• Land and Housing Review
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• v.2 no.4
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• pp.539-552
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• 2011

This research thesis measured potential housing development of 250 'subway station areas' around Seoul Metropolitain Region, with the use of added weighting and data of each indicator based on AHP. The analysis was conducted on the ranking of the development of 'subway station areas' on the basis of measurement results of potential housing development along with the analysis on characteristics of 'subway station areas' in daily life zone. Cluster analysis-oriented analytic measurement results suggested that 'subway station areas' in Seoul Metropolitain Region can be grouped into five clusters: Cluster 1 and Cluster 2 were populated with 'reservation areas' for outside and inside urban development, respectively scoring low all in housing development pressure and capacity. Cluster 3 was populated with 'development maintenance areas', scoring low in housing development pressure but high all in housing development capacity. Cluster 4 was populated with 'development facilitation areas', scored high all in housing development pressure and capacity. Cluster 5 was populated with 'development control areas' scoring high in housing development pressure but low in housing development capacity.

• Journal of Korea Technology Innovation Society
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• v.21 no.4
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• pp.1207-1236
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• 2018

This paper explores the life cycle of innovation cluster, especially focussing on the Korean representative innovation cluster, Daedeok Innopolis. For this purpose, we review theoretically how an innovation cluster has been growing up. In particular, we discuss how a cluster has been formed and activated by governmental innovation policies from an evolutionary perspective. By doing so, the study identifies the typical features of an innovation cluster according to each dimensions of the cluster life cycle. The results of this study are as follows: First, in this study, Daedeok Innopolis has characteristics of latency, emergence, growth, and maturity from evolutionary perspective. Second, the governmental structure of the Daedeok Innopolis is a strong government-led and top-down structure, which has features of inclusiveness and flexibility such as umbrella policy. Third, the Daedeok Innopolis can be seen that adaptive or renewal development, as while, it can be applied fine adjustment the innovation cluster policy towards the recognition of innovation obstacle at each dimensions of the life cycle. Therefore, these discussions expose what kind of policy interventions should be addressed to form and develop the innovation cluster according to the cluster life cycle, as while, the development of adaptive policies during the risk and take-off period. Ultimately, the study provides that a different kind of policy instruments and tools should be implemented according to innovation cluster development and its distinctive characteristic per each dimensions of the cluster life cycle.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.153-170
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• 2013

As global competition of enterprises heats up recently, there is a growing the need to introduce business knowledge platform. Many enterprises work with other partners in a variety of situations and collaboration has emerged as new competitiveness of them. Collaboration improves the performance of members, and besides it has an important bearing on innovation, result, and increased productivity of enterprise. Lots of businesses, locally and abroad, extend the environment of collaboration and try to share business contents efficiently. In addition, they look into ways of invigorating collaboration by providing community tools. Corporations and Governments around the world are pushing smart work to respond effectively to this paradigm change. Smart work provides many types of collaboration and raises the productivity. Various infrastructures should be constructed for activating smart work. Most of all, core technology is to be developed. Virtual Cluster is the space of collaboration corresponding to change in business paradigm. In overseas policy of Virtual Cluster has been already enforced as an alternative to geographical cluster. The establishment and development of collaboration platform through Virtual Cluster can contribute to business competitiveness by smart work.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.1-24
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• 2014

The new Korean government sets its main policy direction as Creative Economy. The Creative Economy can be defined as a growth strategy that establishes new companies, enhances the competitiveness of established companies and creates new markets, industries and jobs in consequence of combining of creative imagination, science and technology and ICT. In this context, the concept of innovation cluster, which aims to foster technological innovations from an organic ecosystem perspective, can be a valid policy instrument for attaining Creative Economy. Innovation cluster can and must make a contribution to achieving the Creative Economy of Korea. In particular, the ICT Convergence Innovation Cluster will be a good strategy for this purpose. Based on this conceptual background, this paper analyzes a recently notable case of an ICT Convergence Cluster in Korea, Pangyo Technovalley (PTV). We argue that the Pangyo Technovalley is a representative cluster of converging ICT and science and technology. We identify the major factors for successful development of ICT cluster: regional government's flexible response to environmental change, careful pre-planning and balance between private and public involvement. In addition, we also found that additional factors, settlement condition for securing good workforce, agglomeration of various innovation actors for promoting convergence, and cluster network revitalization are also important for implementing the creative ICT convergence cluster.

