• Journal of Korea Technology Innovation Society
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• v.19 no.1
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• pp.137-160
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• 2016

This study assesses the structure relationships between resource, product and process innovation capability, technology commercialization competence and performance of firms in Daedeok Innopolis. In particular, this study attempts to analyze technology commercialization competence that may be influenced by product and process capabilities. The development of the research model is based on the literature of resource-based view and the empirical studies of technology commercialization competence. The survey of 109 firms was conducted from January 5, 2015 through February 4, 2015. We investigate the role of a firm's technology commercialization competence in determining its performance by performing Partial Least Squares analysis. The results indicate that a firm's human resources and intangible resources lead to a higher level of its product and process innovation capabilities. This study, however, finds that a firm's tangible resources do not have significant effects on its product and process innovation capabilities. And the study finds evidence that firm's product and process capabilities have positive effects on its technology commercialization competence. The study also finds that a firm's technology commercialization competence is a driving force behind its performance, showing that its technology commercialization competence positively involves its performance. In addition the study finds that technology commercialization competence mediates the relationship between a firm's innovation capability and performance, indicating that the technology commercialization used as mediating variable positively affects its innovation performance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.3
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• pp.233-242
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• 2016

Startup must be agile and be able to handle extreme changes, survive unpredicted threats, and capitalize on emerging business opportunities. Agile teams continually sense changes for competitive action and marshal the necessary knowledge. While team members share their knowledge, there must be emerging various type of conflicts in teams. This study examines the relationship among the conflict, knowledge sharing and agility in startup context. At the same time, we tested the roles of shard vision both moderating variable between conflict and knowledge sharing, and antecedent for knowledge sharing. Different two types of conflict, task conflict and relationship conflict, knowledge sharing, agility, and different impact of shared vision are identified from literatures and tested. 182 data points were collected from under 5-year old startup's representatives to test these hypotheses. PLS data analysis indicated that the task conflict and shard vision positively effect on knowledge sharing, and then knowledge sharing has statistically significant effect on agility. And the impact of conlict has been weakened by shared vision's moderating effect. Based on the results, we proposed practically several team management skills for startup managers, leaders and stakeholder, and explained theoretical contributions.

• Journal of Distribution Science
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• v.14 no.2
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• pp.135-144
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• 2016

Purpose - The purpose of this paper is to empirically investigate the moderating effects of social capital on antecedents factors path of export performance in the materials and components SMEs(Small and Medium-sized Enterprises) of Busan and Kyungnam region. In case of materials and components SMEs, they are always trying to achieve business performance including export sales and market share, but it is difficult for them to increase performance due to the limitation of inner & tangible resources. Therefore intangible asset such as technology capability and its antecedents factors which are technology innovation and learning orientation are getting more important to SMEs. In addition, it is supposed that social capital such as local network including distribution channel in overseas market plays an essential role to enhance export performance. Accordingly, the main goal of this study is to find out the relationship between export performance and antecedents factors and the validity of social capital as a moderating valuable. Research design, data, and methodology - Technology innovation, learning orientation and technology capability have been used as antecedents factors for export performance and social capital such as network diversity and intensity has been used for moderating effects analysis. In order to select these valuables mentioned above, this study examined the existing researches on a basis of Resources Based View, Organizational Learning Theory and Social Capital theory. To achieve the objective of this paper, 7 hypotheses including the moderating effects have been proposed with 6 potential variables measured by 24 questions. The survey was carried out from December 2014 to March 2015 and 137 samples out of total 175 were selected for the analysis. PLS(Partial Least Squares) has been used for the methodology of empirical analysis for both antecedents factors path and moderating effects. Results - Research findings are as follows. First, technology innovation has a significant impact on learning orientation, learning orientation has a positive effect on the technology capability and technology capability also has a significant impact on export performance. Therefore 3 valuables are proved as antecedents factors of export performance. Second, the social capital(both network diversity and intensity) plays a moderating role with learning orientation to technology capability. However, there is no moderating effects between both of social capital and technology capability regarding export performance. Conclusions - According to path analysis results, it is suggested that the materials and components SMEs should raise technology innovation and learning orientation in order to improve technology capability and export performance. Meantime, the moderating effect analysis shows that SMEs should consider local network diversity and intensity along with learning orientation to add up technology capability. But local network diversity and intensity does not work systematically with technology capability for export performance and it means that SMEs should find the appropriate local partners for the purpose of establishing concrete distribution channels based on marketing perspective, not for improving technology capability.

