• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1997년도 제12회 동계학술발표회 논문집
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• pp.104-130
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• 1997

This study empirically examined different patterns of collaborative R&D project with their key success factors(KSFs), using data from 80 projects in the Korean electronic parts industry The patterns in this study were categorized into 4 types by two criteria : product types(off-the-shelf/unique) and project initiator (focal/partner). The bivariate relationships revealed that project characteristics (technological complexity, demand certainty), partner characteristics(the number of partners, precious experience), process characteristics (participation in the project formulation, specificity of the collaboration process and outcomes) appear to be different among four types of collaboration. Furthermore, this study found that each type of collaborative R&D projects has different KSFs for their commercial success. The KSFs of type 1 (off-the-shelf product and focal organization initiation), for instance, include the strategic importance of the project, the problem solving performance of the focal organization while those of type 4(unique product and partner initiation) are technological complexity, demand certainty, reliability of partner relationship, specificity of the goals, specificity of the process and outcomes, information sharing. Finally, based on this empirical results, managerial, policy, and theoretical implications of the study were discussed.

• 한국항공운항학회지
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• 제14권4호
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• pp.48-59
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• 2006

This Study focused on the process of technology transfer for the aircraft development program by the strategic alliance. Especially, this study showed how the learning firms absorb new technology from the foreign leading company. This case study concludes that teachability, asset specificity, relation capital with partner, information sharing system in organization and knowledge base are key factors for absorbing the new technology from the technology leading partner.

• 기술혁신연구
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• 제6권2호
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• pp.122-158
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• 1998

This study empirically examined different patterns of collaborative R&D project with their key success factors(KSFs), using data from 82 projects in the Korean electronic parts industry. The patterns of R&D collaboration were categorized into 4 types by two criteria development motive(technology Push/market pull) and Project initiator (focal firm/partner). The bivariate relationships revealed that project characteristics (technological complexity, market uncertainty), management characteristics (participation in project formulation), problem solving characteristics(problem solving performance of the focal firm, users active role in problem solving, active role of university or research institute in problem solving) and success rates appear to be different among four types of collaboration. Each type of collaborative R&D projects also had different KSFs. The KSFs of type 1 (technology Push and focal firm initiation), for instance, include the strategic importance of the project, focal firms share of cost, active role of university or research institute in problem solving, while those of type 4(market pull and customer initiation) cover reliability of partner relationship, a time at partners involvement, information sharing. The findings suggest that the different contingencies brought different patterns and KSFs of collaborative R&D project, since different information, resources, and partners roles were needed to successfully implement the projects according to development motive and project initiator Finally, managerial, policy, and theoretical implications for the collaborative R&D activities in the Korean electronics parts industry were discussed, based on empirical results of this study.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 2005년도 제26회 동계학술발표회 논문집
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• pp.42-56
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• 2005

Firms cooperating in R&D face a moral hazard problem, because with R&D effort not being observable each partner will focus on its own profit when choosing its effort level. This paper aims to explain the use of optimal license contract for R&D cooperation such as cross-licensing agreement. We argue that in the situations of asymmetric information, the optimal incentive scheme that can solve moral hazard problem is . a linear function of the likelihood ratio. Especially in the case of parallel research, each firm has an extra incentive for cooperative R&D effort, given by the license fee that considers the profit of the cooperating firm, which solely depends on his R&D success if the cooperating firm fails.

• 기업가정신과 벤처연구
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• 제19권4호
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• pp.1-17
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• 2016

