• 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.

• Asian Journal of Innovation and Policy
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• v.6 no.3
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• pp.245-261
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• 2017

As of the end of August 2017, there were 392 academic articles for $4^{th}$ Industrial Revolution in Korea. Is the vigorous discussion on the 4th Industrial Revolution in Korea normal? We checked the main theories on this topic by existing theories and responses of major countries and industries. The findings are that there are technologies called a Technological Revolution, and the industrial application of some technologies is in the starting stage. If comes, the Industrial Revolution is expected with the structure as follows: excellence science, core technologies, base technologies, application and infrastructure, and institutions. Nonetheless, the brisk studies are from three branches such as the Industry 4.0, social connection and artificial intelligence. The Industry 4.0, the digital transformation of manufacturing is the on-going issue in the industry, and artificial intelligence brings the biggest discourse. The 392 literature are mostly from introduction and preparation for future; technology 15.8%, industry 26.3%, society 24.5%, education 19.1%, policy 10.7%. The labor and employment is only 3.6%.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.51-76
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• 2022

Identifying the factors that influence the formation of the entrepreneurial intention is important in cultivating entrepreneurs and inducing entrepreneurial innovation in the country. Previous studies have mainly examined the direct effects of social cognition attributes as predictors on entrepreneurial intentions or entrepreneurial activities. However, the fundamental factors that these social cognition attributes are derived from have not been sufficiently addressed in the field of entrepreneurship. Based on social cognitive theory and schema theory, this study assumes that an individual's entrepreneurial experience is an important antecedent factor in forming social cognitive attributes, and reveals the mechanism for how experience forms entrepreneurial intention. To this end, this study analyzes the influence of entrepreneurs' prior experience of entrepreneurial activities on entrepreneurial self-efficacy, opportunity recognition, and fear of failure which are considered to be the main variables that shape entrepreneurial intention. And it analyzes how these factors have a significant effect on entrepreneurship intention. Along with this, the mediating role of these social cognitive attributes is analyzed in order to understand the path that leads from entrepreneurial experience to entrepreneurial intention. This study also suggests how gender moderates the effect of entrepreneurship experience on social cognitive attributes. As a result of the analysis, it was found that entrepreneurial experience increase entrepreneurial self-efficacy and opportunity recognition of entrepreneurs, and decrease the fear of failure. These social perception attribute significantly mediate the relationship between entrepreneurial experience and entrepreneurial intention. This study also found that there are significant moderating effects of gender on the relationship of entrepreneurial experience and both of entrepreneurial self-efficacy and fear of failure. This study also analyzed the impact of the entrepreneurial experience of failure, which corresponds to the detailed experience. Similar to the results of entrepreneurial experience analysis, entrepreneurial experience of failure plays a role in enhancing entrepreneurial self-efficacy. However, its effect on opportunity recognition and fear of failure were not significant. An empirical analysis of data related to 25,047 entrepreneurs from 87 countries, using the Global Entrepreneurship Monitor (GEM), shows the differences in the formation of individuals' entrepreneurial intentions according to entrepreneurial experience and the mediating role of social cognitive attributes. The study has embodied the social cognitive theory on entrepreneurial intention by shedding light on the variables that are important but alienated for increasing entrepreneurial intention. Moreover, the study enhances the understanding of cognitive processes leading from individual experiences to entrepreneurial intentions. This study also emphasizes the importance of differentiated approach by gender for boosting entrepreneurial intention through analysis of moderating effect of gender.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.205-211
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• 2020

The method of predicting the future may be predicted by technical characteristics or technical performance. Therefore, technology prediction is used in the field of strategic research that can produce economic and social benefits. In this study, we predicted the future market through the study of how to predict the future with these technical characteristics. The future prediction method was studied through the prediction of the time when the market occupied according to the demand of special product. For forecasting market demand, we proposed the future forecasting model through comparison of representative quantitative analysis methods such as CAGR model, BASS model, Logistic model and Gompertz Growth Curve. This study combines Rogers' theory of innovation diffusion to predict when products will spread to the market. As a result of the research, we developed a methodology to predict when a particular product will mature in the future market through the spread of various factors for the special product to occupy the market. However, there are limitations in reducing errors in expert judgment to predict the market.

