• Journal of the Korean Society of Food Culture
• /
• v.34 no.3
• /
• pp.277-283
• /
• 2019

This study explore the market segmentation based on beer consumers' purchase motivation 1) to analyze beer consumers and markets more closely and 2) to demonstrate the characteristics of each market segment and contribute to marketing strategies with beer consumer segment. Using -administrated questionnaires asked questions recognizable beer purchase within 6 months by over 20-years-olds, this study 201 surveys online 22 days. The results as follows: beer consumers' purchase motivation consisted of three factors enhancement, social orientation, and value enhancement. Cluster analysis based on beer purchase showed that there were three groups motivation multi-motivation and motivation group based on average value of beer purchase motive factors and relative load per factor. demographic,beer drinking characteristics and group difference according to cluster gender and monthly average income, and beer drinking characteristics also significantly different by preferred beer, preferred beer type, occasion and drinking place.

• Journal of the Korea Convergence Society
• /
• v.11 no.9
• /
• pp.219-227
• /
• 2020

Smart Factory is one of the fastest developing and changing fourth industrial revolution fields. In particular, the degree of introduction and maturity level in the smart factory is an important part. In this paper, a cluster analysis of companies introduced smart factory was performed based on a new maturity assessment model. The 68% of 193 companies surveyed were at the basic level, with only 21% being the middle one. Most SMEs cited lack of funds as the main reason for not entering the middle one. As a result of the cluster analysis, it was found that all clusters had similar patterns but grouped into one of three levels of high, middle, and low depending on maturity level of smart factory operation, and process domain had the highest maturity and data domain was lowest among the 6 domains. Through this, analysis of more specific and quantified maturity levels can be performed using 6-domain smart factory maturity evaluation model.

• International Journal of Computer Science & Network Security
• /
• v.22 no.6
• /
• pp.7-12
• /
• 2022

The modern stage of society's development is characterized by the rapid penetration of information technologies into all spheres of life. Their use contributes to improving the quality of tourism services, as well as the competitiveness of tourism industry enterprises. The role of information technology in tourism is growing more and more every year, which determines the relevance of the study of modern trends in the use of information technology in the tourism sector. The purpose of the study is to determine the possibilities of using information technologies to improve the quality of services provided to the tourism industry under the COVID-19 restrictions. The article systematizes the main approaches to the "cluster" category and provides an original definition of the "regional tourist cluster" concept. Based on an expert survey, the main trends in the introduction of information technologies in the tourism industry under the COVID-19 restrictions have been identified, which include virtual reality and augmented reality, speech recognition technologies, photo, video, audio (contactless control technologies), mobile IT applications and Big Data technologies. It has been concluded that the vast majority of improvements in the organization of tourism services under restrictions will be based on the organization of virtual solutions and online activities. The types of tourism services will also change, and information technology will help their development and dissemination.

• Proceedings of the KIEE Conference
• /
• 2004.05a
• /
• pp.62-64
• /
• 2004

P2P Systems have grown dramatically in recent years. Now many P2P systems have developed and been confronted by P2P technical challenges. We should consider how to efficiently locate desired resources. In this paper we integrated the existing pure P2P and hybrid P2P model. We try to keep roles of super peer in hybrid and concurrently use pure P2P model for searching resource. In order to improve the existing search mechanism, we present contents-based classification mechanism. Proposed system have the following features. This can forward only query to best peer using RI. Second, it is self-organization. A peer can reconfigure network that it can communicate directly with based on best peer. Third, peers can cluster each other through contents-based classification.

• Korean Journal of Social Welfare Studies
• /
• v.47 no.4
• /
• pp.333-360
• /
• 2016

Social Impact Bonds(SIBs) has emerged as a promising way to finance proven social services programs, fund what works, and drive government accountability and has increased fast. In this context, this study examines and classifies the structure of SIB focusing key criteria of the main steps through two-step cluster analysis. Analysis results are as follows. First, the main commissioners of SIB are the ministries of the central government. And in terms of the stage of invest, there are usually two or three investors mainly consisting of social finance organizations. Second, in terms of target and age of SIB beneficiaries, it focuses on the adolescent and youth. Third, in the outcome evaluation stage, the results show that in most cases outcome payments are determined by a validation of service provider or government administrative data. However, the rate of payments are based on the comparison of the program beneficiaries to other comparable groups is 23.8%. Finally, The results of two-step cluster analysis are as; 'mix of central government and social finance organization', 'multiple agent including private organization', and 'multiple social provider'. Among three types, 'multiple agent including private organization' shows the most active participation between agents and the most systematic outcome measurement and management. The results of this study imply that the importance of the method to manage and measure outcome in SIB structure. Moreover, the consist of commissioners or investors is needed to expanded more.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.18 no.4
• /
• pp.97-110
• /
• 2022

