• Management & Information Systems Review
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• v.15
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• pp.109-145
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• 2004

Upcoming 21st century, Management circumstance for a small and medium enterprise have been rapidly changed by Knowledge management, Informationization, Hi-technology. Changing from an era of small concept to strong concept, It will be a severe innovation period and can not survive with life as the same as the past, It is the era of best which mean only the best can survive, None of the average faculty can survive. Due to rapid proceeding of innovation of Informationization, It stimulate acceleration of technology innovation, infinity competition regardless the nation boarder, result in proceeding to Informationization. A small and medium enterprise is defined as smaller size of business than big business as point of capital, employee, output. It is concept, which usually used against concept of big business. When define a small and medium enterprise, criteria to determine a small and medium enterprise is depends on country and a category of business. However, In every country, A small and medium enterprise is getting be bigger and importance factor in whole industry. A small and medium enterprise is well developed and also well balanced with a large enterprise in the developed country. All around in the world, Interest about a small and medium enterprise is becoming higher. It is actively researching into a small and medium enterprise as the mean to create new employment, new industry, as means to from integration of a all and medium enterprise,as source of high competitive power. The status quo of rapid changing into informationization have been realized at considerable level in Korea. Information society is defined as information technology is main key to determine individuals competitiveness, which can solve effectively the side effect result from industrialization. It cleary imply that information technology is the most promising and important industry in 21st century. Therefore, We should seek to foster independent a small and medium enterprise and develop them corresponding to new concept of a small and medium enterprise in 21st century. The main frame of policy should be new economic system, which can contribute establishment of a small and medium enterprise, management innovation. It also attribute a small and medium enterprise to reveal their creative. New economic paradigm in 21st will be expanded with organization, market, technology. So far, a small and medium enterprise has been acknowledge as economic weaker and the one should be protected. However, In 21st century a small and medium enterprise will be considered as active majority or a source of creative. Development of technology to produce a small quantity with variety product and acceleration of knowledge and informationization will result in comparative merits of a small and medium enterprise. Hereby, The role and relative importance of a small and medium enterprise in our economic will getting be larger and It will be developed as the main force to activate the economic. However, Only a small and medium enterprise, which overcome difficulty with active desire and effort to improve their lot can be developed as a competitive enterprise in 21st century in considering themselves to be developed as diversity, active, independent, business by an enterprise.

• Journal of Convergence for Information Technology
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• v.10 no.3
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• pp.48-57
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• 2020

This study focuses on the development of simple qualitative indicators for evaluating and selecting innovation leading companies that challenge National Award. Another purpose of this study is to complement the aspect in which the innovative or value of the companies' products, technologies, and services is only quantitatively evaluated. Existing evaluation indicators of national award have too many evaluation items and were not suitable for innovation-based company evaluation. The research approach is to select category for developing qualitative indicators based on previous studies and TF discussion. From the input-process-output-outcome point of view, we have set up an indicator system as a series of flows. Finally, five categories such as creativity, system excellence, customer value, performance, and ripple effects are selected as qualitative indicator. For these selected indicators, conceptual definitions and the main points of evaluation are described. And the system level evaluation and the ADLI approach are presented for reference. The appendix also includes examples of qualitative and quantitative evaluation of real companies using these indicators. However, this study implies the possibility that the evaluation results may vary depending on the level and perspective of the evaluator. We hoped that detailed research on candidate indicators that can be used as qualitative indicators and research on the development of mixed indicators(qualitative and quantitative) will continue in the future.

• Journal of Technology Innovation
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• v.24 no.1
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• pp.143-167
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• 2016

The purpose of this study is to analyze changes of innovation activities and their performance in pre-IPO and post-IPO of KOSDAQ IPO listed companies in medical and pharmaceutical fields, which require high R&D investment, from 2000 to 2005 in Korea. The innovation efficiencies of the IPO companies were measured before and after three years based on the DEA model. The financial data and patent information of the listed company during total 6 years, which were 3 years before IPO and 3 years after IPO, were collected. The main results of this research are as follows. First, it took an average 12.86 years until IPO in the start-up of the IPO companies in the pharmaceutical sector, and innovation was on average more active than the IPO before. R&D investment was higher than the IPO before, and the number of the applied patent during 3 years after IPO was 16.67 which was increased from 8.43 during 3 years before IPO. In addition, the average scope of technology of the IPO companies was expanded from 11 to 22 technology fields during previous 3 year and after 3 year each, and financial growth after IPO was lower than the previous IPO. Second, the financial performance of R&D investment and the performance of patent activity were weakened in the efficiency after the IPO, and the integrated performance from the patenting activities and the R&D investment was decreased after the IPO. Finally, the efficiency of the financial performance of the patenting activity was lower than the efficiency of the financial performance of the patent and R&D investment and patent activities under the R&D investment. In particular, the inefficiency of the firms' patenting activities performance after the IPO was caused by the decreasing return to scale, according to the results of this study. This results implicate that the expansion of R&D investments through the IPO had not lead to the financial performance of the market, and that the overall inefficiency since the IPO is due to the inefficiencies at the stage for the outcome of innovation activity rather than the output obtained through the R&D investments that appear to lead the performance of the market.

