• Fashion, Industry and Education
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• v.15 no.2
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• pp.53-63
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• 2017

The growing significance of corporate social responsibility in the fashion industry has shed light on the importance of preparing fashion students to become socially responsible professionals. In spite of numerous benefits of service-learning, the teaching/learning method has been rarely employed in the fashion design and merchandising context. Therefore, the purpose of the study was first, to examine the concept and models of service-learning and compare different types of service-learning programs, and second, to discuss service-learning projects that were adopted in a visual design class as examples that service-learning can be effectively integrated into the fashion design and merchandising curriculum. This study provides the opportunity to share successful service-learning implementation with other educators to help with effective incorporation of the pedagogical program into the curriculum.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.142-152
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• 2022

We study confirmed the relationship between the adversity index, entrepreneurial orientation, and organizational learning competency perceived by organizational members as follows. First, the adversity index showed a positive (+) effect on entrepreneurial orientation (hypothesis 1) and organizational learning competency (hypothesis 2). Second, the entrepreneurial orientation was statistically significant in organizational learning competency (hypothesis 3). Third, the partial mediating role of entrepreneurial orientation (Hypothesis 4) was confirmed in the process of the adversity index affecting organizational learning competency. Meanwhile, the main implications of this study are as follows. First, it is the aspect that provides additional theoretical implications in the reality that studies on the adversity index and entrepreneurial orientation that affect organizational learning competency are lacking. Second, it is the aspect that the importance of adversity index and start-up orientation was confirmed in improving organizational learning competency based on securing differentiated competitiveness for the advancement of the organization's sustainability management system. In addition, it is the aspect of drawing practical implications for strategic human resource management and human resource development to systematically improve it.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.65-76
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• 2022

Recently, not only traditional statistical techniques but also machine learning algorithms have been used to make more accurate bankruptcy predictions. But the insolvency rate of companies dealing with financial institutions is very low, resulting in a data imbalance problem. In particular, since data imbalance negatively affects the performance of artificial intelligence models, it is necessary to first perform the data imbalance process. In additional, as artificial intelligence algorithms are advanced for precise decision-making, regulatory pressure related to securing transparency of Artificial Intelligence models is gradually increasing, such as mandating the installation of explanation functions for Artificial Intelligence models. Therefore, this study aims to present guidelines for eXplainable Artificial Intelligence-based corporate bankruptcy prediction methodology applying SMOTE techniques and LIME algorithms to solve a data imbalance problem and model transparency problem in predicting corporate bankruptcy. The implications of this study are as follows. First, it was confirmed that SMOTE can effectively solve the data imbalance issue, a problem that can be easily overlooked in predicting corporate bankruptcy. Second, through the LIME algorithm, the basis for predicting bankruptcy of the machine learning model was visualized, and derive improvement priorities of financial variables that increase the possibility of bankruptcy of companies. Third, the scope of application of the algorithm in future research was expanded by confirming the possibility of using SMOTE and LIME through case application.

• Information Systems Review
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• v.25 no.3
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• pp.27-41
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• 2023

Unlike the previous works focusing on the state-of-the-art methodologies to improve the performance of machine learning models, this study improves the 'quality' of training data used in machine learning. We propose a method to enhance the quality of training data through the processing of 'local grammar,' frequently used in corpus analysis. We collected a vast amount of unstructured corporate review text data posted by employees working in the top 100 companies in Korea. After improving the data quality using the local grammar process, we confirmed that the classification model with local grammar outperformed the model without it in terms of classification performance. We defined five factors of work engagement as classification categories, and analyzed how the pattern of reviews changed before and after the COVID-19 pandemic. Through this study, we provide evidence that shows the value of the local grammar-based automatic identification and classification of employee experiences, and offer some clues for significant organizational cultural phenomena.

• Journal of Korea Game Society
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• v.21 no.6
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• pp.75-86
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• 2021

Brand image refers to how customers, stakeholders and the market see and recognize the brand. A positive brand image leads to continuous purchases, but a negative brand image is directly linked to consumers' buying behavior, such as stopping purchases, so from the corporate perspective, it needs to be quickly and accurately identified. Currently, methods of investigating brand images include surveys and SNS surveys, which have limited number of samples and are time-consuming and costly. Therefore, in this study, we are going to conduct an emotional analysis of text data on social media by utilizing the machine learning based KoBERT model, and then suggest how to use it for game corporate brand image analysis and verify its performance. The result has proved some degree of usability showing the same ranking within five brands when compared with the BRI Korea's brand reputation ranking.

• Journal of the Korean association of regional geographers
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• v.8 no.3
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• pp.396-411
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• 2002

This paper aims to explore organisational change and learning involving spatial processes and outcomes. In particular, it focuses on the context specific nature of corporate learning and organisational change that can be found in the case of a large Korean firm facing radical economic change. Drawing on the case study of a large Korean firm, the Samsung Electronics Company, three main claims can be followed. First, territorial sources of learning influence the way in which the firm makes use of space/place. Second, corporate learning practices, however, are not based merely on specific localised sources or geographical proximity but on bringing together the local and the global sources by harnessing the properties of relational proximities. It reveals that firms are concerned less on specialising specific local knowledge than promoting organisational knowledge and competences by integrating a variety of knowledge distributed in and out of the boundaries of the firm. Finally, to learn and innovate in a continual basis, firms would attempt to combine codified knowledge with tacit knowledge.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.571-578
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• 2005

Corporate credit rating analysis has drawn a lot of research interests in previous studies, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper applies support vector machines (SVMs) to the corporate credit rating problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, the researcher uses a grid-search technique using 5-fold cross-validation to find out the optimal parameter values of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM, the researcher compares its performance with those of multiple discriminant analysis (MDA), case-based reasoning (CBR), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• Archives of design research
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• v.15 no.1
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• pp.37-48
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• 2002

In the face of rapidly changing society and consumer cognition, eyer-increasing importance of strategies for creating good images for a company among critical factors inf1uencing management in terms of its survive is prevalent. Today, many companies strive for getting or improving their images with advertisements for corporate identity as well as public advertisements, which is considered as a requirement of this society and age for good images of companies rather for only good products and services. In this study, we analyzed and compared the largest companies in Korea, mainly in their printed materials for advertisements over the last 10 years from 1990. Corporate advertisements performed by domestic companies could be classified into several types based on their theoretical backgrounds and creative concepts. Basic theoretical backgrounds of corporate advertisements induced in the study are recognitive-psychological model and associative learning model. And, six areas of cases were classified and analysed in terms of their such creative concepts as random difference, competitive advantage and specific creativity. We analyzed and compared cases of strategies for domestic corporate advertisements with reference to these six each area in their effects and problems in terms of theoretical and practical aspects and thereby purpose to provide companies with reference in developing strategies for corporate advertisements of companies.

• The Journal of Korean Association of Computer Education
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• v.10 no.2
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• pp.49-64
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• 2007

This research aims to investigate e-Learning behavior and its different features which may vary depending on learners' characteristics and their prior e-Learning experiences. For this purpose, a survey was conducted for adult learners who had e-Learning experiences. It included various questions including place, time and process of e-Learning. The result showed that features of e-Learning behavior varies according to learner characteristics, such as gender, educational background, and their work experiences. It also revealed that work environment and the nature of e-Learning courses are influential factors for their learning behavior.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.49-58
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• 2009

In business training, the biggest change through training plan, choosing trainees and conducting the training has been on education environment by information system. These changes are to attain effective learning based on the customer not the supplier. However there are still passive operation on the companies' strategic training course. Accordingly, the purpose of this study is to offer alternatives for the difficulties on educational training operation and to find the way for effective operation.