• STI Policy Review
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• v.9 no.1
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• pp.1-29
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• 2018

With the constant growth of R&D investment, it has been increasingly necessary to evaluate the effectiveness of R&D performance and there is a high emphasis on ensuring the accountability and effectiveness of R&D programs. The evaluation of performance of a firm is especially necessary in times of economic downturn to justify R&D investment. However, there is a marked shortage of clear guidelines as to where and how particular metrics are used to measure the output and outcome of R&D activity in firms. Many firms have difficulties in selecting appropriate indicators for their R&D and financial performances. To fill this gap, this article discusses and presents the findings from the literature in such a way that they become useful for researchers or managers who are in charge of measuring the R&D and business performances arising from innovation activities. Finally, based on the findings about metrics of R&D performance, this article proposes the hypothetical framework to investigate the relationship between technology forecasting, strategic technology planning, and business performance. The framework of this article will assist policy makers, universities, research institutes/national laboratories, and companies to enhance their decision making process in technology development.

• Journal of Korea Technology Innovation Society
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• v.9 no.2
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• pp.199-235
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• 2006

Research interest in TQM has recently begun extending beyond manufacturing to moreinnovative R&D activities. Despite numerous studies of the relationship between TQM and organizational performance, little are known about the relationship between TQM and R&D performance. This is especially true for manufacturing-based R&D performance. The objective of this study is to examine the relationship between TQM and R&D, and also explore several contingencies that moderate the relationship. The study uses data from 133 R&D divisions of Korean manufacturing firms to test hypotheses regarding the relation of TQM with R&D. TQM measures are aligned with the six criteria of Malcolm Baldrige National Quality Award, and the R&D performance measures consist of incremental and innovative R&D aspects. The findings from structural equation modeling show that TQM practices contribute to R&D performance significantly in aggregate, and their specific contributions vary according to the contingencies, which provide further understanding of the relationship between TQM and R&D in the manufacturing sector. Therefore, the results could offer firms a better strategy for their R&D management. This study is, however, exploratory in nature; the conclusion is tentative and may thus be different in other research settings.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.116-132
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• 2023

Technology innovation companies are focusing on contributing to business performance by R&D project as a strategic tool. Successful R&D leads to corporate competitiveness enhancement, national industrial development, but there are high uncertainty and risks in R&D. Public and private R&D projects are carried out to achieve various purposes. It was verified how the risk management and benefit management of the R&D project affect the detailed R&D project performance between the Public and private domain. The impact of Project Leadership on R&D performance was also analyzed. Those who have participated in the Public and Private R&D projects at companies or research institutes were surveyed. First, it was found that project risk and benefit management have partially an effect on R&D project performance. Second, Public and private R&D Project Leadership showed partially a interaction effect between project management and project performance.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.306-316
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• 2010

The purpose of study is to promote the development of contents industry by analysing the causal relationship between R&D collaboration and firms' performance. In study, we use the number of intellectual property and total sales as proxy variables of performance. we use the degrees of collaboration experience, firms' interaction and degree of collaboration as proxy variables of independent variables. The results of study are as follows. First, collaboration experience and firms' interaction are positively influence on technological performance. Second, collaboration experience is positively correlated to economic performance. Finally, firms' R&D collaboration revealed higher performance than R&D collaboration of firm and R&D institution This study emphases on the importances of R&D collaboration for developing new technology and improving economic performance.

• IE interfaces
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• v.22 no.3
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• pp.192-204
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• 2009

Based on the characteristics of 'Korean electric power industry R&D programs', this study proposes a new performance evaluation framework where electric power industry related R&D projects are scrutinized. The abovementioned R&D programs have their own goals and especially they emphasize the effectiveness as well as the efficiency of each subordinate R&D project. Hence, in this framework, a performance evaluation procedure is established and then a mathematical model is developed according to the procedure. The model calculates performance evaluation indices for a set of R&D projects integrating the effectiveness with the efficiency of each R&D project. In a case study with an empirical dataset, statistical significance is tested on the integrated performance evaluation indices of R&D projects regarding organizational types and program categories considered.

