• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.5
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• pp.61-78
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• 2019

This study is about the effect of the founder's self-efficacy on the sales of the founding company by focusing on the factors that are currently emphasized in the founding education. In particular, this paper starts from the consciousness of the problem that the education that is being implemented to achieve the purpose of successful start-up among various government-based start-up support projects is failing to produce many start-up failures. Entrepreneurs cannot be assessed by objective financial data, but there is a high degree of uncertainty that should be determined based on their personal and learning abilities. In addition, many previous studies, which are likely to be successful when there is a high self-efficacy in a specific field due to the influence of factors such as personal experience or learning, will answer the direction of support for start-up companies. This study focuses on the impact of the founder's self-efficacy on the sales of the founding firms, especially the sales that are the key to the survival of the founding firms. This study has six major studies. First, to analyze whether the self-efficacy of entrepreneurs with respect to entrepreneurship affects the sales of entrepreneurs. Second, to analyze whether the self-efficacy of entrepreneurs with respect to market orientation affects the sales of entrepreneurs. Analysis of whether the founder's self-efficacy affects the sales of the founding firms. Fourth, analysis of whether the founder's self-efficiency affects the sales of the founding firms' understanding of management environment changes. An analysis of whether efficacy affects the sales of a start-up company, and sixth, an analysis of whether the founder's self-efficacy of business model building ability affects the sales of a start-up company. As a result of the empirical analysis, this study found that the self-efficacy of entrepreneurs on product differentiation capability and business model building capacity had a positive influence on the sales of entrepreneurs. The self-efficacy had a positive effect on self-efficacy, and the customer orientation had a positive effect on self-efficacy on business model building capacity. Also, it was confirmed that a path exists between the components of self-efficacy and that self-efficacy through the path has a positive effect on the sales of the start-up company. Therefore, the results of this study suggest the implications of establishing such a path and strengthening self-efficacy to create the survival and start-up performance of a start-up company if the goal of the start-up company is to survive when implementing various support projects for the start-up company.

• Korean Security Journal
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• no.33
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• pp.51-80
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• 2012

This study is to summarize main contents which was mentioned by Beomseok Kim' doctoral dissertation. The purpose of this study focuses on presenting the outplacement countermeasure and retention level examination analysis about outplacement competency of special security government official through implement of questionnaire method. The questionnaire for retention level examination including four groups of outplacement competency and twenty subcategories was implemented in the object of six hundered persons relevant to outplacement more than forty age and five grade administration official of special security government officials, who have outplacement experiences as outplacement successors, outplacement losers, and outplacement expectants, in order to achieve this research purpose effectively. The questionnaire examination items are four groups of outplacement competency and twenty subcategories which are the group of knowledge competency & four subcategories including expert knowledge, outplacement knowledge, self comprehension, and organization comprehension, the group of skill competency & nine subcategories including job skill competency, job performance skill, problem-solving skill, reforming skill, communication skill, organization management skill, crisis management skill, career development skill, and human network application skill, the group of attitude-emotion competency & seven subcategories including positive attitude, active attitude, responsibility, professionalism, devoting-sacrificing attitude, affinity, and self-controlling ability, and the group of value-ethics competency & two subcategories including ethical consciousness and morality. The respondents highly regard twenty-two outplacement competency and they consider themselves well-qualified for the subcategories valued over 4.0 such as the professional knowledge, active attitude, responsibility, ethics and morality while they mark the other subcategories below average still need to be improved. Thus, the following is suggestions for successful outplacement. First, individual effort is essential to strengthen their capabilities based on accurate self evaluation, for which the awareness and concept need to be redefined to help them face up to the reality by readjusting career goal to a realistic level. Second, active career development plan to improve shortcoming in terms of outplacement competency is required. Third, it is necessary to establish the infrastructure related to outplacement training such as ON-OFF Line training system and facilities for learning to reinforce user-oriented outplacement training as a regular training course before during after the retirement.

• Journal of Korean Home Economics Education Association
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• v.22 no.4
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• pp.139-154
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• 2010

