• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.90-113
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• 2021

Electronic Records Management System (ERMS) is a computer program or set of applications that is utilized for keeping up to date records along with their storage. ERMS has been extensively utilized for enhancing the performance of academic institutions. The system assists in the planning and decision-making processes, which in turn enhances the competencies. However, although ERMS is significant in supporting the process of decision-making, the majority of organizations have failed to take an initiative to implement it, taking into account that are some implementing it without an appropriate framework, and thus resulted in the practice which does not meet the accepted standard. Therefore, this study identifies the factors influencing the adoption of ERMS among employees of HLI in Yemen and the role of such adoption in the decision-making process, using the Unified Theory of Acceptance and Use of Technology (UTAUT) along with Technology, Organization and Environment (TOE) as the underpinning theories. The study conducts a cross-sectional survey with a questionnaire as the technique for data collection, distributed to 364 participants in various Yemeni public Higher Learning Institutions (HLI). Using AMOS as a statistical method, the findings revealed there are significant and positive relationships between technology factors (effort expectancy, performance expectancy, IT infrastructure and security), organizational factors (top management support, financial support, training, and policy),environmental factors (competitiveness pressure, facilitating conditions and trust) and behavioral intention to adopt ERMS, which in return has a significant relationship with the process of decision-making in HLI. The study also presents a variety of theoretical and empirical contributions that enrich the body of knowledge in the field of technology adoption and the electronic record's domain.

• 한국정보처리학회논문지
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• 제6권8호
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• pp.2106-2112
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• 1999

의사결정에 있어 정보란 의사결정자가 의사결정을 하는데 사용하도록 의미 있고 유용한 형태로 처리된 데이터이다. 이러한 정보들에 있어서 불필요한 속성들을 제거하여 처리함으로써 의사결정의 효율을 높일 수 있다. 러프 집합 이론은 불필요한 속성을 제거하고 분류화 하는데 뛰어난 능력을 가지고 있으나 속성 감축시 속성 수와 튜플 수에 따라 복잡한 계산을 요구한다. 따라서 속성들 사이의 상호연관성을 나타내는 척도로서, 두 변수간의 독립성에 관한 검정방법인 $\chi$2와 러프 집합의 종속성을 이용하여 속성들을 감축하고 이를 신경망의 입력 유니트로 사용하므로써 기존의 모든 속성을 입력으로 하여 신경망을 구성하는 것보다 간단하며 학습효율의 향상 및 정확한 의사결정을 지원할 수 있다.

• 한국IT서비스학회지
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• 제2권2호
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• pp.121-134
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• 2003

To improve the quality of the services and to concentrate on the core capability, in public sector the IT outsourcing is recently being vitalized by the institutional support of the government for the entrusting non-government. Because the lots of general studies so far have simply focused on indicating fragmentary factors i.e. economical factors, risk factors, system factors, or induction objects, etc., they are insufficient in making the practical decisions, therefore we indicated systemized model extending over the whole range of the IT outsourcing to support substantial decision makings, and assorted 4 categories and drew considerable 55 factors from the literature study to materialize the previously considerable factors at each decision making stage. And the principal factors were drawn from each decision making category by a group of 11 experts. Besides, a henceforth plan for the application was also presented through an actual example of the IT outsourcing decision making process of 'M', a public enterprise.

• 경영정보학연구
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• 제25권1호
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• pp.47-73
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• 2023

본 연구는 인공지능 기법 중 다중레이블 속성선택 방법을 적용하여 복잡한 경영환경에서 의사결정의 효과성을 증대시키는 방안을 설명한다. 인공지능 기반의 의사결정 시스템은 의사결정자의 선택과 판단을 돕거나, 대신하는 중요한 역할을 한다. 더욱이 최근 인공지능을 중심으로 한 비즈니스 의사결정은 기업의 성장 동력으로 평가받는데, 이를 위해서는 효과적인 의사결정 방법이 수반되어야 한다. 이에 본 연구는 의미 있는 속성값을 선별하는 CFS-BR(이진연관성 접근 기반의 상관관계 속성선택 모델)을 제안하여, 효과적인 의사결정을 지원하는 것을 돕는다. 예시데이터와 실증데이터의 분석 결과, CFS-BR은 유의미한 속성을 최상우선선별 알고리즘 기반으로 최상의 조합을 선별하므로 효율적 의사결정을 지원할 수 있고, 기존의 다중 레이블 속성선택 방법과 비교하였을 때 정확도가 높은 것으로 보아 효과적인 의사결정을 증대시키는 데 유용하다.

• 한국의류산업학회지
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• 제22권3호
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• pp.323-334
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• 2020

This study analyzed the effects of consumers' characteristic variables on information search and purchase decisions in a decision-making process that validated the path model in purchasing apparel products. In constructing a structural equation model using AMOS 19.0., the variables including enjoyment pursuit, price pursuit, product involvement and product risk were selected as consumers' characteristic variables affecting the stage of information search. A questionnaire was distributed to consumers over 20 years old who purchased apparel products using offline and online channels within one year; consequently, we were able to analyze 468 effective data. The results were as follows. First, the path model of this research proved to be the appropriate model explaining the effects of consumers' characteristic variables on the stage of purchase decision-making. Second, enjoyment pursuit had a significant positive influence on offline information search; in addition, price pursuit and product risk affected the online information search significantly. Product involvement affected online information search as well as offline information search. Third, the offline information search affected offline purchase and online information search affected online purchase. However, consumer's channel switching behavior between the stage of information search and the stage of purchase decision was not proven. The findings suggest that companies need to develop distribution strategies according to consumers' characteristic factors that effect consumer's purchase decision-making.

