PURPOSES : This paper presents a foundational study aimed at strengthening the competitiveness of future overseas construction engineering projects, efficiently guiding investment decisions for the government or private sectors and establishing policy suggestions for areas that need to be supplemented and linked. METHODS : The data envelopment analysis (DEA) model was used to measure the operational efficiency for individual types of work. The DEA model for measuring efficiency uses the representative Charnes, Cooper, and Rhode (CCR) and Banker, Charnes, and Cooper (BCC) models. RESULTS : By using statistics of overseas construction projects and conducting DEA, it was revealed that construction management was most needed in the energy facility sector of overseas construction projects. CONCLUSIONS : Although the capabilities of our country's companies are excellent, it was evident that the energy and industrial facilities sectors, which need to be supplemented to enhance their competitiveness, require policy support that incorporates construction management (CM). Consequently, it was confirmed that the construction management sector needs investment that should continue to be activated in the future. Additional research is needed that considers variables and environments related to overseas construction projects’ on-site conditions. To this end, the government should continue to promote research and government investment linked to CM to make progress in overseas construction sectors.

PURPOSES : This study aims to analyze the efficiency of the safety and management of private highways. METHODS : Variables were selected based on the data and performance related to the safety of 18 private highways. The appropriateness of operations management was reviewed using Data Envelopment Analysis (DEA) analysis. Items with a scope for improvement were reviewed and adjustment measures were presented. RESULTS : To increase safety management efficiency, the degree of reduction in personnel and operating expenses was presented based on the relative efficiency group. CONCLUSIONS : It is necessary to adjust the appropriate management organization and operating costs according to the characteristics of each route. Moreover, the limitations of the study and possible improvements were presented.

Shipping companies are key components of the logistics industry, which is extremely significant in enhancing the country's comprehensive national power and promoting global trade development. In the context of the implementation of the new development pattern strategy in China and the impact of the global novel coronavirus (COVID-19), this paper takes 22 Chinese shipping listed companies as the research object and analyses the operational efficiency of them from 2011 to 2020 based on the Super-SBM DEA Model and Window DEA Model. Factors affecting the efficiency are further analyzed with the Tobit model. The research conclude that the operational efficiency of Chinese shipping companies as a whole shows a steady increase from 2011 to 2020. Although most of them are in a relatively effective operation state, fewer are absolutely effective companies. Besides efficiency among companies differs obviously, which indicates the potential of further improvement and promotion. What’s more, factors such as current economic development level, enterprise size, human resources quality and enterprise turnover speed have significant positive correlation to the operation efficiency of Chinese shipping listed companies, which is significant to improve the operation efficiency of Chinese shipping companies.

Most of the data envelopment analysis (DEA) models evaluate the relative efficiency of a decision making unit (DMU) based on the assumption that inputs in a specific period are consumed to produce the output in the same period of time. However, there may be some time lag between the consumption of input resources and the production of outputs. A few models to handle the concept of the time lag effect have been proposed. This paper suggests a new multi-period input DEA model considering the consistent time lag effects. Consistency of time lag effect means that the time delay for the same input factor or output factor are consistent throughout the periods. It is more realistic than the time lag effect for the same output or input factor can vary over the periods. The suggested model is an output-oriented model in order to adopt the consistent time lag effect. We analyze the results of the suggested model and the existing multi period input model with a sample data set from a long-term national research and development program in Korea. We show that the suggested model may have the better discrimination power than existing model while the ranking of DMUs is not different by two nonparametric tests.

We studied the efficiency of service quality of loan consultants contracted to a bank in Korea. Since the consultant is not an employee of the bank, he/she is paid solely in proportion to how much he/she sell loans. In this study, a consultant is considered as a decision making unit (DMU) in the DEA (Data Envelopment Analysis) model. We use a principal component analysis-data envelopment analysis (PCADEA) model to evaluate quality efficiency of the consultants. In the first stage, we use PCA to obtain 6 synthetic indicators, including 4 input indicators and 2 output indicators, from survey results in which questionnaire items are constructed on the basis of SERVQUAL model. In the second stage, 3 DEA models allowing negative values are used to calculate the relative efficiency of each DMU. An example illustrates the proposed process of evaluating the relative quality efficiency of the loan consultants.

