• Clean Technology
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• v.22 no.1
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• pp.62-72
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• 2016

These days, it seems to be a core time to build proactive prevention systems for small and medium sized enterprises due to the reinforced safety in the production process and the strong environmental regulations (ES) both at home and abroad. On the other hand, a network of experts that combines the industrial environment and production safety as well as even the knowledge services companies are not quite enough to prepare to support them. In this study, through a survey of experts the current statue of the convergence of industrial environment and production safety were reviewed, and the structure of knowledge ES cluster was proposed to overcome this current state. Detailed strategies such as the development and distribution of ES convergence methodology, ES efficiency analysis and an ES roundtable.

• Journal of Information Management
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• v.35 no.3
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• pp.125-138
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• 2004

The purpose of this study is to propose a hierarchical user interfaces for browsing the knowledge structure of a single document. To generate the hierarchical knowledge structure, hierarchical term clustering and cluster representative term selection were performed with a single thesis in information science field, and the result was applied to design the interfaces which browse a single document hierarchically using multidimensional scaling. The interfaces can be applied to develop the user-friendly information retrieval system.

• Educational Technology International
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• v.19 no.1
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• pp.153-173
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• 2018

The purpose of this study was to investigate teaching competence of faculty members based on TPACK which should be examined to ensure high quality in higher education. This study was conducted with a focus on TPACK, which integrate technology knowledge (TK), content knowledge (CK), and pedagogy knowledge (PK). Except insincere responses data from a total of 85 participants were used for data analysis in this study. K-mean cluster analysis method was used to examine how faculty members could be distinguished depending on TPACK type. Study results showed that there were three different types of faculty groups (well-balanced competence type, development required competence type, and lack of technology competence type). First, faculty members defined as well balanced competence type were more than the average level in TPACK. Second, faculty members belonged to development required competence type reported below the average level in TPACK. Thus, faculty members in this type were required to increase teaching competence. Finally, faculty members in lack of technology competence type were needed to enhance competence related to technology because their overall TK level was relatively low. This study examined what distinctive characteristics exited in each type depending on gender, teaching career, nationality, and age. Results from this study offered a basis for better understanding TPACK for enhancing teaching competence at the university level.

• Journal of the Korean Geographical Society
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• v.40 no.1 s.106
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• pp.78-95
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• 2005

The purpose of this paper is to analyze industrial and innovation networks of long-live area of Honam Region and to suggest a policy direction for regional development of rural areas where have been neglected in the knowledge-based information society. Four counties (Sunchang, Damyang, Gokseong, and Gurye) in the Southwestern region of Korea are regarded as long-live belt of Korea. Production and innovation networks :Ire analyzed based on intensive surveys of firms in the belt. Major findings from the surveys are as follows. First, there are considerably strong local networks of production firms in terms of supply of input materials and labor. There are strong backward industrial linkages of the production firms with agricultural activities and considerable forward linkages with tourism industry. In addition, Internet is becoming a useful tool for sales of the new products. Second, the analysis of the innovation networks in the long-live area suggests the development of 'virtual innovation cluster' in the era of knowledge-based information society. The results imply that this innovation networks can be developed as a virtual innovation cluster in the rural areas, which can be the basis for the development of rural innovation systems.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.3
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• pp.103-122
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• 2007

Innovation clusters developed or evolved around a specific region IS the key element of national innovation system and determine national competitiveness. Recognizing the importance of innovation clusters, Korean government has made "Daedeok Special R&D Zone" in 2005. This paper examines the success factors of famous Cluster in advanced countries and China, and proposes the strategy for regional development in Daejeon through boosting Daedeok Innovation Cluster. Although 30.5% of government R&D investment is being concentrated in Daedeok along with 10% of the country's doctorate degree holders, it is lack of increasing revenue by linking corporate R&D with a creative and challenging entrepreneur spirit. The core of the innovation cluster is the integration and mutual networking of the main participants. This paper suggests strategies for developing as a world class innovation cluster, global networking and clustering, venture ecosystem formation, commercialization the knowledge by interacting with market. It also explains the necessity of regional integration for cluster to cluster linkages in the East Asia Region.

