폐기물처리방법별 환경효율성(Eco-efficiency) 평가 연구

이소라 ( Sora Yi Et Al. ) 한국환경연구원 2018 기본연구보고서 Vol.2018 No.-

In conjunction with the Basic Law on Resource Circulation in 2018, Korea established the Basic Plan for National Resource Recirculation (2018-2027), which contains the nation’s mid-to-long term policy directions and detailed strategies to transform into a resource circulating society. The new directive places greater importance in changing Korea’s recycling system from simple recycling to high value-adding material recycling, with the national goal to realize a final disposal rate of 3% by 2027 and zero waste-to-landfill. In this context, this study conducts the much-needed review on the environmental efficiency of Korea’s waste treatment facilities by analyzing their economic and environmental performances. Based on this review, the overall environmental efficiency of each waste treatment method is assessed to propose policies for the effective utilization of the facilities. The wastes were analyzed in terms of combustible waste (disposed in volume-rate waste bags) and organic waste (food waste). Under Korea’s regulations, among municipal/household wastes, food waste is not sent directly to landfills. Instead, a separate volume-rate system is in place for food waste so that most of the food waste is recycled, with only 1.0% and 2.2% sent to landfills or incinerated, respectively. Thus, the different treatment methods for combustible waste and food waste were examined to find the most efficient treatment methods for the respective wastes. Economic performance was evaluated using the treatment facility’s revenue per treating one ton of waste minus the operational costs as the indicator, and environmental performance was determined by conducting a life-cycle assessment (LCA) for calculating the weighted environmental impact per one ton of waste. In assessing the environmental performance, the avoidance effects from utilizing recovered incineration heat and selling the biogas produced from organic waste were excluded to prevent an overlap with the economic performance. The facilities subject to the environmental efficiency evaluation were chosen based on their location, size, treatment method, etc. for each waste disposal method. In particular, to ensure a good mix of the facilities that received high scores and those that did not in the “2016 Evaluation of the Installation and Operation of Waste Treatment Facilities (hereafter 2016 Evaluation),” the facilities were divided into five groups (for waste disposed in volume-rate waste bags: incineration facilities, combustible waste-to-fuel facilities, landfills; for food waste: organic waste biogasification facilities, food waste recycling facilities). 79 facilities were initially chosen, from which 42 facilities were finally selected and analyzed for their environmental and economic performances based on the data submitted by the facilities and the reliability of the evaluation results. The chosen facilities were divided according to their sizes, into small facilities that treat less than 100 tons per day, medium facilities that treat more than 100 tons but less than 300 tons per day, and large facilities that treat more than 300 tons per day. Different facility types were incorporated into the analysis, such as facilities for reducing food waste, converting food waste into animal feed and compost were included under food waste recycling facilities; and landfills for incombustible waste and general waste under landfills. The environmental and economic performance analyses were conducted using the following data from each treatment facility: the amounts of waste sent to the facility, energy use, incineration heat recovery, captured landfill gas, biogas production, and compost and feed production, as well as operational costs and operational revenue, etc. The environmental performance analysis by waste treatment method showed that the weighted environmental impact of landfills was the smallest at 4.42E-02 points, followed by organic waste biogasification facilities (8.87E-02 points), food waste recycling facilities (2.25E-01 points), incineration facilities (3.50E-01 points), and combustible waste-to-fuel facilities (1.39 points). On the other hand, the economic performance analysis based on each facility’s revenue minus operational costs revealed that the economic performance of landfills performed best at 731 won/ton, followed by organic waste biogasification facilities (-33,419 won/ton), food waste recycling facilities (-40,172 won/ton), incineration facilities (-58,646 won/ton), and combustible waste-to-fuel facilities (-60,149 won/ton). The environmental efficiency evaluation based on the environmental and economic performance analyses showed that landfills were most environmentally efficient at 10,837 thousand won/point, followed by the organic waste biogasification facilities (4,760 thousand won/point), food waste recycling facilities (1,540 thousand won/point), incineration facilities (760 thousand won/point), and combustible waste-to-fuel facilities (-184 thousand won/point). More specifically, in terms of the environmental efficiency by facility size, medium-sized facilities were found to have the highest environment efficiency at 2,108 thousand won/point, followed by small facilities (834 thousand won/point), and large facilities (280 thousand won/point). However, in the case of combustible waste-to-fuel facilities, the environmental efficiency of large facilities was the best at 5,306 thousand won/point, followed by small facilities (-212 thousand won/point) and medium facilities (-236 thousand won/point). Also, in the case of organic waste biogasification facilities, large facilities were most environmentally efficient at 10,617 thousand won/point, followed by medium facilities (6,236 thousand won/point) and