• Proceedings of the Korea Association of Information Systems Conference
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• 2005.05a
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• pp.145-160
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• 2005

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.329-347
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• 2017

Early research into category-based feature inference reported various phenomena in human thinking including typicality, diversity, similarity effects, etc. Later research discovered that participants' prior knowledge has an extensive influence on these sorts of reasoning. The current research tested the effects of causal knowledge on feature inference and conducted modeling on the results. Participants performed feature inference for categories consisted of four features where the features were connected either in common cause or common effect structure. The results showed typicality effects along with violations of causal Markov condition in common cause structure and causal discounting in common effect structure. To model the results, it was assumed that participants perform feature inference based on the difference between the probabilities of an exemplar with the target feature and an exemplar without the target feature (that is, $p(E_{F(X)}{\mid}Cat)-p(E_{F({\sim}X)}{\mid}Cat)$). Exemplar probabilities were computed based on causal model theory (Rehder, 2003) and applied to inference for target features. The results showed that the model predicts not only typicality effects but also violations of causal Markov condition and causal discounting observed in participants' data.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.47-75
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• 2010

Two experiments were conducted to explore whether the Or structure works as a default causal model in inferring the causal structure from the contingency data. The contingencies of three unfamiliar variables were used in Experiment 1. Participants inferred the Or structure quite well from the OR data, but incorrectly inferred the Or structure from the And data for about a little less than half of the time, and almost always inferred the Or structure from the chain data. The results suggested that the Or interpretation can be the default causal model. The prevalence of the Or interpretation from the contingency data was reported even when the three variables were familiar ones in Experiment 2. Multinomial modeling performed on the results of the two experiments strongly suggested that the Or interpretation work as a default causal model.

• Knowledge Management Research
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• v.22 no.1
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• pp.1-19
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• 2021

Large-scaled hospital information system projects are often delayed than originally planned. Regarding project management, it is necessary to examine main factors triggering the schedule delay and to analyze the causality of such delay. This study tries to find the delay factors and causal relationship between them based on the case of the hospital information system development project by using the grounded theory method. It turned out that 'unrealistic scheduling' affects overall schedule delays like domino phenomenon, and 'poor analysis of existing systems' leads to poor quality of work analysis while 'poor subsystem integrated interface' triggers poor design quality. This study found out the factors affecting the delay of a project, analyzing cause-and-effect relationships between them in the academic side. From the practical view, it shows a solution to minimize delays in the project schedule for each of SI companies, hospitals and project managers.

• Journal of Korea Technology Innovation Society
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• v.19 no.2
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• pp.324-357
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• 2016

As the transition to the knowledge-based economy has been accelerated in the 21st century, the importance of the service industry has been highlighted. As the proportion of knowledge service industry in the economy and the related employment rate are continuously growing, it is necessary to bring innovation to the industry in order to increase competitiveness. In this study, the innovation types are diversified into product, process, organization, and marketing and the influencing factors have been analyzed with knowledge service firms. The complex causal relationship that is linked to the innovation performance has been analyzed by the structural equation with each innovation types as the intervening variables. The results of this study can be summarized as follows. The innovation capacity of firms in knowledge service industry has very strong positive effects either directly or indirectly on product innovation, process innovation, organizational innovation, marketing innovation, and the revenue and employment of the firm. On the other hand, innovation support policy through government intervention produce negative impact on product innovation and they do not create meaningful impact on the total effect on the revenue nor the employment growth. The innovation should ultimately create effects on the revenue and the employment of the firm. And the government support policies should be carefully designed in consideration of the final destination point of this complex causal structure.

• Asia Marketing Journal
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• v.1 no.4
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• pp.47-75
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• 1999

지식사회, 지식경제의 등장과 더불어 기업의 자원으로서 지식(knowledge)의 중요성이 부각됨에 따라 마케팅 전략의 한 분야로서의 신제품 전략에서도 신제품 개발과정에 있어 기업(혹은 신제품 개발 팀)의 지식과 지식의 활용 능력을 어떻게 확장할 것인가가 중요한 전략적 이슈(issue)가 된다. 신제품 개발 과정에서는 필연적으로 불확실성-시장 불확실성과 기술 불확실성-이 존재하며 불확실성을 해소하기 위하여 정보와 지식의 중요성이 부각되고 기업내의 다양한 조직-특히 R&D, 생산, 마케팅-과의 지식공유·통합과정이 중요시된다. 이에 따라 본 연구는 첫째, 기업이 가지고 있는 지식을 제품으로 구체화하는 과정이 신제품 개발(New Product Development; NPD)과정이며 구체화 과정에서 개발의 효율성과 효과성을 어떻게 달성할 것인가에 관한 문제를 다루고자 한다. 둘째, 기존의 신제품 성과 요인으로 제시되고 있는 많은 요인들을 '지식역량(knowledge competence)'의 개념으로 정리하고 이러한 지식 역량과 신제품 경쟁우위 간의 인과적 관계를 살펴봄으로써 신제품 경쟁우위에 어떠한 영향을 미치는가에 대한 분석을 하고자 한다. 셋째 신제품 개발조직의 지식역량을 향상시키기 위한 전략적 방안을 제시하고자 한다. 이론적 배경으로 기업을 지식의 결집체로 인식하고 있는 지식거점관점(knowledge based perspective)과 이러한 지식자원의 활용에 초점을 맞춘 조직학습(organizational learning) 이론 그리고 심리학에서 다루고 있는 분산된 인지이론(distributed cognition theory)을 활용한다.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.155-178
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• 2023

