• Journal of the Korean Vacuum Society
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• v.8 no.4B
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• pp.541-547
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• 1999

Reactive ion etching process for InP using BCl3/O2/Ar high density inductively coupled plasma was investigated. The experimental design method proposed by the Taguchi was utilized to cover the whole parameter range while maintaining reasonable number of actual experiments. Results showed that the ICP power and the chamber pressure were the two dominant parameters affectsing etch results. It was also observed that the etch rate decreased and the surface roughness improved as the ICP power and the bias voltage increased and as the chamber pressure decreased. The Addition of oxygen to the gas mixture drastically improved surface roughness by suppressing the formation of the surface reaction product. The optimum condition was ICP power 600W, bias voltage -100V, 10% $O_2$, 6mTorr, and $180^{\circ}C$, resulting in about 0.15$\mu\textrm{m}$ etch rate with smooth surfaces and vertical mesa sidewalls Also, the maximum etch rate of abut 4.5 $\mu\textrm{m}$/min was obtained at the condition of ICP power 800W, bias voltage -150V, 15% $O_2$, 8mTorr and $160^{\circ}C$.

• The Journal of Information Systems
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• v.24 no.3
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• pp.75-94
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• 2015

Purpose While new versions of mobile applications could offer users better computing environment, users are not always comfortable with them for various reasons. Considering making update decisions is important task for users, it is crucial for us to understand users' behavior and attitude on app updates. The purpose of this study is to explain why mobile users succumb to both reactance toward the update and satisfaction to the current version, ultimately leading them to feel the regret by employing three theoretical perspectives including regret theory, status quo bias theory and the dual model. Design/methodology/approach Survey data collected from 204 mobile users was used to test the research model using partial least squares analysis. The results have shown that both reactance toward the update and satisfaction to the current version have negative impacts on individuals' decisions to update, which leading to their regret after updating the applications Findings By integrating both status quo bias and regret theory in the model, this study tried to explain why mobile users feel regret in application update settings. More specifically, this study has proposed a novel framework that introduces an individual's update decision on mobile applications.

• The Journal of Information Systems
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• v.27 no.1
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• pp.133-151
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• 2018

Purpose Global fintech industry is proliferating. Although domestic investment in fintech service is also increasing fast, user acceptance of fintech payment service seems slower than expected. Previous fintech literature mainly focuses on overall characteristics and technical aspects of fintech including security issues and explores factors affecting the service adoption. This study aims to examine crucial factors affecting user's resistance intention to fintech payment service adoption. The research model was formulated based on innovation diffusion theory and status quo bias theory and validated empirically. Design/methodology/approach The proposed research model was empirically validated with 149 responses from college students who have used fintech payment service. The component-based SEM was employed for data analysis. Findings The significant findings are as follow. First, compatibility has significant negative effect and complexity, and perceived risk has a positive effect on user resistance. Second, institutional trust does not show a significant effect on user resistance but has an indirect effect through the mediation of trust in service provider. Finally, trust in service provider shows the significant negative effect on user resistance.

• Journal of Distribution Science
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• v.15 no.11
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• pp.49-57
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• 2017

Purpose - In Korea, general super markets have a great impact on the market performance of traditional markets. We propose a modified two stage DEA model for evaluating the performance of traditional markets in Incheon, Korea by identifying the influence of external environmental factors including the presence of general super markets as non-discretionary variables in DEA. Research design, data, and methodology - After obtaining bias-corrected estimates of original DEA efficiency scores using the input and output data of 49 traditional markets, we regress them on several external environmental factors by bootstrap-truncated regression. Results - We obtain bias-corrected efficiency scores from the original DEA efficiency scores by bootstrap and among the five environmental factors, the residential population and the presence of general super markets or SSMs can be considered as the driving forces influencing bias-corrected efficiency scores, positively and negatively, respectively. Conclusions - When DEA efficiency scores tend to be overestimated, we need to use a biased-corrected efficiency score by bootstrap. It is important to note that the efficiency of traditional markets can be largely influenced by external environmental factors such as the presence of general super markets or SSMs that traditional markets can not control. Therefore, it is desirable to consider such environmental factors appropriately for a reasonable performance evaluation.

• Journal of Distribution Science
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• v.20 no.12
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• pp.117-123
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• 2022

Purpose: This study investigates the relationship between earnings forecasts estimated from a cross-sectional earnings forecast model and firm characteristics such as firm size, sales volatility, and earnings volatility. Research design, data and methodology: The association between earnings forecasts and the aforementioned firm characteristics is examined using 214 firm-year observations with analyst following and 848 firm-year observations without analyst following for the period of 2011-2019. I estimate future earnings using a cross-sectional earnings forecast model, and then compare these model-based earnings forecasts with analysts' earnings forecasts in terms of forecast bias and forecast accuracy. The earnings forecast bias and accuracy are regressed on firm size, sales volatility, and earnings volatility. Results: For a sample with analyst following, I find that the model-based earnings forecasts are more accurate as the firm size is larger, whereas the analysts' earnings forecasts are less biased and more accurate as the firm size is larger. However, for a sample without analyst following, I find that the model-based earnings forecasts are more pessimistic and less accurate as firms' past earnings are more volatile. Conclusions: Although model-based earnings forecasts are useful for evaluating firms without analyst following, their accuracy depends on the firms' earnings volatility.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.47 no.3
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• pp.153-174
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• 2021

