• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.3
• /
• pp.87-103
• /
• 2021

The government is trying to create jobs by providing 160 billion won in 2021 to revitalize youth start-ups, but the number of youth unemployment and potential unemployment is hitting a record high of 1.2 million due to the shock of employment due to COVID-19. Although start-ups are encouraged as an alternative to revitalizing jobs, the success rate of young start-ups is low due to lack of start-up funds and experience. The purpose of this study is to understand the need to diversify start-up education and career education by understanding start-up policies through one-time funding and short-term education. The results of the study on the factors affecting the willingness to start a business were as follows, by sampling 344 students from specialized high schools preparing for employment and 344 young people in their 20s who are seeking jobs. First, among the entrepreneurship subvariables, innovation, autonomy of job value, and desire for economic achievement are significant, and the older the person surveyed, the more positive the perception of the entrepreneur was. Second, as you get older, your will to start a business decreases, and your experience in successful start-up models and start-up education has an impact on your will to start a business. Third, perception of entrepreneurs is a partial medium effect, which indirectly influences the willingness to start a business and directly or indirectly influences the willingness to start a business through the autonomy of job values, the desire to achieve economic and entrepreneurship.

• Journal of the Society of Disaster Information
• /
• v.18 no.1
• /
• pp.228-240
• /
• 2022

A comprehensive safety management system will be required in accordance with the implementation of the Major Disaster Punishment Act for close-up safety management of construction sites. Safety management level evaluation management requires a comprehensive relationship between safety management under the Construction Technology Promotion Act and health and health management system under the Industrial Safety and Health Act. Purpose: Safety under the Serious Accidents Punishment Act. The ultimate goal is to study the comprehensive analysis and relationship of health management and to improve the safety evaluation level of health and health management. Methods: The feasibility of the questionnaire was confirmed through the second Delphi analysis of construction site experts and safety managers, and the regression coefficient and path analysis of potential variants in safety management, safety management, health management and safety inspection were confirmed. Result and Conclusion: In the structural model, the regression coefficient (89%) from safety management, health system, and safety management to safety inspection execution and lambda values of appropriate observation variables were confirmed. In the path analysis, the total effect (.809) was confirmed by mediating health hygiene in the relationship between health plan establishment adequacy and post-inspection management, and the path coefficient (.82) of temporary structure safety was confirmed.

• Journal of Korean Home Economics Education Association
• /
• v.32 no.4
• /
• pp.67-79
• /
• 2020

The purpose of the study were to analyze the patterns of adolescent suicide attempts, and to explore the effects of personal psychology (subjective depression, subjective stress), health status (BMI, subjective health perception), and subjective academic performance on the types of youth suicide attempts. For this research, data of 'The 15th Korea Youth Risk Behavior Survey' were analyzed employing a hierarchical logistic regression analysis. The findings are as follows. First, out of 1,731 youth suicide attempts 156 (9%) were impulsive and 1,575 (91%) were planned. Girls(67.3%) attempted suicide more than boys (32.5%), and middle school students (62%) attempted suicide more than high school students (38%). Second, the variables that significantly affect suicide attempt types were subjective depression, subjective stress, and subjective health perception, after controlling for gender, grade level, school type, and SES. The rate of planned suicide attempts was higher among those who experienced depression than among those who did not. In the case of subjective stress, adolescents who felt stressed were likely to commit planned suicide attempts. Those who attempted impulsive suicide showed 1.32 times higher subjective health perception scores than those who attempted planned suicide, indicating adolescents who perceived they were not healthy were more likely to attempt planned suicide. BMI and subjective academic performance did not have a significant effect on the types of youth suicide attempts. These findings suggested the necessity of systematic intervention in Home Economics classes or extra-curricular programs, to prevent potential youth suicide attempts.

• Journal of Intelligence and Information Systems
• /
• v.28 no.3
• /
• pp.185-207
• /
• 2022

Recently, with the development of deep learning technology, researches to apply a deep learning algorithm to analyze unstructured data such as text and images are being actively conducted. Text classification has been studied for a long time in academia and industry, and various attempts are being performed to utilize data characteristics to improve classification performance. In particular, a hierarchical relationship of labels has been utilized for hierarchical classification. However, the top-down approach mainly used for hierarchical classification has a limitation that misclassification at a higher level blocks the opportunity for correct classification at a lower level. Therefore, in this study, we propose a methodology for classifying hierarchical data using the autoencoder-based deeply supervised network that high-level classification does not block the low-level classification while considering the hierarchical relationship of labels. The proposed methodology adds a main classifier that predicts a low-level label to the autoencoder's latent variable and an auxiliary classifier that predicts a high-level label to the hidden layer of the autoencoder. As a result of experiments on 22,512 academic papers to evaluate the performance of the proposed methodology, it was confirmed that the proposed model showed superior classification accuracy and F1-score compared to the traditional supervised autoencoder and DNN model.

