• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.987-994
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• 2015

This study examines how single-person household expenditure patterns are different with respect to age and income groups using Tobit model. The expenditure data of the national household survey from 2006 to 2012 were used. The results show that income elasticities of all items are greater than 1 except for food & beverage, housing, water, electricity & gas, and Communication. Income elasticities are significantly different among consuming items. Additionally the income elasticities are also different between various age and income groups of single-person households. Therefore governments and businesses have to take this into account when devising their policies or strategies regarding single-person households. Especially, businesses need to adopt a strategy targeted at single-person households with high income and buying power such as unmarried professional people. As the number of single-person household increases the proportion of expenditures on necessities such as beverage, food, and energy is expected to decrease while that on services increases. Consequently policy responses are required to prepare for the expansion of service industries such as health, hospital, and housekeeping services.

• Journal of agricultural medicine and community health
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• v.26 no.1
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• pp.1-17
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• 2001

This study was conducted to investigate the role of drinking pattern in the relationship of alcohol consumption by face-to-face interview in rural elderly(n=994) aged 60~64 in Dalsung County, April to September in 1996. Pattern of alcohol drinking included drinking status, alcohol drinking at the morning without breakfast, average drinks per day, frequency of drinks per month, quantity of alcohol drinking, kind of preferred alcoholic beverage and duration of alcohol drinking. Blood pressure was measured once in each subject using a portable automatic sphygmomanometer. Difference in means of systolic blood pressure, alcohol drinking status, alcohol drinking at the morning without breakfast, and kind of alcoholic beverage were statistically significant before adjusting covariates, but alcohol drinking status and alcohol drinking at the morning without breakfast were statistically significant after adjusting covariates. And difference in means of diastolic blood pressure, kinds of alcoholic beverage was statistically significant before adjusting covariates, but no variables was significant after adjusting covariates. Model I multiple regression for systolic blood pressure that included average drinks per day as the variable of drink pattern, age, educational attainment and, previous history of cardiovascular disease were statistically significant, and multiple regression for diastolic blood pressure, educational attainment, BMI, and previous history of cardiovascular disease were statistically significant. Model II multiple regression for systolic blood pressure that included drinking patterns variables except average drinks per day, previous history of cardiovascular disease were statistically significant. However, multiple regression for diastolic blood pressure, no variables were significant. So, inconsistent with prior research, a positive relationship was not found between average drinks per day and diastolic and systolic blood pressure. The effect of alcohol drinking patterns on blood pressure has public health as well as clinical relevance. The study should be replicated to determine the reliability of our findings.

• Environmental and Resource Economics Review
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• v.21 no.1
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• pp.129-156
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• 2012

This study analyzes the contribution to the national economy of the stable water supply through managing multi-purpose dam. For the analysis, we consider 17 major multi-purpose dams and build a CGE model with summer water and winter water being the production factors as the base year of 2007. We analyze the economic impact of meeting water demand due to the dam management and estimate the risk premium of reducing the uncertainty of water supply. The analysis results show a significant production decrease in the industries of agriculture, forestry and fisheries and tap water as well as the food and beverage industry using the former industries' output as intermediates in the production and show an production increase largely in steel industry and electronic and electrical industries. Being compared to the benchmark solution, GNP is analyzed as being reduced by 0.22~0.68%. Meanwhile, the risk premium is estimated to be about 4 billion to 24 billion won for the value 01 the measure of relative risk aversion in the range 01 0.5 to 3.0.

• Journal of Microbiology and Biotechnology
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• v.3 no.2
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• pp.129-133
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• 1993

The effect of different compositions of organic acids on the flavor profile of 10% sugar solution was investigated by the response surface methodology, and the results were used to evaluate the flavor characteristics of lactic acid fermented cereal beverages. A mixture of extruded rice flour (10%) and soymilk (7.8% dry matter) was fermented with Leuconostoc mesenteroides (Sikhae). Depending on the substrate pretreatments, for example, the malt or amylase digestion and the proteolytic enzyme hydrolysis, the sugar and organic acid composition of the product varied. The organic acid composition of the fermented beverages was in the ranges of 0.44-0.55% lactic acid, 0.05-0.09% acetic acid and 0.07-0.09% citric acid, while that of commercial apple juice was 1.59% malic acid and 0.49% acetic acid. The flavor profiles of fermented beverages added with 10% sucrose were compared to those of apple juice and a model mixture containing 0.48% citric acid, 0.39% lactic acid and 0.12% acetic acid in 10% sugar solution. The QDA diagram of fermented beverages approached to that of apple juice, when the substrate was digested by amylase but not by protease.

