• The Korean Journal of Financial Management
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• v.2 no.1
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• pp.55-75
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• 1986

This article is to analyse the economic efficiency of capital market, which plays a role of resource allocation in terms of financial claims such as stock and bond. It provides various contributions to the welfare theoretical aspects of modern capital market theory. The key feature that distinguishes the theory described here from traditional welfare theory is the presence of uncertainty. Securities has time dimensions and the state and outcome of the future are really uncertain. This problem resulting from this uncertainty can be solved by complete market, but it has a weak power to explain real stock market. Capital Market is faced with the uncertainity because it is a kind of incomplete market. Individuals and firms in capital market made their consumption-investment decision by their own criteria, i. e. the maximization of expected utility form intertemporal consumption and the maximization of the market value of firm. We noted that allocative decisions that had to be made in the economy could be naturally subdivided into two groups. One set of decisions concerned the allocation of first-period resources among consumption $C_i$, investment in risky firms $I_j$, and riskless investment M. The other decisions concern the distribution among individuals of income available in the second period $Y_i(\theta)$. Corresponing to this grouping, the theoretical analysis of efficiency has also been dichotomized. The optimality of the distribution of output in the second period is distributive efficiency" and the optimality of the allocation of first-period resources is 'the efficiency of investment'. We have found in the distributive efficiency that the conditions for attainability is the same as the conditions for market optimality. The necessary and sufficient conditions for attainability or market optimality is that (1) all utility functions are such that -$\frac{{U_i}^'(Y_i)}{{U_i}^"(Y_i)}={\mu}_i+{\lambda}Y_i$-linear risk tolerance function where the coefficients ${\mu}_i$ and $\lambda$ are independent of $Y_i$, and (2) there are homogeneous expectations, i. e. ${\Large f}_i(\theta)={\Large f}(\theta)$ for every i. On the other hand, the efficiency of investment has disagreement about optimal investment level. The investment level for market rule will not generally lead to Pareto-optimal allocation of investment. This suboptimality is caused by (1)the difference of Diamond's decomposable production function and mean-variance valuation model and (2) the selection of exelusive investment or competitive investment. In conclusion, this article has made an analysis of conditions and processes of Pareto-optimal allocation of resources in capital marker and tried to connect with significant issues in modern finance.

• Korean Journal of Construction Engineering and Management
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• v.10 no.5
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• pp.135-147
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• 2009

The world has witnessed the dramatic expansion of international construction markets during the last decades, particularly around the developing economies and energy resource-rich countries. However, despite the booming markets, the risks of emerging regions have also increased under the rapidly changing environments confronting the global contractors. Most of all, success in overseas business mainly depends on selecting the right market to enter. Accordingly, the right market selection requires global firms to carefully carry out the scientific market entry decision by evaluating country risks, market prospects, firm's capability, level of competition, and among others. This study aims at developing a market entry model by the use of real option analysis (ROA) and scenario planning, which addresses the corporate strategic flexibility against the uncertainties encompassing the overseas construction markets. Based on the suggested approach, global contractors are expected to make a better decision rather than a typically static approach in pursuing, postponing, or abandoning a prospective market to their capacity with a concurrent consideration of uncertainties as well as its option value.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.182-194
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• 2008