• Journal of Korea Technology Innovation Society
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• v.18 no.1
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• pp.73-97
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• 2015

Various types of government R&D support are available for activating businesses by small and medium sized enterprises (SMEs). However, most existing studies on this topic are focused only on the financial aspect. Interest in non-financial R&D support from the government has recently grown due to the limited provision of government financial support. In this study, government R&D support for SMEs was categorized into financial and non-financial strategies. Performance in terms of technological innovation by type was also analyzed. Furthermore, as R&D performance could vary according to the characteristics of the firms, the study classified performance variables into technological development possibility, technology intensity and technology uniqueness. The relationship between the types of support and the characteristics of the performance was also examined. Based on the results, it was found that government R&D support positively influences the SMEs' technological performance. However, the level of financial support does not significantly influence the technological uniqueness. As such, it is expected that effects from the increase in quantity of government R&D support are limited.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.3
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• pp.24-35
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• 2014

This paper examines, from the perspective of the structure-conduct-performance (S-C-P) paradigm, the structural factors that determine R&D concentration in industries. The results are as follows. First, an industry's R&D concentration is directly related to its market concentration, R&D intensity, capital intensity, and technological opportunities. In contrast, the higher an industry's performance, the more likely the diffusion of R&D investment is for firms belonging to that industry. Second, an industry's R&D concentration has a positive effect on its market concentration but a negative effect on its performance, suggesting that governments should adopt R&D policies that would induce more firms to invest in R&D instead of focusing only on a few firms to enhance industry performance.

• Journal of Technology Innovation
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• v.18 no.1
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• pp.75-98
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• 2010

The purpose of this paper is to give policy implications for relevant policy-makers by analyzing factors affecting performance of industrial R&D programs of the Ministry of Knowledge Economy. The independent variables are type of project leader organization(Big Enterprises, SMEs, Ventures Businesses, Public Research Institutions, Universities), cooperative or noncooperative R&D among industry-university-research institution, total number of project participant organization, total R&D investment, and the ratio of private investment to total R&D investment. The dependent variables are domestic or foreign patents granted and domestic or foreign papers accepted. The method of analysis is Poisson Regression analysis operated by STATA. The results of this research are follows ; Universities show higher R&D performance compared to enterprises or public research institutions in terms of patents and papers as well. Venture businesses show higher patent performance compared to SMEs. Inverted U-shaped relationship between total number of project participant organization and R&D performance is not supported. The higher total R&D investment, the higher R&D performance. The higher the ratio of private investment to total R&D investment, the higher R&D performance.

• Journal of the Korea Safety Management & Science
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• v.12 no.3
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• pp.321-326
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• 2010

Government evaluate annually a performance of government's R&D(Research & Development) and decide a budget and progress. So, a performance target setting of R&D is very important at the planning, The basic performance target setting of railroad R&D is clear. However, a scientific and technological performance target setting of railroad R&D is very difficult and a reasonable level of it can not be judged. Therefore, this study will suggest a solution for a scientific and technological performance target setting of railroad R&D through regression analysis of successfully finished railroad R&D, after judging a reasonability of a scientific and technological performance through comparing railroad R&D with the other R&D.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.153-163
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• 2018

There is insufficient effective management systems to achieve project goalsin disaster and safety R&D. Therefore, to develop an R&D performance management system, this paper develops a R&D performance management matrix based on PMBOK to systematize a process and to enhance efficiency of performance management. Also, this paper identified vulnerable procedures in disaster management by analyzing related laws, work process and performance. Analysis results found that the performance management matrix in disaster management R&D consists of 5 process groups, 7 knowledge areas and 47 processes. Also, the performance of the diffusion knowledge process was evaluated as weak in the present management system. This study defined ITO and developed a data flow diagram for applicationto related work. The suggestions of this study include the related work to enhance R&D performance, contribute to improving diffusion of R&D performance, and enhance the utilization of developed technologies.