• Korean Management Science Review
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• v.28 no.3
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• pp.61-72
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• 2011

This study suggests a DEA(Data Envelopment Analysis) based model to evaluate the value of corporate stock. The model integrating PER(Price-Earning Ratio), PBR(Price-BookValue Ratio), PSR(Price-Sales Ratio) and volatility in DEA structure has an advantage of overcome the limitation of traditional financial ratio based models. In order to show the effectiveness of the suggested model. we compare the performance of portfolio composed by DEA approach with those of portfolios made by traditional approaches such as PER, PBR, and PSR in terms of stock return and volatility. Specifically, we use the data of all the enterprises listed on the S&P 500 in the U.S. in 2007 and 2009 as the sample data for the experiments. The results of the experiments show that the performance of the DEA approach is clearly better than those of other approaches. Particularly, in sharply plummeting market, the performance of the DEA approach is shown to be prominently better than those of other approaches as the DEA approach reflects investment risk as well as profitability and growth. The DEA score combining the existing investment indices may serve as a useful barometer for selecting a stable and profitable portfolio.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.555-564
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• 2020

The purpose of this study is to analyze the efficiency of research institutes of futures companies, and to promote the development of futures market and real economy. This study employs DEA-solver software to conduct super-efficiency data envelopment analysis (SE-DEA), and also selects 40 representative futures research institutes in China as decision-making units (DMUs). For data of input and output indicators, we collect from the China Futures Association, Futures Daily, Hexun.com and Webstock.com respectively, and the time duration is the 103 trading days between from October 2019 to February 2020. Then the indicator for the strategy accuracy rate is calculated separately by analyzing the strategies published by each DMUs in public media. In conclusions, most institutes have excessive investment in human resources, and also have insufficient strategy accuracy rate and insufficient published research reports. The findings of this study suggest that Chinese futures companies need to improve the efficiency of research institutes, and better meet the demand of the financial market. In fact, the analysis of the efficiency of the futures company research institute has not been found in the literature worldwide, Application of DEA model in efficiency analysis of securities and futures research institutions and establishment of indicators are the innovations of this paper.

• The Journal of Fisheries Business Administration
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• v.37 no.1 s.70
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• pp.1-24
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• 2006

Reducing fishing capacity is one of current issues in the international fisheries. This is because that increased fishing capacity has caused not only fish stocks to be depleted, but also additional fishing costs to be incurred, which resulted in reduction of economically viability of fisheries. For this reason, FAO adopted the International Plan of Action for the Management of Fishing Capacity' in 1999 and recommended member countries to estimate fishing capacity and to implement the policy to reduce fishing capacity. This study is aimed to measure fishing capacity of the Large Purse Seines Fishery that is one of offshore fisheries in Korea using both Peak - to - Peak Analysis and Data Envelopment Analysis in order to provide a policy information for preparation of domestic plan of action for the management of fishing capacity. The results of PTP Analysis were almost similar to those of DEA Analysis. The DEA results showed that the capacity utilization in 2004 was about 75%, it was obvious the capacity did not utilize enough. The sensitivity analysis on DEA results indicated that 24% of the number of ships, 26% of the tonnages, or 29% of the horse powers should be reduced if the present catch remained. In addition, if the catch remains at the MSY base level of large purse seines, the analysis suggested that the number of ships, tonnages and horse powers should be reduced by 15%, 18%, and 21% respectively.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.297-304
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• 2020

This paper applies the Data Envelopment Analysis (DEA) to compute the managerial efficiency of 30 insurance companies listed on the Saudi stock exchange for the duration of four years from 2015 to 2018. The companies taken as a sample of study included both conventional and Takaful insurance companies. The insurance sector of KSA is one of the largest sectors in the country, contributing a substantial percentage in the non-oil economy. Efficiency measurement and evaluation will provide a venue to introspect and benchmark frontiers to the sector. In the present study, we have utilized the basic Banker Charnes Cooper and Charnes Copper Rhodes models of DEA. Two inputs, namely, general & administrative expenses and policy & acquisition costs, and two outputs (Net premium earned and Investment Income & other incomes) were taken for efficiency calculations. The final outcomes of the study reveal that a good number of insurance companies operating in KSA are found to be efficient on managerial efficiency scale. Three firms remain the leader on the frontier of the managerial efficiency. And no company found with zero (0) efficiency or a negative efficiency. It is expected that the outcome of the study will provide benchmarks to managers and a road map to further improvement.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.628-641
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• 2014

Stepwise efficiency improvement in data envelopment analysis (DEA)-based benchmarking is a realistic and effective method by which inefficient decision making units (DMUs) can choose benchmarks in a stepwise manner and, thereby, effect gradual performance improvement. Most of the previous research relevant to stepwise efficiency improvement has focused primarily on how to stratify DMUs into multiple layers and how to select immediate benchmark targets in leading levels for lagging-level DMUs. It can be said that the sequence of benchmark targets was constructed in a myopic way, which can limit its effectiveness. To address this issue, this paper proposes an optimization approach to the construction of a sequence of benchmarks in DEA-based benchmarking, wherein two optimization criteria are employed : similarity of input-output use patterns, and proximity of input-output use levels between DMUs. To illustrate the proposed method, we applied it to the benchmarking of 23 national universities in South Korea.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.1-13
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• 2020

