• Korea Trade Review
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• v.46 no.2
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• pp.281-299
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• 2021

This paper analyzes the feasibility of using machine learning methods to forecast the employment. The machine learning methods, such as decision tree, artificial neural network, and ensemble models such as random forest and gradient boosting regression tree were used to forecast the employment in Busan regional economy. The following were the main findings of the comparison of their predictive abilities. First, the forecasting power of machine learning methods can predict the employment well. Second, the forecasting values for the employment by decision tree models appeared somewhat differently according to the depth of decision trees. Third, the predictive power of artificial neural network model, however, does not show the high predictive power. Fourth, the ensemble models such as random forest and gradient boosting regression tree model show the higher predictive power. Thus, since the machine learning method can accurately predict the employment, we need to improve the accuracy of forecasting employment with the use of machine learning methods.

• Fashion & Textile Research Journal
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• v.25 no.5
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• pp.634-642
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• 2023

This study aimed to investigate the influence of career barriers on employment decisions among high school students specializing in beauty-related field. The subjects of this study were 339 students attending beauty-specialized high schools in Gwangju Metropolitan City and Jeollabuk-do, and a self-written questionnaire was employed for conducting the research. This survey was conducted from April 4 to April 18, 2022. A total of 380 questionnaires were distributed, and 350 responses were collected. Of these, 339 questionnaires were considered for the final analysis, as the remaining 11 had incomplete or insincere responses. The results of this study are summarized as follows. First, the career barriers affecting high school students in beauty-specialized schools were categorized into eight factors: lack of interest, economic difficulties, financial support, interpersonal challenges, job information, anxiety about future, conflict with others, and lack of self-clarity. Second, when assessing the impact of career barriers on employment decision-making, it was observed that the level of employment decision-making had a statistically positive (+) effect, and the lack of interest had a negative (-) effect on the level of employment decision-making. Next, the significance of the regression model, considering the specific factors of career barriers in relation to employment confidence, was established as p<.001. Variables such as a lack of interest, limited access to job information, and lack of self-clarity had a negative (-) effect on the level of employment confidence, with a significance level of 0.05.

• Fashion & Textile Research Journal
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• v.24 no.3
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• pp.325-332
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• 2022

The purpose of this study is to provide basic data for career guidance to cosmetology students by examining the effects of job stress on career decisions and job preparation behaviors. Overall 214 parts were empirically analyzed as final samples. Collected data and statistical processing are based on SPSS ver. Analysis was performed using the 21.0 program. An analysis of the effect of job stress on career decision showed that employment anxiety (β= .206, p<.05), job anxiety(β=.824, p<.05), and anxiety in career search(β=.118, p<.05) showed a statistically significant effect(+). However, employment concerns(β=-.312, p<.001) in career determination and employment concerns(β=-.223, p<.01) in career search are statistically significant parts(-). An analysis of the effect of employment stress on employment preparation behavior found that employment anxiety(β=.364, p<.05) has a statistically significant effect(+) on information use preparation, It was found that the statistically significant part(-) affects employment anxiety(β=-.188, p<.01). The study found that the more anxious cosmetology students are about employment, the more they plan and explore career options, and make information-based preparations for employment. Through this research, we hope that there will be lively discussions among cosmetology students on career adaptability, life satisfaction, and employment anxiety.

• Journal of Engineering Education Research
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• v.14 no.2
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• pp.60-67
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• 2011

This study is to analyze employment stress and career decision efficacy of undergraduates from engineering and social science department. Research object is 310 undergraduates(engineering department: 164 and social science department: 146) from three colleges in Seoul and Cheju. As a result of testing employment stress and career decision efficacy undergraduates had significant difference according to major and grade. Employment stress of undergraduates from engineering department was more serious than undergraduates from social science department. As a result of analyzing on the basis of grade employment stress of sophomores was more serious than freshmen. Career decision efficacy of undergraduates from social science department was higher than other group. Career decision efficacy of freshmen was higher than sophomore. Employment stress and career decision efficacy showed negative corelation in corelation analysis. This study implies that course educating program should be specialized according to major and grade. This study suggests that we should develop course educating curriculum connecting with major education.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.1-7
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• 2021

The number of new students at many domestic universities is declining. In particular, private universities, which are highly dependent on tuition, are experiencing a crisis of existence. Amid the declining school-age population, universities are striving to fill new students by improving the quality of education and increasing the student employment rate. Recently, there is an increasing number of cases of using the accumulated big data of universities to prepare measures to fill new students. A representative example of this is the analysis of factors that affect student employment. Existing employment-influencing factor analysis studies have applied quantitative models such as regression analysis to university big data. However, since the factors affecting employment differ by major, it is necessary to reflect this. In this paper, the factors affecting employment by major are analyzed using the data of University C and the decision tree model. In addition, based on the analysis results, a roadmap for student employment by major is recommended. As a result of the experiment, four decision tree models were constructed for each major, and factors affecting employment by major and roadmap were derived.