Loan consultants assist clients with loan application processing and loan decisions. Their duties may include contacting people to ask if they want a loan, meeting with loan applicants and explaining different loan options. We studied the efficiency of service quality of loan consultants contracted to a bank in Korea. They do not work as a team, but do work independently. Since he/she is not an employee of the bank, the consultant is paid solely in proportion to how much he/she sell loans. In this study, a consultant is considered as a decision making unit (DMU) in the DEA (Data Envelopment Analysis) model. We use a principal component analysis-data envelopment analysis (PCA-DEA) model integrated with Shannon’s Entropy to evaluate quality efficiency of the consultants. We adopt a three-stage process to calculate the efficiency of service quality of the consultants. In the first stage, we use PCA to obtain 6 synthetic indicators, including 4 input indicators and 2 output indicators, from survey results in which questionnaire items are constructed on the basis of SERVQUAL model. In the second stage, 3 DEA models allowing negative values are used to calculate the relative efficiency of each DMU. In the third stage, the weight of each result is calculated on the basis of Shannon’s Entropy theory, and then we generate a comprehensive efficiency score using it. An example illustrates the proposed process of evaluating the relative quality efficiency of the loan consultants and how to use the efficiency to improve the service quality of the consultants.

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 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.

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.

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.

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.

이 논문에서는 부트스트래핑 DEA 모형을 이용하여 품목농협의 효율성 분석 값의 통계적 유의성을 분석 하였다. 분석결과, 첫째, 일반적 DEA모형에 의한 기술효율성은 0.878로 추정된 반면, 부트스트래핑 기 법을 적용하면 0.804로 추정되었다. 그러나 두 값의 차이는 신뢰구간 범위 내에 있기 때문에 통계적으로는 유의하지 않다. 또한 95% 유의수준하에서 기술효율성의 통계적 신뢰수준은 0.726에서 0.874로 분석되었다. 둘째, 일반적 DEA모형에서 효율적인 품목농협으로 추정된 19개 농협 모두 부트스트래핑 기법을 적용한 경우 비효율적인 것으로 추정되었다. 이는 일반적 DEA모형의 경우 비효율적인 품목농협이 효율적인 것으로 추정될 수 있다는 것이다.

  This study measured technology transfer efficiency for public institutes. The study made use of DEA being one of the non-parametric linear programming to evaluate technology transfer efficiency for public institutes and to measure technology efficiency,

This study measured technology transfer efficiency for public institutes. The study made use of DEA being one of non-parametric linear programming to evaluate technology transfer efficiency for public institutes and to measure technology efficiency, pure technical efficiency and scale efficiency. The measurement of technology transfer efficiency for public institutes are as follows: The cause of the technology transfer inefficiency was affected by pure technical inefficiency more than by scale inefficiency. The returns effect of scale varied depending upon characteristics of institutes: The characteristics of organization were not significant different but regional characteristics were significant different. The returns effect varied depending upon regional characteristics of public institutes: The organizations at the metropolitan area had decreasing returns to scale, while the ones at local areas had not only increasing returns to scale but also constant returns to scale. The technology transfer efficiency of public institutes varied depending upon the features of the organizations and regions: The technology transfer efficiency of public institutes was as follow : public research institutes at the metropolitan area, public research institutes at the local areas, universities at the metropolitan area and universities at the local areas. In other words, the technology transfer efficiency was affected by organizational characteristics more than by regional characteristics at the place where public institutes were located.

  The enormous budget of government and manpower are invested to the government funded institutes every year. The R&D investment focused on input has to be turned toward the investment based on the effectiveness of R&D activities. Measuring the efficiency

Corporations are faced with the key strategic task of adopting a comprehensive management system of a new paradigm in order to enhance their products' quality, safety, and reliability, as well as to minimize the cost of quality. The purpose of this paper is to present a methodology that can be used by corporations to ensure a product's reliability, safety, and maintainability, with minimal costs, by measuring dependability levels and conducting DEA analysis. The methodology will be a way for corporations to adopt an optimal dependability management system based on a quality management system of ISO 9001:2000 standards.

Data Envelopment Analysis-Assurance Region(DEA-AR) model is used in this paper to investigate the efficiency and performance potential of Korean banks as they engage in activities that incur interest and non-interest expenses and produce income. DEA provides a measure of each bank's relation to the best-practice frontier for its competitors. This can provide a better quality-benchmark than using industry averages or a particular peer bank branches as the benchmark. The banks are classified into efficient and inefficient sets. Multiplier values for AR-inefficient banks with unique slacks indicate the potential for management to improve the bank's performance relative to its peers. DEA-AR that provide economically reasonable bounds for the multipliers lead to profitability potential, as distinct from efficiency, results.