본 연구는 상대적으로 지식과 자원이 부족한 벤처기업이 외부의 다양한 유형의 파트너와 R&D 협력 관계를 효율적으로 활용, 관리하는 것을 통해 혁신 성과에 유의미한 영향을 줄 수 있음을 살펴보고 있다. 혁신은 벤처기업의 생존과도 직결되는 중요한 요인 중 하나로 여겨져 왔다. 일반기업과 달리, 벤처와 같이 자원의 제약이 있는 신생 기업의 경우 R&D 그 자체에 있어 필요한 자원이나 혹은 이러한 신기술 또는 아이디어를 독자적으로 상품화하고 시장에 내놓는데 필요한 자원이 부족한 경우가 많다. 따라서 이를 보완해 줄 외부 협력 파트너를 찾고 효율적으로 관리하는 것이 굉장히 중요한 이슈이다. 오늘날 대부분의 기업들은 하나의 협력 관계만을 보유하지 않고, 다수의 R&D 협력관계를 동시에 맺고 여러 파트너들과 교류하고 있다. 학자들은 이러한 여러 협력 관계를 포트폴리오적인 차원에서 효율적으로 관리하는 것의 중요성에 대해 언급하여 왔다. 협력관계를 맺고 유지하는데 있어서도 상당한 양의 시간과 자원 투자가 요구되며 관리차원의 주의(managerial attention)가 필요하기 때문에, 협력 관계를 전사(全社)차원에서 관리하여 효율성을 높이는 것이 중요하다. 자원의 부족이라는 벤처기업의 근본적인 특성을 생각해 볼 때, 벤처기업에게 있어서 더욱이 전사차원의 효율적 협력 관계 관리에 대한 고찰이 절실하게 필요하다고 할 수 있다. 본 연구를 통해 벤처기업의 협력 파트너 종류의 다양성과 협력 파트너에 대한 의존도의 다양성이 혁신성과에 미치는 영향을 살펴봄으로써, 보다 효율적인 협력 파트너 구성에 대하여 포트폴리오적인 시각에서 고찰하고자 한다. 2010년 제조업을 대상으로 한 한국기업혁신조사(KIS) 자료를 분석한 결과, 기존 기업 대비 벤처기업에게 있어서 R&D 협력이 혁신성과에 더욱 중요한 영향을 준다는 것을 확인하였다. 따라서 벤처기업은 이를 전사차원에서 효율적으로 관리하여야 하는데, 외부 파트너 유형의 다양성과 혁신 성과는 비선형적 관계(역 U자형)를 나타내므로, 다양성만을 지속적으로 추구할 것이 아니라 긍정적 효과를 상쇄하지 않는 범위 내에서 이를 유지하는 것이 중요하다는 것을 발견하였다. 더불어 각 파트너들에 대한 의존도는 다양하게 가져가는 것이 혁신성과에 중요하다는 결론을 얻을 수 있었다.

• Asia pacific journal of information systems
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• 제23권3호
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• pp.25-53
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• 2013

This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.

• 산업경영시스템학회지
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• 제29권3호
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• pp.79-86
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• 2006

Especially, MTO(Make-To-Order) companies take collaborative approaches with their partner companies to make low-price products and/or technologically low intensive products. The collaborative approach to manufacturing requires collaboration with partner companies for inventory review, production plan, and manufacturing to fulfill customer's orders. However, frequent changes of partnerships binder partner companies from sharing production information in effective ways since their information systems have different data architectures and platforms. Therefore, it is required flexible and standardized system integration approach fir effective information sharing. This research studies current status and problems of collaborative production system, proposes an architecture for collaborative production systems based on Web Services which is a standard information technology, and discusses expected effects and the vision of Web Services.

• 기술혁신연구
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• 제19권2호
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• pp.153-184
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• 2011

