• Asian Journal of Innovation and Policy
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• 제4권2호
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• pp.242-262
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• 2015

The relationship between geographical proximity and academics' formal and informal knowledge-transfer activities in the network is analyzed with a mixed research method. With social network analysis as a basis, we have explored the networks between academics and firms in the 16 regions of South Korea. The result shows Seoul and Gyunggi are identified as central nodes, meaning that the academics in other regions tend to collaborate with firms in these regions. An econometric analysis is performed to confirm the localization of knowledge-transfer activities. The intensity of formal channels measured by the number of academic papers is negatively, but significantly associated with the geographical proximity. However, we have not found any significant relationship between the formality of the channels and geographical proximity. Possibly, the regional innovation systems in South Korea are neither big enough nor strong enough to show a localization effect.

• World Technopolis Review
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• 제5권1호
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• pp.47-60
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• 2016

In today's digital non-linear global business environment, innovation initiatives are influenced by inter-organizational, political, economic, environmental, technological systems, as well as by decisions made individually by key actors in these systems. Network-based structures emerge from social linkages and collaborations among various actors, creating innovation ecosystems, complex adaptive systems in which entities co-create value. A shared vision of value co-creation allows people operating individually to arrive together at the same future. Yet, relationships are difficult to see, continually changing and challenging to manage. The Innovation Ecosystem Transformation Framework construct includes three core components to make innovation relationships visible and articulate networks of relational capital for the wellbeing, sustainability and business success of innovation ecosystems: data-driven visualizations, storytelling and shared vision. Access to data facilitates building evidence-based visualizations using relational data. This has dramatically altered the way leaders can use data-driven analysis to develop insights and provide ongoing feedback needed to orchestrate relational capital and build shared vision for high quality decisions about innovation. Enabled by a shared vision, relational capital can guide decisions that catalyze, support and sustain an ecosystemic milieu conducive to innovation for business growth.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1997년도 제12회 동계학술발표회 논문집
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• pp.133-158
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• 1997

This paper analyzes the characteristics of technological knowledge flow-structure of Korean manufacturing in dynamic perspective. In doing that, the concept of the knowledge network is introduced which is defined as a set of industries and their interaction(knowledge flow) or linkage. The analysis of the inter-industrial knowledge flows is based on the technological similarity by using R&D researchers'academic background in the year of 1984, 1987, 1990. The analysis is carried out by such methodology as network analysis, indicator analysis and simple statistical analysis. And the final results are drawn both in absolute terms(dimension effect) and in relative terms (proportion effect) respectively. The main findings are as follow. First, the Korean manufacturing knowledge network appears to strengthen existing inter-industrial knowledge linkages rather than to construct new linkages. Second, the network seems to form a dualistic structure in that some high-technology sectors (knowledge production sectors) emerge along with traditional sectors (knowledge absorbing sectors). Third, since the mid-1980s, an inter-industrial fusion is witnessed among technologically intensive sectors, indicating that some sophisticated innovation modes are emerging in Korean manufacturing system.

• World Technopolis Review
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• 제4권1호
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• pp.11-22
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• 2015

Globalization, increasing technological advancements and dynamic knowledge diffusion are moving our world closer together at a unique scale and pace. At the same time, our rapidly changing society is confronted with major challenges ranging from demographic to economic ones; challenges that necessitate highly innovative solutions, forcing us to reconsider the way that we actually innovate and create shared value. As such the linear, centralized innovation models of the past need to be replaced with new approaches; approaches that are based upon an open and collaborative, global network perspective where all innovation actors strategically network and collaborate, openly distribute their ideas and co-innovate/co-create in a global context utilizing our society's full innovation potential (Innovation 4.0 - Open Innovation 2.0). These emerging innovation paradigms create "an opportunity for a new entrepreneurial renaissance which can drive a Cambrian like explosion of sustainable wealth creation" (Curley 2013). Thus, in order to materialize this entrepreneurial renaissance, it is critical not only to value but also to actively employ this new innovation paradigms so as to derive community-driven shared value that stems from global innovation networks. This paper argues that there is a gap in existing business incubation model that needs to be filled, in that the innovation and entrepreneurship community cannot afford to ignore the emerging innovation paradigms and rely upon closed incubation models but has to adopt an "open incubation" (Ziouvelou 2013). The open incubation model is based on the principles of open innovation, crowdsourcing and co-creation of shared value and enables individual users and innovation stakeholders to strategically network, find collaborators and partners, co-create ideas and prototypes, share their ideas/prototypes and utilize the wisdom of the crowd to assess the value of these project ideas/prototypes, while at the same time find connections/partners, business and technical information, knowledge on start-up related topics, online tools, online content, open data and open educational material and most importantly access to capital and crowd-funding. By introducing a new incubation phase, namely the "interest phase", open incubation bridges the gap between entrepreneurial need and action and addresses the wantpreneurial needs during the innovation conception phase. In this context one such ecosystem that aligns fully with the open incubation model and theoretical approach, is the VOICE ecosystem. VOICE is an international, community-driven innovation and entrepreneurship ecosystem based on open innovation, crowdsourcing and co-creation principles that has no physical location as opposed to traditional business incubators. VOICE aims to tap into the collective intelligence of the crowd and turn their entrepreneurial interest or need into a collaborative project that will result into a prototype and to a successful "crowd-venture".

