The business models has a great impact on the successful management of enterprises. Business environment has been shifting from industrial economy to knowledge-based economy. Enterprises go through numerous trials for successful management in the changing environment. Along with trial tests, research areas have been growing simultaneously. Although many researches have been conducted with regard to business models, it is very insufficient to systematically analyze the knowledge flow of research. Accordingly, successive researchers who want to study the business model may find it difficult to establish the orientation of future application research based on understanding the process of changing the knowledge structure that have accumulated so far. This study is intended to determine the current state of the business model research and to understand the process of knowledge structure changes in keywords that appear in 2,667 business model articles in the SCOPUS database. Identifying the knowledge structure has been completed through social network analysis, a methodology based on the 'relationship', and the changes in the knowledge structure were identified by classifying them into four different periods. The analysis showed that, first, the number of business model co-author increases over time with the need for academic diversity. Second, the 'innovation' keyword has the biggest center in the network, and over time, the lower-rank keyword which was in the former period has emerged as the top-rank keyword. Third, the cohesiveness group decreased from 12 before 2000 to 5 in 2015 and also the modularity decreased as well. Finally, examining characteristics of study area through a cognitive map showed that the relationships between domains increased gradually over time. The study has provided a systematic basis for understanding the current state of the business model research and the process of changing knowledge structure. In addition, considering that no research has ever systematically analyzed the knowledge structure accumulated by individual researches, it is considered as a significant study.
Journal of the Korea Society of Computer and Information
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v.23
no.10
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pp.173-180
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2018
In this paper, we analyzed key keywords and research themes in the field of defense research using keyword network analysis and tried to grasp the whole knowledge structure. To do this, we extracted data from 2,165 research data from defense related research institutes from 2010 to 2017 and applied the Pareto rule to the number of abstracts of words and the number of links between words, We extracted a total of 2,303 words based on the criterion and extracted 204 final key words through component analysis. By analyzing the centrality and cohesiveness through these key words, we confirmed the concept of core research in the defense field and derived a total of 7 large groups and 16 small groups of each group in the knowledge structure of the defense area.
In order to improve organizational performance, organizations should make a knowledge management system to share, distribute, and create related knowledge effectively in the operational process. It is not too much to say that organizational performance depends on the level of network and networking for the use of knowledge among the agents. Theoretically, a web portal is known as a useful instrument not only to link among the actors who have a specific interest and purpose but also to promote social networking which creates new knowledge relevant to user's environment. In the context, this article explored policy implications of building and operating government portals by analysing the efficacy of the "Innovative Portal", which the Korean government had opened to diffuse its innovation activities and to improve organizational innovation capacities in 2005, in innovation process from the knowledge management perspective. In particular, this study tried to identify how did the "Innovation Portal"influence network and networking of innovation knowledge using hyperlink network analysis method.
With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.
Wirawan, Gede Benny Setia;Gustina, Ni Luh Zallila;Januraga, Pande Putu
Journal of Preventive Medicine and Public Health
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v.55
no.4
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pp.342-350
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2022
Objectives: Human immunodeficiency virus (HIV) prevention among youth seems under-prioritised compared to other key populations. HIV knowledge and stigma are important parts of HIV prevention. To inform HIV prevention among youths, this study quantitatively analysed the associations between open communication regarding sexuality and sexual health, comprehensive HIV knowledge, and non-stigmatising attitudes in Indonesia. Methods: This study used data from the Indonesian Demographic and Health Survey (IDHS) 2017. The analysis included unmarried men and women aged 15-25 years old. Comprehensive HIV knowledge and a stigmatising attitude were defined according to the IDHS 2017. Open communication about sexuality and sexual health was defined as the number of people with whom participants could openly discuss these topics in their direct network of friends, family, and service providers, with a scale ranging from 0 to a maximum of 7. Primary analysis used binomial logistic regression with weighting adjustments. Results: The final analysis included 22 864 respondents. Twenty-two percent of youth had no one in their direct network with whom to openly discuss sexual matters, only 14.1% had comprehensive HIV knowledge, and 85.9% showed stigmatising attitudes. Youth mostly discussed sex with their friends (55.2%), and were less likely to discuss it with family members, showing a predominant pattern of peer-to-peer communication. Multivariate analysis showed that having a larger network for communication about sexuality and sexual health was associated with more HIV knowledge and less stigmatising attitudes. Conclusions: Having more opportunities for open sex communication in one's direct social network is associated with more HIV knowledge and less stigmatising attitudes.