The purpose of this study was to put forth of a future vision from examining of social contribution, future direction, and theoretical framework of home economics education and its cases of practice in educational setting. This study was carried with literature review, and results of study were as follows: First, home economics education should contribute to society through (1) educating individuals suffering from family tiredness to maintain autonomous lives free from distorted family ideology by being critically conscious of them in individual dimension, (2) educating individuals to develop a competence as a citizen to be critical of family ego-centric ideas and to participate and support communal life in family-social dimension, and (3) educating female and male students gender sensitivity and management of family life to be critical of gender discrimination ideology in gender dimension. Second, future home economics education should reinforce all round character education which let students develop their creativity and problem solving ability and foster students' wisdom of life with honesty and morality rather than merely acquiring knowledge in individual dimension. Third, this study employed Brown and Paolucci's conceptual scheme as a theoretical framework which focuses on the role of home economics education leading individuals and families as a changing agent. This framework let individuals and families to critically examine the social character and ideas provided by existing social, economical, and political systems, and to transform social character and ideas to build an ideal societal condition when there are any problems in them. Fourth, this study examined sample classroom instruction of Japan and FCCLA of United States of America to see how they educate students to become a changing agent. In conclusion, future vision of home economics education is to accomplish family revolution to sustain happy family relation and their family lives in which they feel pampered from achievement and free from distorted family ideology. For home economics to accomplish family revolution, it should strengthen education for empowerment, enlightenment, and autonomy. This study calls for immediate paradigm shift not as an occupational but as a practical-critical praxis subject matter for family revolution through home economics education.

• 대한공업교육학회지
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• v.41 no.1
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• pp.68-87
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• 2016

This research conducted a survey for total 166 teachers of schools so as to analyze validity and satisfaction for performance objectives of SMB administration subsidy the HRDP and the CEP in Specialized High School. The results of research are as follows. First, teachers recognize that purpose of HRDP is to expand employment of specialized high school and provide human resource of SMB. And, they recognize that HRDP is important to improve school outcomes and makes a positive effect on the improvement of school outcomes. Second, teachers recognize that objectives of HRDP are improvement of student's understanding for SMB, improvement of teacher's understanding for SMB, improvement of SMB's understanding of school, cultivation of student's occupational view, systematization of career guiding program based on employment process, strengthening of industry-academia cooperation education, improvement of the level of student's skill, fulfillment of workplace experience and practice focusing workplace learning, training of customized human resource for SMB, improvement of student's adaptation to the workplace, improvement of employment rate for SMB, expansion of job opportunities for students with SMB, preparation of the base of connection between school and SMB, publicity of school, expansion of opportunities to cooperate between SMB and school, establishment of cooperative system among industrial association and school, introduction and operation of the employment connective model for joint education and employment, strengthening of field professionalism of teachers. However, satisfaction for the achievement of objectives of HRDP except for strengthening of industry-academia cooperation education and improvement of employment rate for SMB is relatively lower than the validity. Third, teachers in charge of human resource training business of middle and small sized company's specialized high school recognize that objectives of CEP are expansion of job opportunities for students with SMB, excavation of good-quality SMB, expansion of opportunities to cooperate between SMB and school, fulfillment of workplace learning, improvement of student's major foundation and in-depth skill, improvement of literacy, math, teamwork and communication abilities for students' job performance, improvement of student's working attitude and student's proper career exploration decision. However, satisfaction for achievement of objectives of CEP is relatively lower than the validity.

• Journal of Korean Classical Literature and Education
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• no.34
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• pp.41-74
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• 2017

This study aimed to investigate the narrative strategy and meaning of fantasy in classic novels and to derive the educational meaning from the fantasy of Sukhyangjeon. This study selected Sukhyangjeon because is considered a suitable literary text that embodies characteristics of fantasy inherent in classical novels through its successful portrayal of the fantasy genre and its high popularity during its time. Specifically, this study observed that the "notice of hardships" which repeatedly appears in the narration of Sukhyangjeon reinforces the fantasy of the novel as it serves as an advance notice of intervention from heaven. Therefore, this study investigated the relationship between the notice of hardships and fantasy by focusing on Sukhyang's life. The way in which the "notice of hardships" is a form of illusion realized it evident in the plot when heaven saves Sukhyang from her hardship even though it was heaven that had granted her those forms of hardship. Firstly, the "notice from heaven" constitutes the macro structure of Sukhyangjeon. Through it, readers realize the enormous power of heaven by seeing how Sukhyang's life has been realized in accordance with heaven's notice with that, it evokes a sense of respect to heaven. In addition, heaven saves Sukhyang from different forms of danger. It enhances a miraculous feeling, which the omnipotent power of heaven shows, against the innocent appearance of Sukhyang during her times of danger. Meanwhile, when heaven notifies Sukhyang and the surrounding people of their fate and subsequently realizes it through dreams, this act creates a mysterious atmosphere and improves the probability of the narrative. If so, the narrative meaning in reinforcing the fantasy of the novel by the use of "notice of hardships" could be revealed through Sukhyang's real life. First, the hardship in which Sukhyang has gone through is so realistic and detailed that the readers' feelings of empathy are evoked with the fear of the coming hardship, wailing together, and trying to resolve the inner anxiety through Sukhyang's happiness. Second, the heavenly beings who are touched by the good behaviors of Sukhyang save her from the dangers of death. This creates the belief in readers that heaven intervenes for the good people. Third, the active attitude that Sukhyang and Leesun show in the process of marriage helps them overcome their earthly hardship and preserve their relationship in heaven. This gives readers hope that they could go to a "higher life" after going through suffering. This fantasy of Sukhyangjeon helps readers overcome their anxieties of reality through fantasy and recognizes the importance of relationships to enhance a sense of unity and solidarity with others. Because of these elements, it is expected that the fantasy of Sukhyangjeon will have a meaningful value to modern readers.