• 기술혁신학회지
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• 제20권1호
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• pp.175-204
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• 2017

산업과 지역의 혁신성과를 높이기 위한 기존의 정책이나 전략들은 지속적인 혁신 활동을 이끌어내고 기술혁신을 확산시키는 데는 한계가 있었다. 이에 대한 대안으로 최근에 혁신생태계가 떠오르고 있다. 이는 혁신 과정에 관련된 주체들의 상호작용이 지속적으로 변화하면서 혁신이 확산된다고 설명한다. 그러나 이 분야의 관련 연구들은 대부분 이론적 프레임웍을 제시하는데 그치고 있으며, 생태계의 구조적 동태성을 실증한 연구는 거의 없다. 본 연구는 산업생태계의 기술혁신에 따른 구조적 동태성을 실증하기 위해 산업기술의 활용을 둘러싼 기업 협력 네트워크에 대해 종단적 네트워크 분석을 수행하였다. 실증분석을 위해 기업 간 상호작용을 네트워크 데이터로 작성하여 구조적 등위성 분석을 실시하였다. 분석 결과에 따르면, 기술혁신의 확산과 관련된 기업 간 상호작용의 변화는 크게 세 가지의 패턴으로 요약된다. 즉, 기술 활용 방식의 제도화, 규모의 경제에 의한 혁신 확산, 기술 개방에 의한 롱테일 가치창출의 산업 구조가 만들어지면서 기술혁신의 성공적 확산이 가능해진다고 할 수 있다. 본 연구는 기술의 상업적 확산을 위한 기술활용 네트워크의 구성 및 기술혁신 관리에 있어 전략적 시사점을 제시하며, 지역혁신을 위한 전략 수립 시 활용될 수 있을 것이다.

• Asian Journal of Innovation and Policy
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• 제5권3호
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• pp.293-314
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• 2016

Patent information as a proxy measure of technological capability has been utilized to establish technological strategies of firms. It is important to monitor what competitors' plans for direction on research and development in the initial stage of new industry. Cancer metabolism has been considered as a beacon of hope for cancer research because it is anticipated that the research field will play a central role in developing effective cancer therapies. There is little attention given to understanding the status quo of organizational configurations. By utilizing network analysis, six sub-groups of cancer metabolism were categorized and the relationship between an individual field and participants were analyzed based on cluster and entire network-level. Although the largest drug and biotech companies tried to take an initiative across the whole fields, the differences in technological capabilities between them was discovered. This paper attempts to improve the validity of the suggested procedure and is significant in that it looks at the entire structure of cancer metabolism research from a strategic perspective for the first time.

• 디지털융복합연구
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• 제13권1호
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• pp.93-110
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• 2015

본 연구는 고객 네트워크와 공급자 네트워크, 그리고 혁신성과간의 관계에서 T자형 기술의 역할을 규명하기 위해 수행되었다. 기업 간 협력관계를 효과적으로 관리하기 위해서 필요한 요소는 관련 선행 지식이다. 흡수역량의 전제조건은 새로운 지식을 인지하고, 완전히 이해하고 이를 적용하기 위해서 기업이 관련 선행 지식을 보유하고 있어야 한다는 것이다. 이러한 관점에서 T자형 기술은 새로운 관련 지식의 학습을 용이하게 해주며, 혁신 성과에 중요한 요소이다. 실증분석 결과 T자형 기술은 네트워크와 혁신성과 간의 중요한 매개변수로 작용하는 것으로 나타났다. 본 연구는 이를 통해 앞으로 고객 및 공급자와의 네트워크를 구축하고 적극적으로 활용하는 기업에게 어떻게 구축된 네트워크를 통한 효과를 극대화 할 수 있는지 그 방향성을 제시하고 있다.

