• Journal of Korean Society for Quality Management
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• v.46 no.4
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• pp.797-820
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• 2018

Purpose: It is to seek for an appropriate cost rate analysis methodology of credit card value propositions in Korea. For this issue, it is claimed that methodologies based on probability distribution is more suitable than methodologies based on data-mining. The analysis model constructed for the cost rate estimation is called VCPM model. Methods: The model includes two major variables denoted as S and P. S is monthly credit card usage amount. P stands for the proportion of usage amount at special merchants over the whole monthly usage amount. The distributions assumed for P are positively skewed distributions such as exponential, gamma and lognormal. The major inputs to the model are also derived from S and P, which are E(S) and the aggregate proportion of usage amount at special merchants over the total monthly usage amount. Results: When the credit card's value proposition is general discount, the VCPM model fits well and generates reasonable cost rate(denoted as R). However, it seems that the model does not work well for other types of credit cards. Conclusion: The VCPM model is reliable for calculating cost rate for credit cards with positively skewed distribution of P, which are general discount card. However, another model should be built for cards with other types of distributions of P.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.189-193
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• 2011

The current standard cost for recycling applied under the Extended Producer Responsibility(EPR) institution, is not coping with continuously increased number of obligatory subject items as well as a variety of variable cost changing factors regarding the recycling treatment cost caused by price fluctuation such as increased material and labor cost entirely across the society; changes in recycling treatment process following the developing technologies; and changes in the required work forces and equipments followed by the trends of automated facilities. Despite such various cost fluctuation factors, the current EPR is not coping with the trends, making the re-calculation process difficult, which causes differences between the real treatment cost for recycling. In this study, the analysis was made on main factors affecting on the related cost and the related price changing index was calculated, by conducting the influence evaluation on the standard cost factors of the current standard cost for recycling. Through theses results, more objective standard will be set for the re-calculation of standard cost for recycling to greatly contribute to setting up the midterm and long-term strategies in the future towards efficient institution.

• Clean Technology
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• v.29 no.1
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• pp.53-58
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• 2023

This study shows the summary of the economic performance of excess electricity conversion to hydrogen as well as methane and returned conversion to electricity using a fuel cell. The methane production process has been examined in a previous study. Here, this study focuses on the conversion of methane to electricity. As a part of this study, capital expenditure (CAPEX) is estimated under various sized plants (0.3, 3, 9, and 30 MW). The study shows a method for economic optimization of electricity generation using a fuel cell. The CAPEX and operating expenditure (OPEX) as well as the feed cost are used to calculate the discounted cash flow. Then the levelized cost of returned electricity (LCORE) is estimated from the discounted cash flow. This study found the LCORE value was ¢10.2/kWh electricity when a 9 MW electricity generating fuel cell was used. A methane production plant size of 1,500 Nm³/hr, a methane production cost of $11.47/mcf, a storage cost of $1/mcf, and a fuel cell efficiency of 54% were used as a baseline. A sensitivity analysis was performed by varying the storage cost, fuel cell efficiency, and excess electricity cost by ±20%, and fuel cell efficiency was found as the most dominating parameter in terms of the LCORE sensitivity. Therefore, for the best cost-performance, fuel cell manufacturing and efficiency need to be carefully evaluated. This study provides a general guideline for cost performance comparison with LCORE.

• Korean Management Science Review
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• v.23 no.2
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• pp.75-91
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• 2006

The purpose of this paper is to propose a new software development cost estimation method using SVR(Support Vector Regression) SVR, one of machine learning techniques, has been attracting much attention for its theoretic clearness and food performance over other machine learning techniques. This paper may be the first study in which SVR is applied to the field of software cost estimation. To derive the new method, we analyze historical cost data including both well-known overseas and domestic software projects, and define cost drivers affecting software cost. Then, the SVR model is trained using the historical data and its estimation accuracy is compared with that of the linear regression model. Experimental results show that the SVR model produces more accurate prediction than the linear regression model.

