• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1445-1453
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• 2023

In 2022, the domestic production performance of functional cosmetics in South Korea reached 4.6 trillion won, accounting for 33.85% of the total cosmetics production. The number of functional cosmetics reviewed increased by about 7.5% from the previous year, totaling 974 items. Especially with the increasing importance of the skin barrier function due to skin sensitivity caused by various environmental pollutants, domestic cosmetic companies are showing interest in the development of new ingredients and products related to this area. This study aims to analyze academic research trends related to in vitro experiments for the development of cosmetics improving the skin barrier, to provide practical information for the cosmetic industry. The findings are as follows: Academic research mainly focused on the efficacy of natural ingredients in improving the skin barrier, but there is a significant lack of quantitative accumulation of research. For the development of skin barrier-improving cosmetic ingredients, efficacy evaluation indicators were set, including hyaluronic acid production, expression of filaggrin gene, loricrin, formation of cornified envelope (CE), and expression of ceramide synthesis enzyme genes. Moreover, effective cosmetic ingredients for improving the skin barrier included lemongrass and perilla leaf extracts, flavonoids, Lactococcus lactis subsp. lactis, Exosomelike Nanovesicles derived from apple callus, Eleutherococcus sessiliflorus, Acanthopanax sessiliflorus, Eleutherococcus gracilistylus, Acer okamotoanum extracts, Aloe vera adventitious root extract, ethanol extract of Aruncus dioicus, and organic solvent fraction of Dracocephalum argunense.

• Journal of the Korean Regional Science Association
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• v.9 no.1
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• pp.65-78
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• 1993

In this study, the significant and enduring concentration of federal R&D spending in metro-scale clusters across the nation is treated as evidence of the operation of a distinct industrial infrastructure defined by the ability of R&D performers to attract external funding and pursue the sophisticated project work demanded. It follows, then, that the agglomerative potential of these R&D concentrations -- performers and their support infrastructures -- requires a search for economic impacts guided by a different stimulative effects attributable to federal R&D spending may be that substantial subnational economic impacts are routinely obscured and diluted by research designs that seek to discover impacts either at the level of nation-scale economic aggregates or on firms or specific industries organized spatially. Therefore, this study proceeds by seeking to link the locational clustering of federal contract R&D spending to more localized economic impacts. It tests a series of models(X-IV) designed to trace federal contract R&D spending flows to economic impacts registered at the level of metro-regional economies. By shifting the focus from funding sources to recipient types and then to sector-specific impacts, the patterns of consistent results become increasingly compelling. In general, these results indicated that federal R&D spending does indeed nurture the development of an important nation-spanning advanced industrial production and R&D infrastructure anchored primarily by two dozed or so metro-regions. However, dominated as it is by a strong defense-industrial orientation, federal contract R&D spending would appear to constitute a relatively inefficient national economic development policy, at least as registered on conventional indicators. Federal contract R&D destined for the support of nondefense/civilian(Model I), nonprofit(Model II), and educational/research(Mode III) R&D agendas is associated with substantially greater regional employment and income impacts than is R&D funding disbursed by the Department of Defense. While federal R&D support from DOD(Model I) and for-profit(Model II) and industrial performer(Model III) contract R&D agendas are associated with positive regional economic impacts, they are substantially smaller than those associated with performers operating outside the defense industrial base. Moreover, evidence that the large-business sector mediates a small business sector(Model VI) justifies closer scrutiny of the relative contribution to economic growth and development made by these two sectors, as well as of the primacy typically accorded employment change as a conventional economic performance indicator. Ultimately, those regions receiving federal R&D spending have experienced measurable employment and income gains as a result. However, whether or not those gains could be improved by changing the composition -- and therefore the primary missions -- of federal R&D spending cannot be decided by merely citing evidence of its economic impacts of the kind reported here. Rather, that decision turns on a prior public choice relating to the trade-offs deemed acceptable between conventional employment and income gains, the strength of a nation's industrial base not reflected in such indicators, and the reigning conception of what constitutes national security -- military might or a competitive civilian economy.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.8-13
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• 2015

One of the most usual indicators to measure the performance of any inventory policy is the mean physical stock. In general, when estimating the mean physical stock in periodic review inventory systems, approximate approaches are often utilized by practitioners and researchers. The mean physical stock is generally calculated by a simple approximation. Still these simple methods are frequently used to analyze various single stockpoint and multi-echelon inventory systems. However, such a simple approximation can be very inaccurate. This is particularly true for low service levels. Even though exact methods to calculate the mean physical stock have been derived, they are available for specific cases only and computationally not very efficient, and therefore less useful in practice. In literature, approximate approaches, such as the simple, the linear, and Simpson approximations, were derived for the periodic review inventory systems that allow backorders. This paper modifies the approximate approaches for the lost sales case and evaluates the modified approximate approaches. Through computational experiments, average (and maximum) percentage deviations of mean physical stock between the exact method and the modified approximations are compared in the periodic review inventory system with lost sales. The same comparison between the modified and the original approximations are also conducted, in order to examine the performance of modified approximations. The results show that all modified approximations perform well for high service levels, but also that the performance may deteriorate fast with decreasing service level. The modified Simpson approximation is clearly better. In addition, the comparison between the modified and the original approximations in the periodic review inventory system with lost sales shows that the modified approximation outperforms the original approximation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.33-51
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• 2022