본 연구는 기업의 핵심 기술전략 중 하나인 기술협력과 관련하여 기업들이 어디에 위치한 기술협력파트너를 더 선호하는지에 대하여 알아본다. 가까운 거리일수록 지식의 전달이나 확산이 효과적이라는 점에서 근접한 파트너가 유리할 수 있지만, 새롭고 다양한 지식의 확보가 기술협력의 목적이라면 원거리 파트너의 장점 역시 간과할 수 없다. 또한, 기업들이 많이 모여있는 집적지에서 발생하는 외부경제 및 불경제 현상 역시 고려할 필요가 있다. 따라서 이번 연구에서는 두 협력파트너가 서로 가까이 위치하는가와 각각 얼마나 많은 기업이 밀집한 곳에 위치하는가를 통해 지리적 특징이 기업의 파트너 선택에 어떠한 영향을 미치는지 살펴보았다. 2008년도 기술혁신조사를 이용한 실증분석 결과를 요약하면, 기업은 기술협력파트너를 선택하는 데에 있어서 파트너의 지리적 근접성을 매우 중요하게 생각한다. 효과적인 의사소통이 가능하고, 정보비대칭성을 줄이며, 협력관계 중에도 꾸준한 모니터링이 용이하기 때문이다. 하지만, 파트너가 집적지에 위치한다는 것은 파트너 선택에 별다른 영향을 주지 못한다. 반면, 자신이 집적지에 위치해있다는 것은 중요한 요소로 여기는데, 관련산업의 집적지에 위치할 경우 파트너를 가까운 곳에서 찾으려는 경향이 있지만, 비관련산업이 많은 곳에 위치했을 경우 파트너를 외부에서 찾으려는 경향을 보인다. 관련산업 집적지 내의 파트너에게서 자신에게 유용한 혁신 정보를 얻을 수 있는 반면, 비관련산업의 집적지는 혼잡비용, 의도치않은 지식유출, 기술적 구속 등의 단점에 대한 우려가 더 큰 것으로 보인다. 이러한 특성은 경쟁사, 공급자, 수요자, 대학, 정부연구소 등 파트너의 종류에 관계없이 상당부분 일정하게 나타나며, 다만 정부연구소와의 협력의 경우에만 지리적 근접성의 효과가 약화된다. 본 연구는 기업의 혁신 행태를 분석하는 데에 여러 시사점을 제시한다. 우선, 기업은 효과적인 지식확산을 위해 근접한 파트너를 선택하지만, 자신이 비관련 산업 집적지에 위치한 경우 외부의 파트너를 적극적으로 선택하려는 행태를 보인다. 가까운 파트너와 관련 기술을 집중적으로 연구하려는 유인과 외부의 파트너에게서 새로운 아이디어를 얻으려는 유인이 종합적으로 작용하고 있음을 유추할 수 있다. 이에 따라 정책 방향 역시, 산업클러스터 내에서 비슷한 기술을 가진 기업들끼리의 협력을 유도하는 한편, 클러스터-클러스터 간 혹은 다양한 지역 간에 여러 기술을 전파하고 공유할 수 있는 기회를 제공할 필요가 있다.

• 한국IT서비스학회지
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• 제4권2호
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• pp.135-144
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• 2005

The plenty of successful cases of Multi-national companies has been realized benefits of offshore outsourcing in particular "cost savings" from offshore IT outsourcing services, such as call center, software development, IT support and maintenance etc. A few Korean companies recently started to make the feasibility study of offshore IT outsourcing to catch up with the global trend. The objective of this study is to present the feasibility of offshore IT outsourcing of Korean companies through the analysis of pilot projects results between Indian and Chinese companies. The analysis include key elementsof cost, productivity, quality, practical issues as well as Gartner's framework, "AD Sourcing Cost Model", composed of 7 model factors. The findings of this study are not limited to understand offshore IT outsourcing but also provide useful guidelines covering wide range from the theoretical framework of selecting suitable offshore partner.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 2005년도 통합학술대회 논문집
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• pp.5-28
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• 2005

This paper estimates the effect of networks on innovative performance at the firm level , using Korean Innovation Survey (KIS) dataset Product innovation, product improvement , and process innovation are used as proxies for innovative activity. The explanatory variables such as firm size, market concentration ratio, lagged profitability, foreign ownership, export ratio, firm's age, formal R&D activity, and industrial R&D intensity are yet other considerations. With two year-long (2000 and 2001) data from 1,124 Korean manufacturing firms, we estimated the logistic regression model. The research finding indicates that the external networks have a strong positive effect on innovative output regardless of type of innovation. However, the network effects by partner (other firms or research institutions) vary across the type of innovation. Especially, we found that the user-supplier linkage plays an important role in product ion innovation, product improvement, and process innovation.