• The Korean Journal of Franchise Management
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• v.6 no.1
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• pp.1-20
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• 2015

Home Meal Replacement (HMR) products are ready-to-eat or pre-cooked food products that are consumed at daily home. HMR market has grown rapidly due to societal changes: increases in female social activities, silver population, and one-person households. Consumption channels of HMR can be classified into take-out, delivery, and retail. In Korean HMR market, retail sector is largely growing, but companies are focusing their business on the home delivery sector. Moreover, franchise companies are expanding their areal coverage in the HMR market based on their multi-unit strategy. However, more research on the HMR market is needed as existing studies are limited in conceptualization, classification, and processed food from malls or home-shopping channels. Therefore, we conducted the efficiency analysis on Gukseonsaeng, one of franchises that applied the take-out channel, using DEA method. According to the research on 29 franchisees of Gukseonsaeng, 77.9% of input appeared inefficient for technical efficiency, while 53.3% of input appeared inefficient for scale efficiency. Thus, we found that franchises of Gukseonsaeng are structured in increasing returns to scale (IRS), so enhancing efficiency by expanding scales need to be implemented.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.315-320
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• 2013

The aim of this study is to compare efficiency and Total Factor Productivity(TFP) between Korean and Japanese construction firms in Korea and Japan over the period of 2005-2011. The results of this study are as follows. Efficiency scores of Korean construction firms are 0.797, and Japanese construction firms are 0.921. Second, annual total factor productivity growth of Korean construction firms is 0.5% and technical progress do much for TFP decrease. However Japanese construction firms marked annual increasing of 2.5% of TFP. Third, technical progress contributed in TFP increase of construction firms in Korea. Korean construction firms, however, relatively lagged behind Japanese construction firms in technical progress. Therefore, Korean construction firms need strategies to achieve technical advances including adopting new technology or process innovation to maintain competitiveness, survive, and develop in the future competition with Japan.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.118-120
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• 2023

Increasing port competition driven by the containerisation has motivated ports and terminals to focus on their performance to efficiently utilise the available resources and to make strategic decisions in port development and expansion. With both inter-port andintra-port competition increasing in the port of Colombo, this study aims to measure the efficiency of the container terminals in Colombo comparing to terminals in the port of Busan using the DEA window analysis to determine their operational efficiency and to provide suggestions for future port development activities. Multiple window analyses were conducted using CCR and BCC models with different orientations and window lengths to compare the efficiencies of 11 DMUs in both ports during the period from 2015-2019 to measure the efficiencies prior to the COVID-19 pandemic. Results revealed the largest terminal operator, PNC in Busan, to be the most efficient overall, while the second highest efficiency was recorded by one of the smallest terminal operators, SAGT in Colombo, among the sample. Although use of DEA in port performance measurement has been popular for many years, efficiency measurements in the port of Colombo, the main hub port in the South Asian region, has not been comprehensively studied so far.

• Korea Trade Review
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• v.45 no.1
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• pp.47-64
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• 2020

For the past few years, the Korean government has been consistently expanding its national research & development budget to accelerate economic growth through technology innovation and the enhancement of international competitiveness in global markets. The objective of this paper is to define the concept and analyze the current status of national R&D programs by measuring R&D efficiencies. We determine R&D efficiency by reflecting inputs and outcomes of the five main agricultural R&D programs between 2010 to 2015, and by categorizing and regrouping figures that may affect R&D performance. Among 1,128 targeted projects, 832 projects with patents and thesis were selected for analysis in terms of measuring technology efficiency, pure technology efficiency, and efficiency of scale. Also, the Kruskal-Wallis test was also utilized as well. As a result of empirical analysis, figures that affected the efficiency level of national R&D programs included differences in research resources, research management levels and skills, and research field. This study can be utilized as a reference for re-establishing national agricultural R&D policies, such as enhancement of national technology competitiveness in the global market environment, improving and adapting to new agricultural conditions, market expansion, national agricultural R&D efficiency, aging rural population, agricultural management cost increase, and climate change mitigation.

• Journal of Navigation and Port Research
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• v.30 no.10 s.116
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• pp.793-800
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• 2006

The purpose of this paper is to show a way for extracting the core input and output variable in Korean seaports by using principal component analysis and DEA(data envelopment analysis). Two inputs(birthing capacity, and cargo handling capacity) and three outputs(export cargo handling amount, import cargo handling amount, and number of ship calls), and three cross sectional data(1995, 2000, and 2004) for 26 Korean seaports are considered for measuring the efficiencies of 21 DEA models. 21 models can be treated as variables and efficiencies as observations for extracting the core inputs and outputs variables by using principal component analysis. An empirical main result indicates that core input variable is cargo handling capacity, and core output is the number of ship calls. The Korean seaport authority can adopt the DEA and principal component analysis for deciding the development and investment to each seaport.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.191-196
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• 2004

This paper is to measure and ealuates the technical efficiency, pure technical efficiency and scale efficiency with three inputs and two outputs with the use of DEA(data envelopment analysis) in Korean RCC(Rescue Co-ordination Center/RSC(Rescue Sub-Center). Several conclusion emerge. first the average efficiency of overall technical efficiency measure about $91.03\%$ and pure technical efficiency $96.80\%$ is much large then scale efficiency $93.83\%$. It means that inefficiency has much more to do whit the inefficient utilization of resources rather then the scale of production. second, DRS(decreasing return to scale) is Tongyeong and IRS(increasing return to scale) is Incheon, Taean, Gunsan, Yeosu, Ulsan, Donghae in RCC/RSC. finally, inefficiency RCC/RSC. have to benchmarking with reference sets.

