• International Commerce and Information Review
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• v.19 no.1
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• pp.235-256
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• 2017

This study is to analyse how trust and asset specificity among partner firms affect on performance of international joint venture(IJV). Especially, the analysis was mainly based on a quadratic model. While it assumes that the previous studies was based on linear model in the relationship between trust, asset specificity and the performance, this study proceeds a empirical analysis by setting up a hypothesis; it would be quadratic relationship between trust, asset specificity and performance which are based on social capital theory and transaction cost theory. The survey was held with 74 manufactures who were established as an IJV by Korean and foreign firms together. In the result of the empirical analysis, trust shows an inverted U-shaped relationship with IJV performance. Also, asset specificity shows the U-shaped relationship with IJV performance. The results suggest that it needs to control and maintain the trust level among the partners in order not to lose an appropriate control caused by too much trust. In order to minimize the cost generated by asset specificity and to transform it into positive impact, it needs a control and the operation of monitoring system on the opportunistic action of the partners. Furthermore, it needs to keep organizational flexibility and innovativeness to continuously develop new capabilities.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.4 no.4
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• pp.208-218
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• 1992

Analytic solutions for the gradient of surface elevation and vertical profiles of velocity driven by the wind stress in the one-dimensional rectangular basin were obtained under the assumption of steady-state. The approach treats the bottom frictional stress $\tau$$_{b}$ as known and includes vertically varying eddy viscosity $textsc{k}$$_{M}$, which is constant, linear and quadratic of water depth. When the $\tau$$_{b}$ is param-terized with surface stress, depth averaged velocity and bottom velocity, the result shows the relation of the no-slip bottom velocity condition and the bottom frictional stress $\tau$$_{b}$. The results of a mode splitted, (x-$\sigma$) coordinate, numerical model were compared with the derived analytic solutions. The comparison was made for the case such that $textsc{k}$$_{M}$ is the constant, linear and quadratic function of water depth. In the case of constant $textsc{k}$$_{M}$, the gradient of surface elevation and vertical profiles of velocity are discussed for a uniform depth, a mild slope and a relatively steep slope. When $textsc{k}$$_{M}$ is a linear and quadratic function of water depth, the vertical structures of velocities are discussed for various $\tau$$_{b}$. The result of the comparison shows that the vertical structure of velocities depends not only on the value of $textsc{k}$$_{M}$ but also on the profile of $textsc{k}$$_{M}$ and bottom stress $\tau$$_{b}$. Model results were in a good agreement with the analytic solutions considered in this study.his study.y.his study.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.99-111
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• 2012

The log-density ratio of the conditional densities of the predictors given the response variable provides useful information for variable selection in the logistic regression model. In this paper, we consider the predictors that are needed and how they should be included in the model. If the conditional distributions are skewed, the distributions can be considered as gamma distributions. Under this assumption, linear and log terms are generally included in the model. The log-odds graph is a very useful graphical tool in this study. A graphical study is presented which shows that if the conditional distributions of x|y for the two groups overlap significantly, we need both the linear and quadratic terms. On the contrary, if they are well separated, only the linear or log term is needed in the model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.749-754
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• 2011

It is common that basic unit and model of fuel consumption have been used to evaluate effectiveness analysis of transportation infrastructure investment programs. However they could not reflect vehicle characteristics such as loading capacity and types of heavy vehicles. For these reasons, this study reviews convention fuel consumption model which is widely used and conducts a field experiment for 5 classes of heavy vehicles. To develop the fuel consumption quadratic model the field data are used and we develop each model by classes, and then compare with convention fuel consumption model. As a result, between convention and suggested model, there are considerable differences, which have a similar pattern between an 11-ton cargo of convention model and a 25-ton cargo type dump truck of the suggested model. Likewise we identify that there is an approximately 26% gap between convention model result and the result which is calculated a weighted average by registered number of heavy vehicles based on 5 types of fuel consumption model suggested in this study. This result implies that convention fuel assumption model has a realistic limitation.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.267-280
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• 2007

Various single-valued design optimality criteria such as D-, G-, and V-optimality are used often in constructing optimal experimental designs for mixture experiments in a constrained region R where lower and upper bound constraints are imposed on the ingredients proportions. Even though they are optimal in the strict sense of particular optimality criterion used, it is known that their performance is unsatisfactory with respect to the prediction capability over a constrained region. (Vining et at., 1993; Khuri et at., 1999) We assume the quadratic polynomial model as the mixture response surface model and are interested in finding efficient designs in the constrained design space for a mixture. In this paper, we make an expanded list of candidate design points by adding interior points to the extreme vertices, edge midpoints, constrained face centroids and the overall centroid. Then, we want to propose a robust design with respect to D-optimality, G-optimality, V-optimality and distance-based U-optimality. Comparing scaled prediction variance quantile plots (SPVQP) of robust designs with that of recommended designs in Khuri et al. (1999) and Vining et al. (1993) in the well-known examples of a four-component fertilizer experiment as well as McLean and Anderson's Railroad Flare Experiment, robust designs turned out to be superior to those recommended designs.

