• Journal of Digital Policy
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• v.1 no.2
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• pp.41-45
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• 2022

In this study, we look at the current address of industrial complexes and the government's support policies for industrial complexes so far, examine the problems and improvements of industrial complexes in the era of great transformation, and then suggest how to innovate industrial complexes, and suggest the plans and tasks. want to report. To summarize the conclusion, in order to enhance the competitiveness and innovation of industrial complexes, which are the main axis of the national economy, a governance system in which the government, regional innovation organizations, and businesses cooperate must be established to transform industrial complexes suitable for the transition period and foster excellent industrial complexes. It is urgent to actively support the policy and budget input of each government department.

• Journal of Technology Innovation
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• v.20 no.3
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• pp.199-228
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• 2012

While there are increasing requests for open innovation, prior studies have focused mainly on the utilizing the external sources. This study suggests to broaden the way of measuring openness to include the innovation management factors and output besides of utilizing the external sources. Additionally, the new measures will compare the status of openness in small and medium enterprises between Korea and Japan. There is greater differences in openness between SMEs and big firms in Japan than ones in Korea. Although SMEs in Japan utilize the external knowledge sources more actively than ones in Korea, they show less openness from the perspective of managerial factors such as metric for open innovation, collaboration system, investment for collaboration, and performance.

• Journal of Korea Technology Innovation Society
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• v.21 no.2
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• pp.818-837
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• 2018

Technological innovation has inherent difficulties, largely due to the uncertainties of technology. Thus, the forecasting methodology to reduce the risk of uncertainty in the innovation process has been presented both in quantitative and qualitative fields. On the other hand, big data and artificial intelligence have attracted great interest recently, and deep learning, which is one of the algorithms of AlphaGo, is showing excellent performance. In this study, deep learning methodology was applied to the prediction of innovation performance. To make the prediction model, we used KIS 2016 data. The input factors were importance of information source and innovation objectives and the output factor was innovation performance index, which was calculated for this study. As a result of the analysis, it can be confirmed that the accuracy of prediction is improved compared with the previous studies. As learning progressed, the degree of freedom of prediction also improved.

• Journal of Korea Technology Innovation Society
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• v.17 no.2
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• pp.380-420
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• 2014

We increasingly see the importance of employees acquiring enough expert capability or innovation capability to prepare for ever growing uncertainties in their operation domains. However, despite the above circumstances, there have not been an enough number of researches on how operational input components for employees' innovation outcome, innovation activities such as acquisition, exercise and promotion effort of employee's innovation capability, and their resulting innovation outcome interact with each other. This trend is believed to have been resulted because most of the current researches on innovation focus on the units of country, industry and corporate entity levels but not on an individual corporation's innovation input components, innovation outcome and innovation activities themselves. Therefore, this study intends to avoid the currently prevalent study frames and views on innovation and focus more on the strategic policies required for the enhancement of an organization's innovation capabilities by quantitatively analyzing employees' innovation outcomes and their most suggested relevant innovation activities. The research model that this study deploys offers both linear and structural model on the trio of learning, innovation capability and innovation outcome, and then suggests the 4 relevant hypotheses which are quantitatively tested and analyzed as follows: Hypothesis 1] The different levels of innovation capability produce different innovation outcomes (accepted, p-value = 0.000<0.05). Hypothesis 2] The different amounts of learning time produce different innovation capabilities (rejected, p-value = 0.199, 0.220>0.05). Hypothesis 3] The different amounts of learning time produce different innovation outcomes. (accepted, p-value = 0.000<0.05). Hypothesis 4] the innovation capability acts as a significant parameter in the relationship of the amount of learning time and innovation outcome (structural modeling test). This structural model after the t-tests on Hypotheses 1 through 4 proves that irregular on-the-job training and e-learning directly affects the learning time factor while job experience level, employment period and capability level measurement also directly impacts on the innovation capability factor. Also this hypothesis gets further supported by the fact that the patent time absolutely and directly affects the innovation capability factor rather than the learning time factor. Through the 4 hypotheses, this study proposes as measures to maximize an organization's innovation outcome. firstly, frequent irregular on-the-job training that is based on an e-learning system, secondly, efficient innovation management of employment period, job skill levels, etc through active sponsorship and energization community of practice (CoP) as a form of irregular learning, and thirdly a model of Yί=f(e, i, s, t, w)+${\varepsilon}$ as an innovation outcome function that is soundly based on a smart system of capability level measurement. The innovation outcome function is what this study considers the most appropriate and important reference model.

