• The Korean Journal of Health Service Management
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• v.9 no.1
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• pp.67-79
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• 2015

The aim of this descriptive cross-sectional study was determine the effect of critical thinking and clinical decision-making on ethical dilemmas. A survey of dental hygienists residing in Busan and South Gyeongsang, Korea was conducted using convenience sampling between September and December, 2013. A total of 153 responses were used in the final analysis. Data analysis and structural equation modeling were performed with IBM SPSS Statistics(version 21.0) and AMOS(version 18.0) programs. A negative(-) correlation coefficient(-0.37) was observed between critical thinking and ethical dilemmas on statistical analysis, i.e., higher critical thinking led to less ethical dilemmas(p=0.024, CR=-2.264). The values from the structural equation model were ${\chi}^2=98.124$ df=66, GFI=0.919, AGFI=0.871, and RMSEA=0.057. This study proposed a theoretical model in which critical thinking, ethical values, and decision-making skills should be firmly established to effectively respond to specific situations, such as ethical dilemmas, and that greater tendencies for critical thinking led to less ethical dilemmas, thereby demonstrating a negative(-) correlation between the two parameters.

• Knowledge Management Research
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• v.16 no.3
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• pp.149-169
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• 2015

In this study, we try to understand the role of online social recommendation and the similarity of preferences between the recommender and the recommendee on consumer decisions in the framework of the two stage purchase decision-making process. Applying construal level theory to our context, we expect that the role of social recommendation and the similarity of preferences would vary over the stages in the two-stage decision making process. To test our hypotheses, we collected the data through an incentive compatible experiment, and analyzed the data with nested logit model. As a result, we found that the role of online social recommendation varies over the stages. Consumers take recommendation from similar others at the stage of consideration set formation, but no longer consider it at the stage of final choice. Consumers take recommendation from dissimilar others at the stage of consideration set formation. At the stage of final choice, however, consumers avoid choosing the option recommended by dissimilar others. The results of our study enrich the understanding about the role of social recommendation, and have implication to marketing practitioners who attempt to make online social recommendation system more efficient.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.4
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• pp.894-899
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• 2007

IT Outsourcing has been take place for ages and its range has expanded. The cases are also often take place more but there are a few criteria for making decision of IT outsourcing project. Companies tend to take IT outsourcing as a trend or to follow competitor's IT outsourcing project. This study suggests the criteria for IT outsourcing project before going into the project. The criteria ate to describe what function of the companies need to take outsourcing. Research model is driven by Statistics and AHP method. Also, variables are presented for clear making decision. This model allows the companies find proper IT outsourcing type and conveniences.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.291-296
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• 2008

This paper presents the dodecagon-based Q-leaning and SVM algorithm for object search with multiple robots. We organized an experimental environment with several mobile robots, obstacles, and an object. Then we sent the robots to a hallway, where some obstacles were tying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making(DBAM) and Area-based action making(ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and SVM to enhance the fusion model with Distance-based action making(DBAM) and Area-based action making(ABAM) process.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.53-59
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• 2021

This research aims to examine the model of investor herding behavior in making investment decisions in the Indonesian capital market, which is influenced by social and information impacting on the value of the Book Value Per Share (BVPS). The latest stock market conditions show that most investors make the same error pattern in making investment decisions that result in losses. The experiment involves two independent variables, namely, information about BVPS and social influence. This study used a 2×2 factorial design laboratory experimental method. Data collection was carried out through treatment of a sample of 100 individual investors listed on the Indonesia Stock Exchange. Univariate Two-Way Analysis of Variance (ANOVA) statistical tool was used to test the independent variable on the dependent variable. Research results showed that the social influence originating from expert investors is more influential than the Book Value Per Share (BVPS) information on the behavior of herding investors in making investment decisions. These findings suggest that investors know their psychological factors, thereby increasing self-control and investment analysis skills. Further research can use psychological bias and other indicators of accounting relevant information such as Earning Per Share (EPS) to test herding behavior in investment decision making in the capital market.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.363-379
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• 2023