Various networks can be observed in the world. Knowledge networks which are closely related with technology and research are especially important because these networks help us understand how knowledge is produced. Therefore, many studies regarding knowledge networks have been conducted. The assortativity coefficient represents the tendency of connections between nodes having a similar property as figures. The relevant characteristics of the assortativity coefficient help us understand how corresponding technologies have evolved in the keyword-based patent network which is considered to be a knowledge network. The relationships of keywords in a knowledge network where a node is depicted as a keyword show the structure of the technology development process. In this paper, we suggest two hypotheses basedon the previous research indicating that there exist core nodes in the keyword network and we conduct assortativity analysis to verify the hypotheses. First, the patents network based on the keyword represents disassortativity over time. Through our assortativity analysis, it is confirmed that the knowledge network shows disassortativity as the network evolves. Second, as the keyword-based patents network becomes disassortavie, clustering coefficients become lower. As the result of this hypothesis, weconfirm the clustering coefficient also becomes lower as the assortative coefficient of the network gets lower. Another interesting result concerning the second hypothesis is that, when the knowledge network is disassorativie, the tendency of decreasing of the clustering coefficient is much higher than when the network is assortative.
Kim, Sungkyu;Son, Changho;Kim, Jongman;Chung, Sehkyu;Park, Jaehyun;Jeon, Jeonghwan
Journal of the Korea Institute of Military Science and Technology
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v.20
no.5
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pp.700-707
/
2017
Recently, the military need more various education and training because of the increasing necessity of various operation. But the education and training of the military has the various difficulties such as the limitations of time, space and finance etc. In order to overcome the difficulties, the military use Defense Modeling and Simulation(DM&S). Although the participants in training has the empirical knowledge from education and training based on the simulation, the empirical knowledge is not shared because of particular characteristics of military such as security and the change of official. This situation obstructs the improving effectiveness of education and training. The purpose of this research is the systematizing and analysing the empirical knowledge using text mining and network analysis to assist the sharing of empirical knowledge. For analysing texts or documents as the empirical knowledge, we select the text mining and network analysis. We expect our research will improve the effectiveness of education and training based on simulation of DM&S.
Journal of Korea Society of Digital Industry and Information Management
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v.10
no.1
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pp.157-167
/
2014
Increasing productivity of knowledge workers is a significant issue in the 21st century referred as knowledge-based society. The core key word is behavior of knowledge transfer among members of an organization. The objective of this study is to investigate a model based on Triandis theory and Social Capital theory. This explored the antecedent factors of knowledge Transfer in ITO(Information Technology Outsourcing) Organization. Data were derived from 42 respondents working IT Cooperation in Seoul, Korea. In this paper, we introduce the research model for the knowledge transfer. In order to validate the proposed research model, social network analysis tool, UCINET, a structural equation modeling tool, SmartPLS, was utilized. The empirical result showed that, all antecedent factors (intention of knowledge sharing, anticipated reciprocal relationships, subjective norm, closeness network centrality) of knowledge transfer behavior were significant. In conclusion, findings and implications were discussed and limitations of the study and future research directions were suggested.
The aim of this study was to investigate why people voluntarily contribute knowledge to others, primarily strangers, in the electronic network of practice for job examination expected potential competing. This paper is organized as follows. First, we introduce the electronic network of practice which is the knowledge sharing community for job examination, and discuss the key issues for understanding knowledge sharing in these networks on the basis of individual motivations, relational capital, sense of community, and sense of rivalry to develop a research model for this study. To test the proposed research model, we adopted the survey method for data collection, and examined our hypotheses by applying the multiple regression analysis method to the collected data. Our unit of analysis was the individual. The findings of this study show that the intention of knowledge sharing is influenced by the reputation and the enjoy helping as the factors of individual motivations, by the reciprocity as the factor of relational capital, and by a sense of rivalry as a psychological factor. Lastly, contributions of this study and future research opportunities are also discussed.
The relationship between geographical proximity and academics' formal and informal knowledge-transfer activities in the network is analyzed with a mixed research method. With social network analysis as a basis, we have explored the networks between academics and firms in the 16 regions of South Korea. The result shows Seoul and Gyunggi are identified as central nodes, meaning that the academics in other regions tend to collaborate with firms in these regions. An econometric analysis is performed to confirm the localization of knowledge-transfer activities. The intensity of formal channels measured by the number of academic papers is negatively, but significantly associated with the geographical proximity. However, we have not found any significant relationship between the formality of the channels and geographical proximity. Possibly, the regional innovation systems in South Korea are neither big enough nor strong enough to show a localization effect.
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