• Journal of Korea Technology Innovation Society
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• v.13 no.4
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• pp.772-793
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• 2010

In this paper, author estimated economic scale of radiation usage in Korea using Input-Output table 2005 and other micro data published. This estimation focused all kind of radiation usage in whole economic activity. Estimation of economic scale is quantitative analysis for how much radiation usage increase productivity and welfare. Economic scale estimation of radiation usage in Korea 2005 is 6,297 Billion Won and it occupies 0.74% of GDP. It is smaller level compared with that of US and Japan. It is 1.5% of GDP in US (1997) and 1.2% of GDP in Japan (2005). Radiation usage in industrial sector is 5,775 Billion Won and it is 0.68% of GDP. Radiation usage in agriculture sector is 171 Billion Won and it is 0.02% of GDP. Radiation usage in medical sector is 351 Billion Won and it is 0.04% of GDP. This implied that radiation usage in industrial sector is larger than other sector. Use of medical radiology may be enlarge in the future due to population structure. The result that radiation usage occupied 0.74% of GDP arouse contribution of radiation usage in daily life. It helps people to have more understanding and public acceptance for radiation.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.123-128
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• 2024

Major countries are trying to expand the construction of smart factories by introducing ICT such as the Internet of Things, cloud, and big data into the manufacturing sector to secure national-level manufacturing competitiveness in the era of the 4th industrial revolution. In addition, Germany is pushing for Industry 4.0 to build a fully automatic production system through the Internet of Things, and China is pushing for the expansion of smart factories to enhance the country's industrial competitiveness through Made in China 2025, Japan's intelligent manufacturing system, and the Korean government's manufacturing innovation 3.0. In this study, considering the increasing security connectivity of smart factories, we would like to identify security threats in the external connection part of smart factories and suggest security enhancement measures based on domestic and international standard security models to respond to the identified security threats. Eventually the proposed method can be applied by accurately identifying the smart factory security status, diagnosing vulnerabilities, establishing appropriate improvement plans, and expanding security strategies to respond to security threats.

• Journal of Service Research and Studies
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• v.10 no.1
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• pp.69-83
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• 2020

The purposes of this study is to identify the critical success factors for the 4th industrial revolution through literature review and to empirically evaluate the validity of these factors through questionnaires from executives engaging in the industries of the 4th industrial revolution. Literature review identifies leadership, change management, top management support, strategic fit, training, empowerment, teamwork, organizational culture, communication, and project management as ten critical success factors, Questionnaires were administered to CIOs and CEOs in the industries belong to the 4th industrial revolution. Response rate was 64.4% which shows quite high participation. Respondents rated strategic fit as the most important factor, followed by top management support, leadership, change management, project management, teamwork, communication, training, organizational culture, and empowerment. To successfully pursue the 4th industrial revolution, the followings are recommended. (1) detailed and refined execution strategy, (2) establishment of effective network among government, public companies, research institutes, universities, and industries, (3) strategic and long-term plan, (4) differentiated execution strategy from other countries and global cooperation system.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.3
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• pp.93-108
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• 2019

This study analyzed the influence of experiential marketing factors of 3D printing and Internet services on technology acceptance factors and usage intention. Furthermore, we analyzed how the user's innovativeness shows the effect on the intention to use. Data acquired from a total of 518 college students was used for the final analysis, which was perfromed by SPSS 21.0 and AMOS 23.0 programs. The results of this study are as follows. We analyzed the influence of the experiential marketing factors of fashion service utilizing the 3D printing and the Internet of Things on the acceptance of technology and intention to use these technologies. As for 3D printing, first, sensory and behavioral factors are positively related to the acceptance of technology. Second, emotional and cognitive factors have negative effects on all technology acceptance. Third, relational factors did not show a significant influence on several conditions of technology acceptance. Fourth, the effects of technology acceptance on the willingness to use have a positive effect on several conditions factors, except the effort expectation. As for the result concerning the Internet of Things first, behavioral factors have a positive effect on all technology acceptance. Second, emotional factors have a negative effect on all technology acceptance. Third, cognitive factors did not have a significant effect on various conditions and showed negative effects on several factors. Fourth, sensory and relational factors did not affect the acceptance of technology. Fifth, the effects of technology acceptance on the intention to use are affected by several conditions, except for effort expectation. As a result of analyzing the moderating effects of user's innovativeness on the willingness to use, 3D printing did not show any significant effect on innovation. However, the Internet of Things has a significant influence on the user acceptance of technology acceptance.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.95-103
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• 2022

Recently, the fourth industrial revolution has a great influence on the development of many industries as well as the construction industry. Various technologies related to the industrial revolution 4.0, such as AI and big data, have gained much attention. However, little has been known about the importance and preparedness of stakeholders of the construction industry in Korea for the industry 4.0 technologies so far. This study revealed how the stakeholders perceive and prepare for industry 4.0 using a survey. In addition, collaboration potential score for each technology was calculated to find technologies with high potential for collaboration. Result is that the importance of the technologies was evaluated high in overall, but the preparedness and implementation in university education or business was evaluated low. Technologies with high potential for industry-university collaboration are AI/big data and 3D printing/3D scanning. This study can contribute to the training of industry 4.0 experts and improving preparedness, which would enable the innovation and application of industry 4.0 technologies in the construction industry.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.4
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• pp.79-98
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• 2019

