• Title/Summary/Keyword: Dummy variables

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An Empirical Study on the "Effects of My Mom's Friend's Son" in the Job Search Process of Youths (청년층 직업탐색에서의 '엄친아효과'에 대한 실증연구)

  • Bai, Jin Han
    • KDI Journal of Economic Policy
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    • v.36 no.3
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    • pp.121-168
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    • 2014
  • After analyzing and finding the explaining factors about the "Effect of My Mom's Friend's Son (MMFS Effect)" with online-surveyed data, we introduce this concept into the conventional job search theory to develop it further. We try to estimate its effects on the hazard rate of youth pre-employment duration with some proxy variables such as his/her parents' schooling, living with parents dummy, increasing rate of consumer price index representing the burdens of parents, monthly temporary/daily workers ratio, relative ratio of quarterly 90th percentile urban household income, monthly average wage differentials between the workers of large and small firms, etc. The results confirm us the fact that so called "MMFS Effect" has been effective enough and strengthened up to recently. The conventional job search theory should be extended to be able to introduce the influencing effects of other person's success, for instance MMFS's success, on the job search behavior of youths, too.

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Development and Application of a Big Data Platform for Education Longitudinal Study Analysis (교육종단연구 분석을 위한 빅데이터 플랫폼 개발 및 적용)

  • Park, Jung;Cho, Wan-Sup
    • The Journal of Bigdata
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    • v.5 no.1
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    • pp.11-27
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    • 2020
  • In this paper, we developed a big data platform to store, process, and analyze effectively on such education longitudinal study data. And it was applied to the Seoul Education Longitudinal Study(SELS) to confirm its usefulness. The developed platform consists of data preprocessing unit and data analysis unit. The data preprocessing unit 1) masking, 2) converts each item into a factor 3) normalizes / creates dummy variables 4) data derivation, and 5) data warehousing. The data analysis unit consists of OLAP and data mining(DM). In the multidimensional analysis, OLAP is performed after selecting a measure and designing a schema. The DM process involves variable selection, research model selection, data modification, parameter tuning, model training, model evaluation, and interpretation of the results. The data warehouse created through the preprocessing process on this platform can be shared by various researchers, and the continuous accumulation of data sets makes further analysis easier for subsequent researchers. In addition, policy-makers can access the SELS data warehouse directly and analyze it online through multi-dimensional analysis, enabling scientific decision making. To prove the usefulness of the developed platform, SELS data was built on the platform and OLAP and DM were performed by selecting the mathematics academic achievement as a measure, and various factors affecting the measurements were analyzed using DM techniques. This enabled us to quickly and effectively derive implications for data-based education policies.

Factors Affecting Job-Seeking Stress in Nursing Students (간호대학생의 취업 스트레스에 영향을 미치는 요인)

  • Choe, Myeong Hui;Kim, Joo Hyun;Nam, Eun Sook;Lee, Yong Mi;Hwang, Ju Hee;Lee, Mi Kyung;Yoon, Sung Ja;Park, Hyunju
    • Korean Journal of Occupational Health Nursing
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    • v.24 no.2
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    • pp.122-131
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    • 2015
  • Purpose: The purpose of this study was to investigate what factors are affecting job-seeking stress in nursing students. Methods: Subjects were 463 students from two 3-year and two 4-year colleges of nursing in K-Province in Korea. Data was collected from self-administered questionnaires. t-test, ANOVA, Pearson's and Spearman's correlation coefficients, and hierarchical multiple regression with dummy variables were used for statistical analysis of data. Results: Job-seeking stress was significantly different by school system (t=2.76, p=.006), family economic status (F=3.40, p=.005), characteristics (t=1.99, p=.047), academic achievement (F=6.54, p=.002), current weight control status (t=2.23, p=.026), times of cosmetic surgery (r=.11, p=.022), self-esteem (r=-.47, p<.001) and appearance stress (r=.40, p<.001). However, after controlling for general characteristics, self-esteem, and perceived appearance stress, job-seeking stress was significantly different by grade (1st vs 3rd, ${\beta}=0.163$, p<.001), academic achievement (low vs. high, ${\beta}=-0.121$, p=.0321), self-esteem (${\beta}=-0.224$, p<.001), and appearance stress (${\beta}=0.099$, p<.001). The explanation power of self-esteem on job-seeking stress was greater compared with that of appearance stress. Conclusion: Results of this study suggest that it is necessary for nursing students to develop intervention program aimed at reducing job-seeking stress, and it would be effective to focus on improving self-esteem for them.

