• Journal of Korean Society of Water and Wastewater
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• v.21 no.1
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• pp.75-82
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• 2007

When one forecasts urban water demand in a long-term, multivariate model can give more benefits than per capita requirement model. However, the former has shortcomings in that statistically high explanatory power cannot be obtained well, and change in customer behavior cannot be considered. If the past water consumption effects the future water demand, dynamic model may describe real water consumption data better than static model, i.e. the existing multivariate model. On these grounds, this study built dynamic model using system dynamics. From a case study in Seoul and Busan city, dynamic model was expected to forecast water demand more descriptively and reliably.

• Journal of Korean Public Health Nursing
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• v.36 no.3
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• pp.361-374
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• 2022

Purpose: This study applies an ecological model to investigate individual and organizational levels to identify factors influencing the HRQOL of industrial employees. Methods: Totally, 133 industrial workers of a vehicle company were enrolled, who understood the purpose and consented to participate in the study. The collected data were analyzed by frequency, percentage, mean, standard deviation, independent t-test, one-way ANOVA, Scheffe Test and hierarchical regression analysis using the SPSS 20.0 program. Results: Hierarchical regression analysis showed that job Stress(β=-.44, p<.001), and hobbies(β=-.21, p=.013) were the major influencing factors of the Physical Component Summary of HRQOL, which had an additional explanatory power of 11.5%. The influencing factors for the Mental Component Summary of HRQOL were job stress(β=-.43, p<.001), and coronary artery disease(β=.17, p=.034) with an additional explanatory power of 13.5%. Conclusion: Results of this study, reveal that a multidimensional approach based on an ecological model is suitable as a health promotion intervention strategy to improve the HRQOL. We further propose developing a multi-dimensional health promotion program that consider the individual and organizational factors such as job stress, activation of in-house clubs, and assessing and managing of the risk of cerebral and cardiovascular diseases.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.21-30
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• 2022

Shear strength is the most important indicator in the evaluation of rock slope stability. It is generally estimated by comparing the results of existing literature data, back analysis, experiments and etc. There are additional variables related to the state of discontinuity to consider in the shear strength of the rock slope. It is difficult to determine whether these variables exist through drilling, and it is also difficult to find an exact relationship with shear strength. In this study, the data calculated through back analysis were used. The relationship between previously considered variables was applied to deep learning and the possibility for estimating shear strength of rock slope was explored. For comparison, an existing simple linear regression model and a deep learning algorithm, a deep neural network(DNN) model, were used. Although each analysis model derived similar prediction results, the explanatory power of DNN was improved with a small differences.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.111-122
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• 2012

In this study, we consider the integration of cognitive components and emotion to account for communication behaviors and activism on a consumer advocacy website. The challenge of integrating situational theory and anger activism model was empirically explored utilizing an online survey with the members of the virtual community, which was designed to raise issues and to protest against the product defects of a product. Our findings indicated that along with the cognitive perception in the situational theory, anger as a negative emotion was the most significant predictor strongly associated with communication behaviors and activism on the organization. More interestingly, the model that integrates anger with cognitive components significantly improves its explanatory power compared with one including only cognitive components as explanatory variables.

• Korean Journal of Child Studies
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• v.15 no.1
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• pp.37-53
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• 1994

The primary purpose of this study was to investigate the validity of a component model of gender role and differences in children's gender concepts with age and sex. The secondary purpose was to investigate the relationship between children's gender schema and memory as well as preference for gender related task. 181 children were interviewed about gender concepts and gender related tasks. Results indicated that three dimensions of the component model (i. e., gender label-component links, within-component links, between-component links) were significantly related to each other. The mean scores of gender role knowledge and attitude were different with age but not with sex. The results of the regression analysis showed that children's age, sex, and gender role attitude explained both memory and preference for gender related tasks. The component model had better explanatory power than the simple model. The findings of the present study suggest that children's gender concepts are better described in terms of the component model than the simple model and may contribute to a theoretical rationale for gender schema theory.

