finns without having proper original technologies.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.451-458
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• 2018

The coast of Incheon reaches Incheon itself, Gimpo, Siheung, and Ansan of Gyunggi-do. Because this area has been seriously polluted, the Ministry of Oceans and Fisheries has established the Incheon Special Area Management Plan (SAMP) to preserve sea water quality as a marine environment asset. However, there is concern that actions taken in this area may change the surrounding marine ecology, being effected by farms, via a river that flows from waste lands, abandoned fishing activities and fishing nets, etc. Given this background, this study estimates the value of SAMP sea water quality using a choice experiment (CE). A CE survey of 1,000 households was undertaken, investigating trade-offs involving price and four attributes for selecting a preferred alternative to obtain a marginal willingness to pay (MWTP) estimate for each attribute. The estimation results showed that MWTP for a 1 %p improvement in sea water quality, the diversity of fauna species, the diversity of flora species, and a 1 %p reduction in marine litter as a result of conserving Incheon coastal sea water quality are estimated to be KRW 75, 135, 309 and 72 per household per year, respectively. All estimation results were statistically significant at the 1 % level. These findings can provide policy makers with useful information for evaluating and planning marine environmental management policies.

• Korea Real Estate Review
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• v.28 no.1
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• pp.105-114
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• 2018

According to Statistics Korea, South Korea has entered the realm of the "aging society" with the rapid development of the country's population. Researchers anticipate that the extremely high (73%) ratio of real estate property to total assets for mid-age to aged households in South Korea that do not have a fixed income may cause serious problems in the future. For example, the real estate market in South Korea may be bombarded with properties listed for sale, causing the average property price to drop due to the abundant supply. Although this prediction may be reasonable, this concept has excluded the idea of pension (which is crucial as it can be considered a consistent and fixed income) due to the limited amount of available data thereon; as such, it is important to include this factor to improve the pertinent research. Thus, this research was conducted using the data from the $3^{rd}$ and $5^{th}$ Korea Retirement and Income Study. For the study results, it was found that variables such as net asset, gender, education, and number of family members have the same impact as that found in the previous studies. To extend from here, two new factors were introduced: the existence of pensions and the amount of pension received by a household. From there, it was found that the existence of a consistent and fixed income such as a pension has led to an increase in housing consumption, the area of interest of the authors.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.45-63
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• 2019

Until recently, most people have invested in a traditional portfolio consisting of stocks, bonds and real estates based on the three-division method of properties in Korea. However, this study analyzed the impact of the composition of a portfolio combining representative real estate indirect investment products such as Reits and real estate funds on the investment performance. For this purpose, the empirical analysis using the mean variance model, which is the most appropriate method for the portfolio composition, was used. For variables used in this study, mixed asset portfolios were classified into Portfolio A through Portfolio G depending on the composition of assets, and the price indices selected as Kospi, Krx bond, Reits Trus Y7, Hanwha-Lasal fund, and Office (Seoul). The results are as follows; first Portfolio D, which combined bonds, stocks, Reits and Real Estate funds, and Portfolio G, which added the office, the actual real estate, were shown to have the lowest risk. second, Portfolio B composed of bonds, stocks and Reits and Portfolio D with added real estate funds had the lowest risk while Portfolio F composed of bonds, stocks, offices and real estate funds, and Portfolio G with added Reits were the most profitable. As a result, it has been analyzed that it was more effective to compose a portfolio including Reits and real estate funds, which were real estate indirect investment products that eliminated the illiquidity limitation of real estates than real estates, the traditional three-division method of properties. Therefore, it is possible to minimize the risk of investors and reduce the cost of ownership of the real estate by solving the illiquidity problem that is the biggest disadvantage of the direct investment, In addition, it is considered that it is more necessary to reinvigorate the real estate indirect investment market where small amounts can be invested.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.83-88
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• 2022

