• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.9
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• pp.979-990
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• 2012

This study explores the correlation between personality traits, customer orientation, job satisfaction, and job performance. This study examines the impacts of personality traits and customer orientation on job satisfaction and job performance. Data were collected using a questionnaire survey. A convenience sample was drawn from salespeople working for department stores in Daegu and Pohang between September $1^{st}$ to $7^{th}$ 2011. A total of 337 responses were complete and usable questionnaires. Data were tested through factor analysis, correlation analysis, and regression analysis, using SPSS 12.0. Three main points are shown through this study. First, the correlation of all five factors extracted from salespeople personality traits with customer orientation was statistically significant. Personality traits and customer orientation were partially correlated with job satisfaction or job performance. Second, the regression analysis was conducted to examine the influence of personality traits and customer orientation on job satisfaction; subsequently, only two factors extracted from customer orientation (consideration for customers and customer-centered thinking) were significant predictors of job satisfaction. Third, the result of the regression analysis between personality traits and job performance showed that the most influential predictor of job performance was conscientiousness, followed by likeability, openness and introversion. The most influential factor between customer orientation and job performance was competence in providing product information, followed by consideration for customers, customer-centered thinking, and a reliability-focused response.

• Health Policy and Management
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• v.17 no.2
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• pp.68-90
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• 2007

Nurse staffing level is an important factor that influences the quality of health service and patient outcomes. This study was carried out to examine the current state of acute hospital nurse staffing and find out factors that affect the nurse staffing level. Nurse staffing of individual hospitals was measured using the number of registered nurses per 100 beds. Descriptive and multiple regression analyses were conducted using 592 acute care hospitals' data. Regression model included structure factors such as referral level, ownership, medical and general staffing, and financial outcome factors such as occupancy rate, inpatient and outpatient revenues. Market characteristics included strength of competition, supply of nurses, and income and health status level of consumers. The average number of nurses per 100 beds was 28 and showed a great variation according to the referral level. Regression model explained this variation as much as 76.87%. Hospital structure variables which affecting the hospital nurse staffing level positively were ICU bed ratio, the staffing level of specialist, training doctor and employees except doctor and nursing personnel, while the negative factor was nurse aid staffing level. General hospitals employed more nurses than hospitals. Among outcome characteristics, occupancy rate and the amount of health insurance inpatient revenue affected positively on the hospital nurse staffing level. The more supply of the new nurse and the higher consumer income and health status in the medical service markets, the more nurses were employed by the medical institutes. According to the study result, hospitals employed more nurses when they had more financial incentive by increasing nurses. This means appropriate hospital incentive policy and regulation policy, which hospital violate nurse staffing level have to pay penality, should be needed. Clarifying job description between nurses and nurse aids and the reentry program for unemployed experienced nurses will be helpful to increase nurse staffing level.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.237-247
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• 2018

The basin characteristics reflect the attributes of geomorphological pattern of basin and stream networks affect the rainfall-runoff. In order to analyze the relationship between the basin runoff and stream morphometric characteristics, the morphometric characteristics were investigated for 27 water-level observation stations on 19 rivers in the Han River basin using Arc-map. The morphometric characteristics were divided into linear, areal and relief aspects for calculation while the annual mean runoff ratio as a basin response by rainfall was estimated using the measured precipitation and discharge to analyze the rainfall-runoff characteristics. The correlation among the morphometric parameters were schematized to analyze the correlations among them. The multiple regression equation for rainfall-runoff ratio was provided with morphometric parameters of stream length ratio, form factor ratio, shape factor, stream area ratio, and relief ratio and the coefficient of determination was 0.691. The RMSE and MAPE between the measured and the estimated annual runoff rates were found as 0.09, 11.61% respectively, the suggested regression equation showed good estimation.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.70-78
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• 2007

