• Journal of Korean Institute of Industrial Engineers
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• v.13 no.1
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• pp.31-38
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• 1987

This paper is concerned with the multiple unit auction under the following assumptions: 1) multiple identical objects are to be sold to the highest bidders, but a bidder may obtain at most one, 2) each bidder has a fixed reservation value and draws his reservation value independently in the same distribution, 3) The greater a bidder's reservation value is, the more a bidder will bid for the object, and 4) a bidder will bid when his expected profit is more than zero. The purpose of this paper is to design the optimal auctions, in terms of the reserve price and entry fee, that can be applied in any types of multiple unit auctions under the above assumptions. Further, auctioneer's expected revenue and profit, and all the winners' expected profit are analyzed.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.360-365
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• 2005

The need of constructing high-tech facilities is one of the important issues concerning the competitiveness by the high-tech companies. It, simultaneously, offers a magnificent opportunity for construction participants. Nevertheless, the high-tech construction is experience-based, resulting in little related construction knowledge that has been statistically analyzed and documented. This study measures and confers with the profit patterns causing the disparity between the traditional and high-tech construction. The database was the result of collecting detailed information of 65 construction projects from eight construction companies, including detailed records of over 20 main construction operations in each project. All of these were performed during the recent 10 years and encompassed in the project types of the high-tech construction, residential building, and commercial building. Rendering suggestions regarding profit management and expecting to economize cost of learning from inexperience while extending to the high-tech construction were both presented.

• Asia Marketing Journal
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• v.11 no.3
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• pp.225-249
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• 2009

Hyundai Marine & Fire Insurance has achieved its goal of revenue growth while most of insurance companies have failed. It is because Hyundai Marine & Fire Insurance continued to make sincere efforts to increase employee satisfaction. The service-profit chain posits that employee satisfaction is linked to customer satisfaction and to revenue growth. The case shows how Hyundai Marine & Fire Insurance put the service-profit chain to work and how different its internal marketing strategy is.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.48-54
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• 2010

S plastic injection molding factory located at Namdong Industrial Complex in Incheon produces plastic parts for semiconductor, vacuum cleaners, office furniture, etc. It produces the parts to customers' order and delivers them directly to customers at due dates using the trucks of freight company. In recent years, it has been suffered from the excessive production cost, high lost sales rate, rigid response to customers' order, and high delivery cost, which affect negatively on its profit. This paper introduces a case study on the profit increase through a newly proposed production and distribution method which applies a make-to-stock and multi-visit delivery strategy at S plastic injection molding factory. The proposed method is evaluated by comparing with the current method with respect to sales profit using the historical data of customer demand. It is confirmed through the computational experiments that the proposed production and distribution method yields almost double increase in profit resulted from the increased production, reduced lost sales, reduced production cost, and reduced delivery cost.

• Health Policy and Management
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• v.9 no.2
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• pp.1-20
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• 1999

This study was conducted to investigate the predictors of hospital bankruptcy in Korea and to examine the predictive power for 3 types of statistical models of hospital bankruptcy. Data on 17 financial and 4 non-financial indicators of 30 bankrupt and 30 profitable hospitals in 1. 2, and 3 years before bankruptcy were obtained from the hospital performance databank of Korea Institute of Health Services Management. Significant variables were identified through mean comparison of each indicator between bankrupt and profitable hospitals, and the predictive power of statistical models of hospital bankruptcy were compared. The major findings are as follows. 1. Nine out of 21 indicators - fixed ratio, quick ratio, operating profit to total assets, operating profit to gross revenue, normal profit to total assets,normal profit to gross revenue, net profit to gross revenue, inventories turnrounds, and added value per adjusted patient - were found to be significantly predictitive variables in Logit and Probit models. 2. The predicdtive power of discriminant model of hospital bankruptcy in 1. 2, and 3 years before bankruptcy were 85.4, 79.0, and 83.8% respectively. With regard to the predictive power of the Logit model of hospital bankruptcy, they were 82.3, 75.8, and 80.6% respectively, and of the Probit model. 87.1. 80.6, and 88.7% respectively. 3. The predictive power of the Probit model of hospital bankruptcy is better than the other two predictive models.

