• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.197-206
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• 2021

There is growing interest in the function and role of public research institutes as "entrepreneurial actors" that can contribute to industrial development by commercializing excellent research outputs. On the other hand, their performance in the commercialization phase is insufficient because of the insufficient technological technology readiness level or repeatability. This study conducted probit model analysis to examine the effect of the technology readiness level and commercialization activities on the success of technology commercialization. The results showed that the possibility of success in technology commercialization increased with increasing TRL at the time of acquisition. In addition, the difference between the TRL at the time of acquisition and the current TRL (TRL Gap) does not affect technology commercialization on its own. It generates additional effects in conjunction with the TRL at the time of acquisition. Finally, the results show that technology commercialization is most likely to succeed if technology with a TRL 4-6 level is improved to TRL 9 level through a marginal effect estimation.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Asia Marketing Journal
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• v.12 no.3
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• pp.43-62
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• 2010

The notion of customer orientation is now importantly considered in the context of banking industries. Despite customer-oriented organizational cultures, there are few studies addressing the relationship between customer orientation and its outcomes. In particular, this study aims at testing the effect of customer orientation as a key marketing effort designed by a bank. This is because interest rate sensitivity is critical for evaluating banking services after raising the base rate. In so doing, first, this study investigates the relationships among customer orientation, interest rate sensitivity, and customer loyalty. Second, this paper examines how the moderating effects of both deposit interest and loan interest rates influence the linkages of customer orientation-interest rate sensitivity and customer orientation-customer loyalty. To test the proposed model, research data are collected from 304 subjects who use banking services(e.g., Shin-Han, Kookmin, the First Bank, Hana, and Woori banks). Each construct was measured by published items and the psychometric properties of the three constructs, excluding two constructs of the moderators, were evaluated by employing the method of confirmatory factor analysis via the use of AMOS. The model fit was also evaluated using the CFI, TLI, and RMSEA fit indices that are recommended based on their relative stability and insensitivity to sample size. The findings show that the relationship between customer orientation and customer loyalty is significant, whereas the relationships between customer orientation and interest rate sensitivity and between interest rate sensitivity and customer loyalty are not supported. Although customer orientation is highly evaluated, customers' interest rate sensitivity that results in the comparison of interest rates plays an important role in reducing the effect of customer orientation. As a consequence, interest rate sensitivity does not influence customer loyalty. First of all, one of interesting results in this study is that the moderating effect of loan interest rate is quite different from deposit interest rate. In the case of deposit interest rate, the linkages both customer orientation-interest rate sensitivity and customer orientation-customer loyalty are insignificant. In the case of loan interest rate, however, the two proposed linkages are supported. As our proposed relationships are still in its infancy in the context of banking industry, our study contributes to enhance scholars' knowledge of bank services and provides insights for practitioners when their marketing strategies, particularly both deposit and interest rates, have to be established. Finally, this research also illuminates the need for further research that considers the influence of customer orientation on consumer's decision-making and bank profits. More specifically, the results are encouraging and will lead us to further investigate this key outcome of the banking deposit/interest rates.

• Management & Information Systems Review
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• v.37 no.4
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• pp.1-20
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• 2018

This study aimed to examine earnings quality of firms selected as Global Champs project which has been promoted by the government since 2013 to support small and medium sized enterprises, for the screening year(t-1) and selected year(t). Earing quality is measured as the value of discretionary accruals estimated by Dechow et al.(1995) adjusted Jones model and Kothari et al.(2005) model, respectively. I analyze the differences of earning quality between the Global Champ firms and the paired firms selected through criteria of the similar total assets and the same industry in the screening year and the selected year. This study is motivated by the needs of measurement of the performance of the Project from the accounting transparent point of view. As the results of this study, major findings are summarized as follows. Firstly the earnings quality of the selected firms was lower than that of the paired firms. This can be explained as a result of motivation of earnings management by companies eager to meet the requirements to be selected for the Project. Secondly, in the selected year, the earnings quality was proved to improve, comparing to the screening year. This can be explained by the efforts of companies to reinforce management innovation and transparent management, which in turn led to positive effects on the earnings quality. These findings were found to be consistent in the additional analyses, where the earning quality of the reconstructed sample with only selected companies was compared for the screening year and the selected year, based on the year before the screening year(t-2).