• Journal of the Korean Home Economics Association
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• v.43 no.9 s.211
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• pp.1-13
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• 2005

The purposes of this study were to classify internet shopping mall user by their shopping styles and to define the characteristics of the classified individual clusters. Questionnaires were completed by 338 men and women who have used internet shopping malls at lead once during the previous 6 months. The internet shopping styles were classified into 4 clusters after factor analysis and k-means cluster analysis. Cluster I, named 'high brand proneness', can be described as having low score on devotee tendency. Cluster II, named 'high value proneness', is characterized by a high score on seeking substance. Cluster III, called 'steadiness orientation', can be described as having a tow score on seeking trend and substance. Cluster IV, named 'individuality inclination', can be described as having low score on seeking trend. These four clusters differ in terms of socio-demographic and environmental characteristics such as gender, age, educational level, occupation, and internet using time. Theoretical and practical implications are discussed.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.313-316
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• 2001

At the end of 1999, the TeraCluster project in the KISTI Supercomputing Center was initiated to explore the possibility of PC clusters as a scientific computing platform to replace the Cray T3E system in KISTI by the year 2002. In order to understand whether an application is scalable to tera-flops sized cluster system, running test is inevitable. Extensive performance tests using well-known benchmarking codes with real applications' characteristics in them were carried out with different combinations of CPUs, system boards, network devices. The lessen learned shows the relationships between system performances and varied applications' different needs resulting in promises of How-Tos in building large scale cluster system. The 64/16 node clusters with Alpha EV6(466MHz), Pentium III(667 MHz) i inter-node network of Fast Ethernet. SCI[1] and Myrinet[2] were evaluated. More detailed specifications of the Linux clusters are described in Table 1.

• East Asian Journal of Business Economics (EAJBE)
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• v.8 no.2
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• pp.29-41
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• 2020

Purpose - This study incorporated the success factors of bio cluster and provided the ways to utilize them for managing the performance of bio cluster. The aim of this study was to present an integrated framework for the success factors of the bio cluster by combining the literature and case studies, and to measure and manage the performance of the bio cluster. Research design, data, and methodology - This study combined the literature review with the case study. We reviewed the literature on the success factors of the bio cluster presented by existing studies. We studied some cases of how these factors are actually applied in the bio cluster also. We integrated the success factors of bio cluster based on both the literature review and the case study. Results - The success factors of the bio cluster presented in this study as an integrated framework were defined as six factors: knowledge base and expertise, industrial infrastructure, funding and investment, government support, start-up activities and innovation activities. These success factors can be measured and managed by some performance indicators of each factor. Conclusions - Through this study, we can identify the integrated success factors of the bio cluster and understand how these factors work in bio cluster. In addition, this integrated framework of success factors will be effectively utilized to measure and manage the performance of the bio cluster.

• International Journal of Contents
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• v.5 no.3
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• pp.57-64
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• 2009

Korea has relied on top down development method, in which companies, research and education institutions move into the industrial complexes established by the government. However, to improve local competitiveness, the paradigm is shifting from the government initiated industrial complex to the clusters based on the cooperative network of the region. Representative case is 'Samcheok-si Fire & Emergency industry cluster construction project' that begun in 2007. AHP technique analysis results on first-stage showed that priority was on policy and network elements, and the results of second-stage analysis show that priority was on Policy incentives to internationalize the cluster and strengthen link,. Cluster branding, Sharing of organizational culture to cope with changes in environment, Creation of group learning culture. The subject of this research is limited to Samcheok-si's the Fire and Emergency Industry cluster formation project. Therefore, the research area and standard should be expanded to increase generality in further researches.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.1-6
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• 2024

Energy efficiency in wireless sensor networks (WSNs) is a critical issue because batteries are used for operation and communication. In terms of scalability, energy efficiency, data integration, and resilience, WSN-cluster-based routing algorithms often outperform routing algorithms without clustering. Low-energy adaptive clustering hierarchy (LEACH) is a cluster-based routing protocol with a high transmission efficiency to the base station. In this paper, we propose an energy consumption model for LEACH and compare it with the existing LEACH, advanced LEACH (ALEACH), and power-efficient gathering in sensor information systems (PEGASIS) algorithms in terms of network lifetime. The energy consumption model comprises energy-sensitive cluster formation and a cluster head selection technique. The setup and steady-state phases of the proposed model are discussed based on the cluster head selection. The simulation results demonstrated that a low-energy-consumption network was introduced, modeled, and validated for LEACH.

• The Korean Journal of Community Living Science
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• v.21 no.4
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• pp.619-631
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• 2010

The purpose of this study is to segment and examine urban farmers behavior by applying a two-step cluster analysis and multi-nominal logit model. The data were collected by a telephone survey with two-staged stratified random sampling in the cities around the country for the purpose of acquiring representative data. Respondents were asked to describe their awareness of urban agriculture, their agricultural activity, and sociodemographic characteristics. Among 2,000 cases, 381 cases(19.1%) which were of participants in urban agriculture were analysed in SPSS. From the findings, 27.3% of respondents had heard the word 'urban agriculture', and 25.5% of them regarded themselves as urban farmers. Four different clusters were derived from two-step clusters based on motive, place, companion, area and hours. They were 'Large scale hobby farming(cluster 1)', ‘Weekend farm/ hobby farming(cluster 2)', 'Land/ Self-supporting farming(cluster 3)', and 'Small scale hobby farming(cluster 4)'. The result of multinomial logistic regression showed that there were significant differences among these four segmented groups in terms of age, city size and housing type. In other words, there is quite a possibility that urbanites select different urban farming types according to their socio-demographic profiles. Therefore, the urbanite profiles can be used as the basis for promoting policy of several urban agriculture types. According to the result, policy directions for facilitating urban agriculture were presented.