• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.327-332
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• 2005

This paper aims to analysis for evaluation factor and success prediction of port innovative cluster. This paper is divided three factors such ac policy, source and operation. In addition, three factors are divided into the twelve detail factors. the weight of each factor is calculated by Kohonen Network. At the result, this paper places the priority on the source factor.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.4
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• pp.377-393
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• 2007

National balanced development and regional innovation have been one of the most important national agendas under the Participatory Government. National balanced development gives a central focus on realizing self-sustaining localization which is based on regional innovation. The core policy goal is to build competitive regional innovation system and innovative clusters in the regions of the country. In this vein, this paper aims to evaluate the present government's policies of regional innovation and innovative cluster. It needs to point out that the regional innovation and cluster policies show some critical problems. Firstly, the policy-making process is based on the top-down approach rather than the bottom-up one. Secondly, regional innovation policies, in many cases, expose the redundancy of similar policies and a lack of linkages between similar policies. Thirdly, the regional innovation policies are too much social infrastructure building-centered, even though the basic principle of regional innovation policy should be based on building superstructure such as networking and social capital.

• World Technopolis Review
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• v.1 no.2
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• pp.118-128
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• 2012

This paper suggests policy implications for Daedeok Innopolis (DI) in Daejeon by comparing the development and problems of DI with the San Diego biotechnology cluster. DI has strengthened its capabilities for technology commercialization and business activities after having created and managed by the Korean central government. While DI has been successful in increasing the number of institutes, researchers, research activities, however, its dynamism is not rigorous enough to be a regional innovative system. San Diego's scientific and entrepreneurial community shows the importance of formulating social and spatial contexts for mutual interactions and engagements. In San Diego, UCSD and networking organizations, especially CONNECT, are central in promoting interactions and communications between regional constituents including entrepreneurs, academics and local governments. The mechanisms of San Diego biotechnology imply that DI should provide more attention to designing and developing social and geographical space that can unleash the creative power of social interactions. To build an innovative regional system, DI needs to renovate its space, public-private relationship and networking platforms.

• Bulletin of the Korean Chemical Society
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• v.26 no.10
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• pp.1603-1606
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• 2005

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

• Management Science and Financial Engineering
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• v.12 no.1
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• pp.35-64
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• 2006

This study empirically investigated cultural differences in the amount of information provided by management accounting information systems as well as the differences in organizational performance according to variations in the amount of information. Through cluster analysis, we classified sample firms into five organizational cultural types: Semi-innovative, innovative, bureaucratic, semi-bureaucratic and supportive. The results showed that in the semi-innovative firms, a greater amount of the traditional and advanced types of information is produced, while in bureaucratic firms, traditional information is much more provided than in the innovative, semi-bureaucratic and supportive firms. These results confirmed cultural differences in the amount of information produced. According to the results of this study, it was found that in organizational performance, the rankings of semi-innovative firms, which have the highest scores in the amount of information, are also the highest, and the performance scores in innovative firms are generally next to those of semi-innovative firms. Hence, it is concluded that there are cultural differences in the amount of information provided, and these differences affect organizational performance.

• Journal of Convergence Society for SMB
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• v.4 no.4
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• pp.7-12
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• 2014

This study empirically investigated cultural differences in the amount of information provided by managerial accounting information systems as well as the differences in organizational performance according to variations in the amount of information. Through cluster analysis, I classified sample firms into five organizational cultural types: Semi-innovative, innovative, bureaucratic, semi-bureaucratic and supportive. The results showed that in the semi-innovative firms, a greater amount of the traditional and advanced types of information is produced, while in bureaucratic firms, traditional information is much more provided than in the innovative, semi-bureaucratic and supportive firms. These results confirmed cultural differences in the amount of information produced. According to the results of this study, it was found that in organizational performance, the rankings of semi-innovative firms, which have the highest scores in the amount of information, are also the highest, and the performance scores in innovative firms are generally next to those of semi-innovative firms. Hence it is concluded that there are cultural differences in the amount of information provided and theses differences affect organizational performance

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

• World Technopolis Review
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• v.8 no.2
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• pp.104-119
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• 2019

Innovation clusters are essential in the economic development of many developed countries across the world. While they present ways for under-developed and developing countries to grow their economies, fully operational innovation clusters are yet to be established in Nigeria. Many experts argue that learning from experience is an effective way of galvanizing economic development. Therefore, in this study, an empirical analysis involving a multi-variable quantitative analysis was used to examine the factors that influence the performance of the Daedeok Innopolis Innovation Cluster (South Korea). The results obtained show that the investment in education, Research and Development (R&D), labor capacity of key players within the innovation cluster, and the transfer of technology (within the cluster) were essential factors that influence the performance of the Daedeok Innopolis Innovation Cluster.