• 대한안전경영과학회지
• /
• 제7권4호
• /
• pp.165-177
• /
• 2005

Supply Chain Management(SCM) system is a critical investment that can affect future competitiveness and performance of a company. Selection of a right SCM system is one of the critical issues. This paper provides the characteristic factors of SCM system selection and the SCM system evaluation and selection model based on Analytic Hierarchy Process(AHP). The proposed model can systematically construct the objectives of SCM system selection to support the business goals. A empirical example demonstrates the feasibility of the proposed model and the model can help a company to make better decision-making in selecting SCM system.

• 한국건축시공학회지
• /
• 제11권5호
• /
• pp.523-529
• /
• 2011

In a tall building construction with reinforced concrete structures, the selection of an appropriate formwork system is a crucial factor for the success of the project. Thus, selecting an appropriate formwork system affects the entire construction duration and cost, as well as subsequent construction activities. However, in practice, the selection of an appropriate formwork system has depended mainly on the intuitive and subjective opinion of working level employees with restricted experience. Therefore, in this study, a formwork system selection model using the Adaboost algorithm is proposed to support the selection of a formwork system that is suitable for the construction site conditions. To validate the applicability of the proposed model, the selection models Adaboost and ANN were both applied to actual case data of tall building construction in Korea. The Adaboost model showed slightly better accuracy than that of the ANN model. The Adaboost model can assist engineers to determine the appropriate formwork system at the inception of future projects.

• 대한안전경영과학회지
• /
• 제11권2호
• /
• pp.153-158
• /
• 2009

An optimal selection problem of SCM system is one of the critical issues for the company's competitiveness and performance under global economy. This paper presents a hierarchy model consisted of characteristic factors for introducing SCM system and an AHP (Analytic Hierarchy Process) based decision-making model for SCM system evaluation and selection. The proposed model can systematically construct the objectives of SCM system selection to meet the business goals. This paper focuses on selecting an optimal SCM system considering both all decision factors and sub-decision factors of a hierarchy model. Especially, the benefit/cost analysis is applied to choose SCM system. A case study shows the feasibility of the proposed model and the model can help a company to make better decision-making in the SCM system selection problem.

• 산업경영시스템학회지
• /
• 제30권3호
• /
• pp.158-164
• /
• 2007

Supply Chain Management (SCM) system is a critical investment that can affect the competitiveness and performance of a company. Selection of a right SCM system is one of the critical issues. This paper presents the characteristic factors of SCM system and a Fuzzy AHP (Analytic Hierarchy Process) based decision-making model for SCM system evaluation and selection. This study focuses on quantitative factors, applying the fuzzy concept to various evaluative factors. The proposed model can systematically construct the objectives of SCM system selection to achieve the business goals. A empirical example demonstrates the feasibility of the proposed model and the model can help a company to make better decision-making in the SCM system selection problem.

• 산업경영시스템학회지
• /
• 제37권1호
• /
• pp.9-25
• /
• 2014

It is very important to select the best employees who are suitable for their jobs and duties as considering the efficiency and productivity of the firms' performance. As a result, many kinds of selection methodologies and systems have been developed. Among them is the selection system based on the core competencies which is known as the superior selection systems that can increase the predictive validity who is the right people, compared to the traditional selection system based on the job analysis. Hence, the former has been focused in the complex business situation in recent years. In this case study, we examine the selection system case based on the core competencies of OSS team in Company A, which is one of the largest telecommunication firms and we suggest the implications. According to the results of this case study, defining the core competencies of the job and selecting the right people who had the related competencies not only decreased the turnover rate of OSS team in Company A, but also increased the employees' loyalty and satisfaction for the organizations. This study will be a benchmark to other departments that don't use competency selection system of Company A as well as the firms that want to adapt the selection system based on the core competencies. Also, this case study has a contribution that shows us an alternative model how can the firms identify and select the best right employees.

• 기술혁신연구
• /
• 제2권1호
• /
• pp.116-141
• /
• 1994

This paper presents a model for R&D project selection and evaluation system design developed through literature review. The model emphasizes the fitness between the five elements of the system : evaluation phase and purpose, personnel and organization, evaluation critiria and decision model, evaluation form and procedure, and projects. The model was applied in real situation as a test case. The important findings are that a good project selection and evaluation model contributes only partially to the effectiveness of the project selection and that system development and implementation activity is a dynamic and multi-facetted learning process.

• 한국인터넷방송통신학회논문지
• /
• 제11권6호
• /
• pp.15-21
• /
• 2011

애드혹 네트워크에서는 협동 다이버시티를 적용하여 네트워크의 전력소모를 줄이고, 통달거리의 확장 및 시스템의 성능을 향상시키고 있다. 그러나 가장 큰 신호 대 잡음비(SNR, Signal-to-noise ratio)을 갖는 릴레이를 선택하여 송신하는 선택 릴레이 협동 다이버시티 방식은 느린 페이딩 채널에서 특정 릴레이가 계속 송신하므로 네트워크의 생존시간을 줄이게 된다. 그러므로 최근에 네트워크의 생존 시간을 늘이기 위하여 균일전력 릴레이 선택방식이 연구되었다. 본 논문에서는 소스-릴레이 및 릴레이-목적지간의 수신 신호 대 잡음비가 일정수준 이상이 되는 릴레이를 선택하여 송신할 수 있는 하는 이중 기회전송 협동 다이버시티(DOT, Double opportunistic cooperative diversity) 시스템에 균일전력 릴레이 선택방식을 적용하고 시스템의 성능을 유도하였다. 유도한 결과는 선택결합(SC, Selection combining) 방식과 최대비 합성결합(MRC, Maximal ratio combining) 방식과 비교하였다. 균일전력 릴레이 방식을 사용하였을 때 다른 방식에 비해서 시스템의 성능저하가 있었는데, 이는 네트워크의 생존 시간을 늘이기 위해서 릴레이에 균일한 송신기회를 주었기 때문으로 해석되었다.

• 경영과학
• /
• 제21권1호
• /
• pp.113-129
• /
• 2004

Nowadays many enterprises build e-procurement systems. An e-procurement is a Web-based procurement process and its functionalities are considered important in the B2B e-commerce. Buyers should select competent suppliers for a successful e-procurement. Therefore, this study proposes a method using the analytic hierarchy process(AHP) for building a Web-based supplier selection system. In detail, the purpose of this study is (1) to review methods previously used when buyers selecting suppliers and to extract important selection criteria： (2) to explain extended AHP method adopted by this study among supplier selection methods： (3) to describe the supplier selection steps using extended AHP ： and (4) to propose a decision support system embedding the methodology described above. The proposed system comprises of three phase： first phase is to evaluate suppliers on enterprise level： second phase to evaluate them on each transaction level： third phase to post-evaluate them.

• 한국정보시스템학회지:정보시스템연구
• /
• 제26권3호
• /
• pp.63-90
• /
• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
• /
• pp.219-223
• /
• 2001

Within a mechanical system such as an automotive the number of standard machine parts is increasing, so that the parts selection becomes more important than ever before. Selection of appropriate bearings in the preliminary design phase of a machine is also important. In this paper, three decision-making approaches are compared to find out a model that is appropriate to bearing selection problem. An artificial neural network, which is trained with real design cases, is used to select a bearing mechanism at the first step. Then, the subtype of the bearing is selected by the weighting factor method. Finally, types of peripherals such as lubrication methods are determined by a rule-based expert system.