• Nuclear Engineering and Technology
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• v.47 no.3
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• pp.306-314
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• 2015

This paper examines the difference in the value of the nuclear fuel cycle cost calculated by the deterministic and probabilistic methods on the basis of an equilibrium model. Calculating using the deterministic method, the direct disposal cost and Pyro-SFR (sodium-cooled fast reactor) nuclear fuel cycle cost, including the reactor cost, were found to be 66.41 mills/kWh and 77.82 mills/kWh, respectively (1 mill = one thousand of a dollar, i.e., $10^{-3}$ $). This is because the cost of SFR is considerably expensive. Calculating again using the probabilistic method, however, the direct disposal cost and Pyro-SFR nuclear fuel cycle cost, excluding the reactor cost, were found be 7.47 mills/kWh and 6.40 mills/kWh, respectively, on the basis of the most likely value. This is because the nuclear fuel cycle cost is significantly affected by the standard deviation and the mean of the unit cost that includes uncertainty. Thus, it is judged that not only the deterministic method, but also the probabilistic method, would also be necessary to evaluate the nuclear fuel cycle cost. By analyzing the sensitivity of the unit cost in each phase of the nuclear fuel cycle, it was found that the uranium unit price is the most influential factor in determining nuclear fuel cycle costs.

• Journal of Distribution Science
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• v.18 no.3
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• pp.53-65
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• 2020

Purpose: This study tests the suitability of a new technology acceptance model for a mobile payment system by checking how statistically significant the change is from the UTAUT (Unified Theory of Acceptance and Use of Technology) and UTAUT 2 models. Research, Data, and Methodology: We surveyed 250 students at Incheon University who are using the mobile payment system. The analysis was conducted on 243 valid questionnaires. The survey was conducted for one month in October 2018. The collected data were analyzed using SPSS and hierarchical regression analysis was applied. Results: Using hierarchical regression analysis, this study confirmed whether the newly added hedonic motivation, switching cost, and perceived risk variables in the UTAUT2 model are good explanatory variables. Mobile payment usage experience was found to have a moderating effect on mobile payment reuse intention. According to the analysis, the UTAUT2 model brought about more influential change than the variables of the UTAUT model. Conclusions: This study found that consumers' psychological factors added in the UTAUT2 model greatly influenced the reuse intention for mobile payment. As an implication of this study, mobile payment providers need to develop strategies that could meet hedonic motivation, switching cost and perceived risk for their customers.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.17-22
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• 2008

Construction project have extremely high risk in the process of construction owing to unexpected event, like as design amendment. As a result, owner have to endure enormous extra-cost to control the risk and continue to the project having more higher uncertainty. Also, if the structure is completed, it is needed that the structure is protected and maintained continuously during life cycle time to satisfying original aim of structure itself. LCC analysis to calculate cost of structure alternatives divides into two stage, one is design_LCC and the other is maintenace_LCC. But two stages all is needed in the transition deterioration model to calculate more reasonable LCC analysis. This paper developed the model using analysis of FMS contents and survey from professional about Prestressed concrete beam girder bridge(PC Beam bridge)in railway. The model is focused in project level of PC beam because any condition state information for element level analysis can not get up. This paper is intended to use the developed model in LCC analysis of PC Beam bridge in railway and constitute the foundation to perform more deep study in the near future.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.767-780
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• 2021

The purpose of this research is to analyze the effect of financial elements (asset growth, liability growth, equity growth, revenue growth, and profit growth) on stock price performance and to analyze the growth of Corporate Social Responsibility (CSR) costs as a moderating effect. The technique analysis used is regression analysis. Samples in this analysis are manufacturing firms listed on the Indonesian Stock Exchange (IDX) for the period 2014-2018. The use of regression models for hypothesis testing must fulfill several applicable assumptions such as Normality Test, Heteroscedasticity Test, Multicollinearity Test, Autocorrelation Test, Model Fit Test, Determination Coefficient Test, and Hypothesis Test. Data analysis used two research models, namely model 1 and model 2. Model 1 is without the moderating variable, and model 2 is with the moderating variable, that is, CSR cost growth. Based on the result of the regression analysis, it can be inferred that the asset, revenue, and profit growth have a positive impact on stock price results. Liabilities and equity growth do not affect stock price performance. Operating expense growth has a significant effect on price performance. CSR cost growth can moderate the effect of growth in financial statement elements on stock price performance but is not significant.