The purpose of this study is to present an analysis and implications for the metaverse-based virtual real estate transaction service. Through blockchain-based technology and metaverse, the world we live in is expanding naturally. Therefore, changes in the environment and perceptions of market participants are also very important factors. The concept and thinking about the existing asset value change and investment are also changing. This means that you can generate profits through value and investment in intangible assets. The service user aspect is a case of investing in the future value of virtual real estate that if more users participate rather than the present value, the principle of supply and demand will be applied to increase the number of consumers and the price will naturally rise according to the principle of scarcity. The service provider provides a technical platform for the service to directly transact the portion of the virtual area considered of interest directly through the virtual real estate purchase business. As the number of participants increases as well as funds and transaction fees, various revenue models such as advertisements can be discovered and provided. It plays the role of providing jobs and information through new services. As a stakeholder, governments can exploit the emergence of new technologies and products to create people and services and secure economic benefits. Of course, various institutional supports should be provided so that new services can settle in the market while mitigating risk factors. This study is meaningful in that it contributes to the establishment of a domestic metaverse-based environment and related research and is utilized in the study of virtual space real estate services.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.8
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• pp.269-280
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• 2022

With the rise of a decentralized finance market (so called, DeFi) using blockchain technology, users and capital liquidity of decentralized finance applications are increasing significantly. The Automated Market Maker (AMM) is a protocol that automatically calculates the asset price based on the liquidity of the decentralized trading platform, and is currently most commonly used in the decentralized exchanges (DEX), since it can proceed the transactions by utilizing the liquidity pool of the trading platform even if the buyers and sellers do not exist at the same time. However, Automated Market Maker have some disadvantages since the cost efficiency of each transaction using Automated Market Maker depends on the liquidity size of some liquidity pools used for the transaction, so the smaller the size of the liquidity pool and the larger the transaction size, the smaller the cost efficiency of the trade. To solve this problem, some platforms are adopting Transaction Path Routing Algorithm that bypasses transaction path to other liquidity pools that have relatively large size to improve cost efficiency, but this algorithm can be further improved because it uses only a single transaction path to proceed each transaction. In addition to just bypassing transaction path, in this paper we proposed a Multi-Path Routing Algorithm that uses multiple transaction paths simultaneously by distributing transaction size, and showed that the cost efficiency of transactions can be further improved in the Automated Market Maker-based trading environment.

• Asia Marketing Journal
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• v.13 no.3
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• pp.249-264
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• 2011

Brand is the major enduring asset of a company and more valuable than the totality of specific products and facilities. Thus brands are powerful assets that must be carefully developed and managed. The company should design and implement marketing activities and marketing communication programs to build and grow the brand value. Strarbucks, Samsung Galaxy, and Nike brands get a price premium and generate strong customer loyalty. A power brand has high brand equity, which is the differential effect that brand knowledge has on consumer response to the marketing of that brand. Brand equity is created when brands have strong, favorable and unique brand associations with customers and high level of brand awareness. Therefore marketers in building a strong brand should ensure to develop the right type of customer experiences with products and effective integrated marketing communication(IMC) programs to create the brand equity. Since 2007 Sinhan card acquiring the LG card has developed the new brand identity and carefully managed the advertising campaign and other marketing communication mix tools to create the high brand awareness and differential brand image. In this case study we examine how Sinhan card with the goal of being No.1 brand in the credit card market has developed and implemented the IMC Strategy to build a high level of consumer brand awareness, unique brand image and strong customer relationship.

• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.239-276
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• 2009

The paper investigates the possible relationship between earnings prediction by security analysts and special ownership ties that link security companies those analysts belong to and firms under analysis. "Security analysts" are known best for their role as information producers in stock markets where imperfect information is prevalent and transaction costs are high. In such a market, changes in the fundamental value of a company are not spontaneously reflected in the stock price, and the security analysts actively produce and distribute the relevant information crucial for the price mechanism to operate efficiently. Therefore, securing the fairness and accuracy of information they provide is very important for efficiencyof resource allocation as well as protection of investors who are excluded from the special relationship. Evidence of systematic distortion of information by the special tie naturally calls for regulatory intervention, if found. However, one cannot presuppose the existence of distorted information based on the common ownership between the appraiser and the appraisee. Reputation effect is especially cherished by security firms and among analysts as indispensable intangible asset in the industry, and the incentive to maintain good reputation by providing accurate earnings prediction may overweigh the incentive to offer favorable rating or stock recommendation for the firms that are affiliated by common ownership. This study shares the theme of existing literature concerning the effect of conflict of interests on the accuracy of analyst's predictions. This study, however, focuses on the potential conflict of interest situation that may originate from the Korea-specific ownership structure of large conglomerates. Utilizing an extensive database of analysts' reports provided by WiseFn(R) in Korea, we perform empirical analysis of potential relationship between earnings prediction and common ownership. We first analyzed the prediction bias index which tells how optimistic or friendly the analyst's prediction is compared to the realized earnings. It is shown that there exists no statistically significant relationship between the prediction bias and common ownership. This is a rather surprising result since it is observed that the frequency of positive prediction bias is higher with such ownership tie. Next, we analyzed the prediction accuracy index which shows how accurate the analyst's prediction is compared to the realized earnings regardless of its sign. It is also concluded that there is no significant association between the accuracy ofearnings prediction and special relationship. We interpret the results implying that market discipline based on reputation effect is working in Korean stock market in the sense that security companies do not seem to be influenced by an incentive to offer distorted information on affiliated firms. While many of the existing studies confirm the relationship between the ability of the analystand the accuracy of the analyst's prediction, these factors cannot be controlled in the above analysis due to the lack of relevant data. As an indirect way to examine the possibility that such relationship might have distorted the result, we perform an additional but identical analysis based on a sub-sample consisting only of reports by best analysts. The result also confirms the earlier conclusion that the common ownership structure does not affect the accuracy and bias of earnings prediction by the analyst.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.3
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• pp.502-516
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• 2014

This study has decomposed the Gini coefficient using Korean Labor & Income Panel Study data and empirically analyzed the impact of demographic characteristics and source-specific income of householder on the household income gap using panel analysis. The scope of areas were divided into 'nationwide,' 'metropolitan areas,' and 'non-metropolitan areas,' and the period before and after the global financial crisis was examined. The analysis findings are as follows. First, when the entire period was examined by income source using Gini decomposition with division of areas into 'nationwide,' 'metropolitan areas,' and 'non-metropolitan areas', the following results were revealed. The absolute and relative contribution level of property income to the gross income was the largest in the category of 'nationwide' and 'metropolitan areas,' while the contribution level of earned income was the largest in the category of 'non-metropolitan areas'. In addition, property income worsened the household income gap the most in the category of 'nationwide' and 'metropolitan areas.' Second, property income worsened the household income gap less after the financial crisis than before the crisis. It is probably because the price of real estate skyrocketed before the global financial crisis, worsening the household income gap, whereas the price drop after the crisis temporarily alleviated the gap. Third, a correlation analysis revealed that households with older householders whose education is high school graduation or below had relatively low gross income, and households with higher source-specific income, especially earned income, had relatively high gross income. Fourth, when the household income determinants were compared through panel analysis with division of areas into 'nationwide,' 'metropolitan areas,' and 'non-metropolitan areas,' the following results were obtained. While the impact of earned income, financial income, and other incomes was greater in non-metropolitan areas than in metropolitan areas, the impact of property income was greater in metropolitan areas than in non-metropolitan areas. To reduce the income gap, the government should impose higher taxes on the high-income class and provide tax benefits to the low-income class, with efforts to create a wide variety of jobs. In addition, since income inequality gets worse as the proportion of incomes generated through asset holdings becomes higher, the government should focus on stabilizing property prices while paying attention to the regional differentiation when carrying out related policies.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.