• Proceedings of the Technology Innovation Conference
• /
• 2002.06a
• /
• pp.238-256
• /
• 2002

Competitiveness of a nation can be explained by the concept of national innovation systems(NIS). As components of NIS, industry clusters become the issue in analysing innovative activity of an economy. Innovative clusters can be identified by the innovation survey or other economic activity data. Input-output Table was used widely as a tool for quantitative analysis, This paper classifies seven clusters in Korean industry based on inter-industries trade of intermediary goods and services, Maximizing procedure method is used in analysing input-output table. Identified clusters are Textiles/chemicals, Construction/Material, Instrument/Equipment, Automobile, Services, Energy, and Agriculture/Food cluster, Among these clusters, some different characteristics in R&D portfolios are detected. R&D investment characteristics of each cluster give us significant implications in understanding innovative dynamics of Korean industry.

• Journal of the Economic Geographical Society of Korea
• /
• v.16 no.3
• /
• pp.492-511
• /
• 2013

According to IASB(International Accounting Standards Board), R&D(Research and Development) is defined as a tertiary sector industry combining research and development. Many studies investigated R&D industry clusters in the form of high-tech cluster(Coe et al., 2007). However, these studies only generalized various spatial cluster of R&D industries. In particular, the studies could not considers cluster formation process over time lacking statistical significance in space-time perspectives. This study, therefore, indicates the limitation of recent R&D cluster literature which only considers either time or space. In addition, this study explores space-time clusters in R&D industry together with textile and cloth industry for comparison. Discovering the existence and location of clusters, this study utilized space-time K function and space-time scan statistics. The result shows that R&D industry presents significant clusters only in spatial dimension. No significant clusters were found in space-time dimension. However, textile and clothing industry presents significant clusters in both spatial and space-time dimensions.

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

• STI Policy Review
• /
• v.3 no.1
• /
• pp.63-79
• /
• 2012

Regional innovation systems and clusters represent a fashionable conceptual basis for regional innovation policies in many industrialized countries (including South Korea). Due to questions related to climate change and environment-friendly energy production, the green industry has been increasingly discussed in relation to regional innovation systems and clusters. This explorative paper analyzes these discussions and critically examines the emergence of green clusters in South Korea based on the case of the wind power cluster in Jeonbuk Province. It tentatively concludes that the role of the central government is too powerful and the role of regional actors (policy-makers and entrepreneurs) is too weak for the successful emergence of green clusters.

• Journal of the Korean Institute of Gas
• /
• v.7 no.1 s.18
• /
• pp.41-46
• /
• 2003

The Phase and temperature changes of large clusters formed in a free jet expansion of acetylene in 14atm and 233K has been studied. The cluster has been treated as a sphere composed of many shells. A mean diameter of 4.88 microns was obtained by modeling the experimental cooling curve of clusters based on evaporation and heat conduction theory.

• The Journal of Economics, Marketing and Management
• /
• v.10 no.6
• /
• pp.9-16
• /
• 2022

Purpose: This research investigates the differences in knowledge exchange activities and performances between startups and large companies in software industry clusters. Research design, data, and methodology: Six independent factors of human resource information, R&D and technology, marketing knowledge, government support information, strategic knowledge, and cooperation information were extracted to test the firm size effect in the relationships with two performance factors such as satisfaction with industry cluster location and satisfaction with financial performances. Data were collected through a survey of entrepreneurs, managers, and employees and tested by statistical analysis methodologies. Results: Three independent factors of human resource information, R&D and technology, and cooperation information were particularly significant in the relationship with both dependent factors. Strategic knowledge significantly affected financial performance. Knowledge exchange activities were more important in startups than in large companies for all eight factors. Conclusion: Policies for software industry clusters need a different approach for startups and large companies.

• Journal of Navigation and Port Research
• /
• v.30 no.2
• /
• pp.145-150
• /
• 2006

Recently we have seen a noticeable trend in ports to establish port clusters. Despite this trend, little research has actually been undertaken to fully define and analyse port clusters. A couple of exceptions have descriptively defined port clusters but the boundaries of port clusters are not apparent. Therefore, the aim of this paper is to define port clusters in terms of set theory and in particular look at them in terms of their distinct characteristics and system boundaries. The main concern of this paper is that there is a need to distinguish, from a system and a competition perspective, between port clusters, ports, maritime clusters and port ranges. This paper proposes a conceptual model relevant to the relationship among port clusters related assemblages and that has been applied to the north western europe region This model suggests six levels of competition that will help port authorities and government to develop appropriate policies and strategies for port operation and port industry.

• Journal of the Korean association of regional geographers
• /
• v.6 no.3
• /
• pp.169-184
• /
• 2000

Industrial clusters and their boundaries are identified by factor and hot spot analyses for the greater Cincinnati metropolitan area in USA. While traditional input-output approach identified aspatial industrial clusters, this study combines traditional approach with GIS techniques to identify their boundaries. Combining the results of input-output industrial clusters with the leading industries groups, we have identified five leading industry clusters. They are food (20), chemicals (28), metal manufacturing (32), metal products (33), and machinery (35). We also used hot spot analysis to visualize each industry cluster on the research area by using Arcview software. Determining the degree to which such industries are associated spatially and their spatial delimitation may be an additional approach to measuring the efficiency of the spatial organization of an economy. It is hoped that the industrial clusters and industrial spatial clusters approaches may also proved the basis for the development of new models of the spatial arrangement of industry at a level more aggregated than that of the single plant or firm.

• The Journal of the Korea Contents Association
• /
• v.19 no.5
• /
• pp.48-63
• /
• 2019

We tried new analysis including social network analysis(SNA) on the transaction network centered on electronic companies using more than 50 thousand company transaction data obtained from Korean enterprise data (KED) for the year of 2015. We found 97 clusters having more than 10 firms and remarkable 13 clusters having more than 90% sales of the electronic industry in Korea. Clusters are the groups of companies having most of their transactions in the clusters they belong to. We found 5 clusters have 83% of sales in the electronic industry. Most of clusters have main single firms having most of the sales in each clusters except a few clusters. However, we found a few firms to have high rear production linkage effect and found the firms with high linkage effect specially for the small and medium size enterprise (SME). The companies with high production linkage (specially on SMEs) should be managed in terms of (SME) growth policy. The last firm group consisting of the small clusters with less than 10 firms has high employment coefficients. The clusters or company having high production linkage effect on this last firm group should be noted in the terms of employment policy. We also note that there exist the firms with the high value of betweenness coefficients meaning high potential of technology development. They should be managed carefully in terms of technology development policy.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.43 no.4
• /
• pp.491-505
• /
• 2019

This study analyzes global fashion clusters to provide insight for the domestic fashion market to form a competitive fashion cluster. We examine formation factors and operation types of the global fashion clusters to understand their characteristics. We also explore the effectiveness of each global fashion cluster by investigating the stage of development in fashion clusters. Fourteen cases of global fashion clusters are collected and analyzed. First, global fashion clusters show three types of formation and operation: self-formation, self-formation & government based development, and government, institute, and enterprise based formation & development. Second, the characteristics of global fashion clusters are based on functions related to space, learning, innovation, network, and knowledge. Third, there are four steps in the development stage of global fashion clusters: professional clusters, industrial clusters, learning clusters and innovative industrial clusters. In particular, innovative industrial clusters, the final stage of development, have high levels of effectiveness in terms of co-growth and collaboration among fashion-related businesses in fashion clusters. The results of this study can help guide the development of local fashion cluster in Korea.