• Journal of the Korea Safety Management & Science
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• v.17 no.1
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• pp.337-348
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• 2015

This research introduces the Financial Effect Measurement (FEM) models which measures both the improvement and the innovation performance of Quality Control Circle (QCC) and activities of Six Sigma. Concepts and principle of Comprehensive Income Statement (CIS), Balanced Scorecard (BSC), Time-Driven Activity Based-Costing (TDABC) and Total Productive Maintenance (TPM) are applied in order to develop the 4 FEM models presented in this paper. First of all, FEM using CIS depicts the improvement effects of production capacity and yield using relationships between demand and supply, and line balancing efficiency between bottleneck process and non-bottleneck processes. Secondly, cause-and-effect relation of Key Performance Indicator (KPI) is used to present Critical Success Factor (CSF) effects for QC Story 15 steps of QCC and DMAIC (Define, Measure, Analyze, Improve, and Control) of Six Sigma. The next is FEM model for service management innovation activities that uses TDABC to calculate the time-driven effect for improving the indirect activities according to the cost object. Lastly, FEM model for TPM activities presents the interpretation of improvement effect model of TPM Capital Expenditure (CAPEX) and Operating Expenditure (OPEX) maintenance using profit, cash and Economic Added Value (EVA) as metrics of enterprise values. To better understand and further investigate FEMs, recent cases on National Quality Circle Contest are used to evaluate new financial effect measurement developed in this paper.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.41-56
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• 2006

The real estate portal has grown into a successful e-Business model that is combined on and off line. Although IT technologies have shown rapid growth, the real estate portals have failed to satisfy the expectations of the Internet users. Based on Michael Porter's competitive forces framework, this study proposes five competitive strategies for continuing growth of the real estate portals. First, to strengthen bargaining power against supplier, buyer and potential new entrants, the real estate portals need to construct a basic network that is cost efficient and maintains real estate goods and makes profits by collaborative deals. Second, strengthen brand value and endeavor to escape from dependency on the Internet portals. Third, develop services to consider changed circumstances and give a lot of sources to make profit to real estate agencies. Fourth, concentrate on marketing to draw in the Internet users and adapt strategies that have been successful in other fields. Finally, real estate fields can seek out ideas for developing new business models from other successful e-Business models and should benchmark them to reduce expenses to a minimum and increase benefits to a maximum.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1654-1666
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• 2024

The goal of this research is to propose a way to maximize small modular reactor (SMR) utilization to gain better market feasibility in support of carbon neutrality. For that purpose, a comprehensive tool was developed, combining off-design thermohydraulic models, economic objective models (levelized cost of electricity, annual profit), non-economic models (saved CO2), a parameter input sampling method (Latin hypercube sampling, LHS), and a multi-objective evolutionary algorithm (Non-dominated Sorting Algorithm-2, NSGA2 method) for optimizing a SMR-combined heat and power cycle (CHP) system design. Considering multiple objectives, it was shown that NSGA2+LHS method can find better optimal solution sets with similar computational costs compared to a conventional weighted sum (WS) method. Out of multiple multi-objective optimal design configurations for a 105 MWe design generation rating, a chosen reference SMR-CHP system resulted in its levelized cost of electricity (LCOE) below $60/MWh for various heat prices, showing economic competitiveness for energy market conditions similar to South Korea. Examined economic feasibility may vary significantly based on CHP heat prices, and extensive consideration of the regional heat market may be required for SMR-CHP regional optimization. Nonetheless, with reasonable heat market prices (e.g. district heating prices comparable to those in Europe and Korea), SMR can still become highly competitive in the energy market if coupled with a CHP system.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.472-482
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• 2012

There are many investors in the stock market, and more and more people get interested in the stock investment. In order to avoid risks and make profit in the stock investment, we have to determine several aspects using various information. That is, we have to select profitable stocks and determine appropriate buying/selling prices and holding period. This paper proposes a data mining tool for the investors' decision support. The data mining tool makes stock investors apply machine learning techniques and generate stock price prediction model. Also it helps determine buying/selling prices and holding period. It supports individual investor's own decision making using past data. Using the proposed tool, users can manage stock data, generate their own stock price prediction models, and establish trading policy via investment simulation. Users can select technical indicators which they think affect future stock price. Then they can generate stock price prediction models using the indicators and test the models. They also perform investment simulation using proper models to find appropriate trading policy consisting of buying/selling prices and holding period. Using the proposed data mining tool, stock investors can expect more profit with the help of stock price prediction model and trading policy validated on past data, instead of with an emotional decision.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.8
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• pp.909-922
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• 2012

To fully utilize scarce spectrum resource, it's necessary to develop and evaluate promising business models prior to making technology R&D plan and industrial promotion policy. The purpose of this paper is to design potential business models, evaluate the propriety of commercializing the models, and discuss promotion policies after exploring promising sectors consuming spectrum resources. The research is based on TV white space, which is vacant TV channels in region or time domain and considered as core spectrum resource along with digital terrestrial television switchover. As the result, four kinds of business models were derived, including broadcasting and telecommunication types. Each model was discussed from four standpoints: customer value proposition, profit formula, key resources, and key processes, and the propriety for commercialization was evaluated by three dimensions: technological evaluations, business-oriented evaluations, and user-oriented evaluations. The promotion policies of government and market participants for the activation of TV White space-based business models were discussed as well.