Dental implants are popular for dental rehabilitation after tooth loss. The goal of this systematic review was to assess bone changes around bone-level and tissue-level implants and the possible causes. Electronic searches of PubMed, Google Scholar, Scopus, and Web of Science, and a hand search limited to English language clinical trials were performed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines up to September 2020. Studies that stated the type of implants used, and that reported bone-level changes after insertion met the inclusion criteria. The risk of bias was also evaluated. A total of 38 studies were included. Eighteen studies only used bone-level implants, 10 utilized tissue-level designs and 10 observed bone-level changes in both types of implants. Based on bias assessments, evaluating the risk of bias was not applicable in most studies. There are vast differences in methodologies, follow-ups, and multifactorial characteristics of bone loss around implants, which makes direct comparison impossible. Therefore, further well-structured studies are needed.

• Journal of the Korean GEO-environmental Society
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• v.16 no.6
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• pp.5-11
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• 2015

Recently the necessity of developing the Load and Resistance Factor Design (LRFD) for shallow foundation has been raised to implement to the domestic design codes related to geotechnical engineering since the limit state design is requested as international technical standard for the foundation of structures. In this study, applicability of LRFD for shallow foundation on weathered soils was investigated and resistance factor for this case was proposed. The quantitative analyses on the uncertainty and resistance bias for shallow foundation on weathered soil ground were performed by collecting the statistical data about domestic case studies for design and construction of shallow foundation. Reliability analyses for shallow foundation were first performed using FDA (First-order Design value Approach) method. Resistance factors were calibrated using the load factors obtained from the specifications of shallow foundations on weathered soil ground. The influence of the load factors developed in this study on the resistance factors were discussed by comparing with the resistance factor obtained from using AASHTO load factors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1C
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• pp.19-29
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• 2008

As a part of study to develop LRFD (Load and Resistance Factor Design) codes for foundation structures in Korea, reliability analyses for driven steel pipe piles are performed and the target reliability indices are selected carefully. The 58 data sets of static load tests and soil property tests conducted in the whole domestic area were collected and analyzed to determine the representative bearing capacities of the piles. The static bearing capacity formula and the Meyerhof method using N values are applied to calculate the expected design bearing capacity of the piles. The resistance bias factors were evaluated for the two static design methods by comparing the representative bearing capacities with the design values. Reliability analysis was performed by two types of advanced methods: First Order Reliability Method (FORM), and Monte Carlo Simulation (MCS) method using resistance bias factor statistics. The static bearing capacity formula exhibited relatively small variation, whereas the Meyerhof method showed relatively high inherent conservatism in the resistance bias factors. Reliability indices for safety factors in the range of 3 to 5 were evaluated respectively as 1.50~2.89 and 1.61~2.72 for both of the static bearing capacity formula and the Meyerhof method. The target reliability indices are selected as 2.0 and 2.33 for group pile case and 2.5 for single pile case, based on the reliability level of the current design practice and considering redundancy of pile group, acceptable risk level, construction quality control, and significance of individual structure.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.101-127
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• 2016

Irrational ordering decisions of supply chain members have been gaining growing importance in the area of supply chain management. Irrational ordering behaviors that deviate from the profit maximizing decisions in the newsvendor settings have observed with human experiments in recent research. These behaviors can be modeled with several typical decision bias elements. This bias in ordering decisions affects the performance of supply chain contracts designed based on the assumption that the supply chain members make optimal decisions, making it necessary to design supply chain contracts by considering the irrationality. The purpose of this research is to derive a method to design the revenue sharing contract that considers human irrationality in ordering decisions. This research considers a simple two-echelon supply chain consisting of one supplier and one retailer, where the supplier is assumed to be perfectly rational while the retailer making newsvendor type ordering decisions displays irrational ordering behaviors. Under this environment, this research analytically models the revenue sharing contract to maximize the total supply chain profit or the supplier's own profits while considering the three decision bias patterns of the retailer, which include the pull-to-center effect, the prospect theory, and the increased subjective sensitivity to the revenue sharing ratio. Irrationality parameters are measured through human experiments based on which and through numerical simulations, we showed that significant improvements in the supply chain performance can be achieved.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.1-14
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• 2003

In this study, we suggest the method of small area estimation based on the Economically Active Population Survey (EAPS) data in producing unemployment statistics for the local self-government areas (LSGAs) within large areas. The small area estimators considered are design-based indirect estimators such as the synthetic and composite estimators. The jackknife mean square error was used as a measure of accuracy of such small area estimators. The total unemployed and jackknife mean square errors of the 10 LSGAs within the large area of ChoongBuk region are derived from the estimation procedure suggested in this study, using EAPS data of December 2000. The reliability of small area estimators was assessed using the relative bias values and relative root mean square errors of these estimators. We find that under the current Korean EAPS system, the composite estimator turns out to be much more stable than other estimators.