small facilities (2,859 thousand won/point). The environmental efficiency of food waste recycling facilities turned out to be best for medium-sized facilities at 1,959 thousand won/point, followed by small facilities (1,308 thousand won/point). In the case of food waste recycling facilities, large facilities were not included in the evaluation. The environmental efficiency of landfills for incombustible waste was higher at 18,957 thousand won/point than that of landfills for general waste, which came out to be 9,458 thousand won/point. Based on the results of the environmental efficiency evaluation and a waste disposal scenario based on future projection, the environmental efficiency mix for 2027 was estimated and compared with the current environmental efficiency mix. In the case of waste disposed in volume-rate waste bags, the landfill disposal rate was 31.1%, incineration rate was 53.2%, and combustible waste-to-fuel conversion was 15.6% in 2016, but in 2027, which is the target year of the first Basic Plan for Resource Circulation, it was projected that the rates would change to 2.5%, 33.5%, and 23.5%, respectively. In the case of food waste, 10% was converted to biogas and 90% was recycled into compost or feed in 2016, but in 2027, the rates were projected to be 69.7% and 30.3% in 2027, respectively. Overall, the environmental efficiency mix for all treatment facilities was calculated to be 5,173 thousand won/point in 2016 and 4,118 thousand won/point in 2027. When it was assumed that all landfills were landfills for general waste in 2016 and will become landfills for incombustible waste in 2027, the environmental efficiency mix came out to be 4,744 thousand won/point in 2016 and 4,321 thousand won/point in 2027. The results of the environmental efficiency evaluation were compared with those of the 2016 Evaluation. The comparison revealed that incineration facilities that scored high environmental efficiencies had also received good scores in the 2016 Evaluation, although with some differences that seem to be due to the inclusion of the incineration heat recovery rate in the 2016 Evaluation. Incineration heat recovery rate was excluded from the environmental performance analysis of the present environmental efficiency evaluation, and the life-cycle assessment of the fuel used at incineration facilities was also reflected only in the environmental efficiency evaluation. In the case of combustible waste-to-fuel facilities also, the results of 2016 Evaluation and the environmental efficiency evaluation mostly agreed with each other, with slight differences due to the insignificant effect of SRF production rate on economic performance. In the case of organic waste to biogas facilities, the 2016 Evaluation and environmental efficiency evaluation did not match, which can be attributed to the exclusion of indicators such as odor management, the rate of operation, and facility management, all of which are included in the 2016 Evaluation but not in the environmental efficiency evaluation. For landfills, the 2016 Evaluation and the environmental efficiency evaluation showed similar tendencies, and any differences seemed to have been caused by the discrepancies between the technical evaluation index of the 2016 Evaluation, which includes compaction efficiency and leachate reduction rate, etc., and the index used for the environmental efficiency evaluation. The results of this study were used to develop strategies on how the environmental efficiency evaluation can be utilized through policy implementation. The factors that significantly affected the environmental efficiency evaluation for each waste treatment method were analyzed and listed in Table 4 below, which can be used as an index to improve the environmental and economic performances of the treatment facilities. It may not be appropriate to perform simple comparisons between the environmental efficiencies of individual facilities since their revenues and operational costs, which are used as economic indicators, can vary greatly depending on the location, condition, and operation standards of individual facilities. Therefore, the environmental efficiencies of waste treatment facilities need to be compared among the same facilities or analyzed specifically for individual facilities when identifying and suggesting areas for improvement. As such, three comparison coefficients were proposed for understanding how the environmental efficiency of each waste treatment facility can be improved in comparison to others, namely, the improvement comparison coefficient, benchmark comparison coefficient, and capacity design comparison coefficient. The improvement comparison coefficient can be used to compare the before and after of a specific facility when efforts are made to reduce its economic costs or environmental impacts. The benchmark comparison coefficient can be used as a guideline for identifying whether a particular facility has low environmental efficiency among comparable facilities or needs improvement when compared to the best performing facility of its type, or to understand how effective the efforts toward improvement will be and how much the facility can be improved in terms of its conditions. The capacity design comparison coefficient, on the other hand, provides a guideline for environmental efficiency depending on the size of the facility, thus preventing excessive operational costs projections or potentially adverse environmental impacts when constructing new waste treatment facilities. The improvement comparison coefficient and benchmark comparison coefficient were used to study how an improvement in waste-to-resource capacities at facilities can improve their environmental efficiencies. Specifically, case studies (types A, B, C, D) were performed by assuming an improvement in the waste-to-resources