The purpose of this study is to derive factors that affect the acceptance of digital transformation in ports and empirically analyze the impact of these factors on the acceptance of digital transformation through a survey of port workers. Additionally, we test whether acceptance attitude plays a mediating role in the relationship between these factors and digital transformation acceptance. The variables used in this study are as follows. First, knowledge, self-efficacy, and involvement were included as variables related to individual characteristics, relative advantages, complexity, observability were included as variables related to innovation characteristics, and government regulations and competitor pressure were included as variables relate to environmental characteristics, so that a total of eight latent variables were selected. The results of this study are summarized as follows. First, two variables among individual characteristics, self-efficacy and involvement, were able to confirm a positive(+) causal relationship with the attitude of accepting digital transformation, and knowledge initially expected a positive(+) causal relationship with the attitude of accepting digital transformation, but the result was a negative(-) causal relationship, so that the hypothesis was rejected. Second, among the characteristics of innovation, complexity has a negative(-) causal relationship with the attitude of accepting digital transformation, and relative advantages and technological innovation have a positive(+) causal relationship with the attitude of accepting digital transformation. Finally, among the environmental characteristics, government regulations and competitor pressure, confirmed a positive(+) causal relationship with the attitude of accepting digital transformation. In addition, it was found that the attitude of accepting digital transformation had a positive(+) causal relationship with personal acceptance and social acceptance of digital transformation.

• Journal of Intelligence and Information Systems
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• v.2 no.1
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• pp.11-26
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• 1996

본 논문에서는 화학공정의 이상 진단을 위한 지식 기반 조업 지원 시스템의 개발에 관하여 살펴보고자 한다. 조업지원 시스템에서 가장 핵심적인 부분은 공정에 비정상 상황이 발생한 경우 이를 감지하고, 공정에 발생한 증상들을 분석하여 이상의 근본 원인을 찾아내는 작업-이상 진단이다. 이상 진단을 효과적으로 수행하기 위해서는 적절한 데이터의 해석이 매우 중요한데, 기존의 데이터 해석법들은 정상상태에 기반한 방법들을 동적거동을 효과적으로 표현하기에는 어려움이 많다. 본 연구에서는 RBF에 기반한 신경망을 사용하여 동적을 효과적으로 표현할 수 있는 정성적인 데이터 해석 모듈을 구축하였으며, 이 모듈에서는 공정에서 측정된 정략적인 센서값들을 정성적인 정보로 가공하여 이상진단 모듈에 제공한다. 본 연구에서는 효과적인 이상진단을 위하여 기존의 인과관계 그래프 모델(Cause Effect DiGraph)에 기반한 두가지 그래프 모델을 개발하였다. RCED(Reduced Caue Effect Digraph)는 공정의 측정 변수만으로 공정의 인과관계를 표현하는 오프라인으로 구축된 지식베이스 모델이며, PGTT(Pattern Graph Through Time)는 공정에서 발생한 증상간의 인과관계를 실시간으로 나타내는 동적인 모델이다. 이상, 신경망에 기반한 정성적인 데이터 해석 모듈과 이상진단 모듈을 전문가 시스템 도구인 G2를 DEC AlphaStation 상에서 폴리프로필렌 공정에 대한 조업지원전문가 시스템을 구축하고 이를 적용하여보았다.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.249-257
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• 2018

The purpose of this study was to analyze the knowledge and ability levels of middle school students in four areas: conceptual understanding, argument construction, justification schemes, and use of scientific knowledge in a causal explanation for a genetic phenomenon. A group of 162 middle school students who have taken a class titled Genetics and Evolution participated in the study. Each student answered-and justified the answer to-one question pertaining to genetics. Ability levels were rated from level 0 to level 4, with 4 being the top rating. Students were required to choose one of two competing arguments to explain whether green seed pimps and red seed pimps of the same size and shape were the same species or not. Analyzing conceptual understanding: 47% of the respondents provided the correct answer. Analyzing their abilities for constructing an argument: 75% of the students with the correct answer and 42% of the students with the incorrect answer were evaluated to be at ability level 3 or 4 for argument construction. Analyzing the students' justification schemes: "Scientific idea" and "Analogy" were the most frequently used schemes. Analyzing their use of scientific knowledge: of the students who selected the scientific idea justification scheme, 36% used the correct scientific knowledge, but the remainder used inaccurate or nonspecific scientific knowledge. These findings provide implication for encouraging argumentative writing explaining scientific phenomena regarding epistemic practice.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.893-908
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• 2011

This study aims to examine how attendees' motivation of convention & exhibition visitors on their satisfaction, revisit and recommendation intention. It is also another goal of this study to provide strategic materials through making out preventive measures against the convention & exhibition. To accomplish the goals, a field survey was conducted on the visitors of the COEX in Seoul area. The results of this study, based on a positive analysis, could be summarized as follows. First, the knowledge seek, friendly relations, deviation ure and area characteristic turned out to have affirmative effects on convention & exhibition visitors on their satisfaction. Second, the knowledge seek, friendly relations and area characteristic turned out to have affirmative effects on convention & exhibition visitors on their revisit intention. Third, the knowledge seek, friendly relations and deviation ure turned out to have affirmative effects on convention & exhibition visitors on their recommendation intention. Fourth, the satisfaction turned out to have affirmative effects on their revisit and recommendation intention.