The performance of face recognition is greatly affected by the illumination effect because intra-person variation under different lighting conditions can be much bigger than the inter-person variation. In this paper, we propose an illumination robust face recognition by separating identity factor and illumination factor using the symmetric bilinear models. The translation procedure in the bilinear model requires a repetitive computation of matrix inverse operation to reach the identity and illumination factors. Sometimes, this computation may result in a nonconvergent case when the observation has an noisy information. To alleviate this situation, we suggest a ridge regressive bilinear model that combines the ridge regression into the bilinear model. This combination provides some advantages: it makes the bilinear model more stable by shrinking the range of identity and illumination factors appropriately, and it improves the recognition performance by reducing the insignificant factors effectively. Experiment results show that the ridge regressive bilinear model outperforms significantly other existing methods such as the eigenface, quotient image, and the bilinear model in terms of the recognition rate under a variety of illuminations.

• Journal of the Korea Safety Management & Science
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• v.8 no.5
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• pp.193-209
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• 2006

Multiple regression is used to examine the relationship between a set of two or more independent variables and one dependent variable. It provides the information necessary to make predictions of the dependent variables based on several independent variables. To do so, the multiple regression equation is extended to: y=$a+{\beta}_1x_1+{\beta}_2x_2+{\ldots}+{\beta}_kx_k$ y=attractiveness a=the value of the intercept ${\beta}_1$=the slope(weighting) of the first variable ${\beta}_1$= the slope(weighting) of the second variable ${\beta}_k$=the slope of the $\kappa$th variable The resulting regression equation of this research is y=$a+{\beta}_1site's\;system+{\beta}_2customer\;satisfaction+{\beta}_3products+{\beta}_4delivery$ y=3.233+0.374(site's system)+0.268(customer satisfaction)+0.17(products)+0.077(delivery)

• Korean Journal of Community Nutrition
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• v.1 no.3
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• pp.366-375
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• 1996

The effect of carbohydrates, fat and protein consumption on the blood pressure of adolescents was investigated from the cross sectional data. The two major areas of inquiry were : 1)measuring the variation of blood pressure at various levels of macronutient intake. 2)measuring the relative importance between the factor of nutrient intake and physical growth. A total of 726 students(341 boys and 385 girls) in the first grade of middle school in Kangwha country were studied for their dietary consumption and physical growth as well as blood pressure. Multiple regression analysis was used as the analytical method to identify the relative importance between the factors. Besides the macronutrient consumption, other nutrients such as vitamin and mineral intakes were included in the regression model. The results showed a variation of blood pressure by macronutrient intake level was in consistant both in blood pressure and by gender. Systolic and diastolic blood pressure decreased with increasing protein intake for girls(p<0.05). However, it was not observed in the case of boys. The systolic blood pressure of boys showed a tendency to decrease with fat intake increase, while their diastolic blood pressure showed the opposite trend. Results of the regression analysis showed that physical growth was a more influential factor than nutrition on blood pressure for both sexes. This could imply that the dietary hypertension factors observed in adults may not be operative generally in a population with normotensive blood pressure during growth.

• Korean Journal of Hospice Care
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• v.6 no.2
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• pp.69-78
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• 2006

Purpose: This study was conducted to analysis relationship about quality of life and family burden of the home-based hospice patient families. Method: The subjects consisted of 94 families with home-based hospice patient. The ages of the subjects were 17-73 years with hospice patient who receivedhome visiting care and registered at 4 hospitals in Daegu and Kyung-Buk. The data was collected from March to November 2004. The instruments used for the study were Quality of Life Scale (GLS) and Family Burden Questionnaire (FBQ). The analysis was done using frequency, mean, standard deviation, correlation and stepwise multiple regression with SPSS WIN 11.0. Results: The results were as follows: 1. The mean score of family burden was 3.36 ($\pm0.55$). The highest mean score of family burden 6 factors were wellness of future 3.85($\pm1.10$), and the second was economic family burden 3.63($\pm0.97$). 2. The mean score of quality of life was 3.09 ($\pm0.48$). The lowest score of quality of life 6 factors were economic status 2.86($\pm0.54$), and the second was physical state and function 3.01($\pm0.62$). 3. In the home-based hospice patient families, family burden had significant negative correlation with quality of life(r=-0.25, p=0.012). 4. Emotional status accounted for 11% of family burden in the home-based hospice patient families by means of stepwise multiple regression. 5. Economical status accounted for 18 and age accounted for an additional 11% of quality of life in the home-based hospice patient families by means of stepwise multiple regression. Conclusion: The finding showed that family burden and quality of life of home-based hospice patient families were significantly negative correlation and the highest factor of family burden was wellness of future and the most important factor of quality of life was economic status.