capacities of existing incineration and biogasification facilities with low environmental efficiencies and comparing them against other facilities with different levels of economic and environmental performances. Type A compared between facilities with similar operational costs and environmental performance when the energy recovery (economic value) is improved in the target facility. Type B looked into how the improvement in the target facility’s energy recovery (economic value) would compare to a facility with higher environmental performance, and Type C, to a facility with higher operational costs and similar environmental performance. Lastly, Type D compared the target facility against a facility with higher operating costs and higher environmental performance. In the case of incineration facilities, Hanam incineration facility was chosen for Type A and B case studies to investigate how an improvement in the facility’s thermal energy recovery (economic value) level would make it comparable to Asan and Gumi incineration facility, respectively. For Type C and D, Sejong incineration facility was selected and compared against Asan and Gumi incineration facilities, respectively. In the case of biogasification facilities, only Types B and D were studied due to the limited availability in facility types. For Type B, Gimhae biogasification facility, assuming an improvement in its waste-to-resource production, was compared to Namyangju biogasification facility, and for Type D, Asan biogasification facility was compared to Namyangju biogasification facility. When a 50% improvement was projected for the incineration heat recovery rate of Hanam incineration facility the improvement comparison coefficient came out to be 1.04, and the benchmark comparison coefficient to be 0.56 for Type A and 0.147 for Type B. A 50% improvement in the incinerator heat recovery rate of Sejong incineration facility rendered the improvement comparison coefficient to become 1.03, and the benchmark comparison to become 0.98 for Type C and 0.26 for Type D. Meanwhile, a 35% enhancement in the biogas production of Namyangju biogasification facility resulted in an improvement comparison coefficient of 1.02, and the benchmark comparison coefficients of 0.22 for Type B and 0.40 for Type D. The capacity design comparison coefficient was calculated by computing the mean environmental efficiency by facility size, then comparing it with other facilities of the size that showed the highest environmental efficiency. The capacity design comparison coefficient of small incineration facilities was 0.40, which is better than that of large incineration facilities; and in the case of biogasification facilities, medium-sized facilities had a coefficient of 0.59, which is superior to small biogasification facilities. We propose four ways to translate the present environmental efficiency evaluation into policy implementation: 1) using the evaluation to assess the installation and operation of waste treatment facilities and potential improvements in old facilities, 2) utilizing the evaluation methods in strategic environmental impact assessments and preliminary performance studies, 3) using the evaluation to calculate the social costs of resident subsidy projects and waste disposal charges, and 4) using the evaluation as a guideline for implementing optimization strategies and government-subsidized projects. First, the environmental efficiency evaluation can be applied to the annual evaluation on the installation and operation of waste treatment facilities for assessing the actual conditions of waste treatment operations and improving their energy utilization and recovery and operational efficiency. The current annual evaluation includes the level of efforts made toward improvements such as the efforts to enhance the facility’s economic performance and the efforts of local governments to reduce the amount of waste. However, the annual evaluation has yet to incorporate the level of initiatives for improving environmental efficiency. Thus, it will be helpful to apply the environmental efficiency comparison coefficient presented in Chapter 6.2 to assess the level of efforts to improve the facilities’ operations. Also, based on the survey of treatment facilities nearing the end of their lifecycles, the environmental efficiency comparison coefficient can be used to identify whether the facilities should be improved or closed and to decide whether new facilities should be constructed. Korea’s Act on the Promotion of Waste Treatment Facility Installation and Support to the Surrounding Areas requires strategic environmental impact assessments to be conducted and reviewed in terms of policy plans and basic development plans before making the decisions on the installation cost and site selection when installing and operating waste treatment facilities. Currently, the items reviewed under the strategic environmental impact assessment do not include an environmental performance analysis by facility size, treatment method, or the properties of the waste that is being treated, nor an economic performance analysis on the profitability of the facilities. Therefore, applying the environmental efficiency evaluation conducted in this study will allow a better assessment of the treatment facilities’ suitability in terms of type, size, and location. Also, since the environmental costs included in the preliminary performance studies on environmental facilities are often estimated based on related literature or expert surveys, which can be open to controversy, the methods presented in this study for measuring environmental efficiency using actual data from treatment facilities can be a helpful index for calculating their economic and environmental effects. The environmental efficiency evaluation can also be used to estimate the social costs