• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.1-18
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• 2021

ICT is the main driving force of Korea's economic growth. Korea has the world's best ICT competitiveness, and several policies are being implemented to maintain it. However, for successful policy implementation, it is crucial to understand ICT trends accurately. Therefore, this study analyzes the trends of 18 core technologies in the ICT field. In particular, the degree of scientific development and commercialization by technology are investigated through research paper analysis and patent analysis, respectively. Then, the trends shown by document type are compared based on the two analysis results. As a result, artificial intelligence and virtual reality are at the stage where commercialization is actively taking place after scientific development, and at the same time, since research is being conducted, it is expected to develop continuously. On the other hand, quantum computer and implantable device are in the basic research stage. It is necessary to understand the current research status and determine the direction of future support. The results of the ICT trend analysis conducted in this study can be used as a criterion for determining the future direction of Korean policy.

• Journal of Korea Technology Innovation Society
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• v.22 no.3
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• pp.382-415
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• 2019

This study analyzes the impact of exclusive subcontracting on the input, behavior, and output of innovation in manufacturing industries of Korea. Based on the analysis of pooled cross-sectional data of 6,029 small venture firms, this study proved that the exclusive subcontracting between small venture firms and large enterprises are lowering R&D investment of small venture firms. Second, the innovation activities of small venture firms including the ratio of R&D personnel and the scope of cooperation and partnership with external organizations were lower than those of small venture firms that have non-exclusive or no relations with large enterprises. Third, the innovation performance of small venture firms such as the number of patent applications, the ratio of sales by new products, and the cumulative sales growth rate was lower than those of small venture firms that have non-exclusive or no relations with large enterprises. This study verifies that the exclusive subcontracting relationships significantly weaken the innovation process and performance of small venture firms systematically, resulting in a kind of market failure in which small venture firms have almost no incentive to facilitate innovation.

• Korean small business review
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• v.42 no.4
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• pp.147-172
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• 2020

This study presents the determinants of R&D efficiency as the focus on CEO's competency, which influences R&D competency and R&D efficiency. The research samples are 6,708 technology-innovation small and medium-sized enterprises (SMEs). The independent variable is the R&D competency(existence of R&D organization, level of R&D personnel, R&D personnel management, R&D investment), the dependent variable is R&D efficiency. The moderator is the CEO's competency(experience level in its own industry, technical knowledge level, technology management strategy, management ability). R&D efficiency measures the relationship between inputs(level of R&D personnel, R&D investment) and outputs(patent applications, prototype) by the DEA. and the determinant analysis uses Tobit regression. As a result of the analysis, the existence of R&D organization and R&D personnel management is positively significant, level of R&D personnel and R&D investment is negatively significant for R&D efficiency. The moderating effect of CEO's competency on the relationship between the R&D competency and R&D efficiency is significant determinants of CEO's experience(experience level in its own industry, technical knowledge level) and technology management strategy. The finding is to measure the efficiency of R&D performance, and to analyze its determinants as the moderating effect of CEO's competency, using the technology appraisal data. In the conclusion session, the limitations of the research and future research directions were discussed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.53-64
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• 2022

The purpose of this study is to analyze the difference in importance and performance of the university start-up support system focusing on D university students to grasp the perception of the start-up support system provided the university from the perspective of students who are real users. Through this, a plan for qualitative growth and advancement of the university start-up system was derived using the IPA (importance-performance analysis) analysis. The findings are as follows. The importance of all elements of university start-up education and start-up support system is higher than the performance, which means that the start-up education and support programs currently implemented by universities are recognized as important, but do not play a big role in terms of performance for students. In addition, the highest priority factors for improvement in the importance-performance matrix were funding and investment support, start-up space and facilities support, management advisory, patent and intellectual property support, and entrepreneurship field practice. Therefore, This study can be used as objective data to identify the factors that universities should focus on and establish a start-up support system from a long-term perspective, and to build and operate a start-up support system that reflects the needs of students.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.55-73
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• 2024

Unicorn companies are attracting attention around the world as they are recognized for their high corporate value in a short period of time as an innovative business models. Their growth process presents good lessons for the startup ecosystem and have a positive impact on national economic development and job creation. However, previous studies related to unicorn companies are focused on 'event studies' and 'case studies' such as characteristics of founders, environmental factors, business models and success/failure cases of companies already recognized as unicorns rather than a multifaceted approach. The occurrence of unicorn companies and Macroscopic analysis of related factors is lacking. Against this background, this study are considering the characteristics of unicorns examined through previous research and the current status unicorns with a high proportion of technology companies, the purpose was to analyze the impact of the country's technological competitiveness, such as 'technology human resource index', 'R&D index', and 'technology infrastructure index', on the increase in unicorn companies. For statistical analysis, data published by various international organizations, the Bank of Korea, and Statistics Korea from 2017 to 2020 and unicorn company data compiled by CB Insights were used as panel data for 44 countries to be tested by multiple regression analysis. As a result of the study, it was confirmed that the number of science majors had a positive (+) effect on the increase of unicorn companies in the case of technology human resource index, and in the case of R&D index, the total amount of R&D investment had a positive (+) effect on the increase of unicorn companies, while the number of Triad Patents Families and the number of scientific and technological papers published had a negative (-) effect on the increase of unicorn companies. Finally, in the case of technology infrastructure index, it was confirmed that the number of the world's 500th-ranked universities had a positive (+) effect on the increase of unicorn companies. This study is the first to reveal the causal relationship between national technological competitiveness and unicorn company growth based on country-specific and time-series empirical data, which were insufficiently covered in previous studies. and compared to the UN's ranking of the global industrial competitiveness index and the OECD's total R&D investment by country, Korea is considered to have technological and growth potential, while the number of unicorn companies driving growth as leaders of the innovative economy is relatively small, so the research results can be used when establishing policies to discover and foster unicorn companies in the future.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.1
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• pp.15-22
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• 2017