• Journal of Global Scholars of Marketing Science
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• v.16 no.3
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• pp.107-123
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• 2006

This study suggest a model to find out relationships among the servant leadership as a preceding factor, the trust in higher officers as mediating factors, and leader satisfaction, additional efforts as a resulting factor. Then, empirical study testify the relationship among these factors. This study confined the subjects of empirical analysis to the employees in super-deluxe hotels located in Seoul, Gyeongju, Busan, and Daegu areas. In order to clarify the utility of this study, This study took only hotel employees as the subject of measurement because only hotel organization is able to reveal sensitively the behavioral response between the leader and the members of organization. The preceding study has systematized a basic theory on the servant leadership, and provided factor structure in regard to the servant leadership, but this study has searched the factor structure of the servant leadership with the hotel employees as the subjects of study. Also, from the side of the personnel manager of hotel business, this study can be a criterion for clarifying a leadership program. Especially, in order to cultivate their servant leadership, it is necessary to testify morality and pride as sub-behavioral characteristics of new employees. Also to change the mid-managers' leadership for the effective achievement of the object of organization, this study can be utilized for the development of servant leadership.

• Journal of Navigation and Port Research
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• v.44 no.4
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• pp.338-346
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• 2020

In this study, we first measured the Malmquist productivity index by DEA among the Korean ocean carriers. Second, it was intended to present measures to improve productivity by identifying the influence and discriminating power between productivity and the major financial ratios (profitability, financial stability, liquidity, efficiency and value-added productivity). Compared to 2017, there are 11 more shipping carriers with decline in productivity (MPI) than those with an increase in 2018. The increase in productivity is attributed to an increase in the Technology Change Index (TCI) affected by the external environment. There is strong significant correlation between the productivity (MPI) and the management efficiency (CRS). Additionally, the TECI (TECHI) index of the technological efficiency changes from internal factors of the shipping carrier is significantly higher than that of the efficient shipping carrier. This is because of the differences in scale efficiency. The ratio of charter cost/sales is also lower than that of the carriers with high productivity (0.17) and with low productivity (0.21). With 7% of the shipping carrier with MPI>1, only 1% of MPI <1 is found to have a significant impact on its productivity.

• Journal of The Korean Association For Science Education
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• v.38 no.6
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• pp.825-838
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• 2018

The purpose of this study is to develop a survey tool of scientific character for elementary student which connects science education and character education effectively by figuring out traits of elementary students' character being presented in teaching and learning context of elementary school science. For this, we adapted the theocratical model from the previous research which defined scientific character as the competencies being able to practice in concrete teaching and learning context of science. Based on this model, we developed the survey tool as 'Scientific Character Inventory for Elementary Student' to assess elementary students' scientific character as the competences to practice the virtues being pursued in the context of elementary school science and verified its reliability and validity. As a result of an exploratory and confirmatory factor analysis, we confirmed all the items could be summarized into 28 items and eight constructs such as scientific problem-solving, self-management, self-reflection, communication, interpersonal skill, community participation, global citizenship, and environmental ethics awareness. We found that minimum reliability coefficient of constructs was over than 0.5 and reliability coefficient of the total items was 0.878. And also, there was modest relationship between each construct and the total score of scientific character. These results show that the developed survey tool can be useful in evaluating the effectiveness of science character education. This study is meaningful in that it systematically reveals constructs of scientific character which can be raised in concrete context of science teaching and learning so as to suggest the survey tool to assess this.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.448-448
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• 2021