• Proceedings of the Technology Innovation Conference
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• 1996.12a
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• pp.265-295
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• 1996

This paper investigates empirically the relationship between various business portfolio properties (particularly technological properties) and chaebol′s performance using data on the 50 largest chaebols in Korea. In addition to the traditional indexes to measure diversification such as entropy index we calculated inter-industry technological similarity using R&D expenditure data by industry and 1990 Input-output Table in Korea, and obtained chaebol-level technological relatedness and internal transaction proportion from chaebols′business profile, inter-industry technological similarity and 1990 input-output table. We applied factor analysis on 13 business portfolio property indexes and showed that they could be grouped into 3 dimensions, diversification scope, inter-business relatedness and degree of vertical integration. In this paper, using 50 largest chaebols′financial data (1989-1994), we analyzed empirically the effect of business portfolio properties on ROS (Return On Sales) which is conventional index for firm performance and on TFP(Total Factor Productivity) growth which is a pure measure of firm performance. To utilize the advantage of panel data, FEM(Fixed Effect Model) and REM(Random Effect Model) were used. The empirical result shows that the entropy index as a measurement of inter-business relatedness is not significant but technological relatedness index is significant. OLS estimates on pooled data were considerably different from FEM or REM estimates on panel data. By introducing interaction effect among the three variables for business portfolio properties, we obtained three findings. First, only VI (Vertical integration) has a significant positive correlation with ROS. Second, when using TFP growth as an dependent variable, both TR(Technological Relatedness) and f[ are significant and positively related to the deepened variable. Third, the interaction term between TR and VI is significant and negatively affects TFP growth, meaning that TR and VI are substitutes. These results suggest strategic directions on restructuring business portfolio. As VI is increased, chaebols will get more profit. A higher level of either TR or W will increase TFP growth rate. but increase in both TR and VI will have a negative effect on TFP growth. To summarize, certain business portfolio properties such as VI and TR can be considered "resources" themselves since they can affect profit rate and productivity growth. VI and TR have a synergy effect of change in profit rate and productivity growth. VI increases ROS and productivity growth, while TR increases productivity growth representing a technological synergy effect.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.1-26
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• 2016

The period after the PhD has a huge impact on the careers of researcher from a researcher lifecycle perspective. This is a turning point which student receives guidance from professor and become an independent researcher. Furthermore, they learn to develop ideas for independent research, apply for grants and manage a project; they also form expert networks in related filed and publish papers to share their findings. This study focuses on the period between earning doctoral degree and being employed as a stable position in university. This study starts from a research questions that asks which factors of postdoctoral experience affect research output. In this study, the paper performance, especially co-authorship of paper, of postdoctoral researchers was investigated. The cumulative advantage theory and Matthew effect were employed to shed a light on this research question. The empirical work is based on the Survey & Analysis of National R&D program in Korea conducted by Korea Institute of S&T Evaluation and Planning (KISTEP). The correlations between the research output and characteristics of postdoctoral experience were verified. These results are expected to contribute as new empirical evidences on investigating knowledge transfer activities of new PhDs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.340-347
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• 2016

Since the 1970s, manufacturing has been one of the key driving forces that has led to Korea's economic growth. However, this growth rate has been reduced significantly since the 2000s, and shows that revenues and employment are steadily decreasing. In addition, while manufacturing investment in Korea has dropped sharply, the United States, Germany, Japan, and other major countries have increased investment in manufacturing. These countries have promoted manufacturing innovation strategies that include the convergence of information and communications technologies (ICT) and manufacturing. For manufacturing innovation, it is important for time and cost savings required for product development to be achieved by changes in the production process, especially product design. Modeling and simulation (M&S) is a process that replaces physical product design, mockup making, and testing, with virtual product creation (modeling) and engineering analysis (simulation). In this paper, we analyze the economic ripple effect of supercomputing M&S using an input-output model technique based on the input-output tables published by the Bank of Korea. When we set the M&S budget (about US$16 million for the last 10 years) of the Korea Institute of Science and Technology Information (KISTI) as input coefficients, the effect on production inducement, value-added inducement, and employment inducement was analyzed to be US$24 million, US$13.4 million, and 267, respectively.