• Journal of Korean Society of Forest Science
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• v.96 no.2
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• pp.222-226
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• 2007

This study developed the Korean roundwood import prediction model using vector autoregressive (VAR) method. The roundwood was divided into softwood and hardwood by species. The VAR model of roundwood import was specified with two lagged endogenous variables, that is, roundwood import volume and roundwood import price. The results showed that the significance levels of F-statistics in the softwood and hardwood roundwood import equations rejected the hypothesis that all coefficients are zero. So, we concluded that roundwood import volume can be explained by lagged import volume and lagged import price in Korea. The coefficient signs of all variables were as expected. Also, the model has good explanatory power, and there is no autocorrelation.

• Korean Journal of Agricultural Science
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• v.44 no.4
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• pp.620-635
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• 2017

This study was intended to identify the main factors responsible for the decline in purchase of imported agricultural and fish products after Japan's nuclear power plant accident in 2011 and to compare the effects on imported agricultural produce and imported fish products. Logit model and multiple regression model analyses were performed using consumers' survey data. Psychological and qualitative factors reflecting consumers' food safety awareness and purchasing preferences, which were extracted by Factor analysis, were included as the models' explanatory variables, along with socio-demographic and economic factors. The Logit estimation showed aged, married, and low-income households had significantly higher probability of reducing their purchases of imported agricultural and fish products. However, the multiple regression results pointed out that the actual rate of decrease of imported agricultural and fish products purchases were more significantly affected by non-socio demographic factors such as past experience of purchasing imported agricultural and fish products, future intention to purchasing Japanese agricultural and fish products, and the ratio of imported to domestic agricultural and fish products before the nuclear accident, as well as consumers' feeling of food insecurity and their purchasing preferences. Moreover, the results showed that Korean consumers have reacted more sensitively to the decline in imported fish products than imported agricultural produce after the nuclear accident based on the marginal effects of various socio-demographic and economic factors.

• International Journal of Contents
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• v.14 no.3
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• pp.32-38
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• 2018

This study examined the factors influencing the intention to use smartwatches using the integrated model of technology acceptance model (TAM) and innovation diffusion theory (IDT). An online survey was conducted and the data were analyzed using the structural equation modeling (SEM). The results showed that the research model had an acceptable fit, and all paths, except for the one from the perceived ease of use to the intention to use, were supported. Regarding paths from IDT to TAM, it was observed that higher the compatibility, the users perceived greater usefulness. Additionally, both observability and trialability influenced the perceived ease of use. However, perceived ease of use affected the intention only through the mediated effect of perceived usefulness. The implication of the study lies on the major focus on the effects of users' perceptions regarding innovative characteristics of smartwatches on the intention to adopt and attempted to increase the explanatory power of the TAM and IDT by combining both.

• Land and Housing Review
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• v.11 no.1
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• pp.59-66
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• 2020

This thesis investigates relationship between Stock-to-Flow price and housing starts in Seoul metropolitan form 2008 year to 2019 year. The paper tests the relationship through two time-series models such as a vector error correction model and Dynamic Panel regression model. The model results show evidence of positive correlation between Stock-to-Flow price and housing starts in the long run. By transforming the regional data into a panel data set and running a fixed effects model, we test the explanatory power of PBR on housing starts. The result of VECM confirms that one unit uprising PBR raises up apartment construction by 7.4%. This result supports that PBR is a major factor in choosing a start of housing construct. Base on the result of empirical model, We also suggest that the market self-regulation function of housing providers is operating in the entire metropolitan area market.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.20 no.1
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• pp.6-17
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• 2013

Purpose: The purpose of this study was propose and test a predictive model that could explain and predict factors influencing the sexual satisfaction of women with diabetes mellitus. Method: The conceptual frame for this study was formed as a hypothesized model based on Roy's adaptation model. Participants for this study were 240 out-patient women from P university hospital in Y city. The data were analyzed using SPSS 18.0 and AMOS 19.0 program. Results: The paths that had direct effects on sexual satisfaction, and were statistically significant were showing intimacy with spouse, and sexual function. The explanatory power of these variables for sexual satisfaction was 64%. Conclusion: The results of the study suggest that it is necessary for enhancement of sexual satisfaction for women with diabetes to increase intimacy with husband, and that sexual function, frequency of exercise, adequate glycemic control be maintained, and depression decreased.