• 한국경영정보학회:학술대회논문집
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• 한국경영정보학회 2008년도 춘계학술대회
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• pp.1072-1077
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• 2008

This study is aimed at proposing a new approach to designing UDSS (Ubiquitous Decision Support System) which allows context-awareness and connectivity. In the previous studies, the need to design UDSS and analyze its performance empirically was raised. However, due to the complexity of empirical approaches, there is no study attempting to tackle this research issue so far. To fill this research void, this study proposes a Mobile Delivery System (MDS) as a form of UDSS, empirically analyzing how users perceive its context-awareness and connectivity functions. Especially, to add more rigor to the proposed approach to know how much it works well in the decision-making contexts, we considered three decision making phases (intelligence, design, choice) in the research model. With the valid questionnaires collected from 340 users of the MDS, we induced statistically proven results showing that both context-awareness and connectivity of the proposed UDSS (or MDS) influence the decision making steps positively and then contribute to improving the decision making quality.

• 한국도서관정보학회지
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• 제13권
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• pp.131-166
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• 1986

This study is designed to review the methods of duplicate copies decision making in the academic library. In this thesis, I surveyed queueing & markov model, statistical model, and simulation model. The contents of the study can be summarized as follows: 1) Queueing and markov model is used for one of duplicate copies decision-making methods. This model was suggested by Leimkuler, Morse, and Chen, etc. Leimkuler proposed growth model, storage model, and availability model through using system analysis method. Queueing theory is a n.0, pplied to Leimkuler's availability model. Morse ad Chen a n.0, pplied queueing and markov model to their theory. They used queueing theory for measuring satisfaction level and Markov model for predicting user demand. 2) Another model of duplicate copies decision-making methods is statistical model. This model is suggested by Grant and Sohn, Jung Pyo. Grant suggested a model with a formula to satisfy the user demand more than 95%, Sohn, Jung Pyo suggested a model with two formulars: one for duplicate copies decision-making by using standard deviation and the other for duplicate copies predicting by using coefficient of variation. 3) Simulation model is used for one of duplicate copies decision-making methods. This model is suggested by Buckland and Arms. Buckland considered both loan period and duplicate copies simultaneously in his simulation model. Arms suggested computer-simulation model as one of duplicate copies decision-making methods. These methods can help improve the efficiency of collection development and solve some problems (space, staff, budget, etc, ) of Korean academic libraries today.

• 가정과삶의질연구
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• 제23권3호
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• pp.77-91
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• 2005

This study conceptualized the factors affecting college students' consumer decision-making styles from the perspective of consumer socialization. A number of antecedent variables identified by preceding studies (age, gender, place where one grew up, job experience, main reason for working, amount of allowance, family income, socio-economic status) and socialization agents such as family, peers, mass media were included in the analysis. This study extends previous studies by examining a theoretical link between the antecedent variables and socialization agents. Three hundred and forty one undergraduate students in Daejeon were participated in this study. Stepwise multiple regression md path analysis were conducted. The results of this study are as follows: 1. Six consumer decision-making styles were identified. 2. The influence of the socialization agents, especially mass media and several antecedent variables, especially gender and main reason for working, played important roles in consumer decision-making styles. 3. Several antecedent variables, especially gender and family income, were related only with the influence of socialization agents. 4. Six path-analysis models that illustrate the relationships among the antecedent variables, the socialization agents and consumer decision-making styles were proposed.

• 한국산업정보학회논문지
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• 제2권2호
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• pp.189-207
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• 1997

Recently, we have witnessed a host of emerging tools in the management support systems (MSS) area including the data warehouse/multidimensinal databases (MDDB), data mining, on-line analytical processing (OLAP), intelligent agents, World Wide Web(WWW) technologies, the Internet, and corporate intranets. These tools are reshaping MSS developments in organizations. This article reviews a set of emerging data management technologies in the knowledge discovery in databases(KDD) process and analyzes their implications for decision support. Furthermore, today's MSS are equipped with a plethora of AI techniques (artifical neural networks, and genetic algorithms, etc) fuzzy sets, modeling by example , geographical information system(GIS), logic modeling, and visual interactive modeling (VIM) , All these developments suggest that we are shifting the corporate decision making paradigm form information-driven decision making in the1980s to knowledge-driven decision making in the 1990s.

• 대한공간정보학회지
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• 제12권1호
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• pp.3-10
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• 2004

최근 GIS는 국내에서 뿐 아니라 외국에서도 마케팅의 의사결정문제와 그에 따른 의사결정지원시스템에 적용이 시도되고 있다. GIS는 강력한 공간분석 기능과 함께 자료의 통합과 그래픽 기능 등을 갖추고 있으며 이와 같은 기능으로 인해 많은 소매 운영자와 생산자들로 구성되는 패션 산업에 있어서 의사결정을 지원하는 하나의 좋은 수단으로서 점차 인식이 확산되고 있다. 이러한 시점에 본 논문에서는 GIS를 패션마케팅에 적용함에 있어서 몇가지 주요한 요소들을 고찰하여 보았다. 이를 위해 현재의 패션마케팅 의사결정문제에 있어서의 주요 이슈에 대한 문제제기에서 출발하여 다속성 의사결정과 다목적 의사결정의 프레임이 어떻게 패션마케팅 의사결정지원에 이용될 수 있는가를 알아보고 이를 실제로 구현하는데 있어서의 한계점 역시 아울러 고찰하여 보았다. 논의의 주안점은 주로 현재의 패션마케팅 의사결정시스템과 GIS 기능의 통합에 두었다.