• Korea Trade Review
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• v.46 no.1
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• pp.169-187
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• 2021

This paper analyzes the feasibility of using machine learning and deep learning methods to forecast the income and employment using the strategic industries as well as investment, export, and exchange rates. The decision tree, artificial neural network, support vector machine, and deep learning models were used to forecast the income and employment in Busan. The following were the main findings of the comparison of their predictive abilities. First, the decision tree models predict the income and employment well. The forecasting values for the income and employment appeared somewhat differently according to the depth of decision trees and several conditions of strategic industries as well as investment, export, and exchange rates. Second, since the artificial neural network models show that the coefficients are somewhat low and RMSE are somewhat high, these models are not good forecasting the income and employment. Third, the support vector machine models show the high predictive power with the high coefficients of determination and low RMSE. Fourth, the deep neural network models show the higher predictive power with appropriate epochs and batch sizes. Thus, since the machine learning and deep learning models can predict the employment well, we need to adopt the machine learning and deep learning models to forecast the income and employment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7971-7977
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• 2015

This paper attempts to select the attributes of job creation and to rank them for evaluation of companies' job creation. And the results of this paper are expected to provide the information for the polices of job creation. In doing so, this paper applies fuzzy decision making analysis that reflects ambiguity and uncertainty in decision-making process. According to the results, the weight of quality of employment is similar with that of quantity of employment. In addition, annual employment growth rate, annual net employment are ranked as first and the percentage of irregular employment, the average length of employment of all workers, average monthly wages of all workers, and employment growth over sales growth rate are next ranked.

• Korean Journal of Social Welfare
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• v.58 no.1
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• pp.291-318
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• 2006

There were many studies conducted on economical aspects of employment among the elderly in national level, however, very few studies examined social and psychological aspects of senior employment and employment preferences of the elderly persons. The purposes of this study were to examine major determinants of decision making in employment, and to explore some relationships among decision making of employment, socio-economic factors, health and psycho-social factors, and labor and economical factors among non-working elderly persons in the community. In all, two-hundred-twenty elderly persons were interviewed and one-hundred-ninety-four were analyzed in this study. The descriptive statistics, analysis of variance, correlation analysis, and logistic regression were used for the data analysis in this study. The study found that the respondent's sex, ages, education, numbers of children, physical health, ADL, self-efficacy, economical stress, numbers of years in labor, asset of real estate, family allowances, and the benefit levels of pension were major determinants of decision making in employment among non-working elderly persons. Finally, some implications were discussed for developing effective senior employment in national policy, job related services, and welfare programs of the elderly persons for the successful aging.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.73-83
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• 2018

The purpose of this study was to investigate the effects of career decision self-efficacy and career maturity on employment stress in order to investigate the factors that can lower employment stress. For this purpose, the subject of 3rd and 4th grades 502 students in S university was analyzed by hierarchical regression analysis. The results of this study are as follows. First, gender and age were found to affect overall employment stress. Female students had higher employment stress than male students, and the older they were, the higher the employment stress. Second, career decision self-efficacy and career maturity had negative effects on employment stress. This study will be used as basic data for the career guidance of university authorities.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.817-828
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• 2013

This study was pre-experimental research designed to compare the differences between pre-and post-program on nursing student's career maturity, career decision-making self-efficacy and employment stress. The subjects were 247 junior-year students in nursing school. Mean value for career maturity was from 2.59 to 2.57, career decision-making self-efficacy from score 3.44 to 3.65 in average(t=8.67, p<.001), and employment stress from score 2.94 to 2.83 in average(t=-3.46, p<.001). Career maturity was significantly different according to high employment rate(F=3.15, p=.025), high career preparation(F=2.69, p=.032). Career decision-making self-efficacy and employment stress was significantly different according to high career preparation(F=1.22, p=.031) and low career preparation(F=2.52, p=.030).