• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.409-418
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• 2011

An aims of this study is to examine substitute or complementary among types of special interest tourism and a causal relationship between total individual tourism demand and each types. Of 500 surveyed respondents in Seoul, 348 was valid to analyse. As statistical analysis method, correlation analysis was utilized for substitute or complementary and Econometrics models were applied for causal relationship. The results of this study demonstrate that agro tourism and ocean tourism lie on substitute which means competitive. Also, ocean tourism has had more impacted on total individual tourism demand than any other types of special interest tourism.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.373-378
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• 2005

The diagrammatic language for pathways is widely used for representing systems knowledge as a network of causal relations. Biologists infer and hypothesize with pathways to design experiments and verify models, and to identify potential drug targets. Although there have been many approaches to formalize pathways to simulate a system, reasoning with incomplete and high level knowledge has not been possible. We present a qualitative formalization of a pathway language with incomplete causal descriptions and its translation into propositional temporal logic to automate the reasoning process. Such automation accelerates the identification of drug targets in pathways.

• Knowledge Management Research
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• v.9 no.4
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• pp.35-49
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• 2008

The purpose of the study is to develop and validate an instructional design model from the perspective of the knowledge creation. To serve the purpose, the researcher conducted 1) literature review to find causal relationship model among knowledge creation factors and to propose a hypothetical instructional design model, 2) data analysis with 50 senior level e-Learning instructional designers, and 3) testing the fitness of the proposed model and relevant causal-relational hypotheses. Results indicate; 1) the proposed model fit to the empirical evidence, 2) 6 hypotheses among 11 were validated. A typical instructional designer's personal competency was evidenced as the most powerful independent variable that predicted knowledge acquisition, knowledge sharing, and the application of the instructional models. However, the expected effect of instructional design models toward other dependent variable was not be found. In addition, further suggestions for the future research are addressed.

• Journal of the Korean Society for information Management
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• v.8 no.2
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• pp.32-73
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• 1991

The purpose of this study is to find important personal characteristics that affect search process and outcome, and to formulate causal models about searching behavior, by examining the channels and the magnitude of the factors identified. The study was designed to conduct a quasi-experiment with 67 student subjects. A total of 29 elements concerned with aptitude, personality, formal education, effectiveness of online training, search process, and search outcome are measured and reduced to 9 variables. 12 hypotheses were tested statistically and path analysis was done to investigate causal relationship among variables. Finally 5 models were formulated.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.65-86
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• 2000

The estimates from an EM when it is applied to a large causal model of 10 or more categorical variables are often subject to the initial values for the estimates. This phenomenon becomes more serious as the model structure becomes more serious as the model structure becomes more complicated involving more variables. In this regard Wu(1983) recommends among others that EMs are implemented several times with different sets of initial values to obtain more appropriate estimates. in this paper a new approach for initial values is proposed. The main idea is that we use initials that are calibrated to data. A simulation result strongly indicates that the calibrated initials give rise to the estimates that are far closer to the true values than the initials that are not calibrated.

• Korean System Dynamics Review
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• v.9 no.1
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• pp.33-56
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• 2008

With emphasis on the importance of systems thinking for the establishment of learning organization, Senge in his famous book "The Fifth Discipline", explains in depth four disciplines such as personal mastery, mental models, shared vision, team learning, which are all geared up to the implementation of learning organization. However, two critical pitfalls are found: First, a holistic picture is absent in his presentation of learning organization, which just seems like a puzzle with linking pieces missing between disciplines. Secondly, as is often the case too much details are discussed in expense of insights on each discipline. This paper thus attempts to draw core metaphysical insights underlying Senge's learning organization disciplines by reinterpreting them from oriental perspectives; and to identify mechanisms depicting how they are working together as a whole, which is enabled by exploiting causal loop diagrams as a tool of systems thinking. In addition some thoughts on the implications of systems thinking on each of the learning organization disciplines.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.129-139
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• 2023

Forecasting volatility is essential to avoiding the risk caused by the uncertainties of an financial asset. Complicated financial volatility features such as ambiguity between non-stationarity and stationarity, asymmetry, long-memory, sudden fairly large values like outliers bring great challenges to volatility forecasts. In order to address such complicated features implicity, we consider machine leaning models such as LSTM (1997) and GRU (2014), which are known to be suitable for existing time series forecasting. However, there are the problems of vanishing gradients, of enormous amount of computation, and of a huge memory. To solve these problems, a causal temporal convolutional network (TCN) model, an advanced form of 1D CNN, is also applied. It is confirmed that the overall forecasting power of TCN model is higher than that of the RNN models in forecasting VIX, VXD, and VXN, the daily volatility indices of S&P 500, DJIA, Nasdaq, respectively.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.295-300
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• 1998

Recently graphical modelling is being studied as a useful process analysis tool for exploratory causal analysis. Graphical modelling is a presentation method that uses graphs to describe statistical models of the structures of multivariate data. This paper describes an application of this graphical modeling with two cases from the automotive parts industry. One case is the unbalance problem of the pulley, an automotive generator part. There is multivariate data of the product from each of the processes which are connected in the series. By means of exploratory causal analysis between the variables using graphical modeling, the key processes which causes the variation of the final characteristics and their mechanism of the causal relationship have become clear. Another case is, also, the unbalanced problem of automotive starter parts which consists of many parts and is manufactured by complex machinery and assembling process. By means of the similar technique, the key processes are obtained easily and the results are reasonable from technical knowledge.

• Korean System Dynamics Review
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• v.7 no.1
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• pp.91-118
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• 2006

The purpose of this study is to find what factors are directly related to the delay of public projects, usually going beyond the planned deadline and budget. From a series of System Dynamics simulation works applied to the Cheongju Cremation Project, the research finds that the negative externalities originated from the adjacent location of the LULU(locally unwanted land use) facilities have exerted significant influence on dynamic perceptions of key stakeholders, typically resulting in project delay. As shown repeated experiments, the proposed negotiation-based models would produce relatively higher planning performance level than the typical approaches hinged on the administrative-expediency tactics. Even though the former may require more human and material resources in the very beginning stage, as they have to deal with diverse grievances raised by major stake-holders, most of them would bound for strengthening reinforcing loops within the complex structure. These results also imply that negotiation or consensus-building approaches would enhance mutual agreement among stake-holders, upgrading the overall quality of project management.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.533-542
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• 2020

This study estimates the nature of the relationship of entrepreneurship and business confidence on youth unemployment in the Philippines over the 2001-2017 period. The paper employed a range of cointegrating regression models, namely, autoregressive distributed lag (ARDL) bounds testing approach, Johansen-Juselius (JJ) and Engle-Granger (EG) cointegration models, dynamic OLS, fully modified OLS, and canonical cointegrating regression (CCR) estimation techniques. The Granger causality based on error correction model (ECM) was also performed to determine the causal link of entrepreneurship and business confidence on youth unemployment. The ARDL bounds testing approach, Johansen-Juselius (JJ) and Engle-Granger (EG) cointegration models confirmed the existence of long-run equilibrium relationship of entrepreneurship and business confidence on youth unemployment. The long-run coefficients from JJ and dynamic OLS show significant long-run and positive relationship of entrepreneurship and business confidence on youth unemployment. While results of the long-run coefficients from fully modified OLS and canonical cointegrating regression (CCR) found that only entrepreneurship has significant and positive relationship with youth unemployment in the long-run. The Granger causality based on error correction model (ECM) estimates show evidence of long-run causal relationship of entrepreneurship and business confidence on youth unemployment. In the short-run, increases in entrepreneurship and business confidence causes youth unemployment to decrease.