• Information Systems Review
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• v.8 no.2
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• pp.51-72
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• 2006

This study investigates the typology of Internet business models according to revenue sources, and empirically tests how the revenue sources of each Internet business model are different each other. This study consists of the following two steps. First, AHP(Analytic Hierarchy Process) is adopted in developing the influential factors(indexes) for the profitability of each Internet business model and the weight score of each factor. The questionnaire for AHP consists of 47 questions on 9-point scales, and was distributed to 10 experts on Internet business model. Expert Choice program has been used for analysis. Second, the questionnaire to survey the current profitability of each Internet business model was developed on 5-point scale. In order to analyze the actual revenue quality and source of Internet business models, we used MANOVA and ANOVA. This study contributes to develop the desirable revenue or profit model of each Internet business model, and also provides a reference in evaluation of the revenue quality of Internet business models.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.207-222
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• 2024

Purpose - This study investigates whether the lagged price difference ratio between preferred and common stocks is related to the return and closing price of the preferred stock using three panel models. Design/methodology/approach - As a first step, we use a two-way fixed effect panel model with stationary preferred stock returns as a dependent variable. For robustness, we then apply the autoregressive distributed lag model (ARDL) and error correction model (ECM) with nonstationary closing prices of the preferred stocks as a dependent variable and compare the results of each model. The ARDL and ECM models provide an advantage of estimating a long-run equilibrium equation together if a long-run relationship exists between the two time-series variables compared to the fixed effect model. Findings - Our sample consists of 107 preferred stocks with at least four years of daily observations as of the end of December 2023. The coefficients of the error correction terms in the ARDL and ECM models are highly statistically significant, approximately -0.08. This indicates that the disequilibrium between the closing prices of common and preferred stocks adjusts by about 8% per day toward equilibrium. In all three models, the price difference ratio on day t-1 was statistically significant in explaining the preferred stock returns or closing prices on day t, implying that trading based on the previous day's price difference ratio is effective for one day. Research implications or Originality - Furthermore, the returns on preferred stocks are higher for firms with a lower proportion of foreign investors or a lower foreign market capitalization of preferred stocks. This suggests that foreign investors with informational advantages do not actively engage in profit-taking by trading preferred stocks, thus not narrowing the price difference. In summary, the recent surge in preferred stock prices is likely driven mainly by the irrational behavior of retail investors.

• Smart Media Journal
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• v.11 no.4
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• pp.19-29
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• 2022

Recently, with the development of IoT technology, the number of farms using smart farms is increasing. Smart farms monitor the environment and optimise internal environment automatically to improve crop yield and quality. For optimized crop cultivation, researches on predict crop productivity are actively studied, by using collected agricultural digital data. However, most of the existing studies are based on statistical models based on existing statistical data, and thus there is a problem with low prediction accuracy. In this paper, we use various predition models for predicting the production and sales profits, and compare the performance results through models by using the agricultural digital data collected in the facility horticultural smart farm. The models that compared the performance are multiple linear regression, support vector machine, artificial neural network, recurrent neural network, LSTM, and ConvLSTM. As a result of performance comparison, ConvLSTM showed the best performance in R2 value and RMSE value.

• Journal of Platform Technology
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• v.11 no.4
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• pp.62-70
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• 2023

This research is one of a series of studies to develop a system to help agricultural producers and sellers determine when and how much to ship products to the wholesale market to maximize their profit. The purpose of this research is to incorporate the time-varying quality change effect, which was not used in the previous agricultural and marine product shipping model. The researchers developed four models to measure the quality change effect: quality declining steadily over time, quality declining rapidly at first and then slowly, quality declining first slowly and then rapidly, and quality rising over time and then decreasing again. According to the results of an empirical analysis of the effect of each model's quality change effect on shipments for apples traded in the Garak Wholesale Market from 2014 to 2021, statistical significance was found in the quality change effect of all four models. And there was no significant difference in explanatory power between the four models. Therefore, any of the four models should be introduced into the decision-making system for shipping time for apples.

• Journal of Biosystems Engineering
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• v.28 no.2
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• pp.107-116
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• 2003

One of the major obstructing factors against managing dairy farm in Korea has been a shortage of roughage supply. The shortage of roughage caused excessive use of concentrate feed increase of production cost and deterioration of cattle quality. In order to solve this problem for the dairy farm, use of fallow paddy field in the winter was feasible to produce barley and rye forage during the winter season after harvesting of in. And many desirable effects of raising cattle productivity, saving dollars for importing feeds and providing huge ground for manure spreading are expected by enlarged local roughage production. Through analysing the forage producing process, a mechanized operation model was developed for dairy farms in Korea. Its model consists of seeding models(till, no-till model) and harvesting models(wrap silage, traditional silage, hay model). Currently, the government policies are being executed to urge producing winter cereal wrap silage in the fallow paddy field with various supporting programs. Ant with enlarged local forage production, it is possible to make a new huge market fur forage producing machine.