• Journal of Science Education
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• v.34 no.1
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• pp.1-11
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• 2010

This study analyzes the factors influencing academic achievement on mathematic and scientific subject and its change in Korean youth by using a sample from KYPS(Korea Youth Panel Survey) data. The results are as follows: First, academic achievement on mathematic and scientific subject of Korean youth shows quadratic curve that their interrelationship between intercept and slope of academic achievement are negative which is statistically significant. Second, analysis of Latent Growth Models shows that parents, teacher, peer group, self esteem, income of family, high school tracks are found to be a statistically significant factor on mathematic. And scientific subject is affected by parents, teacher, peer group, self esteem, income of family, high school tracks. Also, Interesting finding is that father's job is not significant to dependent variables. These findings show that academic achievement on mathematic and scientific subject of the Korean youth are the quadratic curve and influenced by parents, teacher, peer group, self esteem, income of family, high school tracks. To improve youth's mathematic and scientific, Korea educational fields and educators should have policy to care youth's relationship with parents, teachers and self esteem.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.13-25
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• 2004

In the online shopping environment, consumers suffer from the process of selecting an optimal supplier. Although comparison shopping agent-based web sites and consumers' online community sites support the selection process, they have limitations when considering diverse and dynamic purchase conditions as a whole, which is the cause of additional consumer effort for optimal supplier selection. This study provides a decision support model with a sensitivity analysis for selecting an optimal supplier considering purchase conditions as a whole. It screens suppliers with filtering factors and provides optimal suppliers through a sensitivity analysis from a Quadratic Programming model. We implemented a prototype system and showed that it could be an effective decision support system for selecting the optimal supplier in the online shopping environment.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.569-578
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• 2020

By estimating conditional quantile functions of the response, quantile regression (QR) can provide comprehensive information of the relationship between the response and the predictors. In addition, kernel quantile regression (KQR) estimates a nonlinear conditional quantile function in reproducing kernel Hilbert spaces generated by a positive definite kernel function. However, it is infeasible to use the KQR in analysing a massive data due to the limitations of computer primary memory. We propose a divide and conquer based KQR (DC-KQR) method to overcome such a limitation. The proposed DC-KQR divides the entire data into a few subsets, then applies the KQR onto each subsets and derives a final estimator by aggregating all results from subsets. Simulation studies are presented to demonstrate the satisfactory performance of the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.287-296
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• 2011

Thirty six female students participated in the experiment of the fat mass weight loss. they kept diary for foods they ate every day, took a picture of the foods, transmitted the picture to the experimenter by the camera phone, and consulted him about fat mass loss once a week for 8 weeks period. Fat mass weight and its related factors of the students had been measured repeatedly every week during 8 weeks, The repeated measurement data were used for applying various random coefficient models. And hence optimal random coefficient model was selected. From the optimal model, the baseline, body mass index, diastolic blood pressure, total cholesterol and time of the fixed factors were very significant. The fixed quadratic time effect existed. The variance components corresponding to the subject effect, linear time effect of the random coefficients were all positive. Thus random coefficients up to the linear terms were considered as the optimal model. The treatment effect reduced the weight loss to an average of 2.1kg at the end of the period.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.2
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• pp.69-77
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• 1987

A finite element method has been developed to study the material nonlinear analysis of reinforced concrte structures. Concrete behavior under the biaxial state of stress is represented by a nonlinear constitutive relationship which incorporates tensile cracking, tensile stiffening effect between cracks and the strain-softening phenomenon beyond the maximum compressive strength. The concrete model used is based upon nonlinear elasticity by assuming concrete to be an orthotropic material and modeled as equivalent uniaxial stress-strain constitutive relationship using equivalent uniaxial strain. The streel reinforcement is assumed to be in a uniaxial stress state and is modeled as a bilinear, elasto-plastic material with strain hardening approximating the Bauschinger effect. In plane stress state, R.C. beams is modeled as a quadratic element that has two degrees of freedom in each node. And this results of finite element analysis are compared with the experimential results of midspan deflection, stresses and strains.