• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• Journal of Distribution Science
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• v.12 no.5
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• pp.93-107
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• 2014

Purpose - The pool of entrepreneurs with progressive qualities such as creativity and innovation was considered concurrently with such factors as work and capital that stimulate economic development and growth. This study aims to present a model to support the development of a strategic approach for achieving an overall academic entrepreneurship system in Iran. Research design, data, and methodology - The research design of this study is based on applied research because of its objectives, using principles and techniques formulated for basic research to solve operational and real organizational issues. This design also drives the method used, describing and interpreting the findings. Secondary data (library research) was used for this study's data collection. Because of this research's essential characteristics, no hypothesis is launched, and no research setting, questionnaire design, population or population sampling, validity or reliability tests, or statistical analysis are needed. Results and Conclusions - The model is created using a strategic approach acting in an octal setting comprising social, cultural, legal, economic, political, technological, competitive, and natural environments to present a conceptual framework for future studies.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.9-15
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• 2018

Policy polls, which investigate the degree of support that the policy has for policy implementation, play an important role in making decisions. As the number of Internet users increases, the public is actively commenting on their policy news stories. Current policy polls tend to rely heavily on phone and offline surveys. Collecting and analyzing policy articles is useful in policy surveys. In this study, we propose a method of analyzing comments using deep learning technology showing outstanding performance in various fields. In particular, we designed various models based on the recurrent neural network (RNN) which is suitable for sequential data and compared the performance with the support vector machine (SVM), which is a traditional machine learning model. For all test sets, the SVM model show an accuracy of 0.73 and the RNN model have an accuracy of 0.83.

• Industrial Engineering and Management Systems
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• v.7 no.3
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• pp.245-256
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• 2008

In order to cope with the ill-defined problem of human behavior being immanent uncertainty, several methodologies have been studied in game theoretic, social psychological and political science frameworks. As methods to arrange system elements systematically and draw out the consenting structural model concretively, ISM, FSM and DEMATEL based on graph theory etc. have been proposed. In this paper, we propose a modified structural modeling method to recognize the nature of problem. We introduce the statistical method to adjust the establishment levels in group decision situation. From this, it will become possible to obtain effectively and smoothly the structural model of group members in comparison with the traditional methods. Further we propose a procedure for achieving the consenting structural model of group members based on the structural modeling method. By applying the method to recognize the nature of ill-defined problems, it will be possible to solve the given problem effectively and rationally. In order to inspect the effectiveness of the method, we conduct a practical problem as an empirical study: "Behavior analysis of passengers for the Joban line of East Japan Railway Company after new railway service of Tsukuba Express opened".

• Korean journal of communication and information
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• v.26
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• pp.291-326
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• 2004

This study explores the process within which whereas the majority of Korean people agree on the principle of the unification policy, the opinions about the concrete policy alternatives related to the principle do not converge. To account for this phenomenon, a.k.a. 'the principle-policy puzzle in public opinion', this study constructs and tests a covariance structural model with the explanatory variables such as political knowledge, political ideology, authoritarian personality, social distance, and the evaluation of the president. In addition, the interaction effects of the interpretive frames regarding the unification policy and political knowledge along with the main effects of socio-demographic variables are tested to explain the degree to which people show the gap between the agreements on the unification principle and policy alternatives. A sample of 600 Seoul people are recruited to provide the data for the analysis of structural equation modeling. Ie was found that the proposed model receives empirical supports from the data. In particular, political knowledge and authoritarian personality play key roles in accounting for the complex process of public opinion in the 'principle-policy puzzle'. The findings were discussed in terms of the representations of the Engagement policy in the mass media and the public perception of them.

• Management & Information Systems Review
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• v.37 no.2
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• pp.209-233
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• 2018

This study investigates the question of how political and economic factors may affect the export of renewable energy technologies. The relationships are tested using panel data for 19 OECD member countries over the period 1992-2012. Before establishing the empirical model, the current study checks the characteristics of the panel data, which includes various panel framework analyses, such as tests for the presence of normality, structural breaks, first-order autocorrelation, heteroscedasticity, cross-sectional dependence, panel unit-root. From the panel framework analyses, a dynamic panel model is established to test the relationship between the variables examined in this study. In order to reduce the bias of the estimation of the dynamic panel model and obtain efficient parameters, this study uses the bias-corrected least square dummy variable(LSDVC) estimator to estimate the empirical model. The results of this study show that governmental policies expressed as coercive pressure and market size positively affect the export growth of renewable energy technologies. However, public pressure and traditional energy industry have no significant effects on export performance. Policy implications are presented based on the results of this study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.171-178
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• 2018

Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.

• Journal of Research and Publication Ethics
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• v.1 no.2
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• pp.11-13
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• 2020

Purpose: The author wants to specify scope of research, identify without giving burden, prevent unfair identification of the author, admit of production of the outcome, enact rules of identification, and build up foundation of development. Also, this study defines scope of publication of outcome of research to prevent unfair identification of authors and admit of them. Research design, data and methodology: The study described literary research, standard research, phenomenon research, and empirical result without methodologies, statistical analysis and scientific test and investigated operation system of KODISA cases. Results: At publication of findings of the research, researchers shall identify the ones of production of the finding to allocate help of the research. Conclusions: Scientific journals shall be controlled to develop ability and to grow up and have a system. Researchers shall give direction of other scientific journals. The study made efforts to be a model. KODISA Edition Team shall make an effort to keep and develop. So far, no regulation of identification of authors has produced disturbance so terminologies should be uniformed. Researchers shall keep rules of identification of authors to uniform and regulate identification of authors, conditions of authors, and order and correspondent authors. KODISA enacted rules of identification of authors for the first time in Korea to develop science.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.133-152
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• 2013

This study strives to perform a pilot collection assessment study with the political science collection in a university library. Employing the basic list-checking analysis method, the study scrutinized the collection statistics and the circulation statistics, and check the current library holdings with a standard list which was composed of cited works extracted from course syllabi, theses, dissertations and faculty research papers. Although the study is a pilot case study that a particular model was applied to a collection in the field of political science, the result and procedures of the assessment will provide some implications regarding collection assessment in university libraries.

• Information Systems Review
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• v.8 no.1
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• pp.265-285
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• 2006

The purpose of this research is to identify the major evaluation criteria of IT investment projects and establish the importance weights of criteria through AHP analysis. Seven evaluation criteria which have been drawn from prior studies and industry practices are direct costs, indirect costs, financial benefits, strategic value, risk, technical necessity, and political considerations. Data have been collected from 95 IT projects in 40 public organizations and private firms in Korea. After having applied the data reliability test, 79 projects have been selected. The results of AHP analysis show the importance weights and priorities of seven evaluation criteria as follows: financial benefits 25.2%, strategic value 22.36%, direct costs 14.34%, risk 12.10%, technical necessity 11.55%, political considerations 8.3%, and indirect costs 6.48%. And the weights of seven criteria shows considerable differences among three different IT project types such as transactional, informational, and infrastructural.