Corporate managers look at IT outsourcing as long-term strategic choices not as short-term tactical ones, and maximizing the effect that IT outsourcing brings about is the main concern to them. Emerging different types of IT outsourcing and their effects on the corporate business decisions necessitate the research on this subject. According to previous researches, the Intent for IT outsourcing is categorized as IS Improvement, Business Impact, and Commercial Exploitation. The decison factors for these IT outsourcing include corporate strategy types, IT role, and interaction between these two. Firm size and IT maturity are selected as moderating factors to add the credibility to the research of the effect of IT outsourcing decision making. Analyzing collected data revealed that corporate strategy rather than IT role is more significant factor affecting the intent for IT outsourcing decision. Defenders(as in corporate strategy types) tend to use IT outsourcing more as a means to improve information systems, compared to analyzers and reactors. Prospectors tend to use IT outsourcing more as a commercial exploitation, compared to analyzers and reactors. These outcomes prove that corporate strategy characteristics reflect outsourcing intent. There were previous researches that showed outsourcing decision depends on IT role, however the hypothesis was rejected that IT role determines outsourcing intent. It was also rejected that the interaction between corporate strategy types and IT role determines outsourcing intent. Corporate decision makers should first analyze corporate strategy, and reflect it on the outsourcing intent when they make IT outsourcing decisions. Only the precise defining of IT outsourcing intent will lower the risk and increase the possibility of success.

• Korean Journal of Construction Engineering and Management
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• v.20 no.1
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• pp.73-85
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• 2019

Since the beginning of a new century, many Korean construction and engineering companies are facing a very dynamic and fast changing business environment which includes severe competition, higher risk, economic depression, declining revenues and profits, etc. In order to cope with these challenges, they need to secure special capabilities to actively adapt to the paradigm changes. One of those capabilities could be project management capability which allows us to manage organizational resources dynamically and integratively based on project portfolio management concept. The objective of this study is to investigate how the dynamic capability of a project-based organization to control the resource affects the firm performance and the competitive advantages. Data was collected from the construction and engineering companies in South Korea by using survey questionnaire, and analyzed for empirical tests by using statistical methods such as structural equation modelling and path analysis. The results showed that the organizational resources, if they had the VRIN characteristics, would have positive impacts on creating the dynamic capabilities for project organization. In turn, the dynamic capabilities of a project organization would have impacts on improving business performance and creating competitive advantages. Also, it was found that the organizational resources may have direct impact on business performance and competitive advantages. The academic contribution of this study is that it attempts to integrate resource based view and the dynamic capability theory about creating competitive advantages for project based organization. This study also provided practical implications to the companies in construction industry by showing how to use organizational resources strategically to create competitive advantages.

• Korean small business review
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• v.43 no.3
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• pp.91-117
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• 2021

The purpose of this study is to study the effect of internatioanl entrepreneurial orientation of small and medium-sized Chinese manufacturing companies on export performance. A total of 183 corporate data were used for empirical analysis for Chinese manufacturing export companies. In summary, first, international entrepreneurial orientation was shown to have a significant positive effect on export performance, second, international etrprenurial orientation was shown to have a significant positive effect on absorption capacity, and third, the stronger environmental dynamics and network capacity, the stronger international business orientation and export ability. The implications of this study are summarized as follows. It suggests that the more innovative, enterprising and risk-taking Chinese SMEs are, the better their export performance and the better their ability to absorb foreign knowledge. It also suggests that small business managers must continue to strengthen their network capabilities to improve export performance through international entrepreneurial orientation, and this relationship is further strengthened in a dynamic environment. It also suggests that the impact of firm's absorption capacity on export performance will weaken over time.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.697-703
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• 2022

Due to the recent economic downturn caused by Covid-19 and the unstable international situation, many investors are choosing the derivatives market as a means of investment. However, the derivatives market has a greater risk than the stock market, and research on the market of market participants is insufficient. Recently, with the development of artificial intelligence, machine learning has been widely used in the derivatives market. In this paper, reinforcement learning, one of the machine learning techniques, is applied to analyze the scalping technique that trades futures in minutes. The data set consists of 21 attributes using the closing price, moving average line, and Bollinger band indicators of 1 minute and 3 minute data for 6 months by selecting 4 products among futures products traded at trading firm. In the experiment, DNN artificial neural network model and three reinforcement learning algorithms, namely, DQN (Deep Q-Network), A2C (Advantage Actor Critic), and A3C (Asynchronous A2C) were used, and they were trained and verified through learning data set and test data set. For scalping, the agent chooses one of the actions of buying and selling, and the ratio of the portfolio value according to the action result is rewarded. Experiment results show that the energy sector products such as Heating Oil and Crude Oil yield relatively high cumulative returns compared to the index sector products such as Mini Russell 2000 and Hang Seng Index.

