This paper was to evaluate social enterprises’ management efficiency with Data Envelope Analysis (DEA). The data was based on the 168 social enterprises’ of annual performance reports published in 2015. The research focused on to measure both financial efficiency and social impact of the companies simultaneously. To apply DEA, the paper classified the enterprises into seven types based on types of socal impacts which each company provides before the estimation of the efficiency. The research results showed that group D, which employes disadvantaged people, provides social services and shares resources was the most efficient group and had higest net worths in Pure Technical Efficiency. In contrast, Group B, which only employs social advantage people and provides social service, was the least efficient one. The research suggests a practical and efficient framework in measuring social enterprises’ management efficiency, including both the financial performance and social impacts simultaneously with their self-publishing reports. Because the Korea Social Enterprise Promotion Agency does not open business reports which social enterprises submit each year, there are basic limitations on researchers attempting to analyse with data from all social enterprises in Korea. Thus, this study dealt with only 10% of the social enterprises which self-published their performance report on the Korea Social Enterprise Promotion Agency’s web site. Regardless of these limitations, this study suggested substantial methods to estimate management efficiency with the self-published reports. Because self-publishing is increasing each year, it will be the main source of information for researchers in examining and evaluating social enterprises’ financial performance or social contribution. The research suggests a practical and efficient framework in measuring social enterprises’ management efficiency, including both the financial performance and social impacts simultaneously with their self-publishing reports. The research results suggest not only list of efficient enterprises but also methods of improvement for less efficient enterprises.

Due to the rapid change of global business environment, the growth of China’s steel industry and the inflow of cheap products, domestic steel industry is faced on downward trend. The change of business paradigms from a quantitative growth to a qualitative product is needed in this steel industry. In this environment, it is very important for domestic steel distribution companies to secure their competitiveness by selecting good supply companies through a efficient procurement strategy and effective method. This study tried to find out the success factors of steel distribution industry based on survey research from experts. Weighted values of each factors were found by using AHP (analytic hierarchy process) analysis. The weighted values were applied to DEA(data envelopment analysis) model and eventually the best steel supply company were selected. This paper used 29 domestic steel distribution firms for case example and 5 steps of decision process to select good vendors were suggested.This study used quality, price, delivery and finance as a selection criteria. Using this four criterions, nine variable were suggested. Which were product diversity, base price, discount, payment position, average delivery date, urgency order responsibility and financial condition. These variables were used as a output variable of DEA. Sales and facilities were used as an input variable. Pairwise comparison was conducted using these variables. The weighted value calculated by AHP pairwise comparison were used for DEA analysis. Through the analysis of DEA efficiency process, good DMU (decision making unit) were recommended as a steel supply company. The domestic case example was used to show the effectiveness of this study.

본 연구는 3개의 투입변수와 3개의 산출변수로 구성된 DEA법을 이용하여 우리나라 항만의 노무효율성을 측정 평가하였다. 대상항만의 전체 기술적 효율성은 평균 94.18% 수준이었으며, 순수 기술적 효율성은 100%로 나타났고 규모의 효율성은 94.18%로 전체 기술적 비효율성이 가장 높게 나타났다. 분석결과 7개의 항만은 효율적인 항만으로 측정되었고 4개의 항만은 비효율적 항만으로 측정되었다. 4개의 비효율적 항만중 규모에 대한 수익체증은 동해항으로 나타났다. 그러나 비효율적인 항만들은 생산규모의 비효율성보다 자원운영의 비효율성이 높은 것으로 나타났다. 한편 초효율법을 이용하여 효율적인 항만의 우선순위를 분석한 결과 인천항, 목포항, 평택당진항, 마산항, 여수광양항, 제주항, 군산대산항 순으로 효율성이 높은 것으로 나타났다. 특히 비효율적인 부산항은 목포항 및 인천항을 벤치마킹하여 항만 물동량의 증대, 장비의 현대화 및 노무효율성의 향상을 위해 전면적인 노무상용화가 필요하다.