This study analyzes newly listed companies on KOSDAQ from 2011 to 2020 for both firms having experience in attracting venture investment before listing (VI) and those without having experience in attracting venture investment (NVI) by examining differences between two groups (VI and NVI) with respect to both the level of listing performance and that of firm performance (growth) after the listing. This paper conducts descriptive statistics, mean difference, and multiple regression analysis. Independent variables for regression models include VC investment, firm age at the time of listing, firm type, firm location, firm size, the age of VC, the level of expertise of VC, and the level of fitness of VC with investment company. Throughout this paper, results suggest that listing performance and post-listed growth are better for VI than NVI. VC investment shows a negative effect on the listing period and a positive effect on the sales growth rate. Also, the amount of VC investment has negative effects on the listing period and positive effects on the market capitalization at the time of IPO and on sales growth among growth indicators. Our evidence also implies a significantly positive effect on growth after listing for firms which belong to R&D specialized industries. In addition, it is statistically significant for several years that the firm age has a positive effect on the market capitalization growth rate. This shows that market seems to put the utmost importance on a long-term stability of management capability. Finally, among the VC characteristics such as the age of VC, the level of expertise of VC, and the level of fitness of VC with investment company, we point out that a higher market capitalization tends to be observed at the time of IPO when the level of expertise of anchor VC is high. Our paper differs from prior research in that we reexamine the venture ecosystem under the outbreak of coronavirus disease 2019 which stimulates the degradation of the business environment. In addition, we introduce more effective variables such as VC investment amount when examining the effect of firm type. It enables us to indirectly evaluate the validity of technology exception policy. Although our findings suggest that related policies such as the technology special listing system or the injection of funds into the venture ecosystem are still helpful, those related systems should be updated in a more timely fashion in order to support growth power of firms due to the rapid technological development. Furthermore, industry specialization is essential to achieve regional development, and the growth of the recovery market is also urgent.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.129-140
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• 2020

In the future, the global container handling market will be reorganized into larger ships and shipping alliances, and the bargaining power of shipping companies will be further strengthened. Therefore, the global terminal operator (GTO), which has a global network, vast experience, and operational know-how, is expected to strengthen its competitiveness. In Korea, the central government promoted the development of GTOs in the mid-2000s, but it failed, mainly due to disagreements between port stakeholders. In this study, the macroeconomic indicators that have the same effect in all regions were used to analyze GTO management performance. In the short term, it could be used to establish the business strategy of domestic terminal operators based on changes in macroeconomic indicators. In the long term, it would be used to establish a promotion strategy for GTOs in Korea. The results of analyzing the impact of macroeconomic indicators on the GTO's profit show that the GTO's profit is significantly affected by cargo handling capacity, the consumer price index of the United States, the Shanghai Composite Index, the Crude Oil Price, and the London Inter-bank Offered Rate (LIBOR). However, the scale of impact was not significantly different between public and private GTOs.

• International Journal of Quality Innovation
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• v.8 no.2
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• pp.1-19
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• 2007

Achievement of objectives of education and training is one of significant factors influencing quality of life. Higher education institutions use different work, teaching methods and tools; however they are inadequate in many cases. Today higher education institutions have problems concerning sustention and rise of certain level of education by giving the job for graduates, using of new technologies that help to present, manage, evaluate and control knowledge. The main objectives of quality management system (QMS) at higher education institutions are as follow: to assure continuous improvement of education quality; to demonstrate performance results and relevant facts to the interested parties (customers of college or university, social partners, administrative institutions) showing the abilities of education institution to prepare high qualification specialists that fully correspond to changing requirements of labour market. The QMS at education institutions should be designed as continuous process, considering that the quality of final product is the result achieved in primary processes. The process shall involve all interested parties. Parameters and indicators of education quality can help to analyze the efficiency and effectiveness of existing QMS. The results of quality audits should be also taken into account when designing and implementing QMS at organization. Literature review showed that for the assurance of education quality three different approaches prevail: total quality management (TQM); requirements of quality awards and assessment models; and QMS corresponding to the requirements of ISO 9001 standard. The case study of QMS design and implementation at Vilnius Law and Business College is presented in the paper. The peculiarities, difficulties and obstacles of QMS implementation in the higher educations institutions are analysed in more detail in this article.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.64-73
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• 2019

