Earticle

본 연구는 최근 국가 정책지원사업으로 급격히 증가하고 있는 사회적기업의 경영효율성을 분석하기 위해 DEA모형을 적용하여, H지역의 간병가사지원업체를 대상으로 실증적으로 규명하고자 하였다. DEA모형의 투입 및 산출요소로 먼저, 투입요소에는 총근로자수와 정부지원금을, 산출요소로 서비스제공을 변수로 선정하여 제안하였다. 선정된 변수를 DEA모형에 적용하여 분석한 결과, 효율적인 업체는 CCR모형에서 2개(14.3%), BCC모형 3개(21.4%) 규모효율성 2개(14.3%)로 분석되었다. 또한 규모의 경제성분석을 위해 CCR 모형의 ∑λ값을 이용하여 분석한 결과, IRS형 업체는 5개(35.7%), CRS형 업체는 2개(14.3%), DRS업체는 7개(50.0%)로 파악되었다. DRS형 7개 업체는 투입물을 증가시켜도 산출물이 증가하지 않으므로 투입물을 줄일 필요가 있는 업체로 판단되며, IRS형 5개 업체는 투입물 증가 대비 산출물 증가의 비율이 크므로 투입요소를 증가시킬 필요가 있는 업체로 판단된다. 이 연구를 통해 도출된 결과를 통해 얻어진 시사점으로 사회적기업의 경영효율성 측면의 평가가 전무한 시점에서 실무적으로 활용 가능한 경영효율성 평가시스템을 제시하였다. 이를 통한 비효율성의 원인과 개선 가능성 정도를 자동으로 도출하여 우리나라 사회적기업의 발전에 큰 기여를 할 것으로 기대된다

The purpose of the study is to analyze managerial efficiency of social enterprises, which are rapidly increasing with the support of the government, by using DEA models. It focus on nursing and health care social enterprise in area H with empirical data. In the DEA models, the inputs are the total number of employees and government funds and the output is the service provided. After analyzing from the DEA model, the number of efficient firms was 2(14.3%) in the CCR model, 3(21.4%) in BCC model, and 2(14.3%) in scale efficiency. Also, analyzing the DEA model using lambda calculus to analyze economic efficiency, IRS-type firms was 5(35.7%), CRS-type firmss was 2(14.3%), and DRS-type firms was 7(50.0%). In 7 DRS-type firms, an increase in input does not guarantee an increase in output. This concludes that with the 7 DRS-type firms increasing input is not necessary. However, an increase in input is lower than an increase in output in 5 IRS-type firms. Thus, an increase in input factors such as new investments is required. As the result of analyzing the managerial efficiency, this study suggests more practical investments. In conclusion, this study shows the reasons of inefficient firms and where the necessary improvements are needed, which will improve the expected overall performance of the social enterprises.

본 연구에서는 전남지역 보건소들의 효율성을 비교 평가하고 실증분석을 통하여 투입요소의 절감 여지나 산출요소의 목표량을 규명함으로써 보건소의 운영 효율성 제고에 실질적인 도움을 주고자 한다. 효율성 평가방법으로는 자료포락분석(Data Envelopment Analysis: DEA)의 CCR모형을 이용하였으며 사업 영역별 효율성과 전체 운영측면의 효율성을 구분하여 평가하였다. 이를 위하여 투입변수로는 인력(의사 및 행정직원 수)을 선정하였고 산출변수로는 보건소 사업(영유아 예방접종 수, 결핵 검사 수, 방문 진료 수, 외래진료 수)을 선정하였다. 본 논문결과를 요약하면 다음과 같다. 첫째, 순천, 목포, 해남 세 곳의 보건소가 효율적인 것으로 분석되었다. 둘째, 효율적인 보건소 중 목포는 의사 투입변수 측면에서 높은 효율이, 해남은 행정직원 투입변수 측면에서 효율적인 것으로 나타났으며, 순천은 두 부분에서 모두 효율적인 것으로 나타났다. 셋째, 사업영역의 효율성 측면에서 의사보다 행정직원들의 공헌도가 높은 것으로 나타났다. 본 연구는 전남지역 보건소의 효율적인 관리 측면에서 유용한 피드백 정보를 제공해 줄 수 있다

In this research, we compared and analyzed the efficiency of public health center of Jeonnam, so the reduction and weakness of input and output factor were found. We used the CCR model of Data Envelopment Analysis as a method of evaluation, made a choice the quantity of doctors and public officers as the input variable, made a selection the quantity of infants' vaccination, tubercle checkup, visiting medical treatment, the ward as the output variable. The analysis results describe as follows. First, the efficient public health centers are Sooncheon, Mokpo, and Haenam. Second, in Mokpo, the factor of doctors’ input is highly efficient. In Haenam, the factor of public officers’ input is highly efficient. In Sooncheon, the efficiency of the both factors is high. Third, in business parts, public officers are used more efficiently than doctors. It is expected that this approach can give a feedback for effective management of Jeonnam Public Health Center.

