• Journal of Hospice and Palliative Care
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• v.24 no.4
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• pp.204-213
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• 2021

Purpose: At the end of life, communication is a key factor for good care. However, in clinical practice, it is difficult to adequately discuss end-of-life care. In order to understand and analyze how decision-making related to life-sustaining treatment (LST) is performed, the shared decision-making (SDM) behaviors of physicians were investigated. Methods: A questionnaire was designed after reviewing the literature on attitudes toward SDM or decision-making related to LST. A final item was added after consulting experts. The survey was completed by internal medicine residents and hematologists/medical oncologists who treat terminal cancer patients. Results: In total, 202 respondents completed the questionnaire, and 88.6% said that the decision to continue or end LST is usually a result of SDM since they believed that sufficient explanation is provided to patients and caregivers, patients and caregivers make their own decisions according to their values, and there is sufficient time for patients and caregivers to make a decision. Expected satisfaction with the decision-making process was the highest for caregivers (57.4%), followed by physicians (49.5%) and patients (41.1%). In total, 38.1% of respondents said that SDM was adequately practiced when making decisions related to LST. The most common reason for inadequate SDM was time pressure (89.6%). Conclusion: Although most physicians answered that they practiced SDM when making decisions regarding LST, satisfactory SDM is rarely practiced in the clinical field. A model for the proper implementation of SDM is needed, and additional studies must be conducted to develop an SDM model in collaboration with other academic organizations.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.239-252
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• 2005

The major reason that spatial data warehousing has attracted a great deal of attention in business GIS in recent years is due to the wide availability of huge amount of spatial data and the imminent need for fuming such data into useful geographic information. Therefore, this research has been focused on designing and implementing the pilot tested system for spatial decision making. The purpose of the system is to predict targeted marketing area by discriminating the customers by using both transaction quantity and the number of customer using credit card in department store. Moreover, the pilot tested system of this research provides OLAP tools for interactive analysis of multidimensional data of geographically various granularities, which facilitate effective spatial data mining. focused on the analysis methodology, the case study is aiming to use GIS and clustering for knowledge discovery. Especially, the importance of this study is in the use of snowflake schema model capabilities for GIS framework.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.243-252
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• 2013

This study analyzes the policy-making process to promote the artists' welfare. In the problems stream, the artists have been found to suffer without any governmental support. In the policy stream, there have been various alternatives but they were not actualized. Meanwhile, a writer died of illness and famine in 2011. In the political stream, the public opinion to require the promotion of the artists' welfare, was strengthened. It made the policy-window open and resulted in the legislation of the Artists Welfare Law. Based upon these analyses, this article concludes that Kingdon's model is applicable to this case. Especially, this study shows that this policy was made with accidental events and the roles of informal participants such as netizen were more critical. However, it should be noted that the content of this Law was modified and trimmed because there was no policy entrepreneur to persuade the dissenters. It could made the policy-making process of this Law distinguished from others.

• Journal of the Korean Society for information Management
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• v.30 no.3
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• pp.71-87
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• 2013

In this study, we analyze the agenda setting and policy making process of the establishment of Gyeonggido Cyber Library, which has played an important role for development of public libraries in Gyeonggido since its launching, based on Kingdon's policy streams model. According to the model, policy formation is described as the result from the convergence of the three streams, such as problem, policy and politics streams. When these streams converge on a specific time point, a policy window is created so that the issues become policy agenda. At this moment, policy entrepreneurs propose their alternatives, which have been prepared already, and try to pass it through the window. We identify coupling of the streams in the policy window and the role of policy entrepreneurs in the process of agenda setting and selection of alternatives of Gyeonggido Cyber Library policy. Suggestions are provided based on the analysis for public policy formation in public libraries domain.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.9-20
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• 2014

Making good predictions about the outcome of one's actions would seem to be essential in the context of social interaction and decision-making. This paper proposes a computational model for learning articulated motion patterns for action recognition, which mimics biological-inspired visual perception processing of human brain. Developed model of cortical architecture for the unsupervised learning of motion sequence, builds upon neurophysiological knowledge about the cortical sites such as IT, MT, STS and specific neuronal representation which contribute to articulated motion perception. Experiments show how the model automatically selects significant motion patterns as well as meaningful static snapshot categories from continuous video input. Such key poses correspond to articulated postures which are utilized in probing the trained network to impose implied motion perception from static views. We also present how sequence selective representations are learned in STS by fusing snapshot and motion input and how learned feedback connections enable making predictions about future input sequence. Network simulations demonstrate the computational capacity of the proposed model for motion recognition.