• 한국경제지리학회지
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• 제15권2호
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• pp.147-165
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• 2012

이 논문은 중소기업을 대상으로 최근 기술혁신의 새로운 패러다임으로 대두되고 있는 개방형 혁신활동을 파악하는데 목적을 두었다. 특히 중소기업들이 기술혁신 과정에서 어떻게 외부와의 협력 네트워크가 구축되며, 실제로 어떤 단계에서 개방형 혁신활동이 이루어지는 가를 분석하였다. 외부와의 협력을 통해 기술개발을 경험한 3,400개 중소기업을 대상으로 개방형 혁신활동의 특성을 파악하였으며, 기술혁신과정의 어떤 단계에서 어떻게 개방형 혁신활동이 이루어지는 가를 구체적으로 파악하기 위하여 충북테크노파크에 입지한 14개 업체를 대상으로 하여 심층 인터뷰도 병행하였다. 연구 결과 기업 자체의 혁신역량이 부족한 중소기업의 경우 아이디어 단계 및 기술개발 단계에서 개방형 혁신활동을 통해 외부로부터 다양한 자원을 활용하며, 기업이 혁신적일수록 개방형 혁신활동을 활발하게 수행하고 있고, 이직이나 창업과 같은 노동시장의 유연성도 나타나고 있다.

• 대한안전경영과학회지
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• 제13권3호
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• pp.133-143
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• 2011

It seems required to determine what might affect the technological innovation activities of manufacturing companies and what kind of role they could play for them to carry out technological innovation activities in an effective way. The objective of the present study is thus to conduct a depth empirical analysis of the structural relations among business environment, technological innovation activities and performance of manufacturing companies. From the analysis, following outcomes could be drawn: First, with regard to the relationship between business environment and technological innovation activities of manufacturing companies, it has become clear that the external environment is a factor that can influence technological innovation activities such as management of technical property, technological innovation system as well as technical network, while it exercises no impact upon adaptation of manufacturers to new technologies. The internal environment, on the other hand, turns out to have influence on such overall factors of technological innovation activities as management of technical property, technological innovation system, adaptation to new technologies and technical network; and Second, as for the relationship between technological innovation activities and their performance, it has been obvious that management of technical property and technological innovation system, both factors of technological innovation activities, affect the performance of product development and financial achievements of manufacturing companies. Their adaptation to new technologies will also affect their performance of product development as well as financial achievements. These findings suggest that it is important for manufacturing companies to set up an operating system that may be able to upgrade the practical applicability of their technological development activities in an attempt to promote performance of their technological innovation activities.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.327-341
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• 2021

The knowledge management was considered as the inevitable result of the rule of knowledge in this era, and its importance became clear in being the main source for achieving success, the need to consider and manage knowledge as an independent field that must be addressed with a clear scientific methodology has become intangible - they are very valuable and a strategic asset. On the other hand, the innovation process relates to all parts of the organization, and helps to improve the behavioral patterns of individuals and their attitudes towards adopting modern and innovative ideas, it is a purposeful process adopted by the senior management and works to provide the capabilities and requirements for embodying the innovative behavior in it. In the field of dealing with the market, it is a product of the organization's innovative approach, which aims at advancement, change, and intended and organized renewal. The main objective of this article is to determine the most appropriate ways to integrate knowledge management mechanisms to employ innovation factors within universities based on the role of universities in supporting innovation. This was achieved through reviewing many relevant research and listing the most prominent concepts of knowledge management, its importance, objectives, and processes determining the stages of knowledge management application, the requirements for applying knowledge management, and the obstacles that impede its application; Then the statement "Innovation in universities, through which it addressed the concept of innovation, its importance, stages, and requirements for its application, as well as identifying the most prominent models of innovation, and obstacles to innovation, in addition to that the role of universities in supporting innovation will be identified. From the surveyed study done in this article, we concluded that the relationship among organizational culture, knowledge management and innovation capability can provide useful insights for managers regarding developing a strong culture, promote knowledge management practices effectively and eventually enhance the whole organization's innovation capability. Also, we found that different components of Knowledge Management as Knowledge activities, Knowledge types, transformation of knowledge and technology have a significant positive effect in bringing innovation through transformation of knowledge into knowledge assets in universities.