• Journal of the Korean Home Economics Association
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• v.37 no.10
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• pp.91-106
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• 1999

The purpose of this study is to analyze empirically the influences of different types of household income and asset in the consumption expenditures of homeowners and lessees with deposit. The data used in this study were the 1996 Korea Household Panel Study. 1,512 households data were selected for the final analysis. The statistical methods adopted for data analysis were frequency, percentage, one-way ANOVA, crosstabs, multiple regression analysis, and chow-test. The results are as follows: (1) There were the differences between three groups in the expenditure levels of each consumption category and the shares of each consumption category of total expenditures. (2) The change of labor income influenced more significantly consumption expenditures of homeowners and lessees with deposit, compared to changes of different types of household income. Also homeowners and lessees with deposit changed their consumption expenditures in different ways to changes of various types of household income. (3) Homeowners increased more significantly their consumption expenditures to increase of net asset than lessees with deposit.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1147-1154
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• 2016

Impact of Korea train express (KTX) on the regional economy in Korea has been studied by many researchers. Current research is limited in the lack of quantitative research using a statistical model to study the effect of KTX on regional economy. This paper analyses the influence of KTX to the household final consumption expenditure, which is one of important regional economic index, using spatial panel regression model. The spatial structure is introduced through spatial autocorrelation matrix using adjacency of KTX connection. The result shows a significant effect of Korea train express on the regional economy.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.769-782
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• 2020

Interest in fruit and vegetables has increased due to changes in consumer consumption patterns, socioeconomic status, and family structure. This study determined the factors influencing the demand for fruit and vegetables (strawberries, paprika, tomatoes and cherry tomatoes) using a panel of Rural Development Administration household-level purchases from 2010 to 2018 and compared the ability to the prediction performance. An artificial neural network model was constructed, linking household characteristics with final food expenditure. Comparing the analysis results of the artificial neural network with the results of the panel model showed that the artificial neural network accurately predicted the pattern of the consumer panel data rather than the fixed effect model. In addition, the prediction for strawberries was found to be heavily affected by the number of families, retail places and income, while the prediction for paprika was largely affected by income, age and retail conditions. In the case of the prediction for tomatoes, they were greatly affected by age, income and place of purchase, and the prediction for cherry tomatoes was found to be affected by age, number of families and retail conditions. Therefore, a more accurate analysis of the consumer consumption pattern was possible through the artificial neural network model, which could be used as basic data for decision making.

• Journal of the Korean Home Economics Association
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• v.35 no.2
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• pp.401-413
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• 1997

The objectives of this study were to measure the characteristics of environmentally conscious behavior in the private household focused on energy consumption, money expenditure and time usage, and to determine the socioeconomic variables, environmental consciousness and environmental education which are associated with the environmentally conscious behavior of private households. The data for this study were collected in a personal interview and the final sample consisted of 178 respondents and the statistics employed to analyze the data are discriminant analysis $\chi$2-test. As a result of the discriminant analysis, it was shown that environmentally conscious private households consumed less energy, had lower transportation costs, but spent more time in purchasing behavior in the market compared with those who did not exhibit environmentally conscious behavior. Environmentally conscious behavior of private households differed significantly according to the education of housewives, and also to the level of environmental consciousness and environmental education of the respondents.