• Journal of Preventive Medicine and Public Health
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• v.29 no.4 s.55
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• pp.831-842
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• 1996

Demand for high quality medical care has recently been increasing in step with high level of income and education. Patients prefer the use of large general hospitals to small community hospitals. Large hospitals, usually located at urban area, expand their capacities to cope with the increasing demand, therefore, they easily secure revenue necessary for growth and development of hospitals. However, small community hospitals are facing with serious financial difficulties caused from the reduction of patients in one hand and the inflation of cost in another. If small rural hospitals were closed, the closure would have negative impacts on local economies in addition to the decrease in access to medical care. Community leaders should have an insight on the contribution of community hospitals to local economies. They could make a rational decision on the hospital closure only with the understanding of hospital's contribution to the community. This study is designed to develop an economic model to estimate the contribution of rural hospital to local economies, and also to apply this model with a specific hospital. The contribution of a hospital to local economies consists of two elements, direct effect and multiplier effects. The direct impacts include hospital's local purchasing power, employee's local purchasing power, and the consumption of patients coming from outside the community. The direct impact induces multiplication effect in the local economy. The seed money invested to other industries grows through economic activities in the region. This study estimated the direct effect with the data of expenditure of the case hospital. The total effect was calculated by multiplied the direct effect with a multiplier. The multiplier was drown from the ratio of marginal propensity of income and expenditure. Beside the estimation of the total impacts, the economic effect from the external resources was also analyzed by the use of the ratio of patients coming outside the region. The results are as follows. 1. The direct economic contribution of the hospital to the local economy is 1,104 million won. 2. The value of multiplier in the region is 2.976. 3. The total economic effect is 3,286 million won, and the multiplication effect is 2,182 million won. 4. The economic contribution from the external resources is 245 million won which is 7.5% of the total economic effect.

• Journal of Distribution Science
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• v.12 no.8
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• pp.5-15
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• 2014

Purpose - The method of TV home shopping is a kind of retail method that provides the viewer with information about products and, further, sells the products to consumers through the media of television. The domestic home-shopping industry has been expanding since 1995, and there are six companies in this arena as of 2012. In this study, we evaluate the management efficiency of TV home-shopping companies and provide suggestions for improving efficiency, using the DEA (data envelopment analysis) model. Hence, we expect to contribute to the progress of the companies' efficiency and the development of the TV home-shopping industry, where deepening competition is inevitable because it is experiencing the maturing market stage in its life cycle. Research design, data, and methodology - Efficiency is the ratio of the quantity of input to the quantity of output of a product or service. It is necessary to estimate aggregate inputs and aggregate outputs, which are calculated by applying a weighting to a number of input and output factors, to measure the efficiency. The DEA model is divided into the CCR model and the BCC model. The CCR model is a basic model that assumed constant returns to scale (CRS), and the BCC model extends the CCR model to accommodate technologies exhibiting variable returns to scale (VRS), and concerns only the technical efficiency without considering the efficiency of returns to scale. In this study, we consider six companies each year from 2008 to 2012 as a DMU (Decision Making Unit) and analyze the differences in efficiency for each company in each year. Furthermore, we evaluate the operating characteristics of TV home-shopping companies, using three models, in accordance with the overall performance, profitability, and marketability of the business. Results - The result of the analysis, using DEA models, shows that Hyundai Home Shopping (2009, 2010, 2011), GS Home Shopping (2011), NS Home Shopping (2011) and CJ O Shopping (2012) possess MPSS (most productive scale size), with a score 1.0 in CCR, BCC, and scale efficiency. Particularly, Hyundai Home Shopping is shown to be the most efficient in terms of overall business performance, marketability, and profitability. The overall efficiency of the home shopping industry has displayed an increasing trend since 2008, even though it decreased marginally in 2012; further, we can observe that home shopping companies operate with increasing efficiency with the passage of time. Conclusions - Home shopping companies have focused on market expansion rather than profits, as they displayed better efficiency in marketability than increase in profitability during the period 2008-2012. In addition, the main reason for the increased efficiency in the home shopping industry is the market expansion through the revenue increase of each home shopping company. This study can be used as a reference when home shopping companies attempt to devise future strategies, as it suggests efficiency benchmarks and development levels for each home shopping company.

