• 한국산학기술학회논문지
• /
• 제10권6호
• /
• pp.1304-1316
• /
• 2009

본 연구는 효율성에 기초한 환산지수의 도입 가능성을 알아보기 위한 기초 연구로 시도되었다. DEA 효율성지표와 환산지수가 전공의 수련교육을 실시하고 있는 60 개 병원을 그룹화하는데 얼마나 유용하게 사용될 수 있는가를 고찰하였다. 이러한 목적을 달성하기 위해 자료수집이 가능한 표본병원의 환산지수와 AHP 개념을 도입해 DEA 모형의 투입변수와 산출변수를 선정하였다. 그 결과 병상규모가 클수록 규모적 비효율성이 큰 것으로 나타났으며 기술적으로 또는 규모적으로 비효율적인 병원일수록 환산지수가 더 큰 것으로 나타났다. 환산지수와 효율성지표는 수련병원을 병원의 종별에 따라 종합전문병원과 종합병원으로 구분하는데 유용하게 사용될 수 있었다. 또한 DEA 효율성을 구하는 과정에서 독립변수로 사용된 투입 산출변수를 판별함수에 도입하였음에도 불구하고 환산지수와 효율성지표는 판별함수를 구성하는 주요 변수로 작용함을 확인하였다. 따라서 만약 모집단을 대표할 수 있는 많은 표본을 기초로 보다 명확한 결과를 얻을 수 있다면 건강보험의 수가계약제 하에서 효율성 개념을 바탕으로 한 환산지수계약의 도입을 신중하게 고려해 볼 수 있다.

• Management Science and Financial Engineering
• /
• 제14권2호
• /
• pp.67-87
• /
• 2008

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations which is of vital practical importance in managerial decision making. While DEA assumes exact input and output data, the development of imprecise DEA (IDEA) broadens the scope of applications to efficiency evaluations involving imprecise information which implies various forms of ordinal and bounded data possibly or often occurring in practice. The primary purpose of this article is to characterize the variable efficiency in IDEA. Since DEA describes a pair of primal and dual models, also called envelopment and multiplier models, we can basically consider two IDEA models: One incorporates imprecise data into envelopment model and the other includes the same imprecise data in multiplier model. The issues of rising importance are thus the relationships between the two models and how to solve them. The groundwork we will make includes a duality study which makes it possible to characterize the efficiency solutions from the two models. This also relates to why we take into account the variable efficiency and its bounds in IDEA that some of the published IDEA studies have made. We also present computational aspects of the efficiency bounds and how to interpret the efficiency solutions.

• 대한산업공학회지
• /
• 제40권2호
• /
• pp.172-183
• /
• 2014

This paper measures and compares the efficiency of national health technology R&D programs focused on translational research program increasing importance using data envelopment analysis (DEA). Three input variables and three output variables are selected for DEA. Inputs are funds, researchers, and project period and outputs are SCI (E) papers, applied and granted patents, and impact factor. This study uses a three-stage approach. In the first stage, output-based DEA model is applied to evaluate the efficiency of decision making unit (DMU). In the second stage, based on efficiency scores of target diseases high-efficiency group and low-efficiency group are classified. And then strategic portfolio matrix of translational research program is composed of four dimensions combining research types. Mann-Whitney U test is then run to compare average efficiency scores among four groups. In the final stage, Tobit regression model is used to estimate factors likely to influence the efficiency. The results are expected to provide policy implications for effectively establishing investment strategy and managing performance of R&D program.

• 한국경영과학회지
• /
• 제41권1호
• /
• pp.127-143
• /
• 2016

This study applied DEA analysis to measure the relative efficiency of 35 companies that produce automobile body components. First, the input and output, the improvement target value of the calculated variables, and the reference group for benchmarking for inefficient groups to become efficient groups were established through DEA analysis. In addition, whether inefficiency was due to technical inefficiency or size was analyzed in connection with the cases of the actual companies through the measurement of scale efficiency. Second, a route for efficiency improvement was derived through DEA-Tier analysis by defining the possible group for benchmarking in actuality within the production industry of automobile body components where the primary cooperative company belonged. Third, the financial variables that generate the difference between efficient and inefficient groups were derived through logistic regression analysis. Financial strategies that determine the direction the indices should be improved to allow the inefficient group to become an efficient one were recommended. This research is expected to provide diagnostic methods for management efficiency and the direction of improvement to enhance the management efficiency of automotive parts makers by identifying the causes of the inefficiency of domestic automotive parts makers empirically. The study also provides financial strategies together with the target values of efficiency improvement for each individual company.

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 2004년도 춘계학술대회 논문집
• /
• pp.351-356
• /
• 2004

부산항은 동북아시아의 급속한 성장과 더불어 지속적인 성장을 해오고 있으며, 향후 이러한 지속적인 성장을 유지하기 위해 정부의 집중 투자 및 정책 지원이 이루어지고 있다. 본 연구는 부산항을 포함한 세계 주요 컨테이너 항만들의 효율성을 DEA(Data Envelopment Analysis)모형을 통해 상대적으로 분석함으로써, 부산항의 현재 위치와 더 효율적인 항만이 되기 위해 Benchmarking 해야할 대상을 구체화 한 것이다. 또한, 본 연구에서는 일정시점의 효율성 분석이 아닌 1995년∼2001년까지 7개년 동안의 효율성을 시계열적으로 분석함으로써 각 항만의 효율성 변화를 살펴볼 것이며 이를 통해서 보다 유효한 효율성 분석 결과를 제시하고자 한다.