Objectives: Extension of the standard model while retaining compliance with it is a challenging issue because there is currently no method for semantically or syntactically verifying an extended data model. A metadata-based extended model, named CCR+, was designed and implemented to achieve interoperability between standard and extended models. Methods: Furthermore, a multilayered validation method was devised to validate the standard and extended models. The American Society for Testing and Materials (ASTM) Community Care Record (CCR) standard was selected to evaluate the CCR+ model; two CCR and one CCR+ XML files were evaluated. Results: In total, 188 metadata were extracted from the ASTM CCR standard; these metadata are semantically interconnected and registered in the metadata registry. An extended-data-model-specific validation file was generated from these metadata. This file can be used in a smartphone application (Health Avatar CCR+) as a part of a multilayered validation. The new CCR+ model was successfully evaluated via a patient-centric exchange scenario involving multiple hospitals, with the results supporting both syntactic and semantic interoperability between the standard CCR and extended, CCR+, model. Conclusions: A feasible method for delivering an extended model that complies with the standard model is presented herein. There is a great need to extend static standard models such as the ASTM CCR in various domains: the methods presented here represent an important reference for achieving interoperability between standard and extended models.

본 연구는 DEA-CCR, DEA-BCC, 수정DEA 모형을 이용하여 2002부터 2009년까지 13개 지역별로 구분된 우리나라 새마을금고를 대상으로 그 효율성 정도를 분석하고, 최적 투입⋅산출요소 및 효율성 강화방안을 제시하였다. 분석결과 첫째, 전체 지역별 새마을금고의 연도별 평균 기술효율성은 최적 프론티어 대비 연 평균 0.888이었다. 이는 11.2%의 비효율성을 가지고 있다는 사실을 의미하며, 규모수익효과 측면에서는 규모수익체증이 0.596으로 아직 새마을금고가 적정규모에 이르렀다고 볼 수 없는 것으로 나타났다. 둘째, 지역별 새마을금고의 평균 기술효율성을 살펴보면 울산⋅경남, 경기지역만이 모든 효율성 지수에서 효율적으로 나타나, 경영효율성이 양호하게 나타났다. 셋째, 최적 투입⋅산출요소 측면을 살펴보면, 광주⋅전남, 울산⋅경남, 경기지역은 투입요소가 적정하게 지출되었고, 광주⋅전남, 대전⋅충남, 울산⋅경남, 경기, 강원지역은 산출요소가 적정하게 지출되었다. 넷째, 효율성이 1로 동일하게 나타난 울산⋅경남과 경기의 경우, 수정DEA모형을 이용하여 효율성 우선순위를 측정한 결과, 경기가 효율성이 더 높은 것으로 나타났다. 분석결과 향후 지역별 새마을금고 효율성을 증대시키기 위하여 적정 새마을금고 수의 유지, 불필요한 고정자산 감축, 임직원 수의 조정, 지역 밀착형 영업력 강화 등이 필요할 것으로 분석되었다.

This study has analyzed the efficiency on 13 provinces of Community Credit Cooperatives to use DEA-CCR model, DEA-BCC model and Modified DEA model from 2002 to 2009. And it is presented the alternatives enhancing the efficiency and the optimum input?output elements. Firstly, yearly average technological efficiency on all provinces of Community Credit Cooperatives was average 0.888 compared with the optimal frontier. This has 11% inefficiency. As a scale revenue accounted 59.6%, it has not yet reached an appropriate-sized Community Credit Cooperatives. Secondly, if it has reviewed the average technological efficiency on individual provinces of Community Credit Cooperatives, only Ulsan?Gyeongnam, Gyeonggee provinces management efficiency indicated good. Thirdly, if it has reviewed the optimum input?output elements, Gwangju?Jeonnam, Ulsan?Gyeongnam, Gyeonggee provinces were spending input elements appropriately and Gwangju?Jeonnam, Deajeon?Chungnam, Ulsan?Gyeongnam, Gyeonggee, Gangwon provinces were spending output elements appropriately. Fourthly, Ulsan?Gyeongnam, Gyeonggee provinces had the same efficiency. As it was measured the efficiency ranking by using the modified DEA model, Gyeonggee province appeared to be higher than Ulsan?Gyeongnam province. Therefore, it will need the alternatives to increase the efficiency of regional Community Credit Cooperatives .