최근 급격한 기후변화와 도시화 및 산업화로 인한 지류하천에서의 수량과 수질의 변동은 생물 다양성 감소와 수생태계 건강성 저하에 큰 영향을 미치고 있다. 효율적인 수생태 관리를 위해서는 지속적인 유량, 수질, 그리고 수생태 모니터링을 통한 데이터 축적과 더불어 면밀한 상관 분석을 통해 수생태계 건강성의 악화 원인을 규명해야 할 필요가 있다. 그러나 수많은 지류하천을 대상으로 한 지속적인 모니터링은 현실적으로 어려움이 있으며, 수생태계의 특성 상 단일 영향 인자만으로 수생태계의 건강성 변화와의 관계를 정확히 파악하는데 한계가 있다. 따라서 지류하천에서의 유량 및 수질의 시공간적인 변동성과 다양한 영향 인자를 고려하여 수생태계의 건강성을 효율적으로 예측할 수 있는 기술이 필요하다. 이에 본 연구에서는 경험적 데이터 기반의 머신러닝 모델 구축을 통해 미계측 하천에서의 수생태계 건강성 지수(BMI, TDI, FAI)의 등급(A to E)을 예측하고자 하였다. 머신러닝 모델은 학습 데이터셋의 양과 질에 따라 성능이 크게 달라질 수 있으며, 학습 데이터셋의 분포가 불균형적일 경우 과적합 또는 과소적합 문제가 발생할 수 있다. 이를 보완하고자 본 연구에서는 실제 측정망 데이터셋을 바탕으로 생성적 적대 신경망 GAN(Generative Adversarial Network) 알고리즘을 통해 머신러닝 모델 학습에 필요한 추가 데이터셋(유량, 수질, 기상, 수생태 등급)을 확보하였다. 머신러닝 모델의 성능은 5차 교차검증 과정을 통해 평가하였으며, GAN 데이터셋의 정확도는 실제 측정망 데이터셋의 정규분포와의 비교 분석을 통해 평가하였다. 최종적으로 SWAT(Soil and Water Assessment Tool) 모형을 통해 예측 된 미계측 하천에서의 데이터셋을 머신러닝 모델의 검증 자료로 사용하여 수생태계 건강성 등급 예측 정확도를 평가하였다. 본 연구에서의 GAN에 의해 강화된 머신러닝 모델은 수질 및 수생태 관리가 필요한 우심 지류하천 선정과 구조적/비구조적 최적관리기법에 따른 수생태계 건강성 개선 효과를 평가하는데 활용될 수 있을 것이다. 또한 이를 통해 예측된 미계측 하천에서의 수생태계 건강성 등급 자료는 수량-수질-수생태를 유기적으로 연계한 통합 물관리 정책을 수립하는데 기초자료로 활용될 수 있을 것이라 사료된다.

• Economic and Environmental Geology
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• v.44 no.2
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• pp.135-152
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• 2011

Nitrate concentrations in springs at the southern slope of Jeju Island were predicted using multiple linear regression (MLR) of spatial variables including hydrogeological parameters and land use characteristics. Springs showed wide range of nitrate concentrations from <0.02 to 86 mg/L with a mean of 20 mg/L. Spatial variables were generated for the circular buffer when the optimal buffer radius was assigned as 400 m. Selected regression models were tested using the p values and Durbin-Watson statistics. Explanatory variables were selected using the adjusted $R^2$, Cp (total squared error) and AIC (Akaike's Information Criterion), and significance. In addition, mutual linear relations between variables were also considered. Small portion of springs, usually <10% of total samples, were identified as outliers indicating limitations of MLR using circular buffers. Adjusted $R^2$ of the proposed models was improved from 0.75 to 0.87 when outliers were eliminated. In particular, the areal proportion of natural area had the greatest influence on the nitrate concentrations in springs. Among anthropogenic land uses, the influence of nitrate contamination is diminishing in the following order of orchard, residential area, and dry farmland. It is apparent quality of springs in the study area is likely to be controlled by land uses instead of hydrogeological parameters. Most of all, it is worth highlighting that the contamination susceptibility of springs is highly sensitive to nearby land uses, in particular, orchard.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.11
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• pp.1435-1442
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• 2008

The purpose of this study was to identify the influence of consumption value on healthy functional food choice. Also, this study explored the role of health motivation, health concern, and food involvement as a moderating variable in the relationship between consumption value and healthy functional food choice. A total of 281 responses were collected using on-site survey (response rate 96.0%) from college students in Daegu, Gyeoungbuk Province. The questionnaire contained questions on consumption value, health motivation, health concern, food involvement, and purchasing intention of healthy functional food. The respondents rated the items using a 5-point scale from 1 (strongly disagree) to 5 (strongly agree). According to the confirmatory factor analysis, item evaluating using factor loading resulted in the retention of 25 consumption value items loading on seven factors, four health motivation items loading one factor, six health concern items loading on one factor, and four food involvement items loading on one factor with an internal consistency. Results of stepwise regression found that social value-I, emotional, functional, epistemic, and conditional values among consumption value determined the purchasing intention of healthy functional food. Results of hierarchical regression showed that health concern had a positive effect on the relationship between social value-I and purchasing intention of healthy functional food.