• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.15-32
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• 2006

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiple criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interactions may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.123-140
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• 2023

In recent times, the global economy has been subject to increasing volatility, which has made it considerably more difficult to accurately predict economic indicators compared to previous periods. In response to this challenge, the present study conducts an exploratory investigation that aims to predict the Business Survey Index (BSI) by leveraging data mining techniques on both structured and unstructured data sources. For the structured data, we have collected information regarding foreign, domestic, and industrial conditions, while the unstructured data consists of content extracted from newspaper articles. By employing an extensive set of 44 distinct data mining techniques, our research strives to enhance the BSI prediction accuracy and provide valuable insights. The results of our analysis demonstrate that the highest predictive power was attained when using data exclusively from the t-1 period. Interestingly, this suggests that previous timeframes play a vital role in forecasting the BSI effectively. The findings of this study hold significant implications for economic decision-makers, as they will not only facilitate better-informed decisions but also serve as a robust foundation for predicting a wide range of other economic indicators. By improving the prediction of crucial economic metrics, this study ultimately aims to contribute to the overall efficacy of economic policy-making and decision processes.

• Journal of Sasang Constitutional Medicine
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• v.29 no.2
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• pp.128-135
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• 2017

Objectives The purpose of this study is to investigate economic decision-making in accordance with Sasang Constitution through Ultimatum Game. Methods 84 subjects classified as Sasang Constitution played Ultimatum Game in two session which are firstly not facing their opponents(responders) and secondly facing ones. And they were also proposed unfair offers(9:1) in the same two session. Amount of proposal and whether they accept or reject to unfair offers were observed. Results and Conclusions Taeeumin tended to offer more to his/her responder in Ultimatum Game when facing the responder then not. Taeeumin seemed to feel more burnden when he/she was facing the responder while Soyangin or Soeumin didn't.

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.6
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• pp.329-339
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• 2019

The strategy for the management of earthquakes is shifting from post recovery to prevention; therefore, seismic performance management requires quantitative predictions of damage and the establishment of strategies for initial responses to earthquakes. Currently, seismic performance evaluation for seismic management in Korea consists of two stages: preliminary evaluation and detailed evaluation. Also, the priority of seismic performance management is determined in accordance with the preliminary evaluation. As a deterministic method, preliminary evaluation quantifies the physical condition and socio-economic importance of a facility by various predetermined indices, and the priority is decided by the relative value of the indices; however, with the deterministic method it is difficult to consider any uncertainty related to the return-year, epicenter, and propagation of seismic energy. Also this method cannot support tasks such as quantitative socio-economic damage and the provision of data for initial responses to earthquakes. Moreover, indirect damage is often greater than direct damage; therefore, a method to quantify damage is needed to enhance accuracy. In this paper, a Seismic Risk Assessment is used to quantify the cost of damage of road facilities in Pohang city and to support decision making.

• Journal of Information Science Theory and Practice
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• v.11 no.2
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• pp.67-81
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• 2023

This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.43-48
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• 2019

The purpose of the study was to examine early childhood teachers' content knowledge of economic education. The subjects, 60 early childhood teachers, were asked to draw concept maps about early childhood economic education. Their concept maps were analyzed in terms of superordinate and subordinate concepts by contents and frequencies. The results were as follows. First, 248 superordinate concepts were shown, and they were categorized into nine representative terms: 'Scarcity and Choice,' 'Decision Making,' 'Monetary Value,' 'Production,' 'Consumption,' 'Distribution,' 'Restrain,' 'Reuse,' and 'Economic Education Activity.' Second, 1,440 subordinate concepts were shown, and 'coin,' 'bill,' 'saving,' 'bank,' and 'money' were frequently shown. Third, the mean numbers of subordinate concepts per superordinate concepts showed that early childhood teachers had more knowledge about 'Consumption,' 'Monetary Value,' and 'Economic Education Activity' than other superordinate concepts. The results showed the need for early childhood teachers to have more systematic and hierarchical pedagogical content knowledge on economic education.

• 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 Digital Convergence
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• v.15 no.12
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• pp.169-185
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• 2017

Given that nowadays things get very fast due to the pervasive use of the Internet and mobile devices, decision-making time can be an important variable in the online economic decisions. Although in experimental and behavioral economics, measures like scores or earnings are usually preferred, this study argues that the time variable can be dealt with as a new decision outcome. Thus, by selecting some psychological factors presumably impactful in the online context (i.e., incidental emotions, psychological distances, and individual's impulsivity), this study tested their effect on decision time in the online centipede game. As a result, the mean decision time in the game was longer (1) in the happiness condition than in the anger condition and (2) in the friend condition than in the stranger condition. The people with attention difficulties spent a short time in the decision and the people who dislike complex problems spent a short time in explaining their decision. This study can contribute to the field as it used the decision time as the dependent variable and it tested the effect of psychological factors in the context of online decision-making. Future studies can be conducted in other online decision situations or by considering other psychological variables.

• Journal of Environmental Impact Assessment
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• v.14 no.4
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• pp.179-193
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• 2005

As the world's attention turns to sustainability and the considerations of cumulative effects, the concept of Strategic Environmental Assessment(SEA) has become more significant and urgent and increasing number of countries and international organizations now undertake some forms of SEA. The term SEA, however, is variously defined and understood; generally it means a formal process of systematic analysis of the environmental effects on development policies, plans, programmes and other proposed strategic actions. This process extends the aims and principles of EIA upstream in the decision-making process, beyond the project level in which major alternatives are still open. There is a shift toward more integrative approaches and greater use of Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) as sustainability tools in cooperation with Environmental Management System (EMS). Currently, Korea has EIA system and Prior Environmental Review System (PERS) which is different type of SEA as Environment Assessment (EA) system. APEMI IA MODEL integrated following three pillar(refer to attached figure.1) ; First pillar symbolized decision making cycle with planning process. Second pillar symbolized integrated assessment which tying SEA and EIA with specific impacts assessment(eg: social impact assessment, economic impact assessment, health impact assessment etc) in cooperation with EMS. Third pillar symbolized EA best practical procedure of International Association for Impact Assessment(IAIA). Considering the above, we applied new conceptual model(APEMI IA MODEL) into Impact Assessment for better integrated decision-making in KOREA as an alternative IA system(IS IA MODEL A and B refer to attached figure 4, 5).

• Health Policy and Management
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• v.19 no.3
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• pp.166-182
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• 2009

Objectives : This study was undertaken to investigate the relationship between career decision-making self-efficacy, social support, career education experience, career attitude maturity for college students with major in health administration. Methods : The subjects were 395 students with major in health administration from 2 universities and 2 colleges located in Incheon city, Gyeonggi province, and Chungcheognam province. Data were collected from June 2 to 20, 2008 using structured questionnaires. Results : For the difference by characteristics of the respondents, the score of career attitude maturity were significantly different according to age(F=3.415), high school style(F=2.661), subject economic status(F=3.627), subject satisfaction of school life(F=7.964), subject health status(F=6.507). For the correlation of major variable, Career attitude maturity was positively correlated with career decision-making self-efficacy, social support from friends, social support from family, social support from professor, career education experience. In a regression analysis, career decision-making self-efficacy($\beta$=.378), social support from friends($\beta$=.198), age($\beta$=.124), grade($\beta$=-.161) significant predictors to explain career attitude maturity(32%). Conclusions : It is necessary to activates the social network from friends and to develop an effective program to improve career attitude maturity of students with major in health administration considering these findings.