• IE interfaces
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• v.20 no.2
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• pp.186-194
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• 2007

Recent deregulation of Korean electricity industry has made each power generation company pay more attention to maximizing its own profit instead of minimizing the overall system operation cost while guaranteeing system security. Electricity power generation problem is typically defined as the problem of determining both the on and off status and the power generation level of each generator under the given fuel constraints, which has been known as Profit-Based Unit Commitment (PBUC) problem. To solve the PBUC problem, the previous research mostly focused on devising Lagrangian Relaxation (LR) based heuristic algorithms due to the complexity of the problem and the nonlinearity of constraints and objectives. However, these heuristic approaches have been reported as less practical in real world applications since the computational run time is usually quite high and it may take a while to implement the devised heuristic algorithms as software applications. Especially when considering long-term planning problem which spans at least one year, the complexity becomes higher. Therefore, this paper proposes an explicit column generation algorithm using power generation patterns and the proposed algorithm is successfully applied to a Korean power generation company. The proposed scheme has a robust structure so that it is expected to extend general PBUC problems.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.435-448
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• 2013

The aim of this study is to investigate and develop the extended models for Economic Cash Amount(ECA), Cash Break Even-Point(BEP), and Cash Flow Statement(CFS) by referencing systematic literature review in the field. The study develops three extended models to determine the optimal cash amount: ECA model with interest opportunity cost, financing transaction cost and financing fail cost, ECA model with daily cash supply and interest opportunity cost, ECA model with financing fail cost and interest opportunity cost. Earnings Before Interests, Tax, Depreciation and Amortization(EBITDA) is obtained by subtracting noncash depreciation costs from Earning Before Interest and Tax(EBIT), which is efficient metric to evaluate operating cash flow. The research also develops two extended Cash BEP models, considered as interest and corporate tax, in order to indentify the break-even point as EBITDA equals zero. Furthermore, this paper proposes the modified version of CFS by introducing the reclassification of operating and financing accounts in the statement of financial position. In addition, the study also present the reclassification of five types of profit, such as gross profit, EBIT, ordinary profit, special profit, and net profit within the statement of comprehensive income. In order to provide a better understanding of the proposed cash flow models, numerical examples, such as two-sample t test and Analysis of Variance(ANOVA), are presented to demonstrate the statistical significance according to the industrial types for net working capital(i.e cash-to-cash), net profit, operating cash flow and free cash flow.

• International Journal of Knowledge Content Development & Technology
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• v.8 no.1
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• pp.79-89
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• 2018

We collected and analyzed data from e3data.org, which is a global registry of data repository services. We analyzed data profile for three leading Asian economies-Korea, China, and Japan-against the reference data for other participating countries. In particular, we examined how individual countries contribute to the repository, organizational type, versioning and product quality management, and subject tagging. We come to the conclusion that all three Asian countries still fall short in terms of involvement. As for participating institutions, there are 7 from Korea, 64 from China, and 120 from Japan. Among Chinese organizations, 3 are profit, 61 non-profit, and 37 organizations (which yields 1.8%) are involved in repository building. In Japan, there is 1 is commercial and 119 non-profit organizations, of which 57 (3.0%) are involved in repository building. All 7 organizations from Korea are non-profit, and 6 of them (0.3%) are involved in repository building. As regards versioning and product quality management, Korea, China, and Japan are up to par with other countries. Subject analysis reveals that Korea contributes more to geosciences, Japan to physics and geosciences, while China, unlike Korea and Japan, is more active in life sciences. It is hoped that this study will help planning domestic infrastructure for research data repositories with proper consideration for specific research domains and national characteristics.

• Journal of the Korea Institute of Building Construction
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• v.12 no.2
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• pp.169-182
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• 2012

In the past, a strategic management of work demands has been increasingly challenged to design-build (DB) firms. Such a management is capable of providing sufficient profitable impact of a project on them. Total project profit is mainly related to actual resources, work completion time, amount of rework, and costs. The degree of recycling work packages in the DB project delivery system is used as a measure of the quality of the performed work. However, there are few models available to evaluate the impact of a demand management strategy on the DB firms and to predict its behavior. We propose a decision-making support model as an aid for assessing the amount of rework and for predicting project profit resulting in a convincible demand management strategy. This model is constructed by using a dynamic feedback approach that can analyze the problems arising in complex managerial systems. For the purpose of illustration, widely acceptable strategies were applied into the model to explore their impacts on the DB firms. The results indicate that the model is helpful for the managers in selecting the most appropriate demand management strategy for successfully achieving their objectives.