• Journal of Korea Port Economic Association
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• v.19 no.1
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• pp.1-22
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• 2003

Recently, the cluster-based industrial policy has become a powerful policy tool for strengthening the competitiveness of nations, industries and firms. The concept of cluster develops as firms choose to locate in each others proximity. Cluster concept can be usefully applied to analyze cluster of port-related activities. Port cluster can be used as a systematic foundation for providing one-stop value added logistics service to its customers. The main purpose of this paper is to suggest a way for establishing the port cluster in Korean seaport. For this aim, the paper defines a concept of port cluster and examines the its necessity. And the procedure for establishment of port cluster in Korea is proposed. In addition, the paper analyzed the port cluster structure-conduit-performance. Especially, the role of port cluster's participants, central and local government, universities and related R＆D institutes, and private companies, are suggested respectively. As a conclusion, policy suggestions for the establishment of port cluster in Korea are suggested.

• Journal of the Economic Geographical Society of Korea
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• v.6 no.2
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• pp.327-338
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• 2003

The concept of industrial cluster began with the agglomeration economies occurring in a small scale place, which are mainly drawn from intense networking between companies, universities, research centers and other institutional bodies. Recently, however, as cooperation between autonomous administrative units and between industrial clusters has been more active than ever, there has emerged the concept of extended industrial cluster (EIC) and, subsequently, policy measures for nurturing it. This study focuses on the concept of EIC, mainly in the perspective of the need to adopt it into the industrial cluster literature. The study identifies the raison d'etre of EIC in the respects of the flexibility of geographic range, complementarity and cooperation between functions and regions, scale economies and productivity, and the development stage of industrial clusters. It also suggests how to establish the concept of EIC in the Korean context and how to apply EIC policy in the Korean industrial policy.

• Journal of the Korean Geographical Society
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• v.52 no.1
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• pp.55-71
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• 2017

This paper points out the semantic unclearness of the jargon "cluster" and suggests the substitution of "industrial cluster" for "cluster". Industrial cluster is the intersection of industrial agglomeration and cluster phenomenon while the actual concept of cluster includes not only industry cluster but also political administration cluster, science research cluster, art cluster, religion cluster, education cluster, etc. Partially reconstructing the concept and significance of industry cluster, industrial cluster is a geographic agglomeration of interconnected productional businesses in a particular industry, forming close industrial networks. The advantage of the agglomeration includes reducing the transaction cost between the businesses, promoting technological innovation and dispersion, facilitating the utilization of the professional workforce, sharing and connecting the external customer. Moreover, this paper discusses the range of the industrial cluster and its distinctness from the other similar concepts. There is a need to discriminate it from the other related jargons and to clarify their relationship. In particular, there is a task to eradicate the mixed usage of industrial cluster with the jargons related to space for learning and innovation.

• Journal of Technology Innovation
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• v.13 no.2
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• pp.23-43
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• 2005

Industrial clusters are geographical concentrations of interconnected companies, specialised suppliers, service providers, firms in related industries, and associated institutions (for example, universities, standard agencies, and trade associations) that combine to create new products and/or services in specific lines of business. At present, the concept of industrial cluster becomes very popular worldwide, policy makers at national, regional and local levels and business people in both forerunner and latecomer countries are keen to implement the cluster concept as an economic development model. Though understanding of clusters and related promoting policies varies from one place to another, the underlying benefits of clusters from collective learning and knowledge spillovers between participating actors strongly attract the attention of these people. In Thailand, a latecomer country in terms of technological catching up, the cluster concept has been used as a means to rectify weakness and fragmentation of its innovation systems. The present Thai government aspires to apply the concept to promote both high-tech manufacturing clusters, services clusters and community-based clusters at the grass-root level. This paper analyses three very different clusters in terms of technological sophistication and business objectives, i.e., hard disk drive, software and chili paste. It portrays their significant actors, the extent of interaction among them and the evolution of the clusters. Though are very dissimilar, common characteristics attributed to qualified success are found. Main driving forces of the three clusters are cluster intermediaries. Forms of these organizations are different from a government research and technology organization (RTO), an industrial association, to a self-organised community-based organization. However, they perform similar functions of stimulating information and knowledge sharing, and building trust among participating firms/individuals in the clusters. Literature in the cluster studies argues that government policies need to be cluster specific. In this case, the best way to design and implement cluster-specific policies is through working closely with intermediaries and strengthening their institutional especially in linking member firms/individuals to other actors in clusters such as universities, government R&D institutes, and financial institutions.