• Korea Journal of Hospital Management
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• v.10 no.1
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• pp.71-92
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• 2005

The purpose of this study is to analyze the efficiency in management of general hospitals and investigate the major factors on efficiency. Specifically, the management of each general hospital is evaluated by using Data Envelopment Analysis(DEA) technique which is a nonparametric statistical method for measurement of efficiency. Then, the influencing factors are investigated through analyses of Decision-Tree Model and Tobit Regression. The target hospitals were general hospitals in which bed sizes are between 200 and 500 among a total of 276 general hospitals. The main data of financial indicators were collected from 48 hospitals, and it was analyzed by using two statistical models. For Model I, three input and two output variables were used for efficiency evaluation. In particular, three input variables were the number of medical doctors, the number of paramedical personnel, and the bed size. And, two output variables were the numbers of inpatients and outpatients per year, adjusted by bed-size. The results of DEA analysis showed that only seven out of 48 hospitals(15%) turned out to be efficient. The decision-tree analysis also showed that there were six significant influencing factors for Model I. Six factors for Model I were Bed Occupancy Rate, Cost per Adjusted Inpatient, New Visit Ratio of Outpatients, Retired Ratio, Net Profit to Gross Revenues, Net Profit to Total Assets. In addition, the management efficiency of hospital is proved to increase as profit and patient-induced indicators increase and cost-related indicators decrease, by the Tobit regression model of independent variables derived from the decision-tree analysis. This study may be contributable to the development of analytic methodology regarding the efficiency of hospital management in that it suggests the synthetic measures by utilizing DEA model instead of suggesting simple ratio-analyzing results.

• The Journal of Fisheries Business Administration
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• v.40 no.1
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• pp.1-26
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• 2009

The aquaculture management considers the maintenance of households lifehood more than profit maximization. As aquaculture industry has developed enterprise farms appeared, and the small and the large scale farms coexist. The features of coexistence could be summarized as followings. First of all, the large scale farms show the higher net profit while the small scale farms show the higher profit per 1ha and the earning rate. Secondly, in the case of over 2ha, the earning rate is stable in spite of the scale expansion. Moreover, in processing method, dried seaweed occupy the biggest proportion in the small scale farms while the raw seaweed occupy the biggest proportion in the large scale farms. Lastly, the scale of farms becomes larger, the participation rate of household labor rises. This thesis analyses the efficiency of Korean seaweed farms in the way of DEA model and suggests the improvements for the efficiency management. The mean technical, pure technical and scale efficiencies were measured to be 0.88, 0.96 and 0.91, respectively. Among the 20 farms included in the analysis, 10 were technically efficient and 12 were scale efficient. In conclusion, it is shown that the aquaculture farms has been becoming the form of coexistence. This appearance results in the effort for reducing the cost in the small scale farms and in profit maximization in the large scale farms. On the other hand, middle scale farms is inefficient compared with the small or large scale farms. Therefore, in order to achieve the efficiency, it is necessary to accomplish economy of scale by extending farm size or to cut expenses by reducing farm area. In other word, the efforts for achieving the efficiency is required in a different direction in spite of the same scale.

• International Commerce and Information Review
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• v.16 no.4
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• pp.55-75
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• 2014

Non-parametric method such as technology efficiency, DEA/Window model and Malmquist Productivity Index (MPI) are used to measure efficiency and productivity of ICT (Information and Communication Technology) manufacturing industry and service industry over the period 2007-2011. The results of this paper indicate following: (1) Technology efficiency of the ICT manufacturing industry were found as the range of 0.34 and 0.39 over the sample period. Technology efficiency of the ICT service industry were found as the range of 0.16 and 0.20 over the sample period. (2) The geometric average of the Malmquist TFP indexes on ICT manufacturing industry indicated the productivity improvement an average of 8.3 percent. The geometric average of the Malmquist TFP indexes on ICT service industry indicated the productivity improvement an average of 1.6 percent. (3) TIER analysis result on ICT manufacturing industry showed that optimal bench marking made by storage devices${\rightarrow}$wireless communication equipment${\rightarrow}$broadcasting equipment${\rightarrow}$radio, recording and playback devices${\rightarrow}$computers, printers, video and audio-visual equipment path. TIER analysis result on ICT service industry indicated that optimal bench marking made by computers and packaged software${\rightarrow}$wired communication${\rightarrow}$communication, information, detection equipment${\rightarrow}$consulting and construction for computer systems integration${\rightarrow}$industrial machinery and equipment rental${\rightarrow}$telecommunications reseller${\rightarrow}$system software development and delivery${\rightarrow}$hosting path.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.125-136
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• 2016

The external R&D, which includes the adoption of the external technology and knowledge in addition to the internal R&D, is one of important factors for the innovation. Especially for small and medium-sized enterprises (SMEs), the external R&D has been considered as a key factor to carry out the innovation more efficiently due to the limitations of their resources and capacities. However, most of extant studies related to external R&D have focused on analyzing the influence of external R&D on innovation outputs or outcomes. Only a few studies have explored the impact of external R&D on the innovation efficiency. This study therefore investigates whether the external R&D effects the industry's innovation efficiency and productivity. On this study, we used Korean manufacturing industry data of SMEs from 2012 to 2014 and employed a global Malmquist productivity analysis technique, which is based on the Data Envelopment Analysis (DEA), to assess the innovation efficiency and productivity. Innovation performances of external R&D group and internal R&D group are compared. Then, the sectoral patterns of both innovation efficiency and productivity are analyzed with respect to the technological intensity, which is introduced by OECD. The results show that the gap of innovation efficiency between external and internal R&D groups has gradually decreased because of the continuous improvement of the external R&D group's performance, while the external R&D group lag behind the internal R&D group. In addition, patterns of the innovation efficiency and productivity change were different depending on the technological intensity, which means that the higher the technological intensity, the greater the effect of external R&D.