• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.329-334
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• 2004

The objective of this study regards the preceding condition of the construction disposal of waste which is appropriate, with occurrence quantity DB anger the occurrence quantity prediction which is accurate the regression model which it sees and with the method which is mote accurate prediction method of existing than to sleep it presents it does. This study acquires apartment results data of public construction and civil construction, and chose factor that exert biggest influence on the waste occurrence amount through question and interview memorial address by regression model variable. And presented regression mode] which uses statistics program named SPSS. Result of this study by regression model through constant results data DB anger existent error big experience than estimate method that corrector estimation is available show.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.1-10
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• 2021

This paper compares the performance of Fama-French three-factor and five-factor models using a dataset of 20 Pakistani commercial banks for the period 2011 to 2020. We focus on an emerging economy as the findings from earlier studies on developed countries cannot be generalized in emerging markets. For empirical analysis, twelve portfolios were developed based on size, market capitalization, investment strategy, and growth. Subsequently, we constructed five Fama-French factors namely, R_M, SMB, HML, RMW, and CMA. The OLS regression technique with robust standard errors was applied to compare the predictive power of both the Fama-French models. Further, we also compared the mean-variance efficiency of the Fama-French models through the GRS test. Our empirical analysis provides three unique and interesting findings. First, both asset pricing models have similar predictive power to explain the expected portfolio returns in most cases. Second, our results from the GRS test suggest that there is no noticeable difference in the mean-variance efficiency of one asset pricing model over the other. Third, we find that all factors of both Fama-French models are statistically significant and are important for explaining the volatility of expected commercial bank returns in the context of Pakistan.

• 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.

• The Korean Journal of Community Living Science
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• v.17 no.3
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• pp.29-41
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• 2006

The purpose of this research is to study the causal model among mother related variables, child abuse, and children's emotional maladjustment behaviors. The sample subjects were 542 pairs of fifth and sixth grade elementary school students and first as well as eighth grade middle school students, and their mothers. The major findings of the research are as follows: First, the result of multiple regression analysis on the effects of the maternal parenting stress and marital satisfaction to the children's abuse indicates that stress related to learning expectation and stress related to relationship with child are the significant contributing factor to physical abuse and verbal abuse. Second, the result of multiple regression analysis on the effects of the maternal parenting stress and child abuse to the children's emotional maladjustment behaviors indicate that verbal abuse is the significant contributing factor. Third, looking at causal relations of the maternal variables (maternal parenting stress, marital satisfaction) and child abuse (physical abuse, verbal abuse, neglect) to the children's emotional maladjustment behaviors, maternal variables impact indirectly through the child abuse factor.

• Journal of Korean Academy of Nursing
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• v.35 no.7
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• pp.1353-1361
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• 2005

Purpose: This study was done to provide fundamental data for developing a depression prediction model by discovering main factors that affect depression in patients who do maintenance hemodialysis. Method: The subjects were 191 patients doing maintenance hemodialysis selected from outpatient dialysis clinics at 9 major general hospitals, The Instrument tools utilized in this study were adapted from depression, fatigue, sleep disturbance, stress, adaptation, symptoms, daily activities, and role limitation and thoroughly modified to verify reliability and validity. The collected data was analyzed with a SPSS-PC 11.0 Window Statistics Program for real numbers, percentage, average, standard deviation, and multiple regression. Results: The correlation factor for depression was (M=2.54) fatigue(M=3.12), sleep disturbance (M=2.82), stress(M=3.04), adaptation(M=2.53), daily activities(M=2.24), symptoms(M=2.37), and role limitation(M=2.24). The strongest factor that affected depression was explained by symptoms of the patients who performed hemodialysis. The analysis of the factors that affected depression revealed a $58.4\%$ prediction in symptoms, stress, role limitation, and adaptation. Conclusion: It has been confirmed that the regression equation model(Depression=7.351 + .266$^{\ast}$symptoms + .260$^{\ast}$stress -.l89$^{\ast}$adaptation + .057$^{\ast}$fatigue) of this research may serve as a prediction factor for depression in Hemodialysis Patients.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.927-940
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• 2023

Online shopping has been undergoing significant developments in the South Asian region in the last decade. Using a representative sample of Sri Lankan consumers, this study explored online food purchasing behavior in Sri Lanka, a developing nation and island in South Asia. Data were collected from 562 respondents from all nine provinces in Sri Lanka using an online survey. Consumer attitudes were evaluated using factor analysis, and factor scores were added as explanatory variables to the final model. An ordered logistic regression model was used to examine the impact of consumer demographics, economic variables, and consumer attitudes on online food purchases. Online food purchasing intensity was categorized into four groups that suited ordinal rankings: zero for never, low for rarely, medium for occasionally, and high for regularly. Results indicated that age, income, education, and living in urban areas affect the online food purchasing behavior of Sri Lankan consumers. In addition, trust, convenience, and attitudes toward price were powerful drivers of online food purchasing. The findings have a number of significant managerial ramifications for creating strategies to promote online food purchases in developing South Asian nations like Sri Lanka. Moreover, promoting online shopping could be a potential solution for traffic congestion, ultimately helping to mitigate the negative externalities associated with it, such as carbon emissions and air pollution.