In this paper, the security behaviors and attitudes related with the personal information of teenagers were investigated using empirical data based on rational behavior theory and protection motivation theory. An experiment for teenagers was conducted on Excel and the statistical packages (i.e., SPSS 21.0 and SmartPLS2.0.M3) to see how self-efficiency, security attitude, security intention and individual innovation affect their security behaviors. The experimental results showed that the security behaviors and attitudes of teenagers between internet and information devices are closely related, and the social influences can affect personal self-efficacy and security attitudes. Finally, we can know that teenagers should recognize the importance of security and protect their personal information safely through continuous education and training so that they can be linked to security behaviors.

• Journal of Korea Technology Innovation Society
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• v.20 no.2
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• pp.368-386
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• 2017

The purpose of this study is to present the technology value model based on profit approach and IITP practical guide for Ethernet network technology, which is the core technology of autonomous vehicles and connected cars in the hyper-connected industry. In-vehicle network, Ethernet technology, Ethernet port count, port pricing, and application data for technology assessment are sources of global market research organizations. The data on the company's COGS (Cost of Goods Sold), operating capital requirement, capital expenditure, and income statement data are used by the Bank of Korea's Business Analysis Report. According to the results of the study, the product market size was estimated to be US $470.3 billion and the technology market size was $52.1 billion over the seven years of economic life cycle of technology. The market value of the technology was estimated to be $260 million reflecting the possibility of entry into the market. In the case of the corporate management analysis report, the average value of the IITP and the top 25% were $0.7 million and $40.2 million, respectively. -27.8 million, and -73.6 million dollars respectively. This implies that government support for policy support is needed when conducting corporate R&D with high cost-to-sales ratio. The results of this study can be used as a reference for the evaluation of technology demand based ICT R&D technology in the industrial internet market in the fourth industrial revolution era.

• Korean System Dynamics Review
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• v.12 no.2
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• pp.69-94
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• 2011

Daejeon, encompassing Daedeok Science Town and Daedeok Innopolis, possesses the advantage of portraying relatively higher regional innovation capacity and facilitating network formation among regional professional research organizations. Applying the Social Network Analysis(SNA) techniques, this paper focuses on divulging structural and spatial characteristics of the Daejeon Information and Communication(ICT) industry network, analyzing co-research projects implemented by the Daejeon-based universities. For the analytical tool, it depends on NETMINER 3.0. Furthermore, based on the Systems Thinking approaches, this study suggests a couple of policy implications. Judging from the Korea Standard Industrial Classification principles, the existing ICT industry is subdivided into 11 sub-industries. The highest degree centralization value comes from the Mobile Communication sub-industry(188.668%), indicating that Mobile Communication sub-industry exerts the most significant impact on the regional innovation networking in Daejeon. Among various stakeholders, Korea Advanced Institute of Science and Technology(KAIST) records the top ranking in most categories, conspicuously leading the institute-industry linkage. In terms of the ICT spatial distribution, the intra-regional cooperation examples present the strongest linkage values, followed by Daejeon-the Capital Region ones. Finally, as well shown in a series of causal loop analyses, this study recommends that Daejeon should put top policy priority in strengthening the internal ICT network within Daejeon proper. Here, Daejeon should keep in mind the fact that there exist reinforcing loops between Daejeon's attractiveness and the entering of new ICT firms.

• Microbiology and Biotechnology Letters
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• v.46 no.1
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• pp.9-17
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• 2018

The aims of this work were to characterize and determine bioactivities of crude exopolysaccharide (EPS) extract from Bacillus tequilensis PS21 isolated from milk kefir from Kampaeng Petch, Thailand. B. tequilensis PS21 produced 112.1 mg dried EPS/l from initial 80 g/l lactose in modified TSB media at 52 h, with EPS product yield of 8.9 mg EPS/g lactose and specific product yield of 0.3 mg EPS/mg biomass. The FTIR result confirmed EPS to be a protein-bound polysaccharide and SEM analysis showed the morphology to be a grainy appearance with an uneven surface, covered with pores. HPLC analysis determined EPS as a heteropolysaccharide consisting of five sugar units with the following molar ratios; xylose (17.65), glucose (2.54), ribose (1.83), rhamnose (1.23), and galactose (1). Chemical components of this EPS were predominantly carbohydrate at 697.8 mg/g EPS (65%), protein 361.4 mg/g EPS (34%), and nucleic acid 12.5 mg/g EPS (1%). The EPS demonstrated antioxidant activities at 57.5% DPPH scavenging activity, $37.2{\mu}M\;Fe(II)/mg$ EPS and $34.9{\mu}M\;TEAC\;{\mu}M/mg$ EPS using DPPH, FRAP and ABTS assays, respectively. EPS also exhibited anti-tyrosinase activity at 34.9% inhibition. This work represents the first finding of EPS produced by Bacillus sp. from Thai milk kefir which shows potential applications in the production of antioxidant functional foods and whitening cosmetics. However, optimization of EPS production for industrial exploitation requires further study to ascertain the economic potential.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.