A Study on the Determinants of Fans' Team Identification in KBO League : Focused on the Effects of Kids Marketing (프로야구 팬의 팀 동일시에 영향을 미치는 요인에 관한 연구: 응원시작 연령의 효과를 중심으로)

  • Choi, Seung-Nyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.1
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    • pp.99-110
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    • 2016
  • This study examined the factors affecting the team identification of professional baseball fans. The factors were divided into the fan factor, game factors, and other factors. For the analysis, two investigators visited stadium three times in total and a total number of 297 spectators were sampled using a convenience sampling method from three baseball teams. For the fan factor, a fan who began supporting his/her team from childhood or after childhood was used as a dummy variable. The interaction effects between the fan factor and other variables were investigated to offer a stereoscopic understanding about the role of kids marketing. In addition, three game factors and four non-game factors were analyzed. The results regarding fan variable and interaction effects were obtained. Fans from their childhood have much stronger team identification, and show interaction effects with the players. Regression analysis revealed player, promotion and fan service, price, and regional connection to have positive relations with team identification. This study is especially meaningful in a sense that it has proposed positive results regarding marketing to children, and the results will contribute to both the academic field and the industry.

The Earnings Quality and Firm Characteristics - KOSDAQ (기업특성에 따른 회계이익의 질 - 코스닥기업 대상)

  • Moon, Hyun-Ju
    • Korean small business review
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    • v.42 no.4
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    • pp.123-146
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    • 2020
  • This study, targeting KOSDAQ-listed companies, examined the relationship between variability of accruals and corporate characteristics. First, the analysis results show that executives of companies with high debt ratios are more likely to violate debt contracts, so there is a strong temptation to use discretionary accrual items. Second, for companies with large volatility in operating cash flows, Executives of these companies are strongly inclined to utilize accruals for the purpose of abuse of discretion. Third, the larger the company, the more sensitive it is to political costs, so it is less tempted to use the accruals item than a smaller company. Fourth, the corporate age is thought to be the maturity of the company, Executives of such companies have little room to use accruals to abuse their discretion. Fifth, in the case of profit dummy variables, the companies reporting losses have more temporary accrual items than those reporting profits, so this increases the uncertainty in their accounting information than the latter. Sixth, for those companies that are indicated as inappropriate as a result of audit, the more likely their executives are to use the accrual items, and the lower the quality of their accounting profits is. Lastly, Companies audited by 4 Big domestic accounting firms have less discretionary accrual fluctuations than companies audited by non-big 4 accounting firms. Thus, it was found that the accrual amount allows the discretion of corporate executives differently according to the characteristics of the company.

Product Recommender Systems using Multi-Model Ensemble Techniques (다중모형조합기법을 이용한 상품추천시스템)

  • Lee, Yeonjeong;Kim, Kyoung-Jae
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.39-54
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    • 2013
  • Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

Corporate Governance and Managerial Performance in Public Enterprises: Focusing on CEOs and Internal Auditors (공기업의 지배구조와 경영성과: CEO와 내부감사인을 중심으로)

