• Korean Journal of Community Nutrition
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• v.21 no.4
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• pp.321-331
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• 2016

Objectives: The purpose of this study was to examine the economic characteristics of single-person households and explain the effects of them on the food service industry. Methods: For this paper, I analysed the data related with single-person households and the food service industry in two surveys, Household Income and Expenditure Survey and Wholesale and Retail Trade Survey published by Statistics Korea from 2006 to 2015, with an empirical test performed utilizing these data. The indicators of the age of householders, disposable income per capita, and the rate of household of worker were compared between single and multi-person households. Furthermore, sales and the number of establishments in the food service industry were used as industry-variables, and disposable income, eating-out expenses and the rate of single-person households as the household-variables were used in a panel analysis. Results: The results showed that household incomes were lower, age of householder was higher, and the percentage of household of worker was lower in single-person households in contrast to multi-person households. According to the empirical analysis, eating-out expenses of single-person households, in comparison to multi-person households, has significantly positive effects on the growth of the food service industry. This means that the recent trend of increasing numbers of single-person households may help the growth of the food service industry. Conclusions: The growth in the rate of single-person households has been one of the most striking demographic shifts in recent decades. Their economic characteristics and the effects were analyzed to give the managers in the food service industry and the policy-makers useful information in dealing with this new trend. Moreover, in considering the fact that single-person households eat out more frequently than multi-person households, the food service business should develop the managerial strategies focused on acclimatizing to single-person households.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.111-126
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• 2000

Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics. In estimating means, totals, and other parameters for small areas of a finite population, samplie sizes for small areas are typically small because the overall sample size is usually determined to provide specific accuracy at a much higher level of aggregation than that of small area. The usual direct estimators that use the only information which is gotten from the sample in a given small area provide unreliable estimates. However, indirect estimators utilize the information from the areas related with a given small area, that is, borrow strength from other related areas, and so give more accurate estimates than direct estimators. In this paper we investigate small area estimation methods such as synthetic, composite and empirical best linear unbiased prediction estimator, and apply them to real domestic data which is from the Survey of Hotels and Restaurants in In-Chon as of 1996 and then evaluate the performance of these methods by measuring average squared errors. This evaluation shows that indirect estimators, which are small area estimation methods, are more efficient than direct estimator.