• 한국조사연구학회지:조사연구
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• 제10권3호
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• pp.1-19
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• 2009

본 연구는 조사연구의 과정에서 활용 가능한 공간분석의 유용성을 지리정보시스템(GIS)과 공간적 이질성을 고려하는 지리적 가중 회귀분석(GWR)을 통해 탐색한다. 많은 사회현상은 공간적 차원을 포함하고 있으며, GIS, GPS 단말장치, 온라인 위치기반 서비스의 발달로 위치정보의 수집과 활용이 용이해짐에 따라 조사연구의 과정에서 공간정보를 활용하는 분석이 이전보다 훨씬 더 용이해지고 있다. 관찰의 독립성과 오차의 동분산성을 가정하는 전통적 회귀분석은 공간적 의존성을 분석하지 못한다. GWR 분석은 속성정보뿐만 아니라 공간정보를 활용하는 공간분석 기법으로서, 공간적으로 근접한 사례들은 유사성을 가진다는 가정에 따라 지리적 가중함수를 활용한다. A 기초자치단체 주민들을 대상으로 한 조사연구 자료를 공간정보와 결합시킨 후 간단한 행정만족도 모형을 추정해 본 결과, 지리적 가중 회귀분석은 전통적 회귀분석에 비해 공간적 자기상관의 문제를 극복하고 모형의 부합도를 증가시키는 것으로 나타났다. GWR 결과를 GIS와 결합시켜 독립변수 효과의 공간적 변이를 시각화시켜 봄으로써, 변수들의 효과와 관계를 더 자세하고 풍부하게 이해할 수 있다. 나아가서 이 기법은 특정 변수의 효과가 예외적으로 낮거나 높은 지역을 더 쉽게 밝혀냄으로써 정책방안을 모색하는 데에도 유용하게 활용될 수 있다.

• 보건행정학회지
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• 제26권4호
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• pp.271-278
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• 2016

Background: This study purposed to analyze the relationship between regional obesity rates and regional variables. Methods: Data was collected from the Korean Statistical Information Service (KOSIS) and Community Health Survey in 2012. The units of analysis were administrative districts such as city, county, and district. The dependent variable was the age-sex adjusted regional obesity rates. The independent variables were selected to represent four aspects of regions: health behaviour factor, psychological factor, socio-economic factor, and physical environment factor. Along with the traditional ordinary least square (OLS) regression analysis model, this study applied geographically weighted regression (GWR) analysis to calculate the regression coefficients for each region. Results: The OLS results showed that there were significant differences in regional obesity rates in high-risk drinking, walking, depression, and financial independence. The GWR results showed that the size of regression coefficients in independent variables was differed by regions. Conclusion: Our results can help in providing useful information for health policy makers. Regional characteristics should be considered when allocating health resources and developing health-related programs.

• 대한원격탐사학회지
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• 제33권6_2호
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• pp.1047-1060
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• 2017

현대사회에서 지속적으로 진행되고 있는 지구 온난화 현상은 비정상적인 기상 현상을 빈번히 발생시키고 있다. 특히 21세기에는 폭우와 같이 수문학적 측면에서 물의 특성이 전과 다르고, 수문학적 재해의 강도와 빈도가 증가하고 있다. 그 중 도시 지역에서는 재해로 인한 피해가 극대화될 가능성이 크기 때문에 피해를 대비하기 위한 재해에 대한 예측이 필요하다. 따라서 본 연구에서는 우리나라의 대표적인 도시 자연 재해인 산사태를 로지스틱 회귀(Logistic regression, LR) 모델을 이용하여 분석하고 현장조사를 통해 산사태 이후의 관리 현황을 조사 및 검증하였다. 현장조사 대상 지역은 기존에 산사태 발생지역 및 본 연구의 연구결과로부터 산사태 취약성이 높게 나타난 지역을 중심으로 수행하였다. 기존 산사태 발생지 데이터는 2011년 우면산 산사태 당시의 현장조사 자료 및 항공사진 비교분석을 통해 추출하였다. 산사태 관련 요인은 항공사진으로부터 제작된 지형도와 임상도에서 추출하였다. 산사태 취약성 지도는 산사태에 영향을 미치는 총 13개 요인을 통해 구성된 공간 데이터베이스에 LR 모델을 적용하여 제작되었다. 마지막으로 ROC(Receiver operating characteristic) 곡선을 이용해 산사태 취약성 지도를 검증한 결과 77.79%의 정확도를 나타냈다. 추가적으로, 연구결과에 나타난 산사태 취약지역에 대해 2011년 산사태 이후 산사태가 어떻게 관리되었는지를 확인하기 위해 현장조사를 수행하였다. 본 연구의 결과는 국내 도시 산사태 관리에 관한 정책 수립에 있어 과학적 근거로 활용할 수 있을 것으로 기대된다.