• Journal of KIISE
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• v.42 no.10
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• pp.1195-1206
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• 2015

For the management of a knowledge system, systems that automatically infer and manage scalable knowledge are required. Most of these systems use ontologies in order to exchange knowledge between machines and infer new knowledge. Therefore, approaches are needed that infer new knowledge for scalable ontology. In this paper, we propose an approach to perform rule based reasoning for scalable SHIF ontologies in a spark framework which works similarly to MapReduce in distributed memories on a cluster. For performing efficient reasoning in distributed memories, we focus on three areas. First, we define a data structure for splitting scalable ontology triples into small sets according to each reasoning rule and loading these triple sets in distributed memories. Second, a rule execution order and iteration conditions based on dependencies and correlations among the SHIF rules are defined. Finally, we explain the operations that are adapted to execute the rules, and these operations are based on reasoning algorithms. In order to evaluate the suggested methods in this paper, we perform an experiment with WebPie, which is a representative ontology reasoner based on a cluster using the LUBM set, which is formal data used to evaluate ontology inference and search speed. Consequently, the proposed approach shows that the throughput is improved by 28,400% (157k/sec) from WebPie(553/sec) with LUBM.

• Journal of Technology Innovation
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• v.27 no.3
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• pp.53-82
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• 2019

This study empirically conduct structural equivalence analysis based on social network analysis in picking up on overall structural characteristics of technological knowledge exchange in a regional cluster. Previous conceptual studies so far have argued that performance differences among structurally equivalent groups exist. However, because little research has been done to empirically investigate this conceptual hypothesis, this study is conducted as complementary to fill this void. For analysis, we utilize two-mode network data consisted of 2,550 firms by investigating 53 technological knowledge exchange-related associations within Gumi national industrial cluster. The results show that some structurally equivalent groups can be defined appropriately and its role can be conditioned by firms' salient characteristics attached to each structural equivalent groups. In addition, it is presented through the present study that performance difference in structural equivalent groups can be distinct by some selected performance indicators. Finally, this study suggests the need to advance the study of performance differences in structurally equivalent groups in the future.

• World Technopolis Review
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• v.3 no.1
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• pp.17-29
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• 2014

The importance of science and technology as the root of exceptional regional economic development has been extolled since the time of Schumpeter. Today emerging technologies are signaling the start of a new economic cycle where regions that are effective in technology translation will gain advantage. The will of policymakers to translate technology into regional job and wealth creation seems to be at an all-time high. Yet an improved process for translating technical development into regional prosperity has proved elusive. If there are no processes other than applying techniques that have worked in the past for other regions to a new region then there is cause for concern. Here the authors seek to add to this field of knowledge by applying elements of the varied cluster theories to provide a basis for policy for regional economic development by turning science and technology into commercial innovation. We provide a review of current cluster theories and discuss the positive and negative issues associated with each. We propose a model that allows interested professionals to utilize aspects of each cluster perspective geared to the realities of their specific area.

• Journal of the Korean Academic Society of Industrial Cluster
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• v.1 no.1
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• pp.1-15
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• 2007

Regional innovation and cluster policies are the new agenda of regional policy, an agenda that began to spread over recent years throughout different countries and regions. In this context, our main question arises: how are we going to evaluate regional innovation and cluster policies? What models and methods are we going to use? Since 1990, regional and national governments have put more emphasis on evaluation as a tool directed to produce knowledge to design better policies. The objective of this article is to summarise the main challenges arising from the evaluation of regional innovation and cluster policies and make some methodological proposals that can contribute to produce better evaluations. In the first section, there is a brief presentation of regional innovation and cluster policies, followed by a more detailed analysis, in the second section, of their principal characteristics and of the main challenges posed by their evaluation. In the third section, some evaluation proposals that can help to improve current evaluation practice are presented. The paper concludes with a short number of general recommendations that we should bear in mind when designing an evaluation of regional innovation and cluster policies.