• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6315-6324
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• 2015

This study analyses the effects of household finances on rental price of apartment in Seoul which play a major role in real estate policy. We estimate VAR models using time series data. Economy variables such as sales price of apartment in Seoul, consumer price index, hiring rate, real GNI and loan amount of housing mortgage, which relate to household finances and influence the rental price of apartment, are used for estimation. The main findings are as follows. In the short term, the rental price of apartment is impacted by economy variables. Specifically, Relative contributions of variation in rental price of apartment through structural shock of economy variables are most influenced by their own. However, in the long term, household variables are more influential to the rental price of apartment. These results are expected to contribute to establish housing price stabilization policies through understanding the relationship between economy variables and rental price of apartment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.189-198
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• 2016

In recent years, the global financial crisis has worsened the economic environment for small and medium-sized businesses. A great number of South Korean enterprises are having various managerial difficulties, such as insufficient funds, shortage of manpower and lack of market information. To overcome these difficulties, many experts have suggested plans to encourage cooperation among small businesses, and such cooperation has provided diverse services to complement the insufficient capabilities of the individual companies. In spite of the efforts made by government to incite cooperation, however, the businesses themselves have displayed a lack of willingness to such cooperation. Cooperation requires a series of complicated and interdependent processes and, thus, governmental support alone cannot guarantee the necessary willingness to cooperate among small businesses. This research empirically analyzed how cooperative and creative leaderships influence the willingness to cooperate among corporate members. We also empirically studied how relationships among corporate members vary in accordance with their absorptive capacity.

• Journal of health informatics and statistics
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• v.43 no.4
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• pp.300-306
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• 2018

Objectives: The purpose of this study is to demonstrate empirically through a specialist AHP analysis what factors should be more important in the development of the public health care system. In addition, we will use Analytic Hierarchy Process (AHP) method for experts to achieve research purpose. Methods: The data analysis method of this study is as follows. First, we set up three metrics in order to measure the relative importance between the factors to be improved for the development of the public health care system and each of the sub-factors. A total of nine measurements (items) were set by combining the three measurement criteria for each measurement index. Second, the relative importance and priority analysis use the AHP analysis. Third, the subjects of this study were 15 experts in the field of public health care. The statistical processing was performed using the Expert Choice 2000 statistical program. Results: In order to development of the public health care system, experts ranked the most important as improvement in the systematic aspect of public health care (56%) as the first priority. Next, the relative importance analysis of the measurement items considering the multiple-weights of the sub-factors is as follows. The strengthen institutional improvement (revitalization of secondary public function hospital) was the number one, strengthen cooperation between agencies was the second, and Re-establishing the role of local public health care system was the third place. Conclusions: Considering the relative importance, factors that are considered to be important in the first place may not be improved as the best policy alternative due to limitations in spatial, temporal, financial, and institutional aspects. In this case, we suggest that we should choose the best policy alternative by using prioritization considering relative weights.

• Journal of Climate Change Research
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• v.4 no.3
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• pp.245-254
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• 2013

Korea government promote renewable energy as the core of their energy matrix to break the dependence and reduce greenhouse effects. This study analyzes the economic assessment of Solid Refuse Fuel project in urban area, considering the marginal external costs of air pollution in this area. Assessment index defined as costs (i.e., construction cost, operation cost) and benefit (margin, external cost) data which is located in Sudokwon landfill site. The result indicates that cost-benefit analysis of SRF is calculated as 1.0. In addition, SRF project is very sensitive about electric power selling price, operating cost and labor cost according to inflation rates. This study shows that the sustainability of SRF project is required the government financial support like investment funds as well as policy support. Variability analysis of SRF economic assessment due to renewable energy can be used for making policies in various fields such as waste and public energy field.

• The Journal of Economics, Marketing and Management
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• v.7 no.1
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• pp.1-14
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• 2019

Purpose - Currently, the economic globalization has become a common channel for China's enterprise to perform the international economic activities. Due to this background, this paper tries to analyze the influence of internationalization level on operation performance of enterprises. Research design, data, and Methodology - This paper aims at 296 companies going listed in Shanghai Stock Exchange and Shenzhen Stock Exchange. The data about the listed companies during the 12 years from 2005 to 2016 have been collected. Relevant theories, including the theory of comparative advantage, monopolistic advantage and product life cycle in developed countries as well as the small scale technology and state on localized technological capacities in developing countries, have been summarized to provide theoretical basis for the influence of international operation on operation performance of the enterprises. Moreover, the current status of international operation of China's enterprises, including the dynamic cause of the internationalization of China's enterprises, its competitive advantage and disadvantage as well as the interest and potential risk of the internationalization, have been also analyzed. Results - Via adopting the panel data to conduct an empirical analysis, It can be found that the relationship between international operation level and operation performance of China's enterprises can be expressed as the S-curve of declining, rising and declining again. Conclusions - This paper has taken the lead in using Ohlson corporate value model to fill the gap in the relevant researches in China. It can also provide guidance for the international operation of China's enterprises. Meanwhile, the two systems for international operation and performance evaluation index have been put forward. The performance of international operation can be classified as financial performance or corporate value so that the operation effect of those China's enterprises going abroad can be better evaluated.