• 한국항해항만학회지
• /
• 제46권2호
• /
• pp.110-120
• /
• 2022

Spain is Europe's second-largest country with total throughput reaching 16.7 million twenty-foot equivalent units (TEU) by 2020. The purpose of this study was to measure and compare the efficiency of 17 container terminals. As a study method, the DEA-CCR model, undesirable variable, and Malmquist Index (MI) were used for data envelopment analysis (DEA). The study results are as follow: (1) DEA-CCR is used to evaluate basic efficiency. The most efficient terminals are decision-making units DMU 1 (APM Terminals (Algeciras Port)), DMU 2 (Total Terminal International Algeciras (Algeciras Port)) and DMU 5 (Barcelona Europe South Terminal (Barcelona Port)). (2) Undesirable DEA was conducted to suggest inefficiency from the undesirable output. Overall, the efficiency scores were reduced. However, DMU 1, DMU 2, and DMU 5 maintained efficiency scores regardless of the finish factor. (3) Malmquist Index was used to observe technology and efficiency changes dynamically. The changes in TCI affected Spanish container terminals more than the Technical Efficiency Change Index (TECI) in 2018-2019. However, in 2019-2020, the TECI was 2.706, higher than the TCI value, indicating that the change in TECI had more influence on the increase in productivity. This study offers a broader understanding of Spanish container terminals.

• 대한예방한의학회지
• /
• 제17권3호
• /
• pp.103-114
• /
• 2013

Objectives : This study aimed to analyze the management efficiency of Korean Medicine hospitals for recent 10 years(2001~2010) using the Data Envelop Analysis(DEA) model. Methods : We collected the management data of 23 Korean Medicine hospitals for DEA model from the Korean Oriental Medicine Hospitals' Association (KOMHA). Input variables of DEA model are numbers of beds, numbers of doctors, numbers of nurses and numbers of other staffs of each Korean Medicine hospitals. Output variables are numbers of inpatients and numbers of outpatients of each Korean Medicine hospitals. Based on the DEA model, we calculated the efficiency score of each Korean Medicine hospital and compared it by hospital's ownership, location, and size. Results : Average DEA efficiency scores of Korean Medicine hospitals by year ranged from 0.86 to 0.92. Private owned hospitals showed higher efficiency scores than the university affiliated hospitals with statistical significance (p=0.001). And Korean Medicine hospitals located in capital region of Korea(Seoul City, Incheon City, Gyeonggi-do) and the rest Korean Medicine hospitals did not show statistical difference (p=0.516). Lastly, Korean Medicine hospitals with different size did not show statistical difference in management efficiency (p=0.499). Conclusion : We have found that Korean Medicine hospitals management efficiency have not changed throughout 10 years, and that different ownership forms of Korean Medicine hospital show statistical difference in management efficiency while location, and size do not.

• 한국건축시공학회:학술대회논문집
• /
• 한국건축시공학회 2012년도 추계 학술논문 발표대회
• /
• pp.125-126
• /
• 2012

Domestic architect office from a period of high growth from the 1970s to the '80s has been established as some of the large corporations or publicly traded corporation. 1997 IMF has pointed out there is a lot of need for improvement activities in accordance with the construction recession since the 2008 global financial crisis. In order to address these causes, the company's continuous efficient operation for accurate efficiency and competitiveness analysis was required. Leverage financial ratio indicators Study Using Data Envelopment Analysis Data Envelopment Analysis (DEA) model, how to find a benchmark for the improvement of the efficiency of inefficient enterprises in various sectors being. In this study, a comparison of the conventional DEA model and the DEA-AR model is used to analyze the efficiency and domestic architect office is to improve the management efficiency.

• 한국경영과학회지
• /
• 제37권4호
• /
• pp.125-138
• /
• 2012

Health care that is considered to be one of the major factors for the quality of life is nowadays receiving a great deal of attention, and thus there is a growing need in Korea to identify the efficiency of national medical service and enhance the competitiveness. Although there exist studies on the medical service efficiency about general hospitals and local hospitals, they mostly deal with the efficiency problems from a domestic and regional perspective. In response, this paper analyzes the competitive efficiency of national medical service with respect to 16 OECD countries, by exploiting Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI). Building on the DEA and MPI analysis results, this paper identifies the competitive position of Korean national medical service and suggests implications for the medical service improvement.

• 대한안전경영과학회지
• /
• 제15권1호
• /
• pp.249-258
• /
• 2013

Data Envelopment Analysis (DEA) is a useful tool to analyze the relative efficiency of decision making units (DMU) characterized by multiple inputs and multiple outputs. This method has been popularly used as an analytical tool to suggest some strategic improvement. To do this, the results of DEA provide decision makers with a single efficiency score, efficient frontier, return to scale, benchmarking decision making units, etc. The purpose of this paper is to evaluate research performance of 38 universities and provide an inefficient university with the way of organizational changes to be an efficient university by using DEA. Various input and output variables are used to identify technical and scale inefficiency. Additionally, we analyze how an inefficient DMU could be changed an efficient DMU based on a case university. This result will give an insight of constructive directions for increasing of research performance to university decision makers.