본 연구는 새마을금고에 대한 기술효율성 분석과 관련하여 모수적 효율성 분석과 비모수적 효율성을 분석할 때, 상호간에 결과가 일치하는지 또는 어떤 관계가 있는지 연구를 위해 2009년도 13개 지역 새마을금고를 대상으로 두 방법론 사이의 관계를 파악해보았다. 이를 위해 모수적 방법으로 확률적 프론티어 생산함수인 콥-더글라스 함수 모형과 비모수적 방법인 수정 DEA-CCR 방법으로 기술효율성을 측정하여 그 결과 값을 비교분석해 보았다. 확률적 프론티어 생산함수 모형에 의한 기술효율성 분석결과와 수정 DEA-CCR 모형을 이용한 효율성 분석결과와는 약간의 차이가 발생하였다. 이 차이점을 분석하기 위해 두 모형에 의한 기술효율성 분석결과 값들에 대한 스피어만 서열상관과 Mann-Whitney 검증을 실시 해본 결과, 완전하지는 않지만 순위의 일치성이 인정된다고 할 수 있었으며, Mann-Whitney 검증결과는 확률적 프론티어 생산함수 모형에 의한 기술효율성과 수정 DEA-CCR 모형에 의한 기술효율성과는 차이가 없는 것으로 나타났다. 하지만 통계적으로는 비유의적으로 나타났다. 결론적으로 모수적, 비모수적 기술효율성 측정결과는 측정방법에 따라 약간의 차이가 있음을 알 수 있었다.

This study is performed to compare what relation is the technical efficiency in stochastic frontier and DEA model. In order to estimate what relation is the two methodologies, it is used to Cobb Douglas production function known as parametric method and modified DEA-CCR known as non-parametric method. The stochastic frontier Cobb-Douglas production function and modified DEA-CCR used cross-sectional data of 13 areas of Community Credit Cooperative in 2009. According to the estimated technical efficiency, there is a little difference between the stocahstic frontier Cobb-Douglas production function and modified DEA-CCR model. To analyze the difference of technical efficiency between two models, it has Spearman rank-order correlation and Mann-Whitney test. The two test results are recognized the convergence of ranking not completely, but it has not the difference in Mann-Whitney test results of the technical efficiency by Cobb Douglas production function model and modified DEA-CCR model, also it is statistically insignificant. In conclusion, parametric and non-parametric efficiency measurements have figured out the fact that there are some differences in depending on how to measure.

Purposes: As super-aging population and low fertility rates are threatening the sustainability of the National Health Insurance funds, enhancing the efficiency of hospital management is paramount. In the past, studies analyzing the efficiencies of hospitals primarily made inter-hospital comparisons, but it is important to assess hospitals' internal efficiency and develop improvement measures in order to attain practical improvements in hospital efficiencies. The purpose of this study is to analyze the efficiencies of specialists by medical specialty in a hospital in order to provide foundational data for efficient hospital management. Methodology/Approach: We used the activity-based costing (ABC) data and hospital statistical data from one tertiary hospital in Seoul to analyze the efficiency of specialists by medical specialty. Efficiency was analyzed and compared among specialists using the data envelopment analysis developed by Charnes, Cooper, and Rhodes (DEA-CCR) model and the slacks-based measure (SBM) models. The input variables were labor cost, material cost, and operational expenses, and the output variables were the number of outpatients, number of inpatients, outpatient revenue, and inpatient revenue. Findings: First, there was a marked deviation in efficiency across specialists. Second, there was a marked deviation in efficiency across medical specialties. Third, there was little difference in efficiency according to the specialist's sex, age, and job position. Fourth, the SBM model produced more conservative results and better explained efficiency parameters than the CCR model. Practical Implications: The efficiency of a specialist was more influenced by their medical specialty than their personal characteristics, namely sex, age, and job position. Therefore, Further research is needed to analyze the efficiencies of each subspecialty and identify factors that contribute to the variations in efficiencies across medical specialties, such as clinical practices and fee structures.