• Journal of the Korean Orthopaedic Association
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• v.54 no.6
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• pp.574-578
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• 2019

For the treatment of a bony Bankart lesion accompanied by an acute traumatic shoulder dislocation, anatomical reduction and stable fixation of the bone fragment and glenohumeral ligament are essential to avoid chronic instability or degenerative changes. If the Bankart lesion has large bony pieces or comminuted fragments, it can be difficult to perform precise and secure fixation of the big intraarticular fragment to the fracture site because of the limited visualization of the arthroscopic procedure. In addition, in the case of the open procedure, it requires an extensive surgical dissection to access the fractured fragment, which may cause surgical approach-related morbidity, such as neurovascular complications, delayed subscapularis healing, and increased risk of stiffness. This paper describes an alternative open suture anchor technique for a large bony Bankart lesion, which was secured anatomically with squared knots after a shuttle relay through bony tunnels and adjacent soft tissue and labrum. This technique can achieve anatomical and firm fixation under direct vision, and reduce the number of surgery related morbidities.

• Korea Trade Review
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• v.43 no.1
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• pp.199-221
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• 2018

The internationalization of venture firms is of importance resulting from the increased opportunities as well as the entry barriers faced in this process. This study is to investigate barrier factors affecting Korean venture firms' internationalization. Among these factors, we measured relative weights using Analytic Hierarchy Process (AHP). Literatures regarding global firm's internationalization was reviewed, and barriers were classified environment, corporate and CEO barriers. Multiple variables were used in order to measure their relative significance. We surveyed executives of venture firms comprising two groups: first, 15 global venture firms, and secondly, gradually internationalizing firms. The two groups show contradictory results as environment barriers are the primary for born-global ventures and corporate barriers are the primary for gradually internationalizing ventures. Concerning corporate barriers, the lack of marketing capability is the highest barrier for both groups. The CEO barrier is the lowest for both groups. Regarding corporate barriers, gradually internationalizing ventures considers the risk of business as highest, whereas born-global ventures features the lack of R&D capacity as highest Results of this paper imply that firms should consider priority and sequential approaches in facing environment, corporate and CEO barriers.

• Management & Information Systems Review
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• v.35 no.4
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• pp.1-19
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• 2016

The researchers in strategic management have focused on identifying the effects of CEO's demographic characteristics and experience on the strategic choices and performance of firms. On the other hand, they have failed to identifying the effects of CEO's psychological characteristics on them because of the difficulties over data collection and measurement for variables. To overcome this limitation of prior researches, this study is designed to achieve two specific objectives. The first is to examine the effect of CEO narcissism on diversification strategy and performance of listed corporations on Korean securities market in an economic downturn. The other is to examine the moderating effects of various corporate governance systems that are related to board and/or ownership structures on those relationships. The empirical setting for this study was drawn from a multi-year(2011~2014) sample of large listed corporations in Korean securities market. To achieve the objectives, the hypotheses of research are analyzed by implementing multiple regression analyses in two separate models. The results of these analyses show that CEO narcissism is positively related to the diversification of listed large corporations in Korean securities market. Regrading the moderating effects, the stake of institutional investors weakens the positive relationship between CEO narcissism and firm's diversification. The findings of this research imply that CEO narcissism can intensify the tendency of Korean corporations to adopt high-risk and high return strategy in an economic downturn. Thus, firms might be able to use CEO narcissism to drastically restructure the business portfolio in an economic downturn. However, Korean corporations should be very cautions to maximize the positive effect of CEO narcissism. They might be use the institutional investors as their corporate governance system to monitor and control the opportunism of CEO in the decision for diversification in an economic downturn.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.