• Journal of the Korean association of regional geographers
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• v.15 no.5
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• pp.525-536
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• 2009

In the period of rapid economic growth, it is possible to practice the growth policy by factors input and the regional development policy by the dispersion of growth. But, in the period of weakened growth, this model loses its theoretical and practical merit. The endogenous regional development model that can efficiently cope with a international competition and a uncertainty of international economy become an alternative policy of growth and regional development. France, which had a problem of overcrowding in the capital region by the centralized growth policy and regional development policy, phase the regional innovation system policy in order to establish the foundation of an endogenous regional development from the 1970's. The regional innovation system policy in France which pursues simultaneously the systematic regional knowledge creation and the regional development is very suggestive to the regional innovation system policy in Korea that pursues the endogenous regional development and the solution of the regional disparity.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.2
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• pp.109-133
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• 2024

This study investigated the impact of the technical characteristics of Generative AI (GAI) and librarians' personal traits on their intention to use GAI. Personalization, interaction, and context awareness were considered as technical characteristics of GAI that influence the intention to use GAI, while innovativeness and frequency of GAI use were considered as librarians' personal traits. The study targeted 187 librarians working in libraries, and 165 questionnaires were collected and analyzed. The results showed that the technical characteristics of GAI had a statistically significant impact on the intention to use GAI. Additionally, librarians' personal traits, namely innovativeness and frequency of GAI use, were also found to have a significant impact on the intention to use GAI. The findings of this study can be used as valuable information to help librarians increase their intention to use GAI and improve the quality and satisfaction of library services.

• Journal of Technology Innovation
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• v.19 no.1
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• pp.111-144
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• 2011

This study is to confirm the core factors of innovative capabilities and technological entrepreneurship affecting the performance of technology management and business management of small and medium-sized enterprises (SMEs). Through the consideration about the complex natures of technological innovation affecting by multidimensional factors, this study designs the research model that innovative capabilities, the performances of technology and business management are arranged in accordance with the innovation process; input-output-outcome. To meet this research purpose, the hypothesis are set up based on the previous research studies and the research samples are selected from members of the Innovative Business (INNO-BIZ) Association, located in Seoul and Geyonggi province. As a result of regression analysis to the responses gathered from 360 firms, the performance of business management is influenced positively by the technology superiority, market growth and business profitability which are the dominant factors of performance of technology management. In addition, three sub-variables of innovative capabilities such as R&D, strategic planning and learning capability, have positive effects on both the managerial performances. Innovativeness and progressiveness of technological entrepreneurship affect both the performances positively. Moreover, the co-relation between technological entrepreneurship of an innovation leader and innovative capabilities of organizational members are identified. Lastly, technological entrepreneurship has the mediating effect on the path of leading innovative capabilities to the managerial performances. In conclusion, the research results imply that technological innovation-type firms should periodically evaluate the performance of technology management which are the output of technological innovations and the reinvestment for ultimate business success. And improving and developing innovative capabilities and technological entrepreneurship is required to continuously and consistently investing and supporting resources on technological innovations at the firm-and government-level. It is considered that these are the crucial methods for securing the technologically competitive advantage of SMEs with less resources and narrow innovation range.