Purpose During Brain SPECT study, critical factor for proper study with $^{99m}Tc-ECD$ or $^{99m}Tc-HMPAO$ is one of the important causes to patent's movement. It causes both improper diagnosis and examination failure. In this study, we evaluated the effect of Dynamic Continuous Mode Acquisition compared to Step and Shoot Mode to raise efficacy and reject the data set with movement, as well as, be reconstructed in certain criteria. Materials and Methods Deluxe Jaszczak phantom and Hoffman 3D Brain phantom were used to find proper standard data set and exact time. Step and Shoot Mode and Dynamic Continuous Mode Acquisition were performed with SymbiaT16. Firstly, Deluxe Jaszczak phantom was filled with $Na^{99m}TcO_4$ 370 MBq and obtained in 60 minutes to check spatial resolution compared with Step and Shoot Mode and Dynamic Continuous Mode. The second, the Hoffman 3D Phantom filled with $Na^{99m}TcO_4$ 74 MBq was acquired for 15 Frame/minutes to evaluate visual assessment and quantification. Finally, in the Deluxe Jaszczak phantom, Spheres and Rods were measured by MI Apps program as well as, checking counts with the frontal lobe, temporal lobe, occipital lobe, cerebellum and hypothalamus parts was performed in the Hoffman 3D Brain Phantom. Results In Brain SPECT Study, using Dynamic Continuous Mode rather than current Step and Shoot Mode, we can do the reading using the 20 to 50 % of the acquired image, and during the test if the patient moves, we can remove unneeded image to reduce the rate of restudy and reinjection. Conclusion Dynamic Continuous Mode in Brain study condition enhances effects compared to Step and Shoot Mode. And also is powerful method to reduce reacquisition rate caused by patient movement. The findings further indicate that it suggest rejection limit to maintain clinical value with certain reconstruction factors compared with Tomo data set. Further examination to improve spatial resolution, SPECT/CT should be the answer for that.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.5
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• pp.49-65
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• 2019

This study was carried out to investigate the domestic and international development of a new cultivar of the Rose of Sharon (Hibiscus syriacus L.), the Korean national flower, and the protection of the new plant variety. In addition, it will be used as basic data for the expansion of domestic distribution, promoting oversea export, and expanding the range of landscape architectural use. A total of 97 varieties received plant variety protection rights from the Korea Seed & Variety Service from 2004 to 2018. The selection criteria were plants having unique flowers, growth habits, and variegated leaves. Some cultivars with unique features, such as flower size, shape, and red eyes were available for focus planting. Plant varieties with tall and strong growth patterns have been highly valuable for street and focus planting. Cultivars with dwarf stems and compact branches are utilized for pot planting and bonsai. The protected cultivars were mostly single flower varieties, with two semi-double flowers. There were 57 cultivars of pink flowers with red eyes and 21 cultivars of white flowers with red eyes. There were 61 cultivars developed by crossing, 23 cultivars through interspecific hybridization and 7 cultivars developed through radiation treatment and mutation. The Hibiscus cultivars registered to the United States Patent and Trademark Office (USPTO) consisted of seven cultivars each from the United States, the United Kingdom, and the Netherlands, four from South Korea, and three from Belgium. The Hibiscus cultivars registered to the European Community Plant Variety Office (CPVO) consisted of 16 cultivars from France, 9 from the Netherlands, 5 from the UK and 1 from Belgium. The cultivars that received both plant patent and plant breeder rights in the United States and Canada were 'America Irene Scott', 'Antong Two', 'CARPA', 'DVPazurri', 'Gandini Santiago', 'Gandini van Aart', 'ILVO347', 'ILVOPS', 'JWNWOOD 4', 'Notwood3', 'RWOODS5', 'SHIMCR1', 'SHIMRR38', 'SHIMRV24', and 'THEISSHSSTL'. 'SHIMCR1' and 'SHIMRV24' acquired both domestic plant protection rights and overseas plant patents. The 14 cultivars that received both US plant patents and European protection rights were 'America Irene Scott', 'Bricutts', 'DVPAZURRI', 'Gandini Santiago', 'Gandini van Aart', 'JWNWOOD4', 'MINDOUB1', 'MINDOUR1', 'MINDOUV5', 'NOTWOOD3', 'RWOODS5', 'RWOODS6', 'Summer Holiday', and 'Summer Night'. The cultivars that obtained US patents consisted of 18 cultivars (52.9%) with double flowers, 4 cultivars (11.8%) with semi-double flowers, and 12 cultivars (35.3%) with single flowers. The cultivars that obtained European new variety protection rights, consisted of 11 cultivars (34.3%) with double flowers, 12 cultivars (21.9%) with semi-double flowers, and 14 cultivars (43.8%) with single flowers. In the future, new cultivars of H. syriacus need to be developed in order to expand domestic distribution and export abroad. In addition, when developing new cultivars, it is required to develop cultivars with shorter branches for use in flower beds, borders, hedges, and pot planting.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.