• 유통과학연구
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• 제18권3호
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• pp.53-65
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• 2020

Purpose: This study tests the suitability of a new technology acceptance model for a mobile payment system by checking how statistically significant the change is from the UTAUT (Unified Theory of Acceptance and Use of Technology) and UTAUT 2 models. Research, Data, and Methodology: We surveyed 250 students at Incheon University who are using the mobile payment system. The analysis was conducted on 243 valid questionnaires. The survey was conducted for one month in October 2018. The collected data were analyzed using SPSS and hierarchical regression analysis was applied. Results: Using hierarchical regression analysis, this study confirmed whether the newly added hedonic motivation, switching cost, and perceived risk variables in the UTAUT2 model are good explanatory variables. Mobile payment usage experience was found to have a moderating effect on mobile payment reuse intention. According to the analysis, the UTAUT2 model brought about more influential change than the variables of the UTAUT model. Conclusions: This study found that consumers' psychological factors added in the UTAUT2 model greatly influenced the reuse intention for mobile payment. As an implication of this study, mobile payment providers need to develop strategies that could meet hedonic motivation, switching cost and perceived risk for their customers.

• 농촌계획
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• 제12권4호
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• pp.23-32
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• 2006

Recently, Owing to booming of leisure activities and national enforcement of 5-day workweek system, Korean government has been promoting rural tourism policy of which operating project's title is Green Rural Experience Village, Rural Traditional Theme Village, etc. In this study, ken investigation result on Green Rural Experience Village sites, an estimation model of returns by green-tourism activities was developed. The model was constructed through factor analysis and regression analysis method. Regression model developed can estimate green-tourism revenue by investment budget, homepage preengagement sales, homepage visitors, capacity of eating and drinking facilities, capacity of lodging facilities. The model developed was applied in sample villages. With these results, estimation revenue was recorded average 138.3% of survey revenue, and statistical significance was good(correlation coefficient $R^2$ = 0.8255, level of significance : 0.000), and the range of relative error was recorded largely from -7.1% to 158.6%, and average relative error was 38.3% and good. And, the model developed in this study have the critical point in aspects of insufficient data, but the results will be used in green-tourism policies and projects, and revenue estimation about each village in the present and future is limited, but in province or the whole country the application is good.

• 대한설비관리학회지
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• 제23권4호
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• pp.65-75
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• 2018

Importance-Performance Analysis(IPA) holds the assumption that the degree of physical fulfilment of quality attributes and the satisfaction of that attribute is linear. Therefore, IPA can be applied to the traditional one-dimensional attributes, not to other quality elements such as attractive or must-be attributes. To overcome this problem, several articles introduced methods that integrate IPA into the concept of two-dimensional quality. However, these articles are rather conceptual focusing on the differentiation of quality attributes depend on quality elements in IPA. To provide empirical evidence of the dependent relationship between attribute importance and satisfaction in IPA, this study introduces a weighted importance approach and provides validation method using Bacon's priority model, a regression model. For this, the current research investigates 23 quality attributes of TV set for the results of Kano's model, which are adopted from Kim et al., and conducted a survey of 118 university students for the results of the importance/satisfaction and improvement priority. The result of the proposed approach shows better result than those using the conventional way, based on R-square of the regression model.

• 한국조사연구학회지:조사연구
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• 제12권3호
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• pp.49-62
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• 2011