This study aims to measure the efficiency and productivity change of 30 domestic construction companies from 2010 to 2018 using data envelopment analysis(DEA) and Malmquist productivity index (MI). In particular, we used the number of employees, capital stock, and non-current assets as input variables, and sales and net income as ouput variables for the analysis. The dataset used for the analysis of efficiency and productivity changes is the employee profile and financial statements for the companies from 2010 to 2018. We found that the MI of the 30 companies is greater than one since 2013. This is because many years of TEC (Technical Efficiency Change) is greater than 1, which means that the productivity index increases as the TEC increases. In addition, the MI value was less than 1, which lowered the productivity of construction firms in 2018. The results of the study may help decision makers to find effective future management plans by analyzing the internal and external factors.

• Journal of Environmental Policy
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• v.14 no.2
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• pp.27-47
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• 2015

In this paper, we present a new empirical method to estimate the environmental efficiency of decision making units. We propose a model with a new approach that describes a network process consisting of two stages, production and wastewater abatement based on the data extracted from 51 Korean industrial complexes. Taking into account the inter-dependency of two stages, we show a process how to decompose the environmental efficiency into production efficiency and abatement efficiency. Moreover, our new proposed method can be used to explain the information on network relationship between economic growth and environmental protection.

• Korean Journal of Community Nutrition
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• v.12 no.2
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• pp.178-188
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• 2007

This study was performed to suggest a new efficiency measurement indicator is necessary for evaluating management efficiency of food service operations in contract-managed foodservice companies, to distinguish efficient food service providers and inefficient ones by measuring comparative efficiency among food service operations, and to provide guidance for effective management through showing benchmarking targets for improving inefficient food service providers. The subjects of this study were the 93 B&I foodservice Operations of a domestic contract food service company. The analysis was conducted using CCR model in DEA model. A software, 'Frontier analyst', was used for the analysis. Based on the results derived from comparison of efficiency evaluation classified by providers with use of DEA, it was possible to identify efficient food providers and inefficient providers, and subsequently provide benchmarking guidelines for improvement of the inefficient groups. In analyzing the differences between the results of DEA efficiency evaluation by detailed operation status of food service providers, there was significant difference of efficiency outcomes in terms of contract types, while there was no significant difference in terms of business condition.

• Journal of the East Asian Society of Dietary Life
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• v.18 no.2
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• pp.242-252
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• 2008

The objective of this study was to suggest a new efficiency measurement indicator for evaluating the menu management efficiency of decision making units(DMUs) in contract-foodservice operations and to determine the relationship between the DEA(data envelopment analysis) menu efficiency score and menu factors. The results of applying DEA revealed relatively efficient types of service and frequency of meals. The efficient service was shown as a self-service type that operates Monday to Saturday. The considered menu factors included meal price, food cost per meal, meal counts, number of menu items, use of favorite menu use, forecasting error, accuracy of ordering, ratio of inventory, ratio of food loss, use of processed foods and use of prepared vegetables are considered. There were significant correlations between the DEA score and meal price, meal counts, number of menu items, ratio of food loss, accuracy of ordering and use of processed foods respectively. According to the regression results, menu price had a positive influence on the DEA menu efficiency score, and food cost per meal and the use of prepared foods had negative influences respectively.

• International Journal of Contents
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• v.4 no.3
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• pp.1-9
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• 2008

The Korean life insurance industry has undergone profound changes, such as the beginning of the variable insurance in July 2001 and the bancassurance enforcement in August 2003. However, little empirical research has analyzed data that includes the bancassurance of life insurance companies operating in Korea. In response to this lack of research, this paper applies DEA (data envelopment analysis) models to measure and decompose their efficiency. We discovered that life insurance companies operating in Korea are a little different in their composition ratio of inputs and outputs, due to the increased variety of distribution channels and new products. We provided efficiency scores, return to scale, and reference frequencies. We also decomposed CCR, BCC, and SBM efficiency into scale efficiency and MIX efficiency. So, we try to investigate whether the sources of inefficiency were caused by the inefficient operation of DMU, disadvantageous conditions, the difference of the composition ratio in inputs and outputs with reference sets, or any combination of the above. Most companies in the sample display had either constant or decreasing returns to scale. The efficiency rankings were less consistent among models and efficient DMUs. In response to this problem, we used the super-efficiency model to rank them and then compared the rankings of the DMUs among the various models. It was also concluded that the availability of panel data, rather than cross-sectional data, would greatly improve the validity of the efficiency estimates.