The purpose of this study is to analyze the level of public data convergence capabilities of administrative organizations and to explore important variables in data-based organizational capabilities. The theoretical background was summarized on public data and use activation, joint use, convergence, administrative organization, and convergence constraints. These contents were explained Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. The research model was set as the data-based organizational capabilities effect by a data-based administrative capability, public data operation capabilities, and public data operation constraints. It was also set whether there is a capabilities difference data-based on an organizational operation by the level of data convergence capabilities. This study analysis was conducted with hierarchical cluster analysis and multiple regression analysis. As the research result, First, hierarchical cluster analysis was classified into three groups. It was classified into a group that uses only public data and structured data, a group that uses public data on both structured and unstructured data, and a group that uses both public and private data. Second, the critical variables of data-based organizational operation capabilities were found in the data-based administrative planning and administrative technology, the supervisory organizations and technical systems by public data convergence, and the data sharing and market transaction constraints. Finally, the essential independent variables on data-based organizational competencies differ by group. This study contributed. As a theoretical implication, this research is updated on management information systems by explaining the Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. As a practical implication, the activity reinforcement of public data should be promoting the establishment of data standardization and search convenience and elimination of the lukewarm attitudes and Selfishness behavior for data sharing.

• Health Policy and Management
• /
• v.33 no.2
• /
• pp.118-128
• /
• 2023

Background: Personal socio-economic abilities are crucial as it affects health inequalities. These multidimensional inequalities across the regions have been structured and fixed. This study aimed to analyze health vulnerabilities by regional cluster and identify regional health disparities of self-rated health, using nationally representative cross-sectional data. Methods: This study used personal and regional data. Data from the Community Health Survey 2021 were analyzed. K-means cluster analysis was applied to 250 si-gun-gu using administrative regional data. The clusters were based on three areas: physical environment, health-related behaviors and biological factors, and the psychosocial environment through the conceptual framework for action on the social determinants of health. And binary logistic regression analyses were conducted to examine the differences in self-rated health status by the regional clusters, controlling human biology, environment, lifestyle, and healthcare organization factors. Results: The most vulnerable group was group 3, the moderate vulnerable group was group 1, and the least vulnerable group was group 2. The group 2 was more likely to have high self-rated health status than the moderate vulnerable group (odds ratio [OR], 1.023; p<0.001). And the group 3 showed low self-rated health status than the moderate vulnerable group (OR, 0.775; p<0.001). However, the moderate vulnerable group had significantly higher self-rated health status than the most vulnerable group (group 2: OR, 1.023; p<0.001; group 3: OR, 0.775; p<0.001). Conclusion: These results demonstrate that community members' health status is influenced by regional determinants of health and individual levels. And these contribute to understanding the importance of specific and differentiated interventions like locally tailored support programs considering both individual and regional health determinants.

• Journal of the Economic Geographical Society of Korea
• /
• v.20 no.1
• /
• pp.105-120
• /
• 2017

Chung-ju enterprise city was selected as a model enterprise city in 2005, and the city is planned to finish the construction in 2020. The main purpose of this study is to suggest the developing strategy and activation plan for Chung-ju enterprise city based on the enterprise city of developed countries. Chung-ju enterprise city will grow into well-being self-sufficient city due to the cutting edge knowledge, industry-centered cluster which is the new growth industry of Chungchungbuk-do and the surrounding excellent nature. For the success of Chung-ju enterprise city, the cooperation between developing agents such as companies, universities, local government, and central government is important. The leading companies and researching facilities should be attracted as well. Also, non-profit exclusive organization must be installed. The successful development of Chung-ju enterprise city means the success of balanced region development policy which will solve overpopulation of capital region and unbalance of Korea.

• Genomics & Informatics
• /
• v.10 no.4
• /
• pp.263-265
• /
• 2012

We developed a user-friendly, interactive program to simultaneously cluster and visualize omics data, such as DNA and protein array profiles. This program provides diverse algorithms for the hierarchical clustering of two-dimensional data. The clustering results can be interactively visualized and optimized on a heatmap. The present tool does not require any prior knowledge of scripting languages to carry out the data clustering and visualization. Furthermore, the heatmaps allow the selective display of data points satisfying user-defined criteria. For example, a clustered heatmap of experimental values can be differentially visualized based on statistical values, such as p-values. Including diverse menu-based display options, QCanvas provides a convenient graphical user interface for pattern analysis and visualization with high-quality graphics.

• Genomics & Informatics
• /
• v.9 no.2
• /
• pp.89-91
• /
• 2011

DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable information such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.