• Analyses & Alternatives
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• v.6 no.2
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• pp.155-183
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• 2022

The purpose of this study is to econometrically analyze the negative impact of the May 18 Democratic Uprising on the Gwangju/Jeonnam regionional economy using the Synthetic Control Method (SCM). The SCM SCM is a methodology similar to the difference-in-difference(DID) method of microeconometrics. It is applied to macroeconomic variables such as country, region, etc. to estimate the causal relationship between specific events and the dependent variable. In this study, as of 1980, local tax revenue data of metropolitan local governments were used as a proxy variable for the economy of the region, and the impact of the May 18 Democratic Uprising on the economy of Gwangju/Jeonnam region was analyzed through various socio-economic indicators. In this study, data were used to analyze from 1971 to 2000, and as a result of empirical analysis, local tax revenues in Gwangju/Jeonnam area were less collected than normal routes up to 17%. In addition, the significance of this analysis was confirmed through in-time placebo effect analysis and in-space placebo effect analysis, which are methods of analyzing the robustness of the control group synthesis method.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.1-11
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• 2023

Big tech companies are further strengthening its status against the background of data accumulation, price competitiveness by the platform, and competitive advantage due to the network effect. The competition subcommittee of the European Union(EU) imposed a huge fine on Google for antitrust violations, which was interpreted as an attempt to collect Google's unpaid taxes. In fact, taxation efforts in the form of 'Google tax' are underway, targeting expedient tax avoidance by global platforms. It has power and has a considerable influence on the startup ecosystem. The domestic sales and tax scale of global platforms, which have a great impact on domestic content startups and small and medium-sized venture companies, are not accurately measured. In the case of Google, according to research literature, sales in Korea were estimated at about 2 trillion to 3 trillion won in 2017, but Google Korea reported sales of 290 billion won in 2021 and paid 13 billion won in taxes. This study aims to verify the economic effect of the global platform that has a great influence on Korea, and specifically to quantitatively estimate the annual domestic sales and taxes of Google, a representative global platform. As a result of estimating Google's annual domestic sales and taxes based on the figures presented in the document related to Google's economic effect published by Google, the result was 4 to 9 trillion won in annual sales and 390.6 to 913.1 billion won in taxes. This study is meaningful in that it provides basic data on the direction of national and tax policies in the future digital economy era by estimating the problem of tax authority by country of global platform companies with a specific example of Google.

• The Journal of Fisheries Business Administration
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• v.22 no.2
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• pp.75-99
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• 1991

