• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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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.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2106-2112
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• 1999

In decision-making, information is the thing manufactured as the useful type for decision -making. We can improve the efficiency of decision-making by elimination of unnecessary information. Rough set is the theory that can classify and reduce the unnecessary. But the reduction process of rough set becomes more complex according to the number of attribute and tuple. After eliminating of the dispensable attributes using $\chi$2 and rough set, the indispensable attributes are used for the units of input layers in neural network. This rough-neural network can support more correct decision-making of neural network.

• Journal of Information Technology Services
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• v.2 no.2
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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.

• Information Systems Review
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• v.25 no.1
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• pp.47-73
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• 2023

Management decision-making based on artificial intelligence(AI) plays an important role in helping decision-makers. Business decision-making centered on AI is evaluated as a driving force for corporate growth. AI-based on accurate analysis techniques could support decision-makers in making high-quality decisions. This study proposes an effective decision-making method with the application of multi-label feature selection. In this regard, We present a CFS-BR (Correlation-based Feature Selection based on Binary Relevance approach) that reduces data sets in high-dimensional space. As a result of analyzing sample data and empirical data, CFS-BR can support efficient decision-making by selecting the best combination of meaningful attributes based on the Best-First algorithm. In addition, compared to the previous multi-label feature selection method, CFS-BR is useful for increasing the effectiveness of decision-making, as its accuracy is higher.

• Fashion & Textile Research Journal
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• v.22 no.3
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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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• 2008.06a
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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.

• Journal of Korean Library and Information Science Society
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• v.13
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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.

• Journal of Families and Better Life
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• v.23 no.3 s.75
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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.

• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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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.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.1 s.28
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• pp.3-10
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• 2004

These days GIS have rapidly deployed as input and solutions to marketing decision making problems and corresponding decision support systems in many countries including Korea. Its powerful spatial analysis tools along with data integration and graphic display capabilities let many retailers and manufacturers in fashion industry to accept GIS as a useful mean for their decision making systems. At this moment, this paper presents many facets of discussions on how GIS be applied to fashion marketing decision making problems. From provoking several questions on current fashion marketing decision making system to explaining multiattribute decision making and multiobjective decision making as tools for decision making analysis and discussing some implementation issues, this paper revealed many aspects of GIS and fashion marketing decision support system from integration point of view.