• The Journal of Information Systems
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• v.21 no.1
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• pp.1-17
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• 2012

Common Method Bias(CMB) may cause the potential inflation of correlations between measures assessed via the same method. The problem of CMB has been well known in behavioral sciences because the survey method with self-reporting is vulnerable to CMB. Thus, the discussion on CMB is still ongoing in the MIS research in US. However, in Korea, the MIS research has never paid attention on the CMB problem. The purpose of this study is to examine the CMB problem in the Korean MIS research. To evaluate the effect of CMB, empirical studies on Technology Acceptance Model(TAM) are selected because (1) TAM is one of the MIS research areas studied intensively, (2) TAM is a theoretical model well supported by the existing empirical studies so that the result of this study would have a great ripple effect when the CMB problem turned out to be serious, (3) CMB is domain-specific. 47 TAM samples (out of 45 studies) from three Korean Journals were selected and the relevant data were collected such as correlation matrixes and the measures of the dependent variable. To find and evaluate the size of CMB, two analytic methods (Marker-Variable Technique and Method-Method Pair Technique) are employed. The result showed that there exists CMB in the Korean studies but the problem is not so serious to distort the empirical testing, compared with that of US studies. However, considering that CMB can contaminate the testing results, Korean MIS researchers should explicitly deal with the problem in designing empirical studies and collecting data.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.353-365
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• 2004

In this paper, we define the weighted U-empirical process for simple linear model and show the weak convergence to a Gaussian process under some conditions. Then we illustrate the usage of our result with examples. In the appendix, we derive the variance of the weighted U-empirical distribution function.

• Geomechanics and Engineering
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• v.20 no.2
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• pp.121-129
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• 2020

In the design of geotechnical structures, engineers choose either peak or critical state friction angles. Unfortunately, this selection is based on engineer's preference for economy or safety and lacks the assessment of the expected level of deformation. To fill this gap in the design process, this study proposes a strain based empirical method. Proposed method is founded on the experimentally supported assumption that higher dilatancy angles result in more brittle soil response. Using numerous triaxial test data on ten different soils, an empirical design chart is developed that allows the estimation of shear strain at failure based on soil's peak dilatancy angle and mean grain diameter. Developed empirical chart is verified by conducting a small scale retaining wall physical model test. Finally, a design methodology is proposed that makes the selection of design friction angle in structured way possible based on the serviceability limits of the proposed structure.

• Journal of Korean Society for Quality Management
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• v.37 no.4
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• pp.31-42
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• 2009

Various studies have been undertaken in order to effectively understand customer requirements. Kano proposed a dualistic approach, physical fulfillment and customer satisfaction, to differentiate Attractive, Must-be, One-dimensional quality attributes. As there were a few limitations on the Kano's method, researchers have proposed improved methods. However, there have been few empirical evidences that the improved methods are superior to the original Kano's method for identifying relevant quality attributes. The objective of this study is to provide a comparative study on Kano and improved Kanomethods based on empirical analysis of quality attributes on University services. For the analysis of the questionnaire formats, the Kano's original 5 scale questionnaire is more effective than improved methods, direct and 3 scale questionnaire. For the analysis of evaluation methods, the original Kano and Timko's method using the evaluation table are more effective than quantifying methods, Domouchel and Lim's methods.

• Journal of the Korean Statistical Society
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• v.25 no.2
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• pp.205-216
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• 1996

The bootstrap calibration method for empirical likelihood is considered to make a confidence region for the regression coefficients. Asymptotic properties are studied regarding the coverage probability. Small sample simulation results reveal that the bootstrap calibration works quite well.

• Journal of Power System Engineering
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• v.15 no.4
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• pp.11-18
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• 2011

A Shock absorber is one of the most important components in vehicle suspension systems. In general, many repeated analyses are required for the design of a shock absorber to satisfy the suspension characteristics of a specific automobile, like fluid flow analysis and mechanical analysis. The purpose of this study is to develop a fast design tool for shock absorber designers. One of the efficient solutions for this can be an empirical design method considering phenomenological effects from the shock absorber design variables. In order to extract the shock absorber's experimental characteristics, we used Taguchi method. This method showed that which design variables have major effects for the shock absorber's damping characteristics. This empirical design method also showed the direction of the design changes to satisfy the designer's intension.

• Smart Structures and Systems
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• v.11 no.1
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• pp.123-134
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• 2013

Identifying structural modal parameters, especially those modes within high frequency range, from ambient data is still a challenging problem due to various kinds of uncertainty involved in vibration measurements. A procedure applying an ensemble empirical mode decomposition (EEMD) method is proposed for accurate and robust structural modal identification. In the proposed method, the EEMD process is first implemented to decompose the original ambient data to a set of intrinsic mode functions (IMFs), which are zero-mean time series with energy in narrow frequency bands. Subsequently, a Sub-PolyMAX method is performed in narrow frequency bands by using IMFs as primary data for structural modal identification. The merit of the proposed method is that it performs structural identification in narrow frequency bands (take IMFs as primary data), unlike the traditional method in the whole frequency space (take original measurements as primary data), thus it produces more accurate identification results. A numerical example and a multiple-span continuous steel bridge have been investigated to verify the effectiveness of the proposed method.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.2
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• pp.59-65
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• 2020

The empirical Green's function method is applied to the foreshock and the mainshock of the 2016 Gyeongju earthquake to simulate strong ground motions of the mainshock and scenario earthquake at seismic stations of seven metropolises in South Korea, respectively. To identify the applicability of the method in advance, the mainshock is simulated, assuming the foreshock as the empirical Green's function. As a result of the simulation, the overall shape, the amplitude of PGA, and the duration and response spectra of the simulated seismic waveforms are similar with those of the observed seismic waveforms. Based on this result, a scenario earthquake on the causative fault of Gyeongju earthquake with a moment magnitude 6.5 is simulated, assuming that the mainshock serves as the empirical Green's function. As a result, the amplitude of PGA and the duration of simulated seismic waveforms are significantly increased and extended, and the spectral amplitude of the low frequency band is relatively increased compared with that of the high frequency band. If the empirical Green's function method is applied to several recent well-recorded moderate earthquakes, the simulated seismic waveforms can be used as not only input data for developing ground motion prediction equations, but also input data for creating the design response spectra of major facilities in South Korea.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.253-264
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• 1999

Conditinal weakly convergence of the blockwise bootstrapped empirical process for stationary sequences to the appropriate Gaussian process is reestablished particularly for severely dependent $\alpha$-mixing sequences. Issue of block size is discussed from the point of validity of bootstrap method.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1179-1189
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• 2017

In this study, we propose an alternative method for discriminant analysis using a multivariate empirical distribution function to express multivariate data as a simple one-dimensional statistic. This method turns to be the estimation process of the optimal threshold based on classification accuracy measures and an empirical distribution function of data composed of classes. This can also be visually represented on a two-dimensional plane and discussed with some measures in ROC curves, surfaces, and manifolds. In order to explore the usefulness of this method for discriminant analysis in the study, we conducted comparisons between the proposed method and the existing methods through simulations and illustrative examples. It is found that the proposed method may have better performances for some cases.