• Journal of the Economic Geographical Society of Korea
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• v.6 no.1
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• pp.45-60
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• 2003

As the process of economic globalization deepens market uncertainty and severe competition, modern companies are tend to rely on non-market, socio-economic mechanisms such as trust, collaboration, and interdependence, They are being more influenced by cultural economic mechanisms like networks, embeddedness, and placeness rather than explicit cost-reductions. This paper analyzes the characteristics of industrial clusters, the formation of social capital, and the process of institutionalization by comparing two distinctive types of clusters, say Teheran and East-Gate Valleys in Seoul, Korea. The one is mainly consisted of IT industries with increasing vertical integration supported by venture capitals and favorable business infrastructures. The other cluster has long been a traditional CBD frame of Seoul and has transformed to the most dynamic and productive area, characterized by one-stop 'R&D-production-distribution-consumption-after sales services'. The study of the developmental trajectory and key characteristics for these kinds of clusters can give us insight for the cluster theory. This paper firstly reviews the similarities and differences between the social capital in general and that of industrial clusters. It then profiles the growth of the two clusters over the past decade, and compares the current spatial and business structure of the two clusters, focusing on transactions costs, the creation and flow of information, and the local institutions. The paper concludes with some comments about the prospects and perils of the two types industrial clusters of Seoul.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.65
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• pp.41-50
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• 2001

Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and intercluster similarity is minimized. The discovered clusters from clustering process are used to explain the characteristics of the data distribution. In this paper we propose a new methodology for clustering related transactions with categorical attributes. Our approach starts with transforming general relational databases into a transactional databases. We make use of inter-dimensional association rules for composing hypergraph edges, and a hypergraph partitioning algorithm for clustering the values of attributes. The clusters of the values of attributes are used to find the clusters of transactions. The suggested procedure can enhance the interpretation of resulting clusters with allocated attribute values.

• Journal of Industrial Convergence
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• v.14 no.1
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• pp.39-45
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• 2016

This paper deals with the consideration of mathematical models with regards to growth of cluster and firms by reviewing the Metcalf and Breuner's articles. prior studies have been argued the phenomenon of local industrial clusters and districts. Several concepts have been adopted to support the success of and changes to these clusters and firm growth. Through the review of two papers, evolution of both cluster and firm growth may be achieved in terms of utilizations of the different local aspects and mechanisms. This paper supports the theoretical back bone with regards to the regional cluster policy implementing in Korea for the purpose of regional developments. In particular, a mathematical model that, on a more abstract level, captures the fundamental dynamic structure of all the observed mechanisms. On the basis of this model, the emergence and evolution of local clusters can be described. Also this model has given that the knowledge sharing between firms has an important role to firms and cluster' growth.

• Advances in nano research
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• v.4 no.2
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• pp.113-128
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• 2016

Luminescent metallic clusters have attracted great interest due to their unique optical, electronic and chemical features. Comparing with intensively studied Au and Ag Clusters, Cu clusters are superior in the aspects of cost and wide industrial demanding. However, tiny copper clusters are extremely prone to aggregate and undergo susceptibility of oxidation, thereby the synthesis of fluorescent zero valent copper clusters is rather challenging. In this review, synthetic strategies towards luminescent copper clusters, including macromolecule-protection and micro molecule-capping, have been systematically surveyed. Both "bottom-up" and "top-down" synthetic routes are found to be effective in fabricating luminescent copper clusters, some of which are quite stable and possess decent luminescence quantum yields. In general, the synthesis of fluorescent copper clusters remains at its infant stage. A great deal of effort on developing novel and economic synthetic routes to produce bright and stable copper clusters is highly expected in future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.1
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• pp.133-158
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• 2011

In 2030s, as we enter in to the era of BT (Bio-Technology) market opening up, technologies in all areas such as IT, data analysis, IC and biochemistry are necessitated. New development in technology will be based on "Convergence", especially between IT and BT. In order to have synergy effects from the convergence, those related industries and universities should be physically inter-related in an appropriate location. Until 2009, 819 industrial clusters where many Korean industries and firms are concentrated have been constructed in Korea. They have had supports from various institutions and facilities. However, few systems designed to assist "intellectual property (IP) service" for technology convergence are found in Korea. Thus, by analyzing current problems and challenges of the Korean industrial clusters, this paper suggests a possible answer to maximize the synergy from technology convergence through organic cooperation among companies in industrial clusters. This paper finds that the Korean industrial clusters need to establish IP service supporting center while suggesting its function and concept on organization structure, and work flow, which help firms to develop IP strategies. In addition, the paper provides a direction for current IP system and policies implemented by the Korean government to be more effective to small-and-medium-sized companies located in the industrial clusters.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.1-8
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• 2018

