• 경영과학
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• 제32권3호
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• pp.71-89
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• 2015

This research empirically investigated the influence factors on the activation of environmental innovations (EI) in Korean manufacturing firms. In this study, external factors (compulsory demand, government regulation, normative pressure and imitative pressure) and internal factors (environmental resources, top management support, integration of environmental tasks, capabilities of environmental personnel, and environmental strategy/environmental management systems) were totally considered. The results of a multiple regression analysis showed that influence factors such as top management support, environmental resources and integration of environmental tasks have a significant and positive impact on levels of EI. However, the effects of external factors were not statistically significant. We also examined whether capabilities of environmental personnel as well as environmental resources, which are directly related with degrees of EI, have a moderating impact on relationships between other internal factors and levels of EI. With a subgroup analysis, the moderating role of abilities of environmental personnel were empirically confirmed. Through a multiple regression analysis, the direct effects of external factors on the adoption or construction of internal factors were demonstrated. The effects of government regulation, normative pressure and imitative pressure on internal factors were significant and positive. It was also found that external factors have indirect effects on EI through internal factors. Finally, the results of multiple regression analyses indicated that EI positively influences the achievement of environmental competitive benefits, and environmental competitive advantages can improve the organizational performance of a firm.

• Journal of Power Electronics
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• 제14권1호
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• pp.165-174
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• 2014

The cascaded H-Bridge Dynamic Voltage Restorer (DVR) is used for protecting high voltage and large capacity loads from voltage sags. The LC filter in the DVR is needed to eliminate switching ripples, which also provides an accurate tracking feature in a certain frequency range. Therefore, the parameter optimization of the LC filter is especially important. In this paper, the value range functions for the inductance and capacitance in LC filters are discussed. Then, parameter variations under different conditions of voltage sags and power factors are analyzed. In addition, an optimized design method is also proposed with the consideration of multiple impact factors. A detailed optimization procedure is presented, and its validity is demonstrated by simulation and experimental results. Both results show that the proposed method can improve the LC filter design for a cascaded H-Bridge DVR and enhance the performance of the whole system.

• 한국건축시공학회지
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• 제12권6호
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• pp.636-647
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• 2012

Construction projects have become so large, complicated and incredibly high-tech that process management is currently considered one of the most important issues. Unlike typical manufacturing industries, most major construction activities are performed in the open air and thus are exposed to various environmental factors. Many studies have been conducted with the goal of establishing efficient techniques and tools for overcoming these limitations. Productivity analysis and prediction, one of the related research subjects, must be considered when evaluating approaches to reducing construction duration and costs. The aim of this research is to present a quantified impact analysis of construction delay factors on construction productivity of a steel staircase system, which has been widely applied to high rise building construction. It is also expected to improve the process by managing the factors, ultimately achieving an improvement in construction productivity. To achieve the research objectives, this paper analyzed different delay factors affecting construction duration by means of multiple regression analysis focusing on steel staircase systems, which have critical effects on the preceding and subsequent processes in structure construction. Statistical analysis on the multiple linear regression model indicated that the environment, labor and material delay factors were statistically significant, with 0.293, 0.491, and 0.203 as the respective quantified impacts on productivity.

• 대한치과기공학회지
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• 제33권4호
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• pp.391-402
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• 2011

Purpose: The purpose of this study was to investigate the factors affecting oral health impact profile. Methods: Subjects included elderly in the metropolitan areas of the cities of Daegu and Gyeong-buk. Statistical analysis was done using the Statistical Package for Social Sciences version 19.0 for Windows. We determined frequencies and percentage, calculating means, and standard deviations, and determining statistical significance using T-tests, analysis of variance, multiple regression analysis. Results: The results of multiple regression analysis between the oral health impact profile and the related factors indicated that Occupation, Economic status are the major component oral health impact profile in general characteristics and the Impediment of oral health promotion behavior is the major component that contribute the oral health impact profile in oral health belief. Conclusion: The comprehensive and reliable research which measures oral health impact profile of elderly is necessary.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2011년도 추계학술대회
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• pp.683-694
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• 2011

This study analysed impact of service quality on customer satisfaction and loyalty in the take-out coffee shop. The switching barrier was also studied as a moderating effect. Particularly, this study focused on relationships between customer loyalty and switching barriers. A lot of previous studies interest only in customers satisfaction. This study also analysed relationships among service quality, customer satisfaction, switching barriers and brand loyalty. Eventually, service quality significantly affects customer satisfaction, moderating effects, brand loyalty and marketing performance. SERVQUAL model which was established by PZB (1988) was used as a service quality factors. The impact on customer satisfaction was analysed using multiple regression analysis. Simple regression analysis was used to find effects of customer satisfaction and customer loyalty. Additional factors of switching barriers was classified based on previous studies. Hierarchical multiple regression analysis was used to find factors of customer loyalty among switching barriers. In the result, we can find that the importance of tangibles, responsiveness in service quality factors and contract cost, search cost and continuous cost in moderating effects.