• Journal of Technology Innovation
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• v.25 no.3
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• pp.51-82
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• 2017

In terms of both economic growth and social welfare, this paper discusses the optimal proportion and size of basic research budget by adding knowledge stock to an endogenous growth model. On the basis of the modified endogenous growth model, this paper derived an equation that consists of kinds of parameters and suggested this equation as a criterion for determining whether allocated basic research budget has been appropriate. This paper also found that the theoretical optimal ratio between government investment spending and investment in basic research is equal to the ratio between the partial elasticity of output with respect of public capital stock and the partial elasticity of output with respect of knowledge stock. In addition, after the required parameters were specified based on precedent literatures, this paper estimated an optimum size of the basic research budget using the theoretical optimal ratio with official statistical records and compared the estimated size to its actual size. This paper therefore is expected to contribute to budget planning and allocation regarding establishing basic research policy, because the results of this paper presents a useful criterion for optimum level and an approximate size of investment in basic research. However, it should be noted that although the optimal solution is optimal in a economic sense, it may not be the best solution from a practical perspective.

• Journal of Technology Innovation
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• v.20 no.3
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• pp.29-55
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• 2012

In order to successfully adopt and implement the Balanced Scorecard(BSC), firms need to respond adequately to the rapid changes of today's business environment and consider the growing importance of non financial factors in the business activities such as intangible assets(R&D expenditure, patent, goodwill, etc.). Our primary focus throughout this paper is on developing Key Performance Index(KPI) of BSC for R&D expenditure activities. In this study, we have developed and named PEI(Patent Efficiency Index),which is the KPI for R&D expenditure by focusing on the efficiency of a patent that is the output from the R&D expenditures. Secondarily, we have attempted to address the solution for the current problems of the traditional R&D performance measurement by using our developed PEI and examine the usefulness and effectiveness of the newly developed our PEI. According to the empirical test results, we find that the PEI is positively associated with ROA and Tobin's Q, respectively and show that our developed PEI is more effective and accurate than the traditional R&D performance measurement as a business performance measurement. Furthermore, these findings proves that we can measure and evaluate how efficiently the firms perform the R&D activities and shows that the PEI can be a critical index for evaluating firm's business performance related to the R&D expenditures.

• Journal of Technology Innovation
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• v.28 no.4
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• pp.97-126
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• 2020

This study evaluated its potentials by quantitatively analyzing the national economic impact of the smart home-related industry, which is attracting attention as a core industry of the 4th industrial revolution. For the analysis, the smart home-related industries were classified into manufacturing and service industries through a literature review of the previous studies. Using the 2018 input-output table, this paper analyzed linkage effects between industries as well as spillover effects in the production, value-added, employment and job. As a result, the smart home manufacturing and service sectors showed a higher spillover effect in value-added than other industries in each industrial field. In the smart home industry, the spillover effects of manufacturing sector to service sector are larger than those of service sector to manufacturing sector. Moreover, it was confirmed that smart home industry was highly related to not only the technology-intensive industry, but also the service sector for smart cities, smart cars, Fin-tech, and etc. On the other hand, the smart home manufacturing sector is a final demanding industry with relatively higher backward linkage effect than forward linkage effect. In the smart home service sector, the forward linkage effect was relatively high compared with the backward linkage effect, indicating that it was an industry with a high supply function to other industries.

• Journal of Technology Innovation
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• v.29 no.3
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• pp.33-62
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• 2021

This study compares and analyzes the efficiency of R&D activities of technology-innovative small and medium-sized enterprises(SMEs) between industries and proposes ways to improve efficiency. The research samples are 6,708 technology-innovative SMEs, which have received a guarantee by the KIBO from 2008 to 2011. Input variables are the level of R&D personnel, R&D investment, and output variables are patent applications, prototype. Efficiency is measured by the DEA model, and indirect comparisons that are individually measured by industry are performed. As a result of the analysis, the CCR for determining the optimal returns to scale is 0.19, the BCC for determining the optimal input distribution is 0.70, and the SE for determining the optimal output is 0.30. By industry type, the medium and low-tech industries have high CCR and BCC, while the high-end and high-tech industries have high SE. R&D activities need to be operated on an optimal scale through managing R&D performance because there is the inefficiency of scale across the industry. The contribution of the study is to analyze the R&D efficiency of each industry of technology-innovative SMEs by the technology evaluation data of the KIBO.