K-means algorithm is one of the most popular and widely used clustering method because it is easy to implement and very efficient. However, this method has the limitation to be used with fixed number of clusters because of only considering the intra-cluster distance to evaluate the data clustering solutions. Silhouette is useful and stable valid index to decide the data clustering solution with number of clusters to consider the intra and inter cluster distance for unsupervised data. However, this valid index has high computational burden because of considering quality measure for each data object. The objective of this paper is to propose the fast and simple speed-up method to overcome this limitation to use silhouette for the effective large-scale data clustering. In the first step, the proposed method calculates and saves the distance for each data once. In the second step, this distance matrix is used to calculate the relative distance rate ($V_j$) of each data j and this rate is used to choose the suitable number of clusters without much computation time. In the third step, the proposed efficient heuristic algorithm (Group search optimization, GSO, in this paper) can search the global optimum with saving computational capacity with good initial solutions using $V_j$ probabilistically for the data clustering. The performance of our proposed method is validated to save significantly computation time against the original silhouette only using Ruspini, Iris, Wine and Breast cancer in UCI machine learning repository datasets by experiment and analysis. Especially, the performance of our proposed method is much better than previous method for the larger size of data.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.1
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• pp.35-55
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• 2020

The support policy of Micro manufacturers clusters should reflect the regional characteristics of Micro manufacturers clusters, but only similar policies are proposed based on the normal collection of information from related companies. Since the regional characteristics of Micro manufacturers clusters are not understood, they are not reflected in the support policy. Therefore, this study analyzed the characteristics of Micro manufacturers clusters as the formation factors of localization, networking/embeddedness, and innovation synergy/collective learning which are the characteristics of clusters, and applied the development stage based on the analyzed formation factors. Since regional characteristics may be different in the same industry, Micro manufacturers clusters in Changsin and Jangwi, which are representative clusters of apparel sewing industry in Seoul, were compared and studied in terms of regional characteristics and developmental stages. As a result of analyzing the characteristics of Apparel Sewing Micro manufacturers clusters, clusters of peers were found to be higher in Changsin than in Jangwi in localization. However, in the synergy and group learning, the Changsin area was mainly centered on designers and the Jangwi area was centered on Micro manufacturers, the Changsin area was active while the Jangwi area was passive in participating in fairs and seminars, and in sample and production. As a result of examining the two formation factors, the development stage of Micro manufacturers clusters in the two regions is progressing beyond the industrial district in the case of Micro manufacturers clusters in Changsin apparel sewing, and the Micro manufacturers clusters in the Jangwi apparel sewing are analyzed to stay in the industrial district. Innovative and long-established garment sewing clusters suggest that the government's support policy needs to reflect the characteristics and development stages of the two regions for sustainable growth.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3446-3451
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• 2011

Nowadays, industry clusters have been considered as critical factors for regional competitiveness and economic revitalization. It should be important to evaluate strategic positioning and establish competition strategies for Korean industry clusters. I proposed strategic positioning, identified problems, and established strategic directions by analyzing potential attractiveness based on growth and productivity and retained capabilities of proximity, networks, correlation and revenue increase for 7 regional industry clusters. In addition, I analyzed best practices of global industry clusters to provide implications on establishing competition strategies.

• Journal of Technology Innovation
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• v.11 no.1
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• pp.195-214
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• 2003

Sweden's regional innovation system is built mainly on innovative clusters, several of them - in automobile, steel, new materials, information and telecommunication, and bioscience - world-class. Most successful clusters were developed at local bases imbued with local history. In fact, a cluster's competitiveness is intimately related to its closeness of fit with its local environment. Geographically dispersed clusters in Sweden - some national, others local, and some local but deemed members of a national cluster as well - have already created many new competitive products and services. In 2001, Sweden has eight national and nine regional clusters, and envisioned eleven national and five regional clusters more. The experience of Swedish clusters indicate several elements that determine the ability of cluster policies to promote and strengthen regional economic growth. Cluster policies require strong public sector support, particularly in the form of providing basic national conditions. Regional cluster policies place new demands on national and regional industrial policies. All policies must be closely interwoven without compromising their primary allegiance to their respective areas.

• Knowledge Management Research
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• v.17 no.3
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• pp.65-91
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• 2016

Although the success of industrial clusters largely depends on whether clustering firms can achieve economic performance, there has been less attention on investigating factors and conditions contributing to the performance enhancement for clustering small and medium-sized enterprises (SMEs). Along this vein, we adopt the theories of social capital and organizational learning as those success factors for clustering SMEs. This study thus aims at examining what effect social capital accrued in the relationships among actors within clusters has on firm performance of clustering SMEs and what role organizational learning plays in the linkage between social capital and firm performance. For the empirical analysis, we operationalized the variables and their measures to develop questionnaires through the theoretical reviews on literatures. As a sample of 227 clustering SMEs, our collected data was analyzed by hierarchical regression analysis. The results confirmed that a high level of social capital, represented by network, trust, and norm, has positive effect on firm performance of clustering SMEs. We also found that clustering firms presenting high organizational learning, represented by absorptive and transformative capability, achieve better performance than those placing less value on organizational learning. Furthermore the significant relationship between social capital and firm performance is mediated partially through organizational learning. These findings imply not only that the territorial agglomeration of industrial cluster does not guarantee the performance creation of clustering SMEs but that they need to develop social capital among various actors within clusters, facilitating their knowledge diffusion. In order to absorb and mobilize the shared knowledge and information into strategic resources, the firms should improve their capability associated with organizational learning. These expand our understanding on the importance of social capital and organizational learning for the performance enhancement of clustering firms. Differentiating from major studies addressing benefits and advantages of industrial cluster, this study based on the perspective of firm-internal business process contributes to the literature advancement. Strategic and policy implications of this study are discussed in detail.