• Proceedings of the Korea Technology Innovation Society Conference
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• 2002.11a
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• pp.5-25
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• 2002

• Journal of Korea Technology Innovation Society
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• v.13 no.3
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• pp.513-537
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• 2010

According to the "FDI-as-market-discipline" hypothesis, inward FDI acts as a mechanism of change in market structure affecting innovative activities of domestic firms. We used panel KIS data for testing this hypothesis. Binary probit estimation shows that, in contrast to the German case of Bertschek (1995), FDI is insignificant in Korean case for explaining product innovation. 1his result maybe comes from the fact that the industries in Korea are more monopolistic or oligopolistic than those of Germany. Using panel data, we tried random parameter estimation using matrix weighted average of GLS and OLS. The result shows different estimates from cross-section outcome and panel estimation with parameter homogeneity, so we can infer large parameter heterogeneity across firms. But, interpretation for FDI variable is similar across panel and cross-section estimation.

• Information Systems Review
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• v.25 no.4
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• pp.291-314
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• 2023

The concept of Mydata emerged with the expansion of the data economy. MyData aims to empower individuals by enhancing their right to self-determination over their personal data. The use of MyData is expected to enable the provision of innovative service in various fields. Since 2022, MyData has been introduced and actively used in the financial sector. In the future, not only financial institutions but also Bigtech and Fintech companies are expected to actively join and demonstrate rapid expansion. To ensure steady growth for MyData in the financial sector, it is necessary to assess acceptance behaviors from multiple perspectives. However, the majority of existing research solely focuses on positive acceptance. This study analyzed the impact of users' personal characteristics and innovation characteristics on both innovation resistance and acceptance resistance. The analysis revealed that personal and innovation characteristics contribute to an increase in distrust and innovation resistance in the MyData service. In addition, it has been confirmed that it can lead to actions such as delayed acceptance and refusal to accept. The results of this study offer both theoretical and practical insights into user behavior within the MyData service market.

• The Journal of Bigdata
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• v.7 no.1
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• pp.113-124
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• 2022

Various methods using machine learning and big data have been applied to prevent failures in Data Centers. However, there are many limitations to referencing individual equipment-based performance indicators or to being practically utilized as an approach that does not consider the infrastructure operating environment. In this study, the performance indicators of individual infrastructure equipment are integrated monitoring and the performance indicators of various equipment are segmented and graded to make a single numerical value. Data pre-processing based on experience in infrastructure operation. And an ensemble of RRCF (Robust Random Cut Forest) analysis and Prophet analysis model led to reliable analysis results in detecting anomalies. A failure analysis system was implemented to facilitate the use of Data Center operators. It can provide a preemptive response to Data Center failures and an appropriate tuning time.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.4
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• pp.169-181
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• 2018

Under the constantly intensifying global competition environment, many companies are exploring new business opportunities in the field of social innovation using creating shared value. In seeking social innovation, it is a key starting point of social innovation to clarify the problem to be solved and to grasp the cause of the problem. Among the many problem solving methodologies, design thinking is getting the most attention recently in various fields. Design Thinking is a creative problem solving method which is used as a business innovation tool to empathize with human needs and find out the potential desires that the public does not know, and is actively used as a tool for social innovation to solve social problems. However, one of the difficulties experienced by many of the design thinking project participants is that it is difficult to analyze the observed data efficiently. When analyzing data only offline, it takes a long time to analyze a large amount of data, and it has a limit in processing unstructured data. This makes it difficult to find fundamental problems from the data collected through observation while performing design thinking. The purpose of this study is to integrate qualitative data analysis and quantitative data analysis methods in order to make the data analysis collected at the observation stage of the design thinking project for social innovation more scientific to complement the limit of the design thinking process. The integrated methodology presented in this study is expected to contribute to innovation performance through design thinking by providing practical guidelines and implications for design thinking implementers as a valuable tool for social innovation.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.193-195
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• 2021

최근 우리나라에서 재배되고 있는 농작물은 지구 온난화 등의 영향으로 점점 북상하고 있다. 이러한 농업 환경의 변화에 적극적으로 대처하기 위해 본 논문에서는 농업 재배지의 환경 데이터를 수집하고 분석하여 현재 농업 재배지에 최적화된 농작물을 추천할 수 있는 농작물 추천 서비스를 제안한다. 이를 위해 농작물 추천 서비스에 활용하기 위해 농업 환경 데이터의 모니터링과 농작물 데이터 관리 스마트팜 모형을 설계 및 구축한다.