• Korean Journal of Comparative Education
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• v.27 no.4
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• pp.255-283
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• 2017

The purpose of this study is to analyze the comtent of the education system of US and the UK in order to build an integrated system that can develop the leadership competency of preschool principle. Based on this, the implications are as follows. First, competencies can developed through learning rather than fixed. Therefore, re-conceptualization of leadership competence appropriate to the characteristics and organization of the individual as the presiding authority of the preschool can be considered as ability to show visible knowledge and skills, invisible self concept. Therefore, it is necessary to establish a capacity development plan based on this. Second, the introduction and implementation of continuous and systematic training programs such as the training system that strengthens the capacity of the directors and principals of the United States and the United Kingdom is necessary. To do this, we must introduce a system that renews certification every five years, like the United States, rather than a system that acquires and maintains certification with a single training. Third, various training methods should be carried out. In the case of the US and the UK, we think it is desirable to train in various ways in the training period, the university, the teacher center, and the private organization or association. Therefore, it is necessary to build a cooperation system with various institutions such as training institutes, universities, teacher centers, educational information research institutes, and private organizations in each province, and strengthen them in various ways. Fourth, the contents and methods of qualification training and future job training of the director of the preschool should be deviated from the uniform level. Therefore, the systematic research that reflects the knowledge and contents of the administration required in the field should be given priority by the university or research organization that is in charge of the training.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• Journal of Korean Home Economics Education Association
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• v.27 no.1
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• pp.51-65
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• 2015

The purpose of the study was to describe the operating status of "Logic and Writing in Home Economics Education(HEE)" course and the students' perception about the course. For this study, the syllabuses of "Logic and Writing" course in HE education department were reviewed. The survey method was used in this descriptive study. Respondents in this study were 116 students taking the "Logic and Writing in Home Economics Education" course. Questionnaires from the students were collected through on-line and off-line mail. The results of the study were as the follows: First, goals of the "Logic and Writing in HE Education" course were as the follows in order: to enhance writing skill about various subjects related to Home Economics; to foster HE teachers' professionalism through persuasive power logically; to foster writing skill logically; to prepare HE teacher recruitment exam; and to foster teaching skills to enhance students' writing. The student evaluation methods in the course were mainly attendance, examination, tasks, discussion and presentation, and class participation. Second, degree of satisfaction of students taking the course was higher than average. The student respondents perceived that the course was helpful to improve their logical thinking and critical analytical skill, writing skill related to HE education and education, ability to express one's opinion clearly and exactly, understanding of the fundamental concept of logic and the structure and method of the essay, comprehensive understanding of HE education, and ability to solve the problems specifically. However, they responded that it was difficult to practice writing, to discuss and debate frequently, to follow uncertain assessment criteria, and to present frequently. They wanted the instructor to give the feedback more frequently.

• Journal of The Korean Association For Science Education
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• v.37 no.2
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• pp.347-358
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• 2017

The purpose of this study is to research on the professional development of pre-service chemistry teachers in terms of personal practical knowledge(PPK), and draw a discussion for pre-chemistry teacher education. A reflective discussion through a Community of Practice(CoP) activity has been conducted with 5 pre-service chemistry teachers studying in a college of education located in Seoul. The analysis of the results reveals that 'Subject-matter knowledge' is leaning toward massive chemical contents, 'Curriculum knowledge' is below the level of selecting, analyzing, and applying curriculum materials. 'Instruction knowledge', especially the knowledge of chemistry experiment and research, is not enough to lead secondary students' scientific experiment. 'Milieu of school knowledge' is stunted in growth for the reason of communication-deficiency between a college of education and a community, and among education- related groups. 'Self-knowledge' has been diminished not only because there is a bad influence from college classmates not wanting to be a teacher, but also a lack of communication in the chemistry-education department which can make pre-teachers' belief strong. In conclusion, it is especially needed for the chemistry-education department to strengthen pre-teachers' 'Self-knowledge' in order to develop PPK. This study suggests operating 'a professional community' that has a periodic meeting with pre-service teachers, teachers, professors, community people, education practitioners, and researchers. In addition, it would be effective for increasing pre-teachers' PPK to reconsider depth and direction of 'Subject-matter knowledge', to give an opportunity to examine curriculum materials critically and reorganize them, to improve the course of chemistry experimental subject to the way of improving pre-teachers' leadership in chemistry inquiry experiment, and to raise the quality of educational service activities.