• 지식경영연구
• /
• 제11권5호
• /
• pp.1-23
• /
• 2010

In order to provide a better understanding about the phenomenon of KM assimilation, this study attempts to conceptually develop and empirically compare two different models: (1) the first model, which considers the KM process as the flow of knowledge that plays an intervening role between knowledge stocks (i.e., knowledge worker, technical knowledge infrastructure, external knowledge linkage, knowledge strategy, and internal knowledge climate) and the level of KM assimilation; and (2) the second model is a simple direct effect formulation without any distinction between knowledge stock and flow. These two models were then tested and compared using the responses of 187 Korean organizations that had already implemented enterprise-wide KM systems. The findings indicate that the two models are useful in explaining successful KM assimilation. However, the first causal model with the distinction between knowledge stock and flow assesses the effectiveness of KM more accurately than the second model without the distinction. Interestingly, the KM process was shown to be the most critical factor for the proliferation of KM activities across an organization. The findings of this study are expected to serve not only as early groundwork for researchers hoping to understand KM and its effective assimilation in organizations, but should also provide practitioners with guidelines as to how they can enhance their KM assimilation level so as to improve their organizational performance.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 1998년도 추계학술대회 논문집
• /
• pp.228-231
• /
• 1998

Artificial Intelligence literatures have recognized that stock market is a highly unstructured and complex domain so that it is difficult to find knowledge that belongs to that domain. This paper demonstrates that the proposed QCOM can derive global knowledge about stock market on the basis of a set of local knowledge and express it as a digraph representation. In addition, inference mechanism using quantitative causal reasoning can describe the qualitative and quantitative effects of exogenous variables on stock market.

• 한국경영과학회지
• /
• 제17권2호
• /
• pp.145-162
• /
• 1992

This paper proposes two design principles for expert systems to solve a stock market timing (SMART) problems : machine knowledge and fuzzy post-adjustment, Machine knowledge is derived from past SMART instances by using an inductive learning algorithm. A knowledge-based solution, which can be regarded as a prior SMART strategy, is then obtained on the basis of the machine knowledge. Fuzzy post-adjustment (FPA) refers to a Bayesian-like reasoning, allowing the prior SMART strategy to be revised by the fuzzy evaluation of environmental factors that might effect the SMART strategy. A prototype system, named K-SISS2 (Knowledge-based Stock Investment Support System 2), was implemented using the two design principles and tested for solving the SMART problem that is aimed at choosing the best time to buy or sell stocks. The prototype system worked very well in an actual stock investment situation, illustrating basic ideas and techniques underlying the suggested design principles.

• 한국철도학회논문집
• /
• 제13권5호
• /
• pp.528-534
• /
• 2010

신성장이론에서 R&D Stock은 노동과 자본 외에 제3의 생산요소이다. 이 관점에서 R&D Stock은 기존의 자본처럼 비용이 투입되어야만 축적이 가능한 자본의 위치를 차지하게 되며 이것을 지식자본이라고 한다. 이러한 지식자본을 향상시키기 위한 노력이 R&D투자이며 이의 축적이 R&D Stock이다. R&D Stock과 총요소생산 성과의 관계를 추정함으로써 경제성장의 기여도, R&D 투자의 수익률 등을 분석한다. 본 논문에서는 철도 R&D 투자에 대한 R&D Stock을 분석하고 기술수준과 비교 한 결과 R&D Stock이 증가하면 기술수준도 비례적으로 증가되었다. 그리고 GDP에 대한 철도산업의 비중과 전 부문에 대한 철도 R&D Stock 비중을 비교한 결과 철도산업의 비중에 비해 철도 R&D Stock 비중이 상대적으로 작아 지속적인 철도 R&D 투자가 필요함을 알 수 있다.

• 한국경영과학회지
• /
• 제20권1호
• /
• pp.159-177
• /
• 1995

The objective of this paper is to propose a knowledge-based fuzzy post adjustment so that unstructured problems can be solved more realistically by expert systems. Major part of this mechanism forcuses on fuzzily assessing the influence of various external factors and accordingly improving the solutions of unstructured problem being concerned. For this purpose, three kinds of knowledge are used : user knowledge, expert knowledge, and machine knowledge. User knowledge is required for evaluating the external factors as well as operating the expert systems. Machine knowledge is automatically derived from historical instances of a target problem domain by using machine learning techniques, and used as a major knowledge source for inference. Expert knowledge is incorporate dinto fuzzy membership functions for external factors which seem to significantly affect the target problems. We applied this mechanism to a prototyoe expert system whose major objective is to provide expert guidance for stock market timing such as sell, buty, or wait. Experiments showed that our proposed mechanism can improve the solution quality of expert systems operating in turbulent decision-making environments.