• Journal of Korea Technology Innovation Society
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• v.13 no.1
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• pp.1-27
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• 2010

In this paper We analyze the correlation between investment and performance of Korean R&D programs, by six factors diversified, based on evolutionary economics of technology. National Science and Technology Information Service(NTIS) started from March, 2008 was used for collecting investment and performance data of national R&D program. We search the investment cost according to science-technology standard classification of Korea, research conductors, socio-economic objectives and cooperation types per year from 2002 to 2008, and we regard this data as "investment". Similarly, we search the number of papers, patents, commercializations, royalties and so forth according to science technology standard classification of Korea, research organizations, socio-economic objectives and cooperation types per year from 2002 to 2008, and this data is regarded as "performance". We expected analysis results of this investment and performance data confirm the diversified factors to affect advancement of science and technology. And we though, as a result, we will get some meaningful directions of investment of national R&D from the analysis results. But this study has several limitations because we did not consider enough microscopic characteristics of sector or technology, research organizations, cooperation network types, and external effect of social, politic, cultural factors.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.1
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• pp.73-87
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• 2018

Creativity, entrepreneurship, and technological innovation orientation are key factors for technological innovation. The main driver of technological innovation in the enterprise is the executives of the firm. According to the Upper Echelons Theory of D.C. Hambrick(2007), the creativity of the managerial individual will be put into various aspects within the organization's innovation system. The organizational innovation system is positively influenced by the creativity of the executives, and is achieved by manifesting innovation orientation and technological innovation orientation with innovative performances. The purpose of this study is to investigate using Structural Equation Modeling(SEM), whether individual creativity of executives of 132 companies with research organizations among domestic semiconductor companies in Korea influences innovation performance of firms through entrepreneurship orientation and technology innovation orientation. We applied the personal creativity level measurement index, the entrepreneurial orientation measurement factor, and the technology innovation orientation measurement factor identified in the previous research literature. The results of the Structural Equation Modeling analysis show that the creativity of executives have a positive (+) relationship with the innovation performance of firms when they are only mediated by technological innovation orientation, and entrepreneurial orientation. On the other hand, the results of the SEM shows the direct effects between the creativity of executives and innovation performance are not statistically valid. As a result, the individual creativity of executives who lead the innovation of the firm, entrepreneurial orientation, and technological innovation orientation of the researcher organization are very important factors and an inseparable relationship for the successful innovation of the firms.

• Journal of Korea Technology Innovation Society
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• v.14 no.3
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• pp.431-465
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• 2011

Focusing on open innovation which is regarded as an important framework for strengthening technological innovation capabilities, in this study empirical analysis is conducted on Korean manufacturing companies, particularly based on the survey results of 149 domestic manufacturing companies that carry out innovation activities in order to identify influence factors for open innovation activities. Analysis on the influence factors of open innovation activities categorized into characteristics of environment, firm-specific characteristics, and characteristics of institutions revealed that characteristics of environment in terms of the degree of market competition and technological changes influence outside-in open innovation activities. Such results suggest that companies respond to increased market competition or technological changes by promoting research and development (R&D) and maintaining or acquiring market competitiveness through introduction of external technology and utilization of external information by means of research collaboration, user innovation, and so on. In terms of firm-specific characteristics, outside-in open innovation activities are influence by R&D personnel, R&D investment, number of international business, export, and openness of corporate culture while inside-out open innovation activities are influenced by characteristics of international organization and CEO's capabilities. In order for companies to strengthen outside-in open innovation activities emphasis on research personnel, R&D input factors such as research funds are necessary whereas to increase inside-out open innovation activities organization solely responsible for international affairs should be established while the CEO needs to focus on open and cooperative entrepreneurship rather than internal technological innovation activities. In terms of characteristics of institutions, outside-in innovation activities are influenced by technological networking whereas inside-out innovation activities are influenced by networking for development of technology and the presence in industrial cluster. This means that the government needs to establish industrial clusters and try to expand technological networking to facilitate open innovation activities.