• Reproductive and Developmental Biology
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• v.29 no.1
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• pp.43-48
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• 2005

To search of a new porcine pheromonal odorants for biostimulation control system technologies to offer a potentially useful and practical way to improve reproductive efficiency in livestock species, the holographic quantitative structure activity relationship (HQSAR) model between odorants, 2-phenoxytetrahydrofurane (A), 2-cyclohexyl-oxytetrahydrofurane (B), derivatives and binding affinity constants (p[Od.]/sub 50/) for porcine odorant-binding protein (pOBP) as receptor of pig pheromones were derivated and disscused. The binding affinity constants of cyclohexyl substituents (A) for pOBP were higher (A>B) than that of phenyl substituents (B). It was revealed that the optimum HQSAR model XI using PLS analyses had a fragment length (5∼8) with chirality at 5 components and hologram length 97 bin, which had a cross-validated q²(predictablities) of 0.916, and a conventional correlation coefficient r² (fitness) of 0.988, respectively. From the atomic contribution, the C3 and C5 atom in 2-oxyfuryl group contributed to binding affinity constants, whereas the central carbon atom in tert-butyl group on the cyclohexyl ring and the C4 atom of furyl group parts showed no contribution.

• International Commerce and Information Review
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• v.19 no.1
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• pp.127-152
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• 2017

One of the biggest challenges in export activities of SME is the increasingly cultural diversity that requires especially export managers to adapt their doing business in many different kinds of cross-cultural situations effectively. A relative newly developed concept 'Cultural Intelligence' has been evaluated as a key element for the success in international business activities. This study aims to investigate empirically the role of Cultural Intelligence(CQ), one component of cultural competence, on export marketing adaptation. The statistical method used to test the hypotheses was Structural Equation Modeling using PLS. The results of this study are follows. The moderating role of Cultural Intelligence between information seeking and information using abilities is more stronger in marketing rather than relationship adaptation. Cultural Intelligence moderates between them. Critical factors affecting Cultural Intelligence are also discussed; foreign language fluency, business travels in abroad, characteristics of the business travels, multi-lingual ability, pre-education related cultural subjects, and visit experience in foreign countries. Especially, export managers' foreign language ability leads to much stronger influence on cultural intelligence. The result of the empirical study provides important implications for export SME and export supporting organizations. Export firms and supporting organizations must expand programs widely in multi cultural training and education to help managers gain a better understanding in a various export environment.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.542-549
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• 2020

Purpose: As nitrate nitrogen produced during fermentation of liquid fertilizer is a pollution indicator of water, in this study, four research areas where liquid fertilizer was sprayed were selected, and a model was designed to estimate the concentration of nitrate nitrogen pollution. Method: Prior to shooting on site, a spectrum library was constructed by dividing the ratio of liquid fertilizer into 5 groups: 0%, 25%, 50%, 75%, and 100%. PLSR (Partial least squares regression) method was applied to hyperspectral images acquired in the study area based on the aspect of spectrum. Result: The behavior of nitrate nitrogen was confirmed by 1st and 2nd differentiation of the spectrum of the constructed liquid fertilizer. PLSR concentration estimation modeling was implemented using images from field experiments and compared with actual concentration of nitrate nitrogen. Conclusion: When comparing the PLSR concentration estimation model with the actual concentration of nitrate nitrogen, it was measured that the detection is possible in high concentration areas where the concentration of nitrate nitrogen is 70mg/kg or more.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.4
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• pp.361-368
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• 2002

The aim of this study was to investigate the effect of preprocessing the transmitted energy spectrum data on development of a robust model to predict the sugar content in intact apples. The spectrum data were measured from 120 Fuji apple samples conveying at the speed of 2 apples per second. Computer algorithms of preprocessing methods such as MSC, SNV, first derivative, OSC and their combinations were developed and applied to the raw spectrum data set. The results indicated that correlation coefficients between the transmitted energy values at each wavelength and sugar contents of apples were significantly improved by the preprocessing of MSC and SNV in particular as compared with those of no-preprocessing. SEPs of the prediction models showed great difference depending on the preprocessing method of the raw spectrum data, the largest of 1.265%brix and the smallest of 0.507% brix. Such a result means that an appropriate preprocessing method corresponding to the characteristics of the spectrum data set should be found or developed for minimizing the prediction errors. It was observed that MSC and SNV are closely related to prediction accuracy, OSC is to number of PLS factors and the first derivative resulted in decrease of the prediction accuracy. A robust calibration model could be d3eveloped by the combined preprocessing of MSC and OSC, which showed that SEP=0.507%brix, bias=0.0327 and R2=0.8823.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1262-1262
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• 2001