• Journal of Technology Innovation
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• v.14 no.2
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• pp.167-181
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• 2006

This paper reviews regional innovation policy in Japan. 'Technopolis' policy, the first technology-based regional development policy in the world, was implemented in Japan. Nonetheless, technology-based regional endogenous development did not occur. Then, regional technology transfer was pursued. In order to make use of universities and public research institutes in a region for development, university-industry collaboration and cross-over, such as university spin-offs, were promoted. Within this background, new technology-based regional development policies have been introduced based on a cluster approach. These policies are the knowledge cluster Initiative and the industrial cluster program. However, existing companies have difficulty in carrying out innovation. This paper argues that a cluster to create new start-ups that carry out innovation is also needed and explains a new concept of venturing cluster. Based on this new cluster concept, this paper analyzes the situation of Sapporo in Japan, where many university spin-offs are being created in the biotechnology field.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.107-116
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• 2014

The purpose of this study is to verify the applicability of concept mapping in the process of planning social welfare program based on community network. Concept mapping is a kind of decision-making method that structuralized complex ideas and presented visually. Already, concept mapping is widely utilized in counseling, nursing and public health area to plan and evaluation their program and service. For recent, effectiveness of concept mapping has been reported. Concept mapping is a effective decision-making method that they recognize outcome gap between service provider and client, reach the outcome's consensus in counseling and nursing, medical area. In this study, we conceptualized 3rd year outcomes of Community Impact Project that was supported from Busan Chest using concept mapping. This CI project intervenes children and youth who lives in Buk-gu, Busan. Concept mapping has six stages-preparation, collecting ideas, structuring statements, representing statement, interpreting the results of the analysis, applying the results. We followed these steps. The participants were working at social welfare organizations, total 11 persons. We obtained 60 statements and analyzed using multidimensional scaling. we collected 5 clusters, cluster 1 'awareness and attitude change of children and youth', cluster 2 'social system change of children and youth', cluster 3 'friendly community formation', cluster 4 'community people change', cluster 5 'service provider change'. As a result, among total 5 clusters formed, 'awareness and attitude change of children and youth' came to the strongest outcomes. When concept mapping was applied to the program planning, the consensus of the opinion came easily in the decision-making process, and the participants were empowered. In addition, clear conceptualization on each element of the program planning was made.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• Journal of Families and Better Life
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• v.26 no.3
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• pp.1-14
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• 2008

The purpose of the study was to examine the internet purchase behavior of items and self-assessment according to self-concept of elementary school students. The data were collected from 716 elementary school students by a self-administered questionnaire. Frequencies and means, Cronbach's Alpha, factor analysis, t-test, Pearson's correlation analysis, cross-tabulation analysis, cluster Analysis were conducted by SPSSWIN 12.0. The results from this study were as follows; First, from self-concept measurements, 4 factors(affective, social, schooling, Family self-concept) were extracted through factor analysis. Second, the subjects were classified into 3 clusters as self-concept types(high self-concept, middle self-concept, low self-concept) through cluster analysis. Third, the significant variables affecting internet purchase behaviors of items included grade, allowance, rank in class, the number of hours on the internet. As the self-concept gets higher, the frequence of the impulsive purchase and imitation purchases gets lower. In the contrary, as the self-concept gets higher, the self-assessment on the impulse purchases and imitation purchases also gets higher. In combination, these results suggest that irrational purchase behaviors were protected by positive self-concept, therefore it is important that children have positive a self-concept.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.3
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• pp.302-318
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• 2008

As socio-economic paradigms have been moving towards the knowledge-based capitalism from the industrial capitalism, it is obvious that research on industrial agglomeration and regional innovation has been explosively increased. However, there is a contradictory tendency that the terms and concepts, which are related to industrial agglomeration, have became less clear and more fuzzy. In this sense, this paper attempts to tackle and reconsider the concept, typology and theories of agglomeration and (or) cluster in economic geography. The main claims are as follows. Firstly, the terms and concepts related to industrial agglomeration and cluster need to be clear. It seems to be that cluster is received as an umbrella concept of agglomerations all-embracing the varieties of a geographical concentration of industry. However, the authors claim that the cluster concept should be part of the diverse types of industrial agglomeration. Secondly, the tendency of a less clear definition on agglomeration and cluster could make it difficult to identify the types of agglomeration being in the forms of diversity. Such a tendency would result in a misguided understanding and interpretation of a typology of agglomeration. Finally and most importantly, as perspectives or theories that are associated with industrial agglomeration and cluster show increasingly a propensity of convergence, it is problematic that related theories and perspectives lose their own identity and distinctiveness.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.107-112
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• 2022

Nowadays clusters are recognized as an important instrument for promoting industrial development, innovation, competitiveness and growth. An educational cluster is a set of interrelated vocational educational institutions of various levels that are united by industry with each other and are connected by partnership with industry enterprises. This article attempts to develop and describe cluster model of university students' multilingual training. The purpose of this study is to describe multilingual training of university students and their polycultural competencies formation and to define the process of multilingual training in form of a cluster. The authors consider clusters as an integral part of the educational campus within the concept framework of Shadrinsk State Pedagogical University. To determine the essence of the concept of a cluster model of university students' multilingual training, theoretical, empirical, observational, and diagnostic methods were implemented, such as a review of scientific literature, a compilation of best practices, observation, statistical methods, etc. The authors analyzed the programs of partner universities and organized international webinars and internships for bachelors and masters abroad and developed online courses "Foreign language for undergraduate students and masters". Experimental data obtained during the implementation of cluster training show the effectiveness of the formation of students' polycultural competencies.