  • Yu, Seung-Won
    • KDI Journal of Economic Policy
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    • v.31 no.1
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    • pp.71-103
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    • 2009
  • Considering the expenditure size of public institutions centering on public enterprises, about 28% of Korea's GDP in 2007, public institutions have significant influence on the Korean economy. However, still in the new government, there are voices of criticism about the need of constant reform on public enterprises due to their irresponsible management impeding national competitiveness. Especially, political controversy over appointment of executives such as CEOs of public enterprises has caused the distrust of the people. As one of various reform measures for public enterprises, this study analyzes the effect of internal governance structure of public enterprises on their managerial performance, since, regardless of privatization of public enterprises, improving the governance structure of public enterprises is a matter of great importance. There are only a few prior researches focusing on the governance structure and managerial performance of public enterprises compared to those of private enterprises. Most of prior researches studied the relationship between parachuting employment of CEO and managerial performance, and concluded that parachuting produces negative effect on managerial performance. However, different from the results of such researches, recent studies suggest that there is no relationship between employment type of CEOs and managerial performance in public enterprises. This study is distinguished from prior researches in view of following. First, prior researches focused on the relationship between employment type of public enterprises' CEOs and managerial performance. However, in addition to this, this study analyzes the relationship of internal auditors and managerial performance. Second, unlike prior researches studying the relationship between employment type of public corporations' CEOs and managerial performance with an emphasis on parachuting employment, this study researches impact of employment type as well as expertise of CEOs and internal auditors on managerial performance. Third, prior researchers mainly used non-financial indicators from various samples. However, this study eliminated subjectivity of researchers by analyzing public enterprises designated by the government and their financial statements, which were externally audited and inspected. In this study, regression analysis is applied in analyzing the relationship of independence and expertise of public enterprises' CEOs and internal auditors and managerial performance in the same year. Financial information from 2003 to 2007 of 24 public enterprises, which are designated by the government, and their personnel information from the board of directors are used as samples. Independence of CEOs is identified by dividing CEOs into persons from the same public enterprise and persons from other organization, and independence of internal auditors is determined by classifying them into two groups, people from academic field, economic world, and civic groups, and people from political community, government ministries, and military. Also, expertise of CEOs and internal auditors is divided into business expertise and financial expertise. As control variables, this study applied foundation year, asset size, government subsidies as a proportion to corporate earnings, and dummy variables by year. Analysis showed that there is significantly positive relationship between independence and financial expertise of internal auditors and managerial performance. In addition, although business expertise and financial expertise of CEOs were not statistically significant, they have positive relationship with managerial performance. However, unlike a general idea, independence of CEOs is not statistically significant, but it is negatively related to managerial performance. Contrary to general concerns, it seems that the impact of independence of public enterprises' CEOs on managerial performance has slightly decreased. Instead, it explains that expertise of public enterprises' CEOs and internal auditors plays more important role in managerial performance rather than their independence. Meanwhile, there are limitations in this study as follows. First, in contrast to private enterprises, public enterprises simultaneously pursue publicness and entrepreneurship. However, this study focuses on entrepreneurship, excluding considerations on publicness of public enterprises. Second, public enterprises in this study are limited to those in the central government. Accordingly, it should be carefully considered when the result of this study is applied to public enterprises in local governments. Finally, this study excludes factors related to transparency and democracy issues which are raised in appointment process of executives of public enterprises, as it may cause the issue of subjectivity of researchers.

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Analysis on Factors Influencing Welfare Spending of Local Authority : Implementing the Detailed Data Extracted from the Social Security Information System (지방자치단체 자체 복지사업 지출 영향요인 분석 : 사회보장정보시스템을 통한 접근)

  • Kim, Kyoung-June;Ham, Young-Jin;Lee, Ki-Dong
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.141-156
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    • 2013
  • Researchers in welfare services of local government in Korea have rather been on isolated issues as disables, childcare, aging phenomenon, etc. (Kang, 2004; Jung et al., 2009). Lately, local officials, yet, realize that they need more comprehensive welfare services for all residents, not just for above-mentioned focused groups. Still cases dealt with focused group approach have been a main research stream due to various reason(Jung et al., 2009; Lee, 2009; Jang, 2011). Social Security Information System is an information system that comprehensively manages 292 welfare benefits provided by 17 ministries and 40 thousand welfare services provided by 230 local authorities in Korea. The purpose of the system is to improve efficiency of social welfare delivery process. The study of local government expenditure has been on the rise over the last few decades after the restarting the local autonomy, but these studies have limitations on data collection. Measurement of a local government's welfare efforts(spending) has been primarily on expenditures or budget for an individual, set aside for welfare. This practice of using monetary value for an individual as a "proxy value" for welfare effort(spending) is based on the assumption that expenditure is directly linked to welfare efforts(Lee et al., 2007). This expenditure/budget approach commonly uses total welfare amount or percentage figure as dependent variables (Wildavsky, 1985; Lee et al., 2007; Kang, 2000). However, current practice of using actual amount being used or percentage figure as a dependent variable may have some limitation; since budget or expenditure is greatly influenced by the total budget of a local government, relying on such monetary value may create inflate or deflate the true "welfare effort" (Jang, 2012). In addition, government budget usually contain a large amount of administrative cost, i.e., salary, for local officials, which is highly unrelated to the actual welfare expenditure (Jang, 2011). This paper used local government welfare service data from the detailed data sets linked to the Social Security Information System. The purpose of this paper is to analyze the factors that affect social welfare spending of 230 local authorities in 2012. The paper applied multiple regression based model to analyze the pooled financial data from the system. Based on the regression analysis, the following factors affecting self-funded welfare spending were identified. In our research model, we use the welfare budget/total budget(%) of a local government as a true measurement for a local government's welfare effort(spending). Doing so, we exclude central government subsidies or support being used for local welfare service. It is because central government welfare support does not truly reflect the welfare efforts(spending) of a local. The dependent variable of this paper is the volume of the welfare spending and the independent variables of the model are comprised of three categories, in terms of socio-demographic perspectives, the local economy and the financial capacity of local government. This paper categorized local authorities into 3 groups, districts, and cities and suburb areas. The model used a dummy variable as the control variable (local political factor). This paper demonstrated that the volume of the welfare spending for the welfare services is commonly influenced by the ratio of welfare budget to total local budget, the population of infants, self-reliance ratio and the level of unemployment factor. Interestingly, the influential factors are different by the size of local government. Analysis of determinants of local government self-welfare spending, we found a significant effect of local Gov. Finance characteristic in degree of the local government's financial independence, financial independence rate, rate of social welfare budget, and regional economic in opening-to-application ratio, and sociology of population in rate of infants. The result means that local authorities should have differentiated welfare strategies according to their conditions and circumstances. There is a meaning that this paper has successfully proven the significant factors influencing welfare spending of local government in Korea.