• Journal of Korean Society of Transportation
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• v.8 no.1
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• pp.17-24
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• 1990

The first-best pricing rule which achieves economic efficiency is to equate price with marginal cost. Since public transport demand is derived from some other demand, the user cost as well as the producer cost are considered in its pricing. The optimal price is derived from a derivative of the total social cost with respect to demand. In case of the bus, if there is enough capacity for demand increase, the optimal price is determined by the marginal producer cost resulting from bus sped decrease and by the marginal user cost resulting from journey time increase. Both are caused by boarding and fare collecting time of an additional passenger. Because of the budget constraints, the marginal cost pricing cannot be applied in practice. Then price discrimination as the second-best pricing is introduced. The Ramsey pricing, to charge different prices for different demand elasticities, and nonuniform prices such as travelcards can be applied. However, there is practical difficulty in implementing these prices because of great informational requirements, the costs of administration and the ease to users.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.574-580
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• 2005

Recently, the number of bridges and tunnels in railway is increasing due to the super high-speedy of train. Also, because of successively accidents of civil structures such as bridges and dams, the importance of maintenance become influential. The purpose of this study is to show the probabilistic life cycle cost analysis technique(PLCC) of the railroad bridge as pubic-infrastructures, and reasonably to indicate the economy in life cycle cost(LCC) through a case study. Rationally for life cycle cost analysis, the data gathered through many materials considered the uncertainty such as covariance. As a result, it is indicated that prestressed concrete bridge is pretty more cost-effective during life-cycle than preflex as well as steel box bridge. In future, if the construction of database and maintenance materials for railroad infrastructure is actualized, the life cycle cost analysis for railroad can be conducted easily and practically.

• Journal of Communications and Networks
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• v.11 no.5
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• pp.500-508
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• 2009

We have designed an algorithm for a problem in multicast communication. The problem is to construct a multicast tree while minimizing its cost, which is known to be NP-complete. Our algorithm, which employs new concepts defined as potential cost and spanning cost, generates a multicast tree more efficiently than the well-known heuristic called Takahashi and Matsuyama (TM) [1] in terms of tree cost. The time complexity of our algorithm is O($kn^2$) for an n-node network with k members in the multicast group and is comparable to the TM. Our empirical performance evaluation comparing the proposed algorithm with TM shows that the enhancement is up to 1.25%~4.23% for each best case.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.971-976
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• 2004

The management of railroad structures is more difficult and complicate because there are many structures such as rail, bridge, tunnel, station, and so on. Therefore, LCC(Life Cycle Cost) analysis of railroad structures as public infrastructure must contain a maintenance cost as well as an initial cost in order to make a more effective management during the life cycle on the design phase. This paper presents a cost classification scheme considering user costs such as value of delayed time of passenger and freight. Also, in this study it is developed a probabilistic life cycle cost(PLCC) analysis model of railroad structures taking into account uncertainties and variations of input variables in order to analyze LCC. It may be stated that the model proposed in this study can greatly contribute to the making optimal decision, the estimate of the maintenance cost and the allocate of budget in the project of railroad structures.

• IE interfaces
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• v.8 no.1
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• pp.31-43
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• 1995

This study is intended to develop a technology cost model (TCM) which treats technology costs appropriately under present advanced manufacturing technology environment. TCM is composed of two elements : cost classification system and cost allocation model. It is proposed to include technology-related department expenses as well as technology investment in the categories of technology costs. For the cost allocation, technology activities are divided into four homogeneous groups. Costs are accumulated into one of the four cost pools and allocated to the cost object using the pool's unique allocation base. It is also proposed to use the capital recovery costs including interest expense rather than the depreciation costs for an invested capital. A case study is performed to verify the applicability of the developed model.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.354-360
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• 2009

The demands for large-scale construction projects such as Mega-projects are largely increasing due to the rapid growth of increasing populations as well as the need to replace existing buildings and infrastructure. Increasing costs of materials, supplies, and labors require the first cost estimates at the preliminary planning stage to be as accurate as possible. This paper presents the results obtained from the survey on evaluating nine critical success factors that influence the accurate first cost estimates for large-scale projects from practical experiences. It then examines the current cost structures of construction companies for large-scale projects, followed by the causes for cost and schedule overrun. Twenty completed surveys were collected and the Analytic Hierarchy Process was applied to analyze the data. The results indicate that technology issues, the contract type, and social and environmental impacts are the significant leading factors for accurate first cost estimates of large-scale construction projects.