본 사례는 공작기계산업의 A사에서 수행한 R&D 개발완료 과제 79건을 대상으로 R&D 효율성을 DEA를 활용하여 분석하고, 그 개선방안을 제시한 것이다. DEA 분석에서투입변수는 R&D 투자비와 연구인력 맨먼스, 산출변수는 개발기간 목표달성률과 예상매출액(5년간)으로 설정하였으며, 표본은 제품, 선행기술, 제어기술로 구분하여 분석하였다. 여기서선행기술은 제품성능을 위한 요소기술과 응용프로그램을 개발하는 것이고 제어기술은 컴퓨터를 토대로 수치제어 프로그램을 설계하는 것이다. 분석결과에 따르면 제품, 제어기술, 선행기술 순으로 효율적으로 운영되고 있어 선행기술의 효율성이 가장 낮았다. 그 이유는 선행기술의 불학실성에 기인한다. 선행기술은 개발목표를 정하기 어렵고 개발계획도 수립하기 어렵다. 심지어 운영하는 과정에도 환경변화가 영향을 미친다. 투자효율성 분석결과에서 CRS는 제품 34.6%, 선행기술 14.3%, 제어기술 38.9%이다. IRS는 제품 53.8%, 선행기술 85.7%, 제어기술 38.9%이다. DRS는 제품 11.5%, 선행기술0%, 제어기술 22.2%이다. 전체적으로 본 사례는 과다투입보다는 과소투입이 문제가 되고 있다. 이는 R&D 투자 부족을 의미한다. 주목할 부분은 기업의 미래 경쟁력이 될 수 있는 응용기술에 대한 과소투입이 심각하다는 것이다. 비효율적 DMU의 효율적 운영을 위해서는 최적의 투입량을 관리해야하며, 이것은 준거집단과의 비교를 통해 구할 수 있다.

With the interest on operational efficiency due to the rapid growth of food material distribution industry and food service industry, the study adopts DEA (Data Envelopment Analysis) model and examines to measure the technological, pure technical and scale efficiency those companies engaging in the food material distribution and food service business. As a result of analysis, the companies operating integrated business have relatively higher efficiency than those operating only food material distribution or food service companies while the result indicates that three efficiencies don’t have significant difference depending on whether affiliated companies or not. In the results from the measuring by DEA.

Recently, nanotechnology has grown as one of the leading science technology along with other converging technologies such as biology, information, medicine etc., bringing the continuous investment of the government in nano-related field. However, it is difficult to measure and evaluate the performance of the national research and development programs because of the multidimensional character of the expected outcomes. This study aims to measuring efficiency of the national nanotechnology research and development programs using DEA model. The decision making units are nine nano-related ministries including the Ministry of Science, ICT and Future Planning. The input variables are total expenditure, number of the programs and average expenditure per program. The output variables are science, technology and economic indicator, and the combination of these outputs are respectively measured as seven different DEA cases. The Ministry of Science, ICT and Future was the first efficient ministry in total technical efficiency. Ministry of Agriculture, Food and Rural Affairs and the Ministry of Food and Drug Safety were efficient in pure technical efficiency, when the Ministry of Commerce Industry and Energy took the first in the scale efficiency. The program efficiency was affected by organizational characteristics such as the institution’s scale, the concentration of the research paper or the patent, technology transfer or the commercialization. The result of this study could be utilized in development of the policy in the nanotechnology and the related field. Furthermore, it could be applied for the modification of expenditure management or the adjustment of the research and development programs’ input and output scale for each ministry.

The purpose of this study is to investigate production efficiency of Oceans and Fisheries Human Resources Development Programs Efficiency using Bootstrap-DEA. The study extracts 33 officials curriculum, 11 fisheries managers curriculum for its analytical. First, the study estimates technical, pure technical, and scale efficiency of each curriculums based on traditional DEA under the assumption of CRS and VRS. 8(official 7, managers 1) curriculums are identified as efficient DMUs under the CCR-model, and 13(official 10, managers 3) under the BCC-model. We provide inputs that allow inefficient curriculum to be efficient DMUs on a production frontier, and a reference set for their bench-marking. Second, rank test, Wilcoxon-Mann-Whitney test to find a statistical significance of heterogeneity existing in efficiences between Bootstrap-DEA tenical vs Bootstrap-DEA pure technical was no significant difference. We have identified that G10, 11, 12 13, 25, 31, 33, 39 curriculums are the most efficiently produced in the technical and pure technical efficiency. Also we managed to measure the inefficiency which exists in efficiently produced curriculums when estimating the bias corrected efficiency scores. In Technical efficiency, Operation and facility was significant at the 10%. In Pure technical efficiency, facility was significant at the 10%.