본 논문에서는 패널회귀모형에서 회귀계수 추정량으로 일반최소제곱추정량과 가중최소 제곱추정량의 설계기반 성질을 고찰한다. 회귀계수의 최소제곱추정량을 선형화하여 일반최소제곱추정량의 근사편향, 근사분산, 그리고 근사평균제곱오차의 수식과, 가중최소제곱추정량의 근사분산 수식을 유도한 후, 모의실험을 통하여 두 추정량의 근사분산 및 근사평균 제곱오차의 크기를 수치적으로 비교한다. 모의실험에서는 한국복지패널 3개년 데이터를 모집단으로 간주하고, 가구소득 변수를 관심변수로 하며 가구와 가구주 관련 7개 변수를 설명변수로 하는 유한모집단 회귀계수를 고려한다. 두 추정량의 설계기반 성질을 비교하기 위하여 표본수를 50에서 1,000까지 50 간격으로 설정하여 일반최소제곱추정량의 근사편향, 근사분산 그리고 가중최소제곱추정량의 근사분산을 계산한다. 모의실험을 통하여 다음과 같은 경향을 확인하였다. 첫째, 표본의 크기가 커지면 일반최소제곱추정량의 평균제곱오차가 가중최소제곱추정량의 분산보다 커진다. 둘째, 일반최소제곱추정량의 평균제곱오차를 가중최소제곱추정량의 분산으로 나눈비(ratio)는 설명변수에 따라 크기가 다르게 나타나고, 일반최소제곱추정량의 편향이 클수록 큰 값을 보인다. 셋째, 분산만 비교하면 일반최소제곱추정량의 분산이 가중최소제곱추정량의 분산보다 대부분의 경우에 더 작게 나타난다.

• 조명전기설비학회논문지
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• 제28권12호
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• pp.103-107
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• 2014

Together with housings, general buildings and industrial facilities, multi-purpose complexes are equipped with various and special equipment. They are often used by many unspecified people, which causes an increase in annual electricity consumption. Because of this, a great amount of money has been spent for electric charge, far more in excess of the budget, so a reasonable electricity rate needs to be estimated. In this study, we surveyed the power consumption, average power use, and annual electricity bill of multi-purpose complexes in the past five years. To see the general tendency of the survey, we conducted a statistical analysis with such parameters as average, maximum, and minimum values. Through regression analysis, we could see the trend of the survey in linear way. Based on the survey, we have developed an electric-rate calculation program to estimate the next year's budget on electricity.

• Nutrition Research and Practice
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• 제15권4호
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• pp.468-478
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• 2021

BACKGROUND/OBJECTIVES: This study aimed to analyze the association between dietary omega-3 fatty acid intake and depression in postmenopausal women using data from the Korea National Health and Nutrition Examination Survey (KNHANES) VI. SUBJECTS/METHODS: The KNHANES is a cross-sectional nationwide health and nutrition survey. Dietary data, including omega-3 fatty acids, were assessed using the 24-h recall method. Depression was evaluated using a survey questionnaire. The association between dietary omega-3 fatty acids and depression was evaluated using multivariate logistic regression analysis. Depression, according to the dietary omega-3 fatty acid intake, was expressed as the odds ratio (OR) with a 95% confidence interval (CI). A total of 4,150 postmenopausal women were included in the analysis. RESULTS: In the fully-adjusted model, the group with the highest dietary omega-3 fatty acid intake significantly showed lower prevalence of depression than the group with the lowest intake (OR, 0.52; 95% CI, 0.33-0.83); a significant linear trend was detected (P for trend = 0.04). According to the dose-response analysis using cubic restricted spline regression, this association was linear and monotonic (P for non-linearity = 0.32). CONCLUSIONS: In this study, the dietary omega-3 fatty acid intake in postmenopausal women was inversely proportional to depression in a dose-response manner. Large cohort studies are needed to verify the causality between omega-3 fatty acids and depression in Korean postmenopausal women.

• 한국물환경학회지
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• 제38권6호
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• pp.306-315
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• 2022

In this study, long-term measurement data were applied to the LOADEST model and used as an analysis tool to identify and interpret trends in pollution load. The LOADEST model is a regression equation-based pollution load estimation program developed by the United States Geological Survey (USGS) to estimate the change in the pollution load of rivers according to flow rate and time and provides 11 regression equations for pollution load evaluation. As a result of simulating the Gwangjuchen2, Pungyeongjeongchen, and Pyeongdongchen in the Yeongbon B unit basin in the middle and upper reaches of the Yeongsan River with the LOADEST model using water quality and flow measurement data, lower values were observed for the Gwangjuchen2 and Pyeongdongchen, whereas the Pungyeongjeongchen had higher values. This was judged to be due to the characteristics of the LOADEST model related to data continuity. According to the parameters estimated by the LOADEST model, pollutant trends were affected by increases in the flow. In addition, variability increased with time, and BOD and T-P were affected by the season. Thus, the LOADEST model can contribute to water quality management as an analytical tool for long-term data monitoring.