The rice plant is one of the important staple crops in Korea. The high yield with low cost in rice is required the soil fertility and the development of new precise method of fertilizer application by nutritional diagnosis. Now, in Korea, the nitrogen application system for the rice plant is composed of the basal fertilization, fertilization at tillering stage and fertilization at panicle stage, which the nitrogen fertilization at panicle stage amount to about 30 percent in the total amount. Thus, this experiment carried out to the development of the system that can measure the nitrogen content in the rice plant at panicle stage rapidly with the near infrared spectroscopy, and to predict the appropriate quantity of the nitrogen fertilization at panicle stage based on calibration model for test of nitrogen content in rice plant. The samples were collected from 48 varieties in 4 regions which are mainly cultivated in the southern part of Korea. And then, it collected by classifying into the leaf, the whole plant and the stem since 7 days before the nitrogen fertilization at panicle stage. The ranges of the nitrogen contents were 1.6∼4.0%, 1.7∼3.0% and 1.4∼2.7% in the leaf, the whole plant and the stem, respectively. In the calibration models created by each part of the plant under the Multiple Linear Regression(MLR) method, the calibration model for the leaf recorded the relatively high accuracy. The mutual crossing test on unknown samples were carried out using Partial Least Square(PLS) calibration model. That is, the nitrogen content in the stem was tested by calibration model made by the leaf model and that of stem was tested by calibration model made by whole plant sample. When unknown leaf sample was tested by calibration model made by all sample that collected from each part in rice plant such as leaf, stem and whole plant, it recorded the highest accuracy. As a result, to test the nitrogen content in the rice plant at panicle stage, the nitrogen content in the leaf shall be tested by the calibration model composed of the leaf, the stem and the whole plant. In future, to estimated the amount of nitrogen fertilization at panicle stage for rice plant , it will be calculated based on regression model between rice yield and nitrogen content of leaf measured by calibration model made by mixed sample including leaf, stem and whole plant.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1281-1281
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• 2001

Near-infrared (NIR) spectra have bean measured for high-density (HDPE), linear low-density (LLDPE), and low-density (LDPE) polyethylene in pellet or thin films. The obtained spectra have been analyzed by conventional spectroscopic analysis methods and chemometrics. By using the second derivative, principal component analysis (PCA), and two-dimensional (2D) correlation analysis, we could separate many overlapped bands in the NIR. It was found that the intensities of some bands are sensitive to density and crystallinity of PE. This may be the first time that such bands in the NIR region have ever been discussed. Correlations of such marker bands among the NIR spectra have also been investigated. This sort of investigation is very important not only for further understanding of vibration spectra of various of PE but also for quality control of PE by vibrational spectroscopy. Figure 1 (a) and (b) shows a NIR reflectance spectrum of one of the LLDPE samples and that of PE, respectively. Figure 2 shows a PC weight loadings plot of factor 1 for a score plot of PCA for the 16 kinds of LLDPE and PE based upon their 51 NIR spectra in the 1100-1900 nm region. The PC loadings plot separates the bands due to the $CH_3$ groups and those arising form the $CH_2$ groups, allowing one to make band assignments. The 2D correlation analysis is also powerful in band enhancement, and the band assignments based upon PCA are in good agreement with those by the 2D correlation analysis.(Figure omitted). We have made a calibration model, which predicts the density of LLDPE by use of partial least square (PLS) regression. From the loadings plot of regression coefficients for the model , we suggest that the band at 1542, 1728, and 1764 nm very sensitive to the changes in density and crystalinity.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1527-1527
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• 2001

Glucose, fructose and sucrose being the main sugars that can be found in natural fruit juice. Many instrumental methods, such as GC, LC, electrochemical or spectrometric methods provide information about both the total content of sugars and the specific concentration of each carbohydrate[1]. The simplicity of sample handling and measurement in the near IR(NIR) wavelength region, which allows the use of long pathlength, optical glass cells and optical fibers, makes NIR a good alternative for sugar determination [2]. In the present study, six varieties of persian grapes were harvested at intervals through august to october and analysed for sugars by NIR. The results were processed by principal component regression (PCR) and partial least squares (PLS) analysis. Sample juice was prepared by squeezing through gauze from crashed grape. This solution was treated by zinc ferrocyanide prior to analysis in order to eliminate colored compounds and all optically active nonsugar substances. For glucose and fructose the most characteristic wavelengths were 1456nm corresponding to the first harmonic O-H stretching and the second at 2062nm corresponding to O-H stretching and deformation; secondary characteristic combination bands were also seen at 2265 nm (O-H and C-C stretching) and at 2240 nm (C-H and C-C stretching). However these spectra were taken over a wavelength range from 1100-2500nm at room temperature of 25-$30^{\circ}C$. To test the accuracy of the described procedure, samples of six varieties of grape were analysed by the proposed NIR and a standard method[2]. Good agreement were found between these two sets of the results. To perform the recovery studies , samples of grape juices previously analysed by the proposed method, were spiked with known amounts of each individual sugars and then analysed again. Relative standard deviations varied from 1.4 to 1.8% for six independent measurements of individual and total sugar concentration. In the analysis of real and synthetic samples, precise and accurate results were obtained , providing accuracy errors lower than 1.9% in all cases. Average recoveries of ${97}{\pm}{4%}$ for total sugar and between ${95}{\pm}{5%}$ and ${99}{\pm}{2%}$ for sing1e sugars demonstrate the applicability of the methodology developed to the direct analysis of grape Juice.