• Culinary science and hospitality research
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• v.14 no.4
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• pp.368-384
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• 2008

This study was designed to investigate the results of a performance analysis on the effect of transformational leadership on the efficacy of organizational citizenship behavior of hotel convention employees. This study referenced the relevant literature, proposed hypotheses to solve the main issues of inquiry, and made a corresponding empirical analysis. For the empirical analysis, a questionnaire was given to a total of 149 kitchen and food & beverage banquet employees at a Seoul area deluxe hotel convention. The model was tested using SPSS 12.0 and AMOS 5.0 on a sample of 149 surveys, of which 71% constituted a usable response rate. The results of the empirical analysis show the following. 1) Charisma and vision have a significant effect on group efficacy. 2) Individual consideration and intellectual stimulation have significant influence on self efficacy. 3) Individual consideration and intellectual stimulation have significant influence on group efficacy. 4) Altruism and conscientiousness have significant influence on group efficacy. 5) Sportsmanship and civic virtue have significant influence on self efficacy.

• Korean Management Science Review
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• v.19 no.1
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• pp.75-88
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• 2002

In recent years, it Is necessary to develop an alternative measure, the time efficiency of management activities, as a more measurable and operational tool Instead of traditional accounting measures such as inventories turnover. Therefore the concept of throughput time has got much attention as useful tool for controlling time based management. The purpose of this paper is to investigate the usefulness and adaptability of throughput time. The sample consists of 212 non-banking firms listed on the Korean Stock Exchange. The test Period were 10 years(1989-1998). The regression analysis for this study was performed using the cross-sectional data for the sample, and it was also performed for each Industry. The results show that net Income to tonal assets and labor productivity (value added Per employee) variables in the model was signiflcantly associated with throughput time. On the other hand, the relationship between throughput time and logistics cost to sales do largely not have statistical significance. Especially, it is found that the relationship do not have significance or negative response in food & beverage industry and wholesale & retail industry. In summary, the results show that the measure of throughput time can be an effective managerial Indicator for time based competition and management.

• Journal of the Korean Society of Food Culture
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• v.26 no.2
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• pp.170-177
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• 2011

We examined household's food expenditures in this study. The empirical work outlined here used quarterly data from 2003 Q1 to 2010 Q3. All variables are in log form and were obtained from the Korea National Statistical Office. The food items included cereals, dairy products, fruits, meat, vegetables, and alcoholic beverages. We applied the ordinary least squares method to a model consisting of household income and seasonal dummies. This is because household expenditures are ordinarily a function of income and have seasonal characteristics. The household's food consumption patterns also reflect the prevailing social and environmental circumstances. This study showed that the income coefficients of cereals, meat, dairy products, and alcoholic beverages tend to increase in the long-run, whereas those of vegetables and fruits decreased. The results also revealed that consumption of alcoholic beverages and meat was greatly affected by household income fluctuations, whereas those of vegetables and dairy products were not sensitive to income. The impulse response functions indicated that expenditures not only increased slowly before peaking one to eight quarters after the income shock but declined very slowly to pre-shock levels. The response of dairy products at the twelfth step was three times as large as that of the first step.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1249-1256
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• 2021

This study investigates the company value determinant by observing the effect of financial performance and Corporate Social Responsibility (CSR) and its role in moderating performance achievement. The macro-economy variables such as inflation and interest rate are also used as the controlling variable. This research employs the sample of manufacturing companies of the food and beverage sub-sector listed on the Indonesia Stock Exchange. This study used panel data from 2013 to 2017, with the moderating regression analysis. The result shows that the profitability of the current or previous period affects the company's value. CSR and company size affect the company value at the next period shows that stock price, which reflects the investor's perception today, will be affected by the CSR, Size, and Return On Asset of the previous year. CSR also shows that it can be the substitute for profitability since a company that performs CSR is the one that has a good performance. The regression moderating model and the profitability of the previous period have a higher explanatory power than the higher R square value in explaining company value.

• Asian Journal of Business Environment
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• v.12 no.3
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• pp.31-39
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• 2022

Purpose: This research aims to analyze the quality and characteristics of foreign tourists to Indonesia. Research design, data and methodology: The indicator used to see the quality of foreign tourists is their expenditure while in Indonesia. The data used is secondary data and the statistical analysis used is panel data regression to see the effect of Economic Distance, GDP per capita, Average Length of Stay and Exchange Rate on the quality of Foreign Tourists from 2010 to 2019. Results: Foreign tourists to Indonesia are dominated by young tourists, male and stay about 8.87 days. Their expenditure is relatively low, mostly spent on accommodation, food and beverage. The variables of average length of stay, exchange rate, economic distance, and GDP per capita have a significant and positive effect on the quality of foreign tourists to Indonesia. Conclusions: The number of foreign tourists visiting Indonesia in 2010-2019 tends to increase where the majority of tourists come from countries that are geographically close to Indonesia, young tourists, and male. The quality of tourists in terms of spending is still relatively low. The characteristics of foreign tourists and economic indicators used in the study have a positive effect on improving the quality of tourists.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.