• Environmental and Resource Economics Review
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• v.19 no.1
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• pp.3-21
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• 2010

By the significant structural change in 1999, a partial privatization has occurred in Korean fossil-fuel power generation sector. Under the current price scheme wholesale electricity price is dependent on output size, and hence, may not satisfy the assumption of price-taking producers. The purpose of our study is constructing the productivity change measurements of Korean power generation sector taking into account possibly imperfect competition and variable returns to scale. Our approach based on Harrison (1994) and Levinsohn (1993) derives the plant-level productivity measurements of the period between 2001 and 2007, as well as the measurements of mark-ups and returns to scale. It is shown that the mark-up size is dependent on the plants' fuel type and is decreasing over time. Allowing for imperfect competition and variable returns to scale adjusts the productivity measurements substantially.

• Journal of Labour Economics
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• v.38 no.1
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• pp.1-30
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• 2015

The aggregate matching function is estimated to explain dynamics among job seekers, vacancies and new hires in Korea. Due to measurement errors inherent in vacancies data, I introduce a latent variable for job openings and use the instrumental variables to correct its endogeneity. Matching efficiency is also estimated using some explanatory variables like job seekers' characteristics and public employment services. The result shows that Korea's matching function also exhibits a constant returns to scale.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.108-119
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• 2015

This study intends to propose a non-oriented DEA based game cross-efficiency approach for supplier selection. With a discussion on the choice of DEA models and approaches that are most appropriate for supplier selection, we propose a game cross efficiency model based upon the non-oriented variable returns-to-scale RAM DEA by adapting the existing game cross efficiency model based upon the oriented constant returns-to-scale CCR DEA. We develop the RAM game cross efficiency model and a convergent iterative solution procedure to find the best game cross efficiency scores that constitute a Nash equilibrium. We illustrate the proposed model with two data sets of supplier selection, and demonstrate that significantly different results are obtained when compared with the existing approaches.

• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.45-58
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• 2010

This study estimated the technical efficiency of coastal composite fishery in Korea by using the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA) methods, and the results on the respective method were compared. In the DEA method, the constant returns to scale (CRS) and the variable returns to scale (VRS) output-oriented DEA models were separated and technical efficiencies were estimated, respectively. The average estimated value of technical efficiency by the SFA method (0.633) was found to be lower than that by the VRS-DEA method (0.738), while it was higher than that by the CRS-DEA method (0.479). It was found that strong correlation exists between the SFA method and the VRS-DEA method. The method which can utilize both methods in mutually complementing way for the estimation of technical efficiency was also considered.

• International Area Studies Review
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• v.15 no.3
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• pp.239-261
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• 2011

The cyclicality of productivity has been one of the essential issues in macroeconomics. Since Solow(1957) developed the dominant approach to the measurement of productivity growth, Solow's approach, which assumes the perfect competition, the constant returns to scale, and the full use of input factor has been modified particularly in Hall's(1990) and Basu's(1996) works. Their researches take account of market power, returns to scale, and variable factor utilization. This paper establishes the empirical model based on Hall's(1990) and Basu's(1996) models, estimates 4 types of Solow's reidual in manufacturing and 2 service industries over the period 1975:1-2010:4, and analyzes the cyclicality of measured productivity. The result proved the measured productivity to be procyclical in manufacturing industries and electricity and water industry, and in contrast to the Basu's, the variable factor utilization transformed the countercyclicality of measured productivity into its procyclicality in the Korean economy.

• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.129-151
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• 2010

This study is to analyze the efficiency of Korean fishing ports using DEA. First, the study calculated the efficiency scores based on a CCR-BCC framework and hence technical, pure technical, and scale efficiency scores are seperated for the 38 fishing ports under study. The Average of technical, pure technical, and scale efficiency are turned out to be 0.6834, 0.8582, and 0.7774 respectively. The 15 fishing ports are fully efficient under the constant returns to scale while 21 fishing ports under the variable returns to scale. Second, the super efficiency scores are also calculated under the radial model without the consideration of slacks. The highest score is turned out to be 4.4984 for the P16 fishing port with the average score of 0.9652 for the entire fishing ports. Nevertheless, P16 fishing port has showed up only once as a reference set. On the other hand, P34 fishing port has showed up 11 times as a reference set, which scored the second highest score of 2.9815. Finally the super efficiency scores are calculated under the non-radial model with the explicit consideration of slacks. Now the P34 fishing port scored the highest score of 2.3424 with even 15 times referred to a bench-mark. Therefore the importance of P34 fishing port is emphasized once again on the field of bench-marking for the efficiency of fishing ports. When the targets for the input factors to improve the efficiency of each DMU are calculated the area of fishing port needs the most adjustment to be reduced for 40.36% on the average, while the cosignment sales area does the least adjustment for 13.70%.

• 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.

• Health Policy and Management
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• v.6 no.2
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• pp.91-114
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• 1996

In this research, the Data Envelopment Analysis(DEA) was applied to measure production efficiency of Public Corporation Medical Centers(PCMCs) operating in Korea. The focus of this research is triple. First, identifing convenience and usefulness of DEA to measure the relative efficiency among PCMCs. Second, assessing magnitudes of the relative efficiency for each PCMC. Third, adding insights into some factors resulting inefficiency in PCMCs. Then, in this paper technical efficiency and scale efficiency measured by DEA[introduced by Charnes, Cooper, and Rhoides(1978) and Banker, Charnes, and Cooper(1984)] were analyzed and a new separate variable was introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decresing returns to scale(in multiple input and output situations). And a multi-factor Tobit analysis was conducted to see which variables are associated with PCMC's efficiency.

• Environmental and Resource Economics Review
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• v.28 no.3
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• pp.415-435
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• 2019

The purpose of this study is to analyze the returns to scale by estimating the bigeye tuna production function of Korean distant longline fisheries in WCFPC waters. In the analysis, number of crews, vessel tonnage, number of hooks, and bigeye tuna biomass are used as input variables and the catch amount of bigeye tuna is used as an output variable in the Cobb-Douglas production function. Prior to the function estimation, the biomass of bigeye tuna was estimated by the Bayesian state-space model. Results showed that the fixed effect model was selected based on the hausman test, and vessel tonnage, hooks, and biomass would have direct effects on the catch amount. In addition, it was shown that the bigeye tuna distant longline fisheries in WCFPC water would have increasing returns to scale.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.4
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• pp.137-152
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• 2011

The purpose of this study is to estimate efficiency of agricultural business corporations using Data Envelopment Analysis. A proposed method employs a bootstrapping approach to generate efficiency estimates through Monte Carlo simulation re-sampling process. The technical efficiency, pure technical efficiency, and scale efficiency measure of the corporations is 0.749 0.790, 0.948 respectively. Among the 692 agricultural business corporations, the number of Increasing Returns to Scale (IRS)-type corporations was analyzed to be 539(77.9%). The number of Constant Returns to Scale (CRS)-type corporations was 108(15.6%), and that of Decreasing Returns to Scale (DRS)-type corporations was 45(6.5%). Since an increase in input is lower than an increase in output in IRS, an increase in input factors such as new investments is required. The Tobit model suggests that the type of corporation, capital level, and period of operation affect the efficiency score more than others. The positive coefficient of capital level and period of operation variable indicates that efficiency score increases as capital level and period of operation increases.