• Journal of Construction Engineering and Project Management
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• v.8 no.2
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• pp.17-33
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• 2018

This study investigates the stability of professionals' cost variability factor-rankings across different levels of cost-variability and response scenarios. Descriptive statistics are used to examine the stability of factor-ranking for 20 cost variability factors and a Multinomial Logistic (MNL) regression model was implemented to examine the stability of cost variability factors across three cost variability levels. The finding on the descriptive statistics indicated that professionals' factors-rankings are stable only for external factors. The MNL regression results on factor-stability suggested that 8 out of the 20 evaluated factors were unstable determinant of lower cost variability levels. These factors are "risk associated with the project", "personal bias and poor professionalism of the estimators", "limited time available to complete the project", "lack of skills and experience by estimator" "geographical location of projects", "incomplete & rush designs for estimate", "unforeseen or unexpected site constraints", "high class bidders for the contractors". Similarly lack of experience and large size projects were observed to be unstable as well. These observations suggest that professionals' view on pre-tender cost variability factor-ranking yields unstable factor rankings hence should not be relied upon as the only mechanisms to mitigate cost related risks in construction projects.

• Fire Science and Engineering
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• v.28 no.2
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• pp.69-75
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• 2014

This study derives the factors which affect the occurrence of arson from statistical data (population, economic, and social factors) by multiple regression analysis. Multiple regression analysis applies to 4 forms of functions, linear functions, semi-log functions, inverse log functions, and dual log functions. Also analysis respectively functions by using the stepwise progress which considered selection and deletion of the independent variable factors by each steps. In order to solve a problem of multiple regression analysis, autocorrelation and multicollinearity, Variance Inflation Factor (VIF) and the Durbin-Watson coefficient were considered. Through the analysis, the optimal model was determined by adjusted Rsquared which means statistical significance used determination, Adjusted R-squared of linear function is scored 0.935 (93.5%), the highest of the 4 forms of function, and so linear function is the optimal model in this study. Then interpretation to the optimal model is conducted. As a result of the analysis, the factors affecting the arson were resulted in lines, the incidence of crime (0.829), the general divorce rate (0.151), the financial autonomy rate (0.149), and the consumer price index (0.099).

• Culinary science and hospitality research
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• v.14 no.2
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• pp.205-214
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• 2008

The purpose of this study was to measure the moderating effect of belief homogeneity on the relation-ships among attitudinal ambivalence, behavior intention and consumption behavior. The questionnaire, which consisted of items to measure the constructs of belief homogeneity, attitudinal ambivalence, behavior intention and consumption behavior, were completed by 338 subjects in Jeonnam area. Moderated regression analysis was used to measure the moderating effect of belief homogeneity. To test validity and reliability of constructs, factor analysis and Cronbach's $\alpha$ were used in this study. Results of the study demonstrated that the moderated regression analysis result for the data also indicated a better model fit in Model 2 than Model 1. In the Model 1, the main effects of behavior intention and attitudinal ambivalence on consumption behavior were statistically significant. In the Model 2, the main effects of behavior intention, belief homogeneity and attitudinal ambivalence on consumption behavior were statistically significant. The interactional effects of belief homogeneity$\times$attitudinal ambivalence on consumption behavior were statistically significant. Moreover, the effects of attitudinal ambivalence on consumption behavior were statistically significant at all levels of belief homogeneity, except for when homogeneity was high.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.79-93
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• 2021

The question of why do you want to start a "start?" Is the most basic step in trying to do something. In other words, previous studies have shown that the degree of confidence in an individual's decision affects the setting of a specific purpose. Based on this, this study aims to provide basic data for deriving the direction of entrepreneurship education in college students by analyzing the effects of goal-oriented behavioral model on college students' self-determination and intention to start a business through the 5 factor model. To achieve the purpose of the study, a self-report questionnaire was conducted from October 01 to November 11, 2019 for university students attending located in Gyeonggi-do, Seoul. A total of 150 questionnaires were distributed, and 125 parts were used for the final analysis, except 25 parts with insincere responses or errors. Data were analyzed using SPSS Win 24, and reliability, validity analysis, frequency analysis, One-way ANOVA and regression analysis were performed, and three-step regression analysis and Sobel verification were performed for mediating effects. The summary of the study is as follows. First, the influence of university students' goal-oriented behavioral model on self-determination showed that attitudes, subjective norms, and perceived behavioral controls had statistically significant positive effects, and positive and negative expectations were statistically significant. Did not affect. Therefore, the higher the attitude, subjective norms, and perceived behavioral control, the higher the university students' self-determination. Second, the influence of college students' goal-oriented behavioral model on the intention to start a business was as follows.). As a result, the higher the perceived behavioral control and positive expectation, the higher the intention to start up. Third, regression model 1 showed that the behavioral control and positive expectation sentiment among the goal-oriented behavioral model had a significant positive influence on the college students' intention to start a business. Affected. Regression model II added the parameters of the 5 factor model, which increased 2.5% of explanatory power than the first regression model. Perceived behavioral control and positive expectations had a statistically significant positive effect, negative expectations had a statistically significant negative effect, and among the 5 factor model, openness had a statistically significant positive (+) Affected. From these results, it can be seen that the Big Five personality factors have a mediating effect on the relationship between goal-oriented behavior model and intention to start up. This study confirmed that the goal-oriented behavioral model of college students is an important variable in implementing self-determination and intention to start a business. In addition, by using his Big 5 personality factors as positive feedback, he has proved to play an important role by identifying the mediation role that can be set, planned and utilized to plan and achieve his life. The result of this study is that college students are interested in the intention of individual start-ups, so they are not freed from difficult employment difficulties. It is intended to provide basic data useful in the age of creation of government.