A quantitative analysis was carried out to monitor the commercial yield level of walleye pollock Theragra chalcogramma in the east coast of Korea, based on available data on catch and fishing effort, catch per unit of effort including fish prices from 1911 to 1988, using a traditional yield model. The results from the quantitative assessment were based to estimate maximum economic yield (MEY) and optimal fishing effort (E-opt) at MEY. On the other hand, interaction aspects between danish seine fishery and trawl fishery mainly targeting walleye pollock in the east coast of Korea were studied to predict optimal situation in fishing effort level from economic point of view which gives the most benefits to the two fisheries. Total production of walleye pollock in 1911 when its catch record was begun for the first time was about 12, 000 metric tons(M/T), and then the catch trend maintained nearly at the level of 50, 000 M/T per annum, showing a decreasing trend until 1930. The highest production from historical data base on walleye pollock fishery statistics was from the years in 1939 and 1940, about 270, 000 M/T and 26, 000 M/T, respectively. No production of the fish species was recorded during the years from 1943 to 1947, and from 1949 to 1951. From 1952 onwards annual production was only available from the southern part of 38$^{\circ}$N in the east coast. During two decades from 1952 to 1970, the production had sustained about less than 30, 000 M/T every year. Annual production showed an increasing trend from 1971, reaching a maximum level of approximately 162, 000 M/T in 1981. Afterwards, it has deceased sharply year after year and amounted to 180, 000 M/T in 1988. The catch composition of walleye pollock for different fishery segments during 1970~1988 showed that more than 70% of the total catch was from danish seine fishery until 1977 but from 1978 onwards, the catch proportion did not differ from one another, accounting for the nearly same proportion. Catch per unit of effort (CPUE) for both danish seine fishery and trawl fishery maintained a decline tendency after 1977 when the values of CPUE were at level of 800 kg/haul for the former fishery and 1, 300 kg/haul for the latter fishery, respectively. CPUEs of gillnet fishery during 1980~1983 increased to about 3.5 times as high value as in the years, 1970~1979 and during 1987~1988 it decreased again to the level of the years, 1970~1978. The bottom longline fishery's CPUE wa at a very low level (20 kg/basket) through the whole study years, with exception of the value (60 kg/basket) in 1980. Fishing grounds of walleye pollock in the east coast of Korea showed a very limited distribution range. Danish seine fishery concentrated fishing around the coastal areas of Sokcho and Jumunjin during January~February and October~December. Distributions of fishing grounds of trawl fishery were the areas along the coastal regions in the central part of the east coast. Gillnet and bottom longline fisheries fished walleye pollock mainly in the areas of around Sokcho and Jumunjin during January~February and December. Relationship between CPUEs' values from danish seine fishery and trawl fishery was used to standardize fishing effort to apply to surplus production model for estimating maximum sustainable yield (MSY) and optimum fish effort (F-opt) at MSY. The results suggested a MSY of 114, 000 M/T with an estimated F-opt of 173, 000 hauls per year. Based on the estimates of MSY and F-opt, MEY was estimated to be about 94, 000 M/T with a range of 81, 000 to 103, 000 M/T and E-opt 100, 000 hauls per year with a range of 80, 000 to 120, 000 hauls. The estimated values of MEY and E-opt corresponded to 82% of MSY and 58% of F-opt, respectively. An optimal situation in the fishing effort level, which can envisage either simultaneously maximum yield or maximum benefit for both danish seine fishery and trawl fishery, was determined from relationship between revenue and cost of running the fleet : the optimal fishing effort of danish seine fishery was about 52, 000 hauls per year, corresponding to 50 danish seiners and 27, 000 hauls per year which is equal nearly to 36 trawlers, respectively. It was anticipated that the net income from sustainable yield estimated from the respective optimal fishing effort of the two fisheries will be about 3, 800 million won for danish seine fishery and 1, 000 million won for trawl fishery.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.603-614
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• 2008

End-uses of household water have been changed by a life style, housing type, weather, water rate and water supply facilities etc. and those variables can be considered as an internal and exogenous factors to estimate long-term demand forecasts. Analysis of influential factors on water consumption in households would give an explanation to cause on the change of trend and would help predicting the water demand of end-use in household. The purpose of this study is to analyze the demand trends and patterns of household water uses by metering and questionnaire such as occupation, revenue, numbers of family member, housing types, age, floor area and installation of water saving device, etc. The peak water uses were shown at Saturday among weekdays and July in a year based on the analysis results of water use pattern. A steep increase of total water volume can be found in the analysis of water demand trend according to temperature from $-14^{\circ}C$ to $0^{\circ}C$, while there are no significant variations in the phase of more than $0^{\circ}C$, with an almost stable demand. Washbowl water shows the highest and toilet water shows the lowest relation with temperature in correlation analysis results. In the results of ANOVA to find the significant difference in each unit water use by exogenous factors such as housing type, occupation, number of generation, residential area and income et al., difference was shown in bathtub water by housing type and shown in kitchen, toilet and miscellaneous water by numbers of resident. Especially, definite differences in components except washbowl and bathtub water, could be found by numbers of resident. Based on the result, average residents in a house should be carefully considered and the results can be applied as reference information, in decision making process for predicting water demand and establishing water conservation policy. It is expected that these can be used as design factors in planning stage for water and wastewater facilities.