• Journal of Korea Trade
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• v.23 no.5
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• pp.27-44
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• 2019

Purpose - The purpose of this paper is to analyze the net effect of the green total factor productivity (GTFP) of China's manufacturing industry from the China-Korea Free Trade Area (China-Korea FTA) quantitatively. Design/methodology - Firstly, the Global Malmquist-Luenberger (GML) index based on the SBM directional distance function is used to measure the GTFP of China's manufacturing and analyze the driving force for its growth. Secondly, the regression discontinuity quantitative analysis is used to determine the impact of the China-Korea FTA on China's manufacturing GTFP. Findings - Our main findings can be summarized as follows: the China-Korea FTA has promoted the GTFP of China's manufacturing with an effect evaluation mainly resulting from green technology progress. And there is industry heterogeneity in the policy effect on the manufacturing GTFP due to the China-Korea FTA. Namely, policy promotion from the China-Korea FTA is more effective on the GTFP of equipment manufacturing than it is on those of other industries. Originality/value - First, an evaluation and analysis of the GTFP development of China's manufacturing that employs GML index based on SBM directional distance function. Second, a quantitative estimate of China-Korea FTA's net effect on China's manufacturing industrial GTFP that uses regression discontinuity analysis, which is considered to be the closest method to natural experiments and superior to other causal inference methods. Third, an in-depth discussion of the practical steps that China's manufacturing can take to improve GTFP development and integrate China-Korea FTA construction into economic development.

• 재활복지
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• v.18 no.4
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• pp.95-117
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• 2014

This study aims to examine the effects of personal assistance services(physical activity support, homemaking activity support, social activity support) on caregiver burden and determine whether family resilience(family belief system, family cohesion, interaction) has a moderating effect between personal assistance services and caregiver burden, thereby presenting a reference data which can be used to seek a practical measure for handicapped welfare. This study was conducted on 200 primary caregivers with disabled family members of rank 1 or 2 in east, west, south, and north Gyeonggi-do using personal assistance services. Data was collected in 2013 from April 1 to May 15, and was analyzed using the SPSS 19.0 statistics program in which a moderated multiple regression analysis based on exploratory factor analysis, confirmatory factor analysis, and hierarchical regression analysis was performed. The primary conclusions of this study were as follows; First, the use of physical activity support was showed to have a positive effect in reducing family burden related to disabled care. Second, personal assistance services exhibit significant moderator effects related to family burden in family belief systems and family cohesion.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.495-506
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• 2021

A Conceptual cost estimate, which is computed in the preliminary step of a project, is important for decision-making by a contractor in terms of the project budget, economic feasibility and validity analysis, and alternative comparisons. Therefore, a high error rate of a prediction model for a conceptual cost estimate can lead to various problems including excessive project expenditures and a delayed break-even point. this study proposed optimal impact factors by configuring quantitative impact factors computable in a preliminary step in various cases(combinations of impact factors). subsequently, the accuracy of different cases was comparatively analyzed by using the cases as input values of a prediction model using regression analysis. when the optimal combination of impact factors proposed in this study and other combination of impact factors were applied to the prediction model, the regression analysis-based prediction model exhibited 0.2-4.7% improvements in accuracy, respectively. the optimal combination of impact factors proposed in this study improved the accuracy of the prediction model of a conceptual cost estimate by removing unnecessary impact factor.