• Journal of Information Technology Services
• /
• v.12 no.4
• /
• pp.399-422
• /
• 2013

The aim of this study is to find the model that best explains members' continued use intention in virtual communities by comparing technical and social perspectives applied in IS context. With the eight major variables identified from prior studies, four alternative models were formulated:1) A base model from Information Systems (IS) continuance perspective, 2) IS continuance model with technology-acceptance perspective, 3) IS continuance model with social-capital perspective, and 4) IS continuance model with socio-technical combined perspective. The adequacies of these four models with different perspective highlighted were tested using survey data collected from virtual community users in Korea. The findings indicated that the IS continuance model and social-capital perspective is the most efficient model that best explains the members' continued use intention in virtual communities.

• The Journal of Society for e-Business Studies
• /
• v.1 no.2
• /
• pp.77-92
• /
• 1996

In recent years, the manufacturing industry begins to demand the PDM which integarates design and manufacturing information concurrently to reduce the time-to-market of new products. However, current commercialized PDM tools have drawbacks in representing by relational data modeling a variety of data types such as CAD files, images, audio, long text, etc. For this reason, object-oriented approaches are suggested as an alternative. In this paper, using one of object-oriented approaches, Rumbaugh's OMT(Object-Modeling Technique), we propose a data model of drawing information management systems essential for PDM. The scope of the model is limited to the information management for drawings, parts, and product structures. Static, dynamic and functional models are suggested in detail. In the models, the drawing status is classified into on-progress, approved, disposed, and released. Also, parts are classified into products, assemblies, and components.

• Food Science and Biotechnology
• /
• v.17 no.5
• /
• pp.1052-1059
• /
• 2008

Sequential Sensitivity Analysis (SSA) and conditional stimulus model have been developed to describe sequence effects in difference tests and proposed to generate prediction of differences in sensitivity between various test protocols and to assist the appropriate selection of difference test. Yet, such models did not furnish a complete explanation of the relative sensitivity in 4 different versions of 3-alternative forced choice (AFC) tests where various interstimulus rinses were introduced. In the present study, the vector of the contrasts between various conditional stimuli were measured using same-different and 2-AFC and a new 16-distribution conditional stimulus model was developed by refining Lee and O'Mahony's contrast model. This new model gave superior predictions than previous models.

• Communications for Statistical Applications and Methods
• /
• v.24 no.5
• /
• pp.421-441
• /
• 2017

In this survey, estimation methods for structural vector autoregressive models are presented in a systematic way. Both frequentist and Bayesian methods are considered. Depending on the model setup and type of restrictions, least squares estimation, instrumental variables estimation, method-of-moments estimation and generalized method-of-moments are considered. The methods are presented in a unified framework that enables a practitioner to find the most suitable estimation method for a given model setup and set of restrictions. It is emphasized that specifying the identifying restrictions such that they are linear restrictions on the structural parameters is helpful. Examples are provided to illustrate alternative model setups, types of restrictions and the most suitable corresponding estimation methods.

• The Korean Journal of Applied Statistics
• /
• v.33 no.4
• /
• pp.467-482
• /
• 2020

We investigate a monitoring procedure for the early detection of parameter changes in location-scale time series models. We introduce a detector for monitoring procedure based on modified residual cumulative sum (CUSUM). The asymptotic properties of the monitoring procedure are established under the null and alternative hypotheses. Simulation results and data analysis are also provided for illustration.

• Korean Management Science Review
• /
• v.12 no.2
• /
• pp.105-127
• /
• 1995

This paper solves different machine-part group formation (MPGF) problems using genetic algorithms to demonstrate that it can be a new robust alternative to the conventional heuristic approaches for optimization problems. We first give an overview of genetic algorithms: Its principle, various considerations required for its implementation, and the method for setting up parameter values are explained. Then, we describe the MPGF problem which are critical to the successful operation of cellular manufacturing or flexible manufacturing systems. We concentrate on three models of the MPGF problems whose forms of the objective function and/or constraints are quite different from each other. Finally, numerical examples of each of the models descibed above are solved by using genetic algorithms. The result shows that the solutions derived by genetic algorithms are comparable to those obtained through problem-specific heuristic methods.

• Computers and Concrete
• /
• v.17 no.4
• /
• pp.523-539
• /
• 2016

Alkali-activated binder (AAB) is increasingly being considered as an eco-friendly and sustainable alternative to portland cement (PC). The present study evaluates 30 different AAB mixtures containing fly ash and/or slag activated by sodium hydroxide and sodium silicate by correlating their properties from micro to specimen level using regression. A model is developed to predict compressive strength of AAB as a function of volume fractions of microstructural phases (physicochemical properties) and ultrasonic pulse velocity (elastic properties and density). The predicted models are ranked and then compared with the experimental data. The correlations were found to be quite reasonable (R2 = 0.89) for all the mixtures tested and can be used to estimate the compressive strengths for similar AAB mixtures.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1995.09a
• /
• pp.334-343
• /
• 1995

In recent years, neural networks have been developed as an alternative to traditional statistical techniques. In this study, a neural network model was compared to traditional forecasting models in terms of their capabilities to forecast passenger traffic for flights between U.S. and Korea. The results show that the forecasting ability of the neural networks was superior to the traditional models. In terms of accuracy, the performance of the neural networks was quite encouraging. Using mean absolute deviation, the neural network performed best. The new technique is easy to learn and apply with commercial neural network software. Therefore, airline decision makers should benefit from using neural networks in forecasting passenger loads.

• Knowledge Management Research
• /
• v.13 no.3
• /
• pp.55-77
• /
• 2012

Selecting promising technology is becoming more and more difficult due to the increased number and complexity. In this study, we propose hybrid AHP/DEA-AR method and hybrid AHP/DEA-AR-G method to evaluate efficiency of technology alternatives based on ordinal rating data collected through survey to technology experts in a certain field and select efficient technology alternative as promising technology. The proposed method normalizes rating data and uses AHP to derive weights to improve the credibility of analysis, then in order to avoid basic DEA models' problems, use DEA-AR and DEA-AR-G to evaluate efficiency of technology alternatives. In this study, we applied the proposed methods to clean technology and compared with the basic DEA models. According to the result of the comparison, we can find that the both proposed methods are excellent in confirming most efficient technology, and hybrid AHP/DEA-AR method is much easier to use in the process of technology selection.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.1
• /
• pp.141-150
• /
• 2015

Graphical paradigms for assessing the adequacy of models in logistic regression are discussed. The residual plot has been widely used as a graphical tool for evaluating the adequacy of the model. However, this approach works well only for linear models with constant variance, and the alternative approach, the marginal model plot, has its defects as well. We suggest a Chi-residual plot that overcomes the potential shortcomings of the marginal model plot.