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

• Knowledge Management Research
• /
• v.16 no.4
• /
• pp.1-16
• /
• 2015

This paper aims to explore the small and medium sized enterprises'(SMEs') technological innovation through an open innovative strategy. Researchers have identified open innovation as external search 'breadth' and 'depth'. Although an open innovation strategy is well known as an effective way for SMEs' innovation, this stream of research examines differences between pursuing breadth of external knowledge and depth of external knowledge for SEMs' innovation. The sample comprises a total of 1106 SMEs included in the Korean Innovation Survey, and logistic regression analysis and odds ratio comparison were used to evaluate the relationship between external knowledge search and innovation outcomes. The results show that both 'breadth' and 'depth' positively affect the SMEs' innovation. When SMEs are simultaneously pursuing external searching for breadth and depth, however, a negative result on innovation outcome followed because of the lack of their internal resources and capacities. Despite these contributions, we have certain limitations that can be regarded as means of future research. Even though breadth and depth are adopted to measure the way of how a firm sources the external knowledge, companies may place the different weight on each source of knowledge. And also, it is difficult to understand how the knowledge gained through external search contributes to a firm's incremental and radical innovation, respectively.

• Journal of Arbitration Studies
• /
• v.32 no.4
• /
• pp.87-101
• /
• 2022

Since Research and Development has been expanded by government, It is very important to evaluate the outcome of Research and Development. Government have levied the penalty of researchers who misused research funding as time goes on. However, there is no protect law for the research before 2021. Government put new committee for the researchers to judge whether their action is legal or illegal based of Innovation Act 2021. Due to the various outcome index of research and development, many firms which is paticipating the research and development have been confused the outcome index. Also, It is difficult for government agencies for management to evaluate the outcome. Even if the committee is trying to solve dispute between researchers and the government agencies, it is not enough to solve it. Therefore, we need to consider Alternative Dispute Resolution(ADR), because the ADR has been developved detail skills for long time.

• The Journal of Society for e-Business Studies
• /
• v.15 no.1
• /
• pp.61-87
• /
• 2010

This study is based on the analysis of technology innovation performance for Inno-biz. The primary purposes of this study are to help the government formulate Inno-biz related supporting policies and improve the fitness of evaluation models for Inno-biz. In this study the definition of "the outcome of technology innovation" includes technology competitiveness changes, technology forecasting as well as the outcome of technology innovation. For this analysis, 55 independent variables were used and categorized into ability of technology innovation, ability of commercialization, and ability of technology management. The results indicate that all three variable groups have positively influenced the outcome of technology innovation. Especially ability of technology innovation is highly related to technology competitiveness and business in future. The ability of commercialization enhances technology competitiveness and predictability in major business indexes; however it doesn't influence business performance in a short-term period. The ability of technology management enables businesses to forecast technology changes, but doesn't effect short-term business outcomes.

• STI Policy Review
• /
• v.1 no.3
• /
• pp.53-68
• /
• 2010

This paper empirically evaluates the effects of regional and industrial R&D on the performances of individual firms in two separated stages: (1) the stage of technological outcome from R&D and (2) the stage of economic outcome from technological outcome. Technological spillovers are separated from negative congestion effects through the stage-specific estimation. The firm-level Korean Innovation Survey data merit in coping with the endogeneity problem inherent in the estimation of spillovers. The estimation results show that: (1) there exist significant R&D spillovers both in regional and industrial dimensions, (2) the hypothesized technological spillovers and economic congestion effects are both in effect, and (3) firms with smaller individual R&D investments show greater spillovers.

• Journal of Service Research and Studies
• /
• v.7 no.3
• /
• pp.71-91
• /
• 2017

The purpose of this study is to suggest directions for enhancing competitiveness of corporate management by examining how individual creativity and organizational members' value innovation culture perception affect innovation behavior and knowledge sharing, and how innovation behavior and knowledge sharing affect organizational innovation performance and management outcomes In order to achieve these research objectives, the measurement variables of each variable were extracted through previous research and 423 valid samples were analyzed using SPSS 22.0 statistical package program and LISREL 9.1 to verify a hypothesis. As a result of this study, it was found that the creative thinking skills of the individual creativity, the meaningful tasks of the value innovation culture recognition, and the risk - taking culture have a significant influence on the innovation behavior. Only the meaningful tasks of organizational members' value innovation culture perception affect knowledge sharing. Innovation behavior has a significant effect on knowledge sharing and innovation performance, but not on business outcome. In addition, knowledge sharing has no significant effect on innovation performance but has a significant effect on business performance. Finally, we confirmed that innovation performance has a significant effect on management outcome.

• Asian Journal of Innovation and Policy
• /
• v.6 no.2
• /
• pp.206-224
• /
• 2017

This article proposes a logic model for assessing the performance of the outcome of public research as a technology valuation method. It consists of two parts and eight steps. The first part is a scoring system and the second part is a validation process of the performance index derived from scoring by valuation method. The scoring in the first part generally requires a focus group method to find out the value drivers and make an evaluation table. The reason why we call it the technology valuation method is that the first part is derived from the simple evaluation of technology value using checklists for value drive. The second part is the regular technology valuation process. The model is designed for the measurement of unquantifiable outcome. Is knowledge or scientific outcome comparable to the measured outcome? If possible, how big is the unquantifiable outcome? This model is based on financial valuation techniques with clear or acceptable market data. Therefore, it cannot work solely for unquantifiable outcomes without comparable measurable outcomes, unlike economic valuation.

• Journal of Korea Technology Innovation Society
• /
• v.8 no.spc1
• /
• pp.451-475
• /
• 2005

This paper focuses to find out and analyse the influence of evaluation and image of government technology development programs on the outcome. A comprehensive survey of domestic technology-intensive industry was carried out. Through the results of this survey, we can understand and find out the impotance of the image and evaluation of the programs taken by the firms. We could find out, however, that the output of the technology development of the enerprises is one thing and outcome in the level of society is another, especially as for the influences of evaluation on the performances. In this regard, we could draw several policy implications as well as discussions.

• Asian Journal of Innovation and Policy
• /
• v.10 no.3
• /
• pp.274-293
• /
• 2021

Utilizing outside knowledge for innovation is an important task for companies in the competitive economy. Due to the rapid advance in the internet communication technology, the number and quality of innovation sourcing methods are increasing. We select co-creation, personalization and in-house R&D as the representative forms of innovation sourcing and suggest a game theory model that enables the comparative analysis between them. The decision and surplus outcome of the innovation mechanisms are compared under various settings of the input parameters of the model. The stakeholders voluntarily participate into all mechanisms when the product price is moderately high and the participation cost is low, while co-creation is the only feasible one when the product quality is niche. When the participation cost is relatively high, personalization outperforms co-creation.

• Journal of Digital Convergence
• /
• v.10 no.5
• /
• pp.177-183
• /
• 2012

The technological innovation of IT industry is the competitive tool for them to survive in the environment of an intensive competition. This technological innovation is critical in the survival of firms, but various factors should be considered to embody technological innovation success. This paper aims to identify the determinant factors of the outcome which influence the technological innovation based on the IT industry, and set up a model for measuring technological innovation success with its relevant understanding through the preceding studies. In addition, research with other related research model is to parallel.