This study analyzed the safety management efficiency through input-oriented BCC Model using DEA by making of Models, in which this study selected the number of staff affiliated with the construction site, number of staff members on the construction team, and number of safety personnel as Input Factor, along with the number of disaster victims and zero-accident accomplished hours as output elements, targeting 40-or-so apartment building construction sites which are being built by 3 domestic construction companies. As a result of efficiency, it was 0.643, the number of efficient DMU was 4. In the aspect of returns to scale, 21 construction sites(52.5%) found to be in a state of increasing returns while 14 construction sites(35%) was in a state of Decreasing returns. The reason for inefficiency was found to lie in technical factors in case of 30 construction sites(75%). Lastly, inefficient DMU is in need of 38.9 % and 66% reduction in site personnel and safety personnel. Based on study results, the 29 construction sites accounting for 72.5% of DMU for safety management efficiency evaluation object turned out to do inefficient safety management that doesn't fit the size of each company.

The objective of this study is to examine the potential of cost reduction and factors affecting production cost of Korean farmers. First, the study estimates technical efficiency, allocation efficiency, and cost efficiency of Korean farmers using DEA. Then, Tobit regressions are conducted to identify factors affecting each of the three efficiency scores. The study uses the Farm Household Economy Survey data from the Korean National Bureau of Statistics for the period from 2008 to 2012. Results from DEA show that overall, technical and cost efficiency scores are low, which suggests a great potential of cost reduction for Korean farmers. The results also show relatively large differences in efficiency scores across provinces. Tobit results suggest that farm size, number of family members, operation costs, and invested capital amount are major factors affecting farm efficiencies.

In this paper, scale efficiencies and relative efficiencies of R&D projects in Industrial Technology Program, sponsored by Ministry of Trade, Industry and Energy, Korea, are calculated and compared. For the process, various DEA (Data Envelopment Analysis) models are adopted as major techniques. For DEA, two stage input oriented models are utilized for calculating the efficiencies. Next, the calculated efficiencies are grouped according to their subprograms (Industrial Material, IT Fusion, Nano Fusion, Energy Resources, and Resources Technology) and recipient types (Public Enterprise, Large Enterprise, Medium Enterprise, Small Enterprise, Lab., Univ., and etc.) respectively. Then various subprograms and recipient types are compared in terms of scale efficiencies (CCR models) and relative efficiencies (BCC models). In addition, the correlation between the 1st stage relative efficiencies and the 2nd stage relative efficiencies is calculated, from which the causal relationship between them can be inferred. Statistical analysis shows that the amount of input, in general, should increase in order to be scale efficient (CCR models) regardless of the subprograms and recipient types, that the 1st and 2nd stage relative efficiencies are different in terms of the programs and recipient types (BCC models), and that there is no significant correlation between the 1st stage relative efficiencies and the 2nd stage relative efficiencies. However, the results should be used only as reference because the goal each and every subprogram has is different and the situation each and every recipient type faces is different. In addition, the causal link between the 1st stage relative efficiencies and the 2nd relative efficiencies is not considered, which, in turn, is the limitation of this paper.

This study is to analyze the efficiency of Korean sea food manufacturing using Data Envelopment Analysis. Firstly, based on an output oriented traditional CCR, BCC model, the study estimated the efficiency scores. The average estimates of technical, pure technical, and scale efficiency turned out 0.6517, 0.7184, 0.9074 respectively, which are separated for 50 marine corporations. The 10 DMUs were efficient under CCR model while the 17 DMUs under BCC model. Also, the study suggested that the operating profit of the two output factors should be more increased relatively and averagely from the viewpoint of efficiency improvement. Secondly, super efficiency scores are estimated under super efficiency and SBM model. As a result, it came to be possible to distinguish and rank the efficiency of the efficient DMUs. The highest score was 4.2975 under Super-CCR, was 2.4947 under Super-BCC, was 2.7160 under SBM-Super- CCR, and was 1.5319 under SBM-Super-BCC model. The average estimates of super efficiency were 0.76 and 0.82 under Super-CCR and Super-BCC model respectively, and were 0.61 and 0.67 under SBM-Super- CCR and SBM-Super-BCC model. Finally, the study conducted a rank-sum test, Wilcoxon-Mann-Whitney test, to find a statistical significance of heterogeneity existing in efficiencies among the sample corporations. The result showed that there was a significant difference in average efficiency between Dried, Salted product manufacturing and Frozen product manufacturing under BCC-Super efficiency model at 10% level of significance. Furthermore, TOBIT model was applied to find out the potential factors that might influence the efficiency, Wilcoxonand the results showed debt and sales cost influenced all of the technical, pure technical, and scale efficiency, while net profit influenced only the technical efficiency.