• Journal of Technology Innovation
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• v.23 no.3
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• pp.43-65
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• 2015

Technology standard continues to exist as an social agreement throughout all industry. With development of Information and Communication, it is recently considered as a strategic factor for enhancing interoperability and increasing market dominance. Hence, technology standard research(standardization research) have a significance in analyzing the process of standard adoption and its economic effect and deriving theoretical and policy implications. However, as existing relative researches are lack in consideration on indigenous value of technology and its interoperability, there exists limitation in drawing the result of technology centered analysis. The goal of this study is to suggest new technology centered standard method by implying function of technology differentiation rate and technology preference that are deduced by technology network analysis into two stage game theory. As an example of empirical case, we selected wireless pan technology of Internet of Things, and derive its technological structure and implications related to standard.

• Journal of Distribution Science
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• v.22 no.9
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• pp.129-139
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• 2024

Purpose: This research aims to examine the impact of social media marketing on buy decisions in Indonesia's B2B market, considering the mediating roles of brand image, perceived quality, and perceived value in relation to interactive flat panel display technology. To better understand technology adoption and distribution, we utilize the innovation diffusion theory. Research Design, Data and Methodology: The Decision-Making Unit of each organization that buy interactive flat panel display technology conducted an empirical survey of 82 participants. The quantitative research design analyzed the data utilizing the PLS-SEM model. outcome: This research reveals that social media marketing significantly impacted perceived quality, brand image, perceived value, and buy decisions. The research also found that perceived quality does not significantly impact buy decisions, but perceived value and brand image significantly impacted buy decisions. This research contributes to understanding the key factorsinfluencing buy decisionsin Indonesia's B2B market. Conclusion: Thisresearch concludesthat B2B consumers in Indonesia are less concerned about product quality but prioritize the value they receive when purchasing interactive display technology. Social media marketing could impacted the distribution of interactive display technology in Indonesia's B2B market by affecting the DMU's purchasing decisions. Brands should leverage social media marketing to positively impact theirsuccess.

• 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 the Korean Society of Food Science and Nutrition
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• v.22 no.2
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• pp.154-160
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• 1993

The strategic plan of nutrition education intervention was established to improve nutritional status and reduce nutrition-related diseases for Korean adults. Nutritional problems and risk factors of the nutrition-related diseases were identified to set the long-term goal and objectives for the intervention. The social learning theory and theory of diffusion of innovation served as theoretical basis for this plan. Mass media and interpersonal channels were used to educate the whole adult population and specific target groups. The outline of the educational contents was developed for the whole adult population and slightly modified according to characteristics of the target groups. This plan can serve as a guideline for the operational plans for the future nutrition education intervention.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.309-321
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• 2011

The u-City construction plan being executed presently involves such problem that services are provided in a suppliers-oriented direction while there are not much discussions on what u-Services citizens should be provided with and what u-Services that city government the supplier shall provide. In order to implement citizen-friendly u-Services the type of u-Services that offer just the right services efficient and convenient for citizens, u-Services should be provided based on active researches on the citizens' use and utilization of u-Services rather than u-Services being provided in suppliers' perspective as so far. To that end, there need be recognition and well-organized methodology that u-Services should be provided through humane, social and scientific analysis of the citizens that are to be provided with u-Services. Thus, in this study, the process of u-Services being transmitted was re-interpreted as background theory to deduce and apply services appropriate for u-Residential Space, and service science for u-Services the scientific and overall approach to seek for service innovation was applied to the development of u-Service deduction method based on such background theory. The u-Service methodology developed based on service science is judged able to deduce and provide u-Services appropriate for the intended services through scientific analysis of citizen-friendly u-Services.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.43-47
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• 2021

In the course of this article, the concept of "innovation" was considered and analyzed, which is considered not only as a subject, something new, but also as a process. The process of introducing something new into life, and in our case, into the educational process. Innovative educational technologies are varied and plentiful. In this article, the most commonly used. Among them: the use of ICT, game techniques, the portfolio method, personality-oriented, information support of the learning process, educational and health-saving technologies, and others.