• The Journal of Industrial Distribution & Business
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• v.12 no.3
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• pp.43-49
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• 2021

Purpose: This study attempted to examine the risk of stock price plunge according to the firm's management strategy. Prospector firms value innovation and have high uncertainties due to rapid growth. There is a possibility of lowering the quality of financial reporting in order to meet market expectations while withstanding the uncertainty of the results. In addition, managers of prospector firms enter into compensation contracts based on stock prices, thus creating an incentive to withhold negative information disclosure to the market. Prospector firms' information opacity and delays in disclosure of negative information are likely to cause a sharp decline in share prices in the future. Research design, data and methodology: This study performed logistic analysis of KOSPI listed firms from 2014 to 2017. The independent variable is the strategic index, and is calculated by considering the six characteristics (R&D investment, efficiency, growth potential, marketing, organizational stability, capital intensity) of the firm. The higher the total score, the more it is a firm that takes a prospector strategy, and the lower the total score, the more it is a firm that pursues a defender strategy. In the case of the dependent variable, a value of 1 was assigned when there was a week that experienced a sharp decline in stock prices, and 0 when it was not. Results: It was found that the more firms adopting the prospector strategy, the higher the risk of a sharp decline in the stock price. This is interpreted as the reason that firms pursuing a prospector strategy do not disclose negative information by being conscious of market investors while carrying out venture projects. In other words, compensation contracts based on uncertainty in the outcome of prospector firms and stock prices increase the opacity of information and are likely to cause a sharp decline in share prices. Conclusions: This study's analysis of the impact of management strategy on the stock price plunge suggests that investors need to consider the strategy that firms take in allocating resources. Firms need to be cautious in examining the impact of a particular strategy on the capital markets and implementing that strategy.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.161-166
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• 2021

The macroeconomic concept represents the movement of a country's economy, and it affects the overall economic activities of business, government, and households. In the macroeconomy, by looking at changes in national income, inflation, unemployment, currency, interest rates, and raw materials, it is possible to understand the effects of economic actors' actions and interactions on the prices of products and services. The US Federal Reserve System (FED) is leading the world economy by offering various stimulus measures to overcome the corona economic recession. Although the stock price continued to decline on March 20, 2020 due to the current economic recession caused by the corona, the US S&P 500 index began rebounding after March 23 and to 3,694.62 as of December 15 due to quantitative easing, a powerful stimulus for the FED. Therefore, the FED's economic stimulus measures based on macroeconomic indicators are more influencing, rather than judging the stock price forecast from the corporate financial statements. Therefore, this study was conducted to reduce losses in stock investment and establish sound investment by analyzing the FED's economic stimulus measures and its effect on stock prices.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.31-36
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• 2021

As the global economy stagnated due to the Corona 19 virus from Wuhan, China, most countries, including the US Federal Reserve System, introduced policies to boost the economy by increasing the amount of money. Most of the stock investors tend to invest only by listening to the recommendations of famous YouTubers or acquaintances without analyzing the financial statements of the company, so there is a high possibility of the loss of stock investments. Therefore, in this research, I have used artificial intelligence deep learning techniques developed under the existing automatic trading conditions to analyze and predict macro-indicators that affect stock prices, giving weights on individual stock price predictions through correlations that affect stock prices. In addition, since stock prices react sensitively to real-time stock market news, a more accurate stock price prediction is made by reflecting the weight to the stock price predicted by artificial intelligence through stock market news text mining, providing stock investors with the basis for deciding to make a proper stock investment.

• Journal of Korea Trade
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• v.27 no.3
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• pp.161-178
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• 2023

Purpose - purpose of this paper is to analyze the effects of the investment facilitation levels of 11 RCEP countries (excluding Myanmar, Brunei, and Laos due to lack of data) on China's outward foreign direct investments(OFDI) using balanced panel data from 2010 to 2019. Design/methodology - First, four investment facilitation measurement indicators (regulatory environment, infrastructure, financial market, ease of doing business) were selected,investment facilitation scores of the 11 countries were obtained using the principal component analysis, an investment gravity model was established with nine explanatory variables (investment facilitation level, market size, population, geographic distance, degree of opening, tax level, natural resources, whether the country is an APEC member or not, and whether a valid bilateral investment treaty with China has been concluded) were used to establish an investment gravity model, and regression analyses were conducted with OLS and system GMM. Findings - The results of the regression analyses showed that investment facilitation levels had the greatest effect on China's OFDI, all four first-level indicators had positive effects on China's OFDI, and among them, the institutional environment had the greatest effect. In addition, it was shown that explanatory variables such as market size, population, geographical distance, degree of openness, natural resources, and whether or not a valid bilateral investment treaty has been concluded would have positive effects on China's OFDI, while tax levels and APEC membership would impede China's OFDI to some extent. Originality/value - Since the Regional Comprehensive Economic Partnership (RCEPT) came into effect not long ago, there are not so many studies on the effects of investment facilitation levels of RCEP member states on China's OFDI, and the investment facilitation measurement index constructed in this paper is relatively systematic and scientific because it includes all the contents of investment facilitation related to the life cycle of company's foreign direct investments.

• The Journal of Information Systems
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• v.32 no.1
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• pp.179-199
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• 2023

Purpose This study builds a prediction model to find stocks that can reach intrinsic value among KOSPI and KOSDAQ-listed companies to improve the stability and profitability of the stock investment. And investment simulations are conducted to verify whether stock investment performance is improved by comparing the prediction model, random stock selection, and the market indexes. Design/methodology/approach Value investment theory and machine learning techniques are applied to build the model. Various experiments find conditions such as the algorithm with the best predictive performance, learning period, and intrinsic value-reaching period. This study selects stocks through the prediction model learned with inventive variables, does not limit the holding period after buying to reach the intrinsic value of the stocks, and targets all KOSPI and KOSDAQ companies. The stock and financial data are collected for 21 years (2001-2021). Findings As a result of the experiment, using the random forest technique, the prediction model's performance was the best with one year of learning period and within one year of the intrinsic value reaching period. As a result of the investment simulation, the cumulative return of the prediction model was up to 1.68 times higher than the random stock selection and 17 times higher than the KOSPI index. The usefulness of the prediction model was confirmed in that the number of intrinsic values reaching the predicted stock was up to 70% higher than the random selection.