The manufacturing companies under Make-To-Order (MTO) production environment face highly variable requirements of the customers. It makes them difficult to establish preemptive production strategy through inventory management and demand forecasting. Therefore, the ability to establish an optimal production schedule that incorporates the various requirements of the customers is emphasized as the key success factor. In this study, we suggest a process of designing the simulation model for establishing production schedule and apply this model to the case of a flat glass processing company. The flat glass manufacturing industry is under MTO production environment. Academic research of flat glass industry is focused on minimizing the waste in the cutting process. In addition, in the practical view, the flat glass manufacturing companies tend to establish the production schedule based on the intuition of production manager and it results in failure of meeting the due date. Based on these findings, the case study aims to present the process of drawing up a production schedule through simulation modeling. The actual data of Korean flat glass processing company were used to make a monthly production schedule. To do this, five scenarios based on dispatching rules are considered and each scenario is evaluated by three key performance indicators for delivery compliance. We used B2MML (Business To Manufacturing Markup Language) schema for integrating manufacturing systems and simulations are carried out by using SIMIO simulation software. The results provide the basis for determining a suitable production schedule from the production manager's perspective.

• Journal of Korea Technology Innovation Society
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• v.20 no.1
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• pp.1-33
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• 2017

In the last decades, technology-oriented small firms, i.e. venture businesses, have been increasingly engaged in R&D collaborations with external parties as strategic means for technological innovation. Despite ample evidence on the benefit of such collaborations for the firms, there has been less attention to examining whether and how the firms' social interactions with cooperating partners and their managerial characteristics contribute to that benefit. Drawing on the theories of social capital and entrepreneurial orientation, this study is to remedy this gap. The theory of social capital, referring to a sum of the value and potential resources embedded in social relationships of collectives, provides an integrated view of social factors among cooperating partners, e.g. strong ties, network stability, trust, reciprocity, shared vision and value. It categorizes these factors into structural, relational, and cognitive dimensions of social capital. Entrepreneurial orientation theory captures firms' managerial characteristics as a combination of innovativeness, proactiveness, and risk-taking. This addresses firms' managerial process to utilize and combine internal and external resources for wealth creation and opportunity realization. Against this background, this study investigates what roles social capital among cooperating R&D partners and entrepreneurial orientation of the collaborating firms play for collective performance improvement in R&D collaborations. In terms of the collective performance, this study adopts two indicators: technological competitiveness and business performance. Technological competitiveness refers to the contribution of a technology developed by a cooperative R&D project to competitive advantage of a firm while business performance is defined as the financial and economic outcome of a collaboration. Using a sample of 218 Korean ventures engaging in R&D collaboration with external parties, the author finds the significant effects of social capital (i.e. structural, relational, and cognitive dimensions) and entrepreneurial orientation (i.e. innovativeness, proactiveness, and risk-taking) on both of the technological competitiveness and the business performance. Further, the higher the social capital among R&D partners, the more likely it is to foster the entrepreneurial orientation at firm-level. Most importantly, the entrepreneurial orientation at firm-level is an significant mediator of the relationship between social capital and collective performance. Beyond these novel empirical findings, this study contributes to the literature on R&D collaboration. The findings' implications for management and policy are deeply discussed in the conclusion.

• Journal of Korea Technology Innovation Society
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• v.20 no.4
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• pp.1212-1242
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• 2017

In this study, the effectiveness of the innovative company certification system, which is one of the important means of the SME innovation promotion policies, was examined in terms of technological innovation activity and performance. To this end, we used the results of 'SME Technology Statistical Survey' conducted by the Small and Medium Business Administration and the Korea Federation of Small and Medium Business in 2013~2015 to compare the innovative SMEs that have received the certifications such as Venture Certification, Innobiz Certification, and Mainbiz Certification with the general SMEs that did not. As a result, it was found that the innovative SMEs have comparative advantage in many detailed indicators related to the technological innovation activity and performance. However, the ratio of external use of R&D expenditure, the number of technology development attempts and the number of successes were not different according to the survey year, so it is necessary to strengthen the follow-up management of the system. On the other hand, the proportion of self-procurement R&D expenditure of the general SMEs was significantly higher than that of the innovative SMEs in all three-year surveys. Therefore, it is necessary to regulate the government funding for the innovative SMEs to be used as a complementary material, not as a substitute for their own R&D investment. In addition, the technological innovation activity and performance of a company were more influenced by the size of the company and the participating industry rather than by the certification, so it is necessary to consider it when establishing the technology innovation promotion policies.