• Review of KIISC
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• v.26 no.2
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• pp.20-24
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• 2016

스마트폰과 태블릿 등 모바일 디바이스의 대중화로 우리 주변에는 규모를 가늠할 수 없을 정도로 많은 정보와 데이터가 생산되는 "빅데이터(Big Data)" 환경이 도래하고 있다. 최근 몇 년간의 빅데이터 기술 혁신은 공히 낙후된 금융 산업에도 많은 변화를 낳고 있다. 해외에는 미국과 영국을 중심으로 핀테크 스타트업에 대한 투자가 활발히 이루어지고 있으나, 국내의 경우에는 아직 금융IT 분야에 있어 선도적인 서비스가 없어[1], 스타트업 회사들에게 많은 기회가 있다고 파악된다. 본 논문에서는 빅데이터의 도래로 인한 시장 환경 변화를 살펴보고, 해외 금융 시장의 혁신을 선도하는 핀테크 스타트업 동향을 알아본다. 이를 통해, 국내에서 핀테크 스타트업이 앞으로 가질 수 있는 기회에 대하여 전망해 본다.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2003.05a
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• pp.31-43
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• 2003

The transformation of sector system in ICT, a prominent character in sector systems, has been paid much attention in innovation theory since Information technologies and technological environment have rapidly changed. In this context, we employ US patent data and proxy variables, measuring the basic elements for analyzing SIS and its technological characteristics in order to explore how SIS is transformed. By utilizing patent analysis, it is demonstrated that technological regimes, key links and Schumpeterian patterns of innovation have transformed drastically over last 3 decades in overall ICT sector. Consequently, our research shows clear evidence that Schumpeterian patterns of innovation have shifted from Mark I to Mark II in ICT. Our study provides a glimpse picture of dynamics of SIS since 1970 in the technological level by utilizing patent analysis.

• 한국벤처창업학회:학술대회논문집
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• 2020.11a
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• pp.47-53
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• 2020

빅데이터 기술은 기업의 경쟁력을 높일 수 있는 혁신 기술 중 하나로 급성장하고 있는 가운데 농업 분야 또한 빅데이터를 활용한 경쟁력 제고와 미래 산업으로의 발전이 중요 당면과제로 부상하고 있다. 해외의 경우 농업 빅데이터를 활용한 스타트업이 빠른 속도로 증가하며 성장하는 반면 국내의 경우 생산 분야 일부 농업 벤처 외에는 빅데이터 활용이 미흡한 실정이다. 또한 기업의 빅데이터 활용수준이나 활용의도에 영향을 미치는 요인에 대한 연구가 대기업이나 특정 산업에 국한되어 이루어지고 있으며, 연구마다 영향요인 변수의 검증결과가 상이하게 나타나 산업/기업특성에 따라 연구가 필요하다. 본 연구의 목적은 농업벤처기업에서 새로운 ICT인 빅데이터를 도입하고 사용하는 데 영향을 미치는 요인을 파악하고, 이를 통해 기대하는 편익에 대해 파악함으로써 활용을 촉진할 수 있는 방안을 제시하는 데 있다. 본 연구는 빅데이터가 조직의 프로세스를 변화시키고, 최고경영층의 지원이 필수적이며, 기업이 처한 환경적 압박에 대응할 수 있는 수단으로 보고 기술·조직·환경(TOE: Technology-Organization-Environment) 프레임워크를 기반으로 혁신확산이론(Diffusion of Innovation Theory) 모형을 결합하여 본 연구에 적합한 변수들을 도출한 후 이들 변수간의 인과관계를 설정하여 연구모형을 구성하였다. 이에 따라 TOE모형의 기술적 요인에 관한 변수로는 혁신확산이론 변수인 상대적이점, 호환성, 복잡성을 채택하였고, 조직적 요인에 관한 변수로 최고경영층 지원, 비용부담능력을, 환경적 요인에 관한 변수로는 법적·정책적 지원, 경쟁자 압력을 채택하였다. 이들 3가지 요인에 속한 7가지 변수들과 빅데이터 사용의도와 기대편익 간의 관련성, 그리고 농업벤처 사업분야의 조절효과에 대한 8개의 가설을 설정하였다. 본 연구는 실제 농업벤처기업 종사자 대상 설문을 통한 실증연구를 통해 벤처 현장에서의 빅데이터 활용수준을 높이기 위한 기술적, 조직적, 환경적 관점의 정책 개선방안을 제시하고, 생산/가공/유통 등 사업분야별 비교를 통해 영향요인의 중요도 차이를 규명해 영역별로 차별적이고 효과적인 정책 방향성을 도출하는 데 시사점을 제시하고자 한다.

• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.159-182
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• 2018

The purpose of this study is to increase the competitiveness of big data in the maritime port organization, by understanding the expected performance and the intention to accept and use big data. In the empirical analysis of factors affecting the intention to use the big data technology for maritime port organizations, the variables employed are based on the Technology Organization Environment(TOE) and Diffusion of Innovations(DOI) theories, which are related to the acceptance of information and communication technologies. To achieve the objective of this study, an empirical analysis was conducted; this analysis targeted the personnel involved in the department of strategic planning and information technology in the related field. We set up eight hypotheses to examine the relevance between variables having three characteristics-technology, organization, and environmental characteristics. The empirical results are summarized as follows. First, it was seen that the technology characteristic, including relative advantage, complexity, and compatibility, has a significant effect on the expected performance. Second, the top management support of the organization characteristic has a significant effect, but the firm size of this characteristic has no significant effect on the expected performance. Third, the competitive pressure of the environment characteristic has a positive effect on the expected performance, while the regulatory support has no significant effect. Finally, the expected performance has a significant effect on the intention to use big data.