of resident subsidy projects and waste disposal charges. According to our analysis, the environmental and economic performances of landfills were better than other types of facilities, possibly because the social costs related to operating landfills are much lower. A pilot project for evaluating the environmental efficiency of landfills will help to identify the social costs for preventing environmental pollution and other negative environmental impacts, especially in terms of the land acquisition costs for landfills, which are difficult to measure, by considering both the direct costs and indirect effects (drop in land prices, etc.) in the measurement of economic performance. The comparison of the social costs of landfills to that of incineration facilities showed that the economic value of general landfills was estimated at -368,703 won/ton. Since the average cost of landfill disposal is 14,956 won/ton, our results suggest that the landfill disposal charges be increased by 340,000 won/ton. Government-subsidized waste treatment facility projects aim to promote systematic government support and investment in waste treatment facilities by providing clear subsidy criteria and priorities for regional waste treatment facility installation. At present, the unit cost guidelines for installing government-subsidized treatment facilities is set according to facility type and size, where the lower the facility capacity, the higher the set unit cost subsidized by the government based on the unit cost ratio. This study revealed that the environmental efficiency of small facilities is lower than that of larger facilities, and since small facilities receive more government subsidies due to the unit cost ratio, our findings suggest that it is necessary to revise the guidelines to provide more efficient government support based on optimal facility sizes. A revision of government subsidy guidelines will also provide a useful basis for promoting investment in regional and direct-disposal waste treatment facilities in line with the national policy direction. Furthermore, it may be possible to consider incorporating he environmental efficiency evaluation in reviewing the applications for facility operation budgets and government subsidies based on the Guidelines on the Budget Support and Integrated Administrative Process for Waste Treatment Facilities (Jan 2018), Waste Treatment Facility Optimization Strategy (2011), and the Environmental Technology and Environmental Business Support Act. We anticipate the effects of utilizing the environmental efficiency evaluation as follows. First, by providing a basis for national policies for each waste treatment method through an integrated evaluation of the environmental and economic performances of waste recirculation, the environmental efficiency evaluation will contribute to the implementation of the strategies formulated under goals of the first Basic Plan for Resource Circulation (2018-2027). Secondly, it will become possible to expand the paradigm for assessing the environmental impact of waste treatment facilities from merely looking at their potentials for environmental pollution to a more robust evaluation of environmental and economic performances. Third, by establishing a model for evaluating waste treatment facilities and introducing a minimum standard for environmental-friendliness, the environmental efficiency evaluation will help improve the public image of waste treatment facilities. Fourth, the environmental efficiency evaluation will make it possible to develop strategies for managing environmental impact and pollution levels efficiently, thereby preventing environmental pollution and inducing the development of advanced technologies that consider economic efficiency through eco-innovation. The environmental efficiency evaluation in this study presents a meaningful methodology for improving and optimizing treatment facilities by providing a more accurate comparison of different treatment facilities and methods. In particular, the methods used in the environmental efficiency evaluation identify the most significant factor influencing environmental efficiency among treatment cost, revenue, and environmental impact, thus allowing for the development of better strategies for improving and optimizing individual facilities. The introduction of the environmental efficiency evaluation to government-subsidized projects, environmental impact assessments, etc., may lead to pilot projects for increasing the reliability of the data on each facility as well as expanding the utilization of the evaluation itself. When installing a preventive facility, such as a malodor prevention facility, at a waste treatment facility to control pollutants that may have negative aesthetic and health-related environmental impacts, the improvements made in this area are not included as an indicator in the environmental efficiency evaluation. As such, the facility, despite its advances, may receive a lower environmental efficiency score due to the increase in the facility’s operational costs from installing new equipment. Thus, further research and pilot projects will be necessary to improve the measurement items and methodology used in the present environmental efficiency evaluation to reflect the specific characteristics of the facilities. In addition, in the process of converting negative (-) indices to positive values, the numerical shifts and the avoidance effects were excluded from the economic performance index and the environmental performance analysis, respectively. To strengthen the robustness of the environmental efficiency evaluation conducted in this study, we suggest more case studies to be undertaken, especially on waste treatment facilities that have negative economic values and environmental impacts, and to discuss them at the global level.

