• Journal of Intelligence and Information Systems
• /
• v.22 no.4
• /
• pp.177-192
• /
• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.43 no.4
• /
• pp.248-256
• /
• 2023

As a means to activate eco pastoral system in alpine grassland, the government can consider public pastures, which are currently unused, to scale them up into public ranches. Depending on ownership and operation, four management models proposed as follows: 1) Government-Owned and Operated with Balanced Profit and Loss 2) Government-Owned and Operated with Revenue Generation 3) Government-Owned but Privately Operated by Outsourced to Professional Manager 4) Full Privatization (Ownership and Operation by Private Individuals). The study outlined above proposes four management models for the activation of eco pastoral system in alpine grassland. It also suggests methods for the selection and performance evaluation of manager to establish a profitable structure. Additionally, the research provides management methods for the conservation of grazing ecology in pastoral ecosystems. Particularly, the adaptation of tools commonly used in South Korean business sector for the selection and performance evaluation of manager within the system of the proposed management models. This aspect is deemed valuable as it aligns these tools with the specific characteristics of eco pastoral system in alpine grassland, contributing not only to the effective implementation of the models but also to the enhancement of the revenue structure.

• Korean Journal of Construction Engineering and Management
• /
• v.12 no.4
• /
• pp.130-138
• /
• 2011

In the construction industry, there is a growing demand for new programs incorporating IT applications. In construction, initiatives calling for changes ensuring the improvement of productivity, quality and safety, and for the strengthening of global competitiveness, have contributed to the increased need for exploring new markets. Moreover, the government's supportive policies have helped develop profit models. Meanwhile, the industry and the government have supported the efforts for identifying and disseminating successful case studies - as part of the strategy for evaluating and promoting the developed programs. However, the criteria for identifying/evaluating successful cases remain vague, and the viewpoints of participants differ depending on their disciplines. These discrepancies could lead to inconsistent results. Thus, it is imperative that a criterion be provided, upon which to judge the success or failure of implementation cases and to disseminate role models. It is also imperative that a direction of improvement be proposed. This study was conducted to propose the criteria for and process of evaluating the success of construction-IT convergence to help promote the construction industry incorporating IT applications. To that end, success factors for and the significance of IT-incorporated construction were identified.

• Korean Business Review
• /
• v.15
• /
• pp.99-114
• /
• 2002

Recently several business models concerning e-Business has been introduced. But the different environment for each business requires the business model which is contingent to its specific situation. We, therefore, need to develop the e-Business models considering environment factors such as capital size, technology level, collection ability and amount of information, profit or target customers, etc. There can be several ways to create the value of an e-Business firm. A way among them is to develop limited area by focusing on core parts of the firm. This way leads for the firm to search the investment priority in order to solve the problem, which is to set a proper production and investment level for concentrating on competitively excellent areas of the firm. In this paper, we propose a method to decide the investment priority effectively when making a decision using fuzzy information. The method by our model is to minimize tolerances of given business fuzzy goals.

• KIPS Transactions on Computer and Communication Systems
• /
• v.1 no.3
• /
• pp.133-142
• /
• 2012

Cournot model is one of representative models among many game theoretic approaches available for analyzing competitive market models. Recent years have witnessed various kinds of attempts to model competitive electricity markets using the Cournot model. Cournot model is appropriate for oligopoly market which is one characteristic of electric power industry requiring huge amount of capital investment. When we use Cournot model for the application to electricity market, it is prerequisite to assume the downward sloping demand curve in the right direction. Generators in oligopoly market could try to maximize their profit by exercising the market power like physical or economic withholding. However advanced electricity markets also have demand side bidding which makes it possible for the demand to respond to the high market price by reducing their consumption. Considering this kind of demand reaction, Generators couldn't abuse their market power. Instead, they try to find out an equilibrium point which is optimal for both sides, generators and demand. This paper suggest a quantitative analysis between market variables based on econometrics for estimating demand responses in smart grid environment.

• Nuclear Engineering and Technology
• /
• v.40 no.1
• /
• pp.49-68
• /
• 2008

The purpose of this paper is to extensively review the condition monitoring (CM) techniques using empirical models in an effort to reduce or eliminate unexpected downtimes in general industry, and to illustrate the feasibility of applying them to the nuclear industry. CM provides on-time warnings of system states to enable the optimal scheduling of maintenance and, ultimately, plant uptime is maximized. Currently, most maintenance processes tend to be either reactive, or part of scheduled, or preventive maintenance. Such maintenance is being increasingly reported as a poor practice for two reasons: first, the component does not necessarily require maintenance, thus the maintenance cost is wasted, and secondly, failure catalysts are introduced into properly working components, which is worse. This paper first summarizes the technical aspects of CM including state estimation and state monitoring. The mathematical background of CM is mature enough even for commercial use in the nuclear industry. Considering the current computational capabilities of CM, its application is not limited by technical difficulties, but by a lack of desire on the part of industry to implement it. For practical applications in the nuclear industry, it may be more important to clarify and quantify the negative impact of unexpected outcomes or failures in CM than it is to investigate its advantages. In other words, while issues regarding accuracy have been targeted to date, the concerns regarding robustness should now be concentrated on. Standardizing the anticipated failures and the possibly harsh operating conditions, and then evaluating the impact of the proposed CM under those conditions may be necessary. In order to make the CM techniques practical for the nuclear industry in the future, it is recommended that a prototype CM system be applied to a secondary system in which most of the components are non-safety grade. Recently, many activities to enhance the safety and efficiency of the secondary system have been encouraged. With the application of CM to nuclear power plants, it is expected to increase profit while addressing safety and economic issues.