• The Journal of Information Systems
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• v.17 no.3
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• pp.205-233
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• 2008

This study suggests the dynamic value chain model, that will be able to not only show changing processes to organization's significant capital by integrating an individual, implicit, and explicit knowledge which affect organizational decision making, but also distinguish the key driver for raising organizational competitive power because it makes possible to analyze sensitivity of performance along with decision making alternatives and policy changes from dynamic view by connecting knowledge management capability, knowledge management activity, and relations with organizational performance with specific strategic map. Recently, a lot of organizations show interest in measuring and evaluating their performance synthetically. In organizations taking knowledge management, they introduce effective value chain model like a dynamic balanced scorecard (DBSC), and therefore they can reflect their knowledge management condition as well as show their changes by checking performance of established vision and strategy periodically. Furthermore, they can ask for their inner members' understanding and participation by communicating with and inspiring their members with awareness that members are one of their group, present a base of benchmarking, and offer significant information for later decision making. The BSC has been a successful framework for measuring an organization's performance in various perspectives through translating an organization's vision and strategy into an interrelated set of key performance indicators and specific actions. The BSC, while having significant strengths over traditional performance measurement methods, however, has its own limitations, due to its static nature, such as overlooking two-way causation between performance indicators and neglecting the impact of delayed feedback flowing from the adoption of new strategies or policy changes. To overcome these limitations, this study employs SD, a methodology for understanding complex systems where dynamic feedback among the interrelated system components significantly impact on the system outcomes. The SD simulation model in the form of DBSC would serve as a useful strategic teaming tool for facilitating an organization's communication process through various scenario analyses as well as predicting the dynamic behavior pattern of their key performance measures over a future time frame. For the demonstration purpose, this study applied the DBSC model to Prototype of Korea manufacturing and service firm.

• Journal of Korean Elementary Science Education
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• v.39 no.1
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• pp.117-132
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• 2020

The purpose of this study is to investigate elementary school teachers' awareness of Artificial Intelligence (AI) and find out how to apply it in elementary science education. The survey was conducted online and involved 95 teachers working in the metropolitan area. The results of this study are as follows. First, teachers need to learn about the general characteristics of AI and how to apply it to education. Second, science classes had the highest preference for AI among elementary school subjects. Third, the preference for AI application by elementary science field was 68.4% for earth and space, 54.7% for exercise and energy, 32.6% for matter, 27.4% for life. Fourth, AI-based Science Education (AISE) teaching- learning strategies were developed based on AI characteristics and the changing perspective of elementary science education, AISE's teaching-learning strategies are five: 'automation', 'individualization', 'diversification', 'cooperation' and 'creativity' and teachers can use them in teaching design, class practice and evaluation stages. Finally, the creative problem-solving Doing Thinking Making Sharing (DTMS) model was devised to implement the creativity strategy in AISE. This model consists of four-steps teaching courses: Doing, Thinking, Making and Sharing based on the empirical learning theory. In the future, follow-up research is needed to verify the effectiveness of this model by applying it to elementary science education.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.563-575
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• 2009

This research has found logical data directly influencing forming consideration set and attitude and attitude strength under the choosing situation based on memory-base proposed by Priester et. al (2004). We've examined the possibility of model extension through physical salient strength according to the location of product display as an external stimulate factor and attitude and attitude strength, consideration set and role on variable choice. Especially, this research practically proposed the method measuring directly the attitude on behavior instead of seeing the intension of behavior or behavior by measuring the behavior itself based on existing experiment methods and applied logistics regression analysis. In conclusion, this research confirmed the possibility of generalization of this model by verifying appropriateness through logical background and actual analysis based on stimulus-base proposed model characters as an integrated model relation between attitude in stimulus-based relation and decision-making.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.635-645
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• 2020

This research was conducted to achieve several objectives and focus research was based on financial behavior theory and prospect theory as grounded theory e.g., investigate the financial decision-making behavior between financial and real assets investment, and confirm the relationship existing between herding behavior and overconfidence factors to the level of loss and regret aversion, and financial literacy into real assets investment decisions. The study used 220 real estate auction respondents as investor samples at the State Assets and Auction Service Office Makassar, South Sulawesi, Indonesia. Data was collected through the use of a questionnaire consisting of 23 questions to measure the variables. Moreover, the research data passed through several feasibility tests like the inner and outer modeling by Partial Least Square - Structural equation model (PLS-SEM) while the hypotheses formulated were also tested to determine the magnitude of the variable relationship. Through the use of the direct and intervening test, loss and regret aversion variables have a positive and significant effect while financial literacy variables have no significant effect. There is a slight difference in the decision-making process for real assets and financial assets investors. Investment decision making behavior in the financial assets sector requires less complicated decisions compared to the decisions related to real assets investments.

• Knowledge Management Research
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• v.10 no.3
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• pp.17-33
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• 2009

The emergence of the Internet shopping agent enabled consumers to enjoy Internet shopping more easily and quickly. Especially, the role of Internet shopping agent is becoming more important following the information overload trend on the Internet in that the consumers can promptly obtain information about a certain product and its price among countless items on the Internet. As a result, consumers can now enjoy shopping more easily, compared to the offline shopping which requires a lot of efforts in comparing the products and purchasing them. Since the Internet shopping agents collect extensive information about the products' price, delivery period, detailed characteristics, etc., and present a comparison table containing the information to the consumers, the consumers can shop more quickly at lower price using such shopping agents. However, it has not been sufficiently studied about how the various functions of shopping agents actually support consumers' purchase decision making procedure in everyday life, and if they do, in which stages they play a supporting role in consumers' purchase decision making system. Therefore, this study conducts an empirical analysis on the role of the Internet shopping agents in the purchase decision making process of the consumers, considering the Internet shopping agent as a decision making supporting system. Moreover, it analyzes how the effects of the Internet shopping agent differs according to the consumers' knowledge level about the products.