• Management Science and Financial Engineering
• /
• 제15권2호
• /
• pp.101-118
• /
• 2009

In quantitative contexts, data mining is widely applied to the prediction of stock prices from financial time-series. However, few studies have examined the potential of data mining for shedding light on the qualitative problem-solving knowledge of experts who make stock price predictions. This paper presents a GA-based data mining approach to characterizing the qualitative knowledge of such experts, based on their observed predictions. This study is the first of its kind in the GA literature. The results indicate that this approach generates rules with higher accuracy and greater coverage than inductive learning methods or neural networks. They also indicate considerable agreement between the GA method and expert problem-solving approaches. Therefore, the proposed method offers a suitable tool for eliciting and representing expert decision rules, and thus constitutes an effective means of predicting the stock price index.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2009년도 춘계학술대회 논문집
• /
• pp.791-794
• /
• 2009

Each nation of the world is intensively propelling the R&D investment to solve the financial crisis and worldwide economic recession occurred from last year. This means the world economic is under economic system based on the knowledge. So, The R&D is continuously propelled for possession of the technology through the R&D stock and which is core in the knowledge based economic system. In this world stream, our government is also increasing the R&D investment and checked the technology level through surveying the R&D stock and corn parison of each industry or world. The R&D investment of the railroad is continued but there is no data of the R&D stock. So, surveying the railroad R&D stock and comparing with korea industry is processed.

• 기술혁신학회지
• /
• 제13권2호
• /
• pp.231-251
• /
• 2010

과학기술 R&D 활동의 대표적 성과인 SCI 논문과 특허의 생산에 영향을 미치는 요인은 연구비, 연구원수, 지식스톡(R&D스톡, 논문스톡, 특허스톡 등), 연구환경, 개방화 정도, 인적자본, GDP 등 다양하다. 일반적인 회귀모형을 이용하여 논문 또는 특허의 생산에 영향을 미치는 요인을 추정하면 생산요인들 간에 다중공선성 문제가 발생하여 추정의 오류가 발생한다. 본 논문에서는 과학기술 지식생산에 영향을 미치는 요인들 간의 다중공선성 문제를 해결하기 위해 주성분 회귀모형을 이용하였다. SCI 논문을 산출로 가정한 과학생산성과와 특허를 산출로 가정한 기술생산성과에 영향을 미치는 요인을 회귀모형과 주성분 회귀모형을 이용하여 3가지 사례를 대상으로 비교 분석하였다. 일반 회귀모형을 이용하여 SCI 논문과 특허의 생산에 영향을 미치는 요인들을 분석한 결과, 요인들간에 다중공선성이 매우 높게 나타났고, 그 결과 회귀계수와 추정과 검정에 오류가 발생되었다. 반면 주성분 회귀모형을 이용하여 분석한 결과 다중공선성문제가 해결되어, 개별 생산요인에 대한 효과를 적절하게 추정할 수 있었다. 본 논문에서 제안한 주성분 회귀모형을 이용한 과학기술 지식생산함수 추정방법은 다중공선성이 강한 소수의 생산요소를 포함한 회귀분석에서 유용하게 적용될 수 있을 것이다.

• Asia pacific journal of information systems
• /
• 제25권3호
• /
• pp.445-472
• /
• 2015

Although knowledge transfer between two different parties occurs in IS development projects, the majority of prior studies focused on knowledge transfer from IT consultants to clients. Considering two parts of knowledge transfer in IS development projects, we must consider both 'where knowledge is transferred from' and 'where it is transferred to'. Therefore, in this study, we attempt to describe two different routes of knowledge transfer, such as knowledge transfer from an IT consultant to a client and knowledge transfer from a client to an IT consultant. In this regard, we have examined the effect of two different routes of knowledge transfer on system implementation success in IS development project. Specifically, we adopted the knowledge stock-flow theory to examine the causal relationship between IT consulting firms and clients in terms of knowledge transfer and eventual system implementation success. Survey data collected from 213 pairs of individuals (both clients and IT consultants) were used to test the model using three different analytic approaches such as PLS (partial least squares) and two types of mediated regression techniques. We found that knowledge transfers partially mediated both the relationships between IT consultants' IT skills (project members' business knowledge) and system implementation success. Furthermore, the effects of each knowledge transfer were distinguished by depending on the types of system, such as ERP or groupware. Our attempts have significant implications for both research and practice given the importance of effective knowledge transfer to IT consulting.

• 지식경영연구
• /
• 제12권4호
• /
• pp.41-54
• /
• 2011

Given the prevalence of home trading systems, it has become important to examine user behaviors in a stock investment environment. In this vein, this paper developed an integrated model to deeply understand the key determinants of user's continuance intention to use investment information through constructs prescribed by incorporating trust and perceived risk into expectation-confirmation model. The proposed research model was tested by using survey data collected from 160 users who have experience with stock investment. PLS (partial least squares) was employed for the analysis of the data. The findings of this study showed that the proposed framework provides a statistically significant explanation of the variation in continuance intention to search investment information. The findings revealed that trust and perceived risk are more prevalent predictors of continuance intention to use investment information compared to perceived usefulness. It was also found that user satisfaction serves as the salient antecedents of continuance intention to use investment information. The theoretical and practical implications of the findings were described.