Purpose: The main objective of this research is to construct an AI-based Composite Supplementary Index (ACSI) model to achieve accurate predictions of the Composite Index of Business Indicators. By incorporating various economic indicators as independent variables, the ACSI model enables the prediction and analysis of both the leading index (CLI) and coincident index (CCI). Methods: This study proposes an AI-based Composite Supplementary Index (ACSI) model that leverages diverse economic indicators as independent variables to forecast leading and coincident economic indicators. To evaluate the model's performance, advanced machine learning techniques including MLP, RNN, LSTM, and GRU were employed. Furthermore, the study explores the potential of employing deep learning models to train the weights associated with the independent variables that constitute the composite supplementary index. Results: The experimental results demonstrate the superior accuracy of the proposed composite supple- mentary index model in predicting leading and coincident economic indicators. Consequently, this model proves to be highly effective in forecasting economic cycles. Conclusion: In conclusion, the developed AI-based Composite Supplementary Index (ACSI) model successfully predicts the Composite Index of Business Indicators. Apart from its utility in management, economics, and investment domains, this model serves as a valuable indicator supporting policy-making and decision-making processes related to the economy.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.1
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• pp.81-91
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• 1978

Decision models are an attempt to reduce uncertainty in the decision making process. The models describe the relationships of variables and given proper input data generate solutions to managerial problems. These solutions may not be answers to the problems for one of two reasons. First, the data input into the model may not be consistant with the underlying assumptions of the model being used. Frequently parameters are assumed to be deterministic when in fact they are probabilistic in nature. The second failure is that often the decision maker recognizes that the data available are not appropriate for the model being used and begins to collect the required data. By the time these data has been compiled the solution is no longer an answer to the problem. This relates to the timeliness of decision making. The authors point out throught the use of an illustrative problem that stocastic models are well developed and that they do not suffer from any lack of mathematical exactiness. The primary problem is that generally accepted procedures for data generation are historical in nature and not relevant for probabilistic decision models. The authors advocate that management information system designers and accountants must become more familiar with these decision models and the input data required for their effective implementation. This will provide these professionals with the background necessary to generate data in a form that makes it relevant and timely for the decision making process.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.23-40
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• 2014

This paper measures the operational efficiency of domestic online game companies and analyze its trends and patterns by using data envelopment analysis (DEA). DEA is a non-parametric approach to measuring the relative efficiency of decision-making units (DMUs) with multiple inputs and outputs. 14 online game companies are selected as DMUs and three inputs (number of employees, capital and asset) and three outputs (sales, operating profit and net profit) are selected as DEA variables. First, the output-oriented BCC model and super-efficiency model are employed to measure the static operational efficiency of the online game companies from 2003 to 2012. We also conduct the dynamic analysis with DEA window model to capture the trends of their operational efficiency influenced by internal and external environmental changes. The results are expected to provide fruitful implications for strategic decision making of online game companies and policy making for the online game industry.

• Journal of Information Technology Applications and Management
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• v.19 no.3
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• pp.49-68
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• 2012

M&A (Merger and Acquisitions) is a standard corporate strategy frequently used by companies seeking to secure new growth engines and gain a solid foothold in their markets in order to become more globally competitive. To achieve the original goals of M&A, the two involved parties need to invest significant time and resources in integrating all aspects of the companies. A well-planned post-merger integration of information technology (IT PMI) by the two M&A parties is considered a crucial and difficult process because IT provides a fundamental infrastructure for integration. Considering various internal and external factors, the two parties normally formulate an IT PMI strategy. The many IT PMI strategies can be categorized into four major types: Renewal, Takeover, Standardization, and Synchronization. This study aims to develop a decision making model to help merger company and IT managers select the proper IT PMI strategy. More specifically, we identify key determinants that need to be considered when selecting a proper IT PMI strategy. The relative importance of each determinant is defined by analytic hierarchy process (AHP) analysis. Finally, this study evaluates each IT integration strategy under the identified determinants.

• Journal of The Korean Association For Science Education
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• v.32 no.8
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• pp.1281-1294
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• 2012

This paper describes the types of models that biology majors use and how they go about making their models in learning key concepts in biology such as the cell membrane, cytoskeleton and cell structure. Initially, a total of 44 biology students from all year levels enrolled in the second semester of calendar year 2008-2009 were asked to make their respective models of the cell membrane, cytoskeleton and cell structure. They were also asked to answer an open-ended questionnaire. Of the 44, only 20 (five from each year level) were randomly selected for a one-on-one interview. Results showed that the student-generated models from all year levels were mostly analogies, some textbook definitions and occasional drawings. In making their model, students first read the text; second, outline similarities in structure and function or both; and third, make the model. Data suggest that models are good diagnostic tools for identifying critical thinking skills of students. In this case, students mostly demonstrate the ability to recognize similarities in structure and function between the concept and their model. Some senior students demonstrated integration and reflective thinking in making their models. Thus, more opportunities for student-generated models must be available if students were to develop integration and reflective thinking in their models.