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.

Selection of efficient supplier is a very important process as risk or uncertainty of a supply chain and its environment are increasing. Previous deterministic DEA and probabilistic DEAs are very limited to handle various types of risk and uncertainty. In this paper, I propose an improved probabilistic DEA which consists of two steps; Monte Carlo simulation and statistical decision making. The simulation results show that the proposed method is proper to distinguish supplier’s performance and provide statistical decision background.

The conventional clustering approaches are mostly based on minimizing total dissimilarity of input and output. However, the clustering approach may not be helpful in some cases of clustering decision making units (DMUs) with production feature converting multiple inputs into multiple outputs because it does not care converting functions. Data envelopment analysis (DEA) has been widely applied for efficiency estimation of such DMUs since it has non-parametric characteristics. We propose a new clustering method to identify groups of DMUs that are similar in terms of their input-output profiles. A real world example is given to explain the use and effectiveness of the proposed method. And we calculate similarity value between its result and the result of a conventional clustering method applied to the example. After the efficiency value was added to input of K-means algorithm, we calculate new similarity value and compare it with the previous one.

Due to the severe market conditions, pre-entrepreneur seeks to start their business through franchise company. This paper, using the data envelopment analysis(DEA) method, examines efficiency of a group of franchise company in order to provide efficiency information with pre-entrepreneur. Output-oriented DEA model is applied in the investigation of efficiency, and the overall efficiency score is decomposed into pure technical efficiency and scale efficiency. The input variables selected to evaluate the efficiency are franchise deposit, franchise contribution cost and the output variables are sales and number of franchises, and length of business. The results of this paper show franchise industry have the low level of overall efficiency and the main sources of inefficiency is found technical rather than scale. As a result, this paper provides not only the current status of efficiency information of a franchise with pre-entrepreneur but also give warning when they sign-up with franchise business.

Because of the changing educational environments, Korean universities have to stand up to the challenge of enhancing their performances in educational activities. Therefore, Korean universities should seek ways to improve its competitiveness. The evaluation of Korean universities has been conducted by the Government and other media agencies like JoongAng’s Daily to promote the development of universities. The purpose of this study is to evaluate and compare the relative efficiency of Korean universities using DEA (Data Envelopment Analysis) and AHP (Analytic Hierarchy Process) models. To produce reasonable results, major input and output variables have been determined in a step using a Profiling method, Spearman correlation analysis and AHP model. Also, this study shows that the relative efficiency for Korean universities is obtained not only based on quantity of output, but also on the basis of the quality of the output. Drawing upon the results of the analysis, this study provides a comprehensive and practical method for evaluating the performance of universities in terms of efficiency.

The government expands its investment on R&D programs for economic growth, thus there is growing attention on the result of R&D Programs. This study proposes more improved measuring method for efficiency when the number of R&D programs is not enough to be for measuring efficiency analysis. It provides more various application method of factors on efficiency analysis. This study analyzes the influence of each input factor on efficiency by using partial efficiency concept. And it also determines input factors in similar influence throughout Spearman correlation coefficient. Finally, it suggests new method to improve discriminatory power of efficiency analysis by determining representative factors. Also, the proposed method can be practiced not only for national R&D programs, but also for other fields of research.

Following the Enterprise's globalization grows, we are going to focus on the performance of branch more. Choosing the performance index is very important today. Thus, this research is regarding the methodology of new measurement of performance in branch business and consist of DEA(Data envelop analysis) and ANP(Analytic network process). First, I find out weight values using ANP, then using it as criterion, I choose the main influential factors on branch's activities and production. Then I suggest DEA-2Stage methodology and conduct the analysis of actual proof on the public enterprise The DEA-2Stage methodology is for discrimination the activity's effectiveness and the production's efficiency. The DEA-2Stage in branch methodology can help guide the strategy's direction as well as can measure the performance. Also the result of ANP is from the paired comparison made by current personnel and professional so it can applicate the suggestion of the branch strategy in future. Based on the DEA result, it also give the benchmark branch model to the branch which has low effectiveness level.