Agency Costs of Clothing Companies with Famous Brand (유명 의류 상호 기업의 대리인 비용에 관한 연구)

  • Gong, Kyung-Tae
    • Management & Information Systems Review
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    • v.36 no.4
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    • pp.21-32
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    • 2017
  • Motivated by the recent cases of negligent social responsibility as manifested by foreign luxury fashion brands in Korea, this study investigates whether agency costs depend on the sustainability of different types of corporate governance. Agency costs refer either to vertical costs arising from the relationship between stockholders and managers, or to horizontal costs associated with the potential conflicts between majority and minority stockholders. The firms with luxury fashion brand could spend large sums of money on maintenance of magnificent brand image, thereby increasing the agency cost. On the contrary, the firms may hold down wasteful spending to report a gaudily financial achievement. This results in mitigation of the agency cost. Agency costs are measured by the value of the principal component. First, three ratios are constructed: asset turnover, operating expense to sales, and earnings before interest, tax, and depreciation. Then, the scores of each of these ratios for individual firms in the sample are differenced from the ratios for the benchmark firm of S-OIL. S-OIL was designated as the best superior governance model firm for 2013 by CGS. We perform regression analysis of each agency cost index, luxury fashion brand dummy and a set of control variables. The regression results indicate that the agency costs of the firms with luxury fashion brand exceed those of control group in the fashion industry in the part of operating expenses, but the agency cost falls short of those of control group in the part of EBITD, thus the aggregate agency costs are not differential of those of the control group. In sensitivity test, the results are same that the agency cost of the firms are higher than those of the matching control group with PSM(propensity matching method). These results are corroborated by an additional analysis comparing the group of the companies with the best brands with the control group. The results raise doubts about the effectiveness of management of the firms with luxury fashion brand. This study has a limitation that the research has performed only for 2013 and this paper suggests that there is room for improvement in the current research methodology.

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A Study on the Age Distribution Factors of One Person Household in Seoul using Multiple Regression Analysis (다중회귀분석을 이용한 서울시 1인 가구의 연령별 분포요인에 관한 연구)

  • Lee, SunHee;Yoon, DongHyeun;Koh, JuneHwan
    • Spatial Information Research
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    • v.23 no.3
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    • pp.11-21
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    • 2015
  • While the number of total population in Seoul has been on the constant decline for the last few years, the number of household has increased due to the rising tendency of the smaller households. In 2010, the small households in the metropolitan areas accounted for 44% of the entire households, and Statistics Korea has reported that one person household, which will take up more than 30% of the whole household, will have been the most common type of household by 2020. This reason of rise will be differently shown according to age like the preferred housing type or surrounding environments, this research is suggest to research hypothesis that distinction of age leads to the spatial distribution of one person household. Therefore, this research is to exercise a multiple regression analysis targeting on the facilities, which become the spatial distribution factor of one person household, with the independent variable gained from the concluded area calculated with the area ratio of the spatial unit followed by the service area analysis based on network. The spatial unit is the census output of Seoul, and based on this the interaction between the number of one person household according to age and the factors of its distribution. Also, the spatial regions - downtown, northeast, southeast, northwest, southwest - are designed as dummy variables and the results of each region are found out. As a result, the spatial regions occupied according to age are found to be varied - people in their 20s prefer housings near the college, 30s lease or the monthly rental housings, 40s the monthly rental housings, and over 60s the housing with the floor area of less than $40m^2$. Likewise, one person household has different types of housing environments preferred according to age, and thus a housing policy concerning this will have to be suggested.