• 복식
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• 제51권3호
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• pp.51-58
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• 2001

The purpose of this study was to investigate the effects of store image preferences on clothing impulse purchasing of male college students. The sample included 290 male college students, and an instrument was developed based on the previous studies. The statistical analyses used for this study were factor analysis and multiple regression. The result of factor analysis showed that store image preferences consisted of five factors : promotion, display, service, product, brand preferences. Clothing impulse purchasing consisted of product-driven impulse purchasing, situation-driven impulse purchasing, emotion-driven impulse purchasing. Multiple regression revealed that there were significant effects of store image preferences on dimensions of clothing impulse purchasing. For example, promotion preference factor had a positive impact on product-driven impulse purchasing and situation-driven impulse purchasing, but had a negative impact on emotion-driven impulse purchasing. The relative importance of store image preference factors were different according to different dimensions of clothing impulse purchasing.

• 한국소음진동공학회논문집
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• 제20권2호
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• pp.172-178
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• 2010

The multiple regression analysis and path analysis in each dominant area of noise source are conducted to analyze the relationship between dependent variables like annoyance and independent ones such as noise and non-noise factors. The multiple regression analysis shows that impact of noise factors is the highest to annoyance in dominant areas of road traffic and railway noise. Meanwhile, impact of non-noise factors such as sensitivity and satisfaction of environment on annoyance is also high in these areas. The path analysis result for multivariate analysis between various independent and dependent variables is similar to that of the multiple regression analysis. However, noise factor is the greatest factor influent on annoyance in the dominant areas of the combined noise, and relationship between annoyance and sensitivity is the highest in combined area exposed to road traffic noise and railway noise.

• 한국기계가공학회지
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• 제7권4호
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• pp.115-120
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• 2008

The fatalities of pedestrian accounted for about 40.0% of all fatalities in Korea (2005 year). In pedestrian involved accident, the most important data to inspect accident is throw distance of pedestrian. The throw distance of pedestrian can be influenced by many variables, such as vehicular frontal shape, vehicular impact speed, the offset of impact point, the height of pedestrian, and road condition. The trajectory of pedestrian after collision can be influenced by vehicular frontal shape classified into sedan type, box type, SUV type and van type. Many studies have been done about pedestrian accident with passenger car model and bus model for simple factors. But the study of pedestrian accident by van type vehicle was much insufficient, and even that the influence of multiple factors such as the offset of impact point was neglected. In this paper, a series of pedestrian kinetic simulation were conducted to inspect relationship between throw distance and multiple factors with using PC-CRASH s/w, a kinetic analysis program for a traffic accident for van type. By based on the simulation results, multi-variate regression was conducted, and regression equation was presented.

• Structural Engineering and Mechanics
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• 제11권3호
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• pp.259-272
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• 2001

The impact behavior of a multigirder concrete bridge under single and multiple moving vehicles is studied based on correlated road surface characteristics. The bridge structure is modeled as grillage beam system. A 3D nonlinear vehicle model with eleven degrees of freedom is utilized according to the HS20-44 truck design loading in the American Association of State Highway and Transportation Officials (AASHTO) specifications. A triangle correlation model is introduced to generate four classes of longitudinal road surface roughness as multi-correlated random processes along deck transverse direction. On the basis of a correlation length of approximately half the bridge width, the upper limits of impact factors obtained under confidence level of 95 percent and side-by-side three-truck loading provide probability-based evidence for the evaluation of AASHTO specifications. The analytical results indicate that a better transverse correlation among road surface roughness generally leads to slightly higher impact factors. Suggestions are made for the routine maintenance of this type of highway bridges.

• 환경영향평가
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• 제20권4호
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• pp.455-464
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• 2011

The purpose of this study is to clarify correlations between soil environments and the growth of trees in forests and thereon analyze effects of seasonal changes in such environments on such growth. To determine seasonal factors of soil affecting the Tree Vitality of Pinus thunbergii, first of all, the study designated the Tree Vitality as a dependent variable and soil hardness, moisture, pH, K, Na, Mg and Ca as independent variables. Then the study performed Pearson's coefficient analysis. To clarify what soil factors influence the seasonal growth of Pinus thunbergii multiple regression analysis is carried out, and findings are as follow; the growth of Pinus thunbergii was basically influenced by pH, followed by soil hardness in spring, K, followed by moisture in summer, and by soil hardness in winter. However, no soil factors affected the vitality at the significance level of 5% for t.