• Journal of Korea Trade
• /
• v.24 no.8
• /
• pp.81-100
• /
• 2020

Purpose - Based on complexity theory, this study develops a configurational model to predict the profitability of Halal cosmetics firms in the Indonesian and Malaysian markets. The proposed research model involves two level configurations-industry context and selling strategies-to predict high and low scores of a firm's profitability. The industry context configuration model comprises industry stability, product homogeneity, price sensitivity, and switching cost. Selling strategies include customer-focused, competitor-focused, and margin-focused approaches. Design/methodology - This is the first empirical study that calculates causal models using a combination of industry context and selling strategy factors to predict profitability. Data obtained from the marketing managers of cosmetics firms are used to test the proposed configurational model using fuzzy-set qualitative comparative analysis (fsQCA). It contributes to the current knowledge of business marketing by identifying the factors necessary to achieve profitability using analysis of condition (ANC). Findings - The results revealed that unique and distinct models explain the conditions for high and low profitability in the Indonesian and Malaysian halal cosmetic markets. While customer-focused selling strategy is necessary to attain a higher profit in both the markets, margin-focused selling strategy appears to be an essential factor only in Malaysia. Complexity of the interactions of selling strategies with industry factors and differences between across two study markets confirmed that complexity theory can support the research configurational model. The theoretical and practical implications are also illustrated. Originality/value - Despite the rapid growth of the global halal industry, there is little knowledge about the halal cosmetic market. This study contributes to the current literature of the halal market by performing a set of asymmetric analytical approaches using a complex theoretical model. It also deepens our understating of how the Korean firms can approach the Muslim consumer's needs to generate more beneficial turnover/revenue.

• Journal of Digital Convergence
• /
• v.16 no.11
• /
• pp.455-464
• /
• 2018

Recognizing the shortage of information about business models to generate profit despite the designers' recent interest in 3D printers as a new creative tool, this study set out to make sunglasses for young children, which lacked diversity in sizes according to age due to the small market scope under the old mass production system, by taking advantage of 3D printers' strength in the small batch production of customized products and propose a practical example to be expandable as a small-size business model. For these purposes, the investigator summarized the basic information about the 3D printing technology and the basic structure of sunglasses and made a size table to manufacture sunglasses for young children by analyzing the size table for vision correction. After this series of work, the study presented final product with the production costs and demonstrated that sunglasses for young children made with a 3D printer could be a practical case expandable as a competitive small-size business model in the market.

• Journal of Korea Port Economic Association
• /
• v.35 no.1
• /
• pp.39-56
• /
• 2019

This study addresses the management performance of the retail industry in Korea. The Non-store e-commerce business, consisting of TV home shopping and online shopping, grew very fast during the 2000s. For roughly six years in the 2010s, the diversification of online shopping business models, intensifying competition, and the proliferation of competition accelerated the entry of offline shopping retailers. During the analysis period from 2001 to 2016, the performance of the Non-­store e-commerce business was statistically better than that of the offline shopping retail business, department stores, general retailers, and small­-sized retailers. As expected, a significant difference between performance and some of the indicators of growth and activity could be seen because of the capital and operating structure of the retail industry. In particular, the Non-store e-commerce businesses have diverse sales media and heterogeneous business models. In this study, we have presented the significance of the differences in the indicators of operating profit and inventory turnover, as well as the discussion required for managing in the future.

• Journal of Digital Convergence
• /
• v.20 no.4
• /
• pp.791-797
• /
• 2022

Through recent metaverse marketing case studies, success factors and activation methods were analyzed from the perspective of content, platform, network, and device of the metaverse ecosystem in each industry. The importance of contents and platform of metaverse could be found in entertainment, fashion, office space and real estate, education, advertisement and commerce industries. In order to vitalize the metaverse, firstly, it is necessary to strengthen active participation and retention by providing a stable revenue model for market participants. Secondly, the importance of attractive content to expand subscribers is a key trigger for metaverse activation. Thirdly, it is necessary to increase the convenience of using metaverse service by using a light and simple device for the user. Fourthly, a win-win cooperation strategy should be supported in the value chain of the industry through ecosystem scalability. In addition, business opportunities for market participants and additional revenue models should be continuously provided.