• Journal of Korean Society of Forest Science
• /
• v.112 no.1
• /
• pp.105-116
• /
• 2023

As forest fires' scale has increased, they have become disasters that destroy not only forests but also property, human psychological balance, and even human lives. As a result, governmental support has become a crucial part of the forest fire restoration process. Quickly restoring victims' quality of life (QOL) from not only an ecological perspective but also from their human perspective has become an important goal. Therefore, through structural equation modeling, this study analyzed effects of government support, post-traumatic stress disorder (PTSD), and resilience on 195 Uljin and Samcheok forest fire victims' QOL. In the final research model, the total standardized effect on QOL of government support to PTSD and resilience was found to have significant effect (0.417). By path, the effect of government support on QOL through resilience was verified as 0.172. Examination of the path between latent variables revealed that resilience had the greatest influence on QOL, and government support had a significant effect, thus confirming that they were the main factors affecting QOL.

• Journal of Life Science
• /
• v.33 no.6
• /
• pp.490-497
• /
• 2023

Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

• Asia Marketing Journal
• /
• v.7 no.1
• /
• pp.21-42
• /
• 2005

Customer Relationship Management (CRM) is a corporate marketing strategy maintaining and managing customers. And with CRM companies maximize the customer's value through a series of processes of new customer retention, VIP customer retention, customer value increase, potential customer activation, and customers for lifetime by collecting the customer information and taking advantage of it effectively. In particular, as the competitive environment is changing rapidly and getting more intense, maintaining the customer retention through customer churn management becomes more important in order to increase the customer value for maximizing the company's profit and to build up the relationship with customers. For example, the financial industry has managed the customer churn with the concept of customer segmentation. Recently the customer retention and churn management is becoming increasingly important in all business fields as well as financial industry since the companies expect the effect of preventing the customer churn by identifying characteristics of customers. However, despite the increasing interest and importance of the management of the customer churn, not many of studies are systematically executed by analyzing the data of customer churn. In this study we analyze the actual data of CRM activities for the customer retention, specifically the data of TV home-shopping. By doing so, we hope to identify the differences of demographic attributes and transaction specific characteristics in consumer behaviors between the churning customer and the retained customers. In addition, we try to find out the variables which can impact the churning of the customers and to predict the churn rate of individual customer through our proposed model of customer churn. In the end, based on our findings we suggest the possible marketing strategies for TV home-shopping companies.

• Korean journal of applied entomology
• /
• v.62 no.3
• /
• pp.215-220
• /
• 2023

A recent discovery of drywood termites (Cryptotermes domesticus) in a residential facility in Seoul has raised significant concern. This exotic insect species, which can damage timber and wooden buildings, necessitates an immediate investigation of potential infestation. In this study, we assessed the climatic suitability for this termite species using a species distribution modeling approach. Global distribution data and bioclimatic variables were compiled from published sources, and predictive models for climatic suitability were developed using four modeling algorithms. An ensemble prediction was made based on the mean occurrence probability derived from the individual models. The final model suggested that this species could potentially establish itself in tropical coastal regions. While the climatic suitability in South Korea was generally found to be low, a careful investigation is still warranted due to the potential risk of colonization and establishment of this species.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.1
• /
• pp.237-251
• /
• 2023

This study tried to understand the effect of internal resources, capabilities, and business model innovation of venture enterprises on industrial property performance, as based on previous studies that securing industrial property rights has a positive effect on the technology commercialization of venture companies. Venture company capabilities were classified into intrinsic elements of a company (company's research resources) and creative elements (commercialization capabilities) that implement them, and they were intended to show that they could lead to a company's potential competitiveness through innovation in business models. In order to verify this research purpose, an empirical analysis was conducted on 1,733 corporate companies among venture confirmation companies subject to the 2019 venture company precision survey. It was confirmed that the systematic research organization and commercialization capabilities of venture companies were significant (+) in industrial property performance. However, in the final research model that applied both the rules of the business model's innovation variable, commercialization capability and business model innovation were significant (-), and research organization × business model innovation showed significant results (+). This means that venture companies' excellent resources and capabilities can have a positive impact on industrial property performance individually, but when applying the level of innovation in the actual business model, they must interact with the business model. The results of this study are meaningful in that it is necessary to pursue business model innovation that secures clear differentiators compared to competitors as well as strengthening the company's internal resources and capabilities to secure industrial assets and innovation growth.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.1
• /
• pp.45-61
• /
• 2022

Despite of the consensus on the critical role of CEO and slack resources for strategic decision making, how they affect in the selection of strategic alliance type is limited. This study investigated the effect of CEO's experiential attributes and the venture firms' slack resource on the selection of strategic alliance type. To this end, this study used multi-variate logistic regression analysis with 1,813 Korean venture firms. The findings indicated that higher education level and large firm experience of CEO positively contributed to form an explorative alliance. And these two experiential attributes has negative effects on the probability of exploitative alliance formation. On the other hand, the entrepreneurial experience has no effect on the selection of strategic alliance type. This study also investigated the effect of slack resource - available slack, recoverable slack, and potential slack-. The more venture firms have available and potential slack, the higher probability of pursuing an explorative alliance. In addition, recoverable slack of venture firms has negative effect only on the selection of explorative alliance. The results of this study are expected to contribute the literatures of strategic management and venture firms by illustrating which CEO and firm-level factors affect the selection of strategic alliance type. This study also extends recent effort to better understand the selection of strategic alliance type with upper echelons theory and slack resource. And this study suggests implications that can increase the probability of successful decision making by venture firms in selection of strategic alliance type.