• Journal of Applied Reliability
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• v.6 no.3
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• pp.195-203
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• 2006

This paper deals with cost analysis model in periodic maintenance policy. The repair policy with minimal repair is considered as follow : as the occurrence of failure between minimal repair and periodic interval time, unit is replaced by a new unit before the periodic maintenance time comes. Then total expected cost per unit time is calculated according to time delta t in a view of customer's. The total expected costs are included repair and usage cost : operating, fixed, minimal repair, periodic maintenance and new unit expected cost. Numerical example is shown in which failure time of item has Normal distribution.

• Journal of Applied Reliability
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• v.6 no.2
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• pp.151-161
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• 2006

This article is concerned with cost analysis model in periodic maintenance policy. The repair policy is differently applied according as unit importance during an item being used and unit restoration during an item being failed. So in this paper the repair policy with minimal repair is considered as follow : as the occurrence of failure between minimal repair and periodic interval time, unit is replaced by a spare unit until the periodic maintenance time arrived. Then total expected cost per unit time is calculated according to scale parameter of failure distribution in a view of customer's. The total expected costs are included repair and usage cost : operating, fixed, minimal repair, periodic maintenance and spare unit cost. Numerical example is shown in which failure time of item has Erlang distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.241-247
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• 1997

This paper is concerned with cost analysis model in free-replacement policy. The free-replacement policy with minimal repair is considered as follows; in a manufacturer's view point operating unit is periodically replaced, if a failure occurs between minimal repair and periodic maintenance time, unit is remained in a failure condition. Also unit undergoes minimal repair at failures in minimal-repair interval. Then total expected cost is calculated according to the parameter of failure distribution in a view of consumer's. The expected costs are included repair cost and usage cost: operating, fixed, minimal repair and loss cost. Numerical example is shown in which failure time of item has weibull distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.287-295
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• 1995

This paper is concerned with cost analysis model in periodic maintenance policy. Generally periodic maintenance policy in which item is repaired periodic interval times. And in the article minimal repair is considered. Mimimal repair means that if a unit fails, unit is instantaneously restored to same hazard rate curve as before failure. In the paper periodic maintenance policy with minimal repair is as follows; Operating unit is periodically replaced in periodic maintenance time, if a failure occurs between minimal repair and periodic maintenance time, unit is replaced by a new item until tile periodic maintenance time comes. Also unit undergoes minimal repair at failures in minimal-repair-for-failure interval. Then total expected cost per unit time is calculated according to scale parameter of failure distribution. Maintenance cost factors are included operating, fixed, minimal repair, periodic maintenance and new item replacement cost. Numerical example is shown in which failure time of system has weibull distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.89-98
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• 1996

This paper is concerned with cost analysis model in free -replacement policy under the periodic maintenance policy The free-replacement policy with minimal repairable item is considered as follows; in a manufacturer's view point operating unit is periodically replaced, if a failure occurs between minimal repair and periodic maintenance time, unit is remained in a failure condition. Also unit undergoes minimal repair at failures in minimal-repair interval. Then total expected cost per unit time is calculated according to maintenance period Tin a viewpoint of consumer's. The expected costs are included repair cost and usage cost: operating, fixed, minimal repair and loss cost. Numerical example is shown in which failure time of item has beta distribution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.193-200
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• 2022

In this study, the finite-failure NHPP software reliability model was applied to the software development model based on the Weibull lifetime distribution (Goel-Okumoto, Rayleigh, Type-2 Gumbe), which is widely used in the software reliability field, and then the cost attributes were compared and evaluated. For this study, failure time data detected during normal operation of the software system were collected and used, the most-likelihood estimation (MLE) method was applied to the parameter estimation of the proposed model, and the calculation of the nonlinear equation was solved using the binary method. As a result, first, in the software development model, when the cost of testing per unit time and the cost of removing a single defect increased, the cost increased but the release time did not change, and when the cost of repairing failures detected during normal system operation increased, the cost increased and the release time was also delayed. Second, as a result of comprehensive comparative analysis of the proposed models, it was found that the Type-2 Gumble model was the most efficient model because the development cost was lower and the release time point was relatively faster than the Rayleigh model and the Goel-Okumoto basic model. Third, through this study, the development cost properties of the Weibull distribution model were newly evaluated, and the analyzed data is expected to be utilized as design data that enables software developers to explore the attributes of development cost and release time.