• (The)Korea Educational Review
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• v.24 no.3
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• pp.167-189
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• 2018

Using the 1st to 5th wave data from Gyeonggi Education Panel Study(GEPS), this study analyzed the change of school effectiveness of middle schools by innovation school expansion in Gyeonggi province. For this purpose, the analysis employed difference-in-difference model with repeated cross-sectional data and the dependent variable was comprised of academic achievement, school satisfaction, creativity, and sense of community. Results showed that the effectiveness of innovation schools had not significantly different from general schools before innovation school expansion but significantly improved in academic achievement and school satisfaction compared to general schools after the policy applied. On the other hand, the school effectiveness in creativity and sense of community not significantly different between innovation and general schools in both before and after. As time passes, the effectiveness of existing innovation schools in the academic achievement was improved and the school satisfaction was maintained. In addition, the effectiveness in satisfaction of the schools was improved as general schools with high effectiveness in academic achievement were transformed into innovation schools. Based on the results, the policy for innovation school expansion was evaluated and the issues related to this policy were discussed.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.125-131
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• 2019

The purpose of this study is to investigate the relationship between attitude, purchase intention, and intention to share content and brand intention according to Influencer contents and branded content types. The results of this study are as follows: First, beauty products have a positive effect on the content intention and purchase intention as well as the sharing intention as compared to the branded contents. Second, V-commerce of innovative products showed that the branded content was more positive than the influencer content, but the purchase intention was lower. In addition, the content of sharing is higher than that of branded content. Third, the sharing intention was more positive than the beauty product, and the influencer content was higher than the branded content. The purpose of this study is to examine the attitude, purchasing intention, and sharing intention of beauty products and innovative products, which are most frequently used and most interested in users, to examine the content strategy of V-Commerce.

• Journal of Industrial Convergence
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• v.20 no.1
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• pp.23-33
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• 2022

The study was conducted to develop an implementation model for digital transformation (DX) of manufacturing companies. To this end, previous studies on the process of management innovation and digital transformation were reviewed. The DX process model was derived based on the NEBIC theory and innovation theory applied in the innovation process of the Internet business. In addition, a research model including the factors of the will of the top management class (TMT) was constructed and confirmed through empirical data. The research hypothesis were verified based on data collected from members of mid-sized manufacturing companies promoting digital transformation. Through regression analysis, the influence relationship of each stage of the research model (technical knowledge, TK → opportunity perception, OR → performace expectation, PE and → Intention to execute, IE) was confirmed. Hierarchical regression analysis was conducted to understand the mediating effect of the members' perception of the top management's willingness to promote DX in the process. As a result of checking the Sobel test, it was confirmed that the management's perception of DX promotion partially mediated the relationship at each stage. This study is meaningful in that it presented a model applicable to the digital transformation of the mid-sized manufacturing industry. It is also valuable in providing an empirical basis for innovative research and NEBIC expansion. Longitudinal studies are required to overcome the limitations of empirical data for process models with dynamic characteristics whereas extended empirical studies are required in various fields other than manufacturing to generalize research results.

• The Korean Journal of Applied Statistics
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• v.35 no.6
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• pp.703-724
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• 2022

Although longitudinal studies mainly produce multivariate longitudinal data, most of existing statistical models analyze univariate longitudinal data and there is a limitation to explain complex correlations properly. Therefore, this paper describes various methods of modeling the covariance matrix to explain the complex correlations. Among them, modified Cholesky decomposition, modified Cholesky block decomposition, and hypersphere decomposition are reviewed. In this paper, we review these methods and analyze Korean children and youth panel (KCYP) data are analyzed using the Bayesian method. The KCYP data are multivariate longitudinal data that have response variables: School adaptation, academic achievement, and dependence on mobile phones. Assuming that the correlation structure and the innovation standard deviation structure are different, several models are compared. For the most suitable model, all explanatory variables are significant for school adaptation, and academic achievement and only household income appears as insignificant variables when cell phone dependence is a response variable.