한국 문화산업의 기업체 성과에 대한 효율성 분석 연구

박계화(Park Kye-hwa) 한국문화산업학회 2010 문화산업연구 Vol.10 No.1

It is important for Korean cultural industry to raise the efficiency of the departmental and local company activities which can progress continuously and effectively. So evaluation of cultural industries is needed to see how it works to estimate, analyze and evaluate the efficiency of each departmental and local industry and then apply those to a control factor for later, and the efficiency evaluation is very important to realize them. Purpose of this study is to find the way for cultural industry to progress according to the results. So, we collected the departmental and local companies data (Decision Marketing Unit: DMU) and then analyzed them with DEA (Data Envelopment Analysis) model to evaluate the efficiency. The data in this study is from Mun-Hwa-San-Eop-Baek-Seo 2001~2008. We divided them into two groups and analyzed. The departmental industries data is from 2003~2007 and the local industries data is from 2007~2008. Based on this data, we analyzed the comparative efficiency of the data of 50 DMU (Decision Making Unit)s of 10 departmental industrial companies (publication, comics, music, game, movie or video, animation, advertisement, broadcasting, character, digital education and information) for 5 years (2003~2007) which are the objects of cultural industrial supportive policy and 32 DMUs, which are 7 contents industries (publication, comics, music, movie, animation, character, edutainment) in 16 areas (Seoul, Busan, Daegu, Inchon, Gwangju, Daejeon, Ulsan, Gyeonggi-do, Gangwon-do, Chungcheongbuk-do, Chungcheongnam-do, Jeonrabuk-do, Jeonranam-do, Kyoungsangbuk-do, Kyoungsangnam-do, Jeju-do) for 2 years (2007~2008). And we divided 32 DMU which are the objects of local industries evaluation into two groups considering the similarity of administrative area. One group is consist of 14 DMUs of 7 metropolises; Seoul, Busan, Daegu, Inchon, Gwangju, Daejeon and Ulsan, and another group is consist of 18 DMUs of 9 provinces; Gyeonggi-do, Gangwon-do, Chungcheongbuk-do, Chungcheongnam-do, Jeonrabuk-do, Jeonranam-do, Kyoungsangbuk-do, Kyoungsangnam-do and Jeju-do. We applied the basic theory of DEA model which is the tool for the scientific and rational comparative evaluation to evaluate the comparative efficiency. We used WARWICK DEA S/W for Windows Program which can analyze the data in various ways as actual proof tool. It is important for Korean cultural industry to raise the efficiency of the departmental and local company activities which can progress continuously and effectively. So evaluation of cultural industries is needed to see how it works to estimate, analyze and evaluate the efficiency of each departmental and local industry and then apply those to a control factor for later, and the efficiency evaluation is very important to realize them. Purpose of this study is to find the way for cultural industry to progress according to the results. So, we collected the departmental and local companies data (Decision Marketing Unit: DMU) and then analyzed them with DEA (Data Envelopment Analysis) model to evaluate the efficiency. The data in this study is from Mun-Hwa-San-Eop-Baek-Seo 2001~2008. We divided them into two groups and analyzed. The departmental industries data is from 2003~2007 and the local industries data is from 2007~2008. Based on this data, we analyzed the comparative efficiency of the data of 50 DMU (Decision Making Unit)s of 10 departmental industrial companies (publication, comics, music, game, movie or video, animation, advertisement, broadcasting, character, digital education and information) for 5 years (2003~2007) which are the objects of cultural industrial supportive policy and 32 DMUs, which are 7 contents industries (publication, comics, music, movie, animation, character, edutainment) in 16 areas (Seoul, Busan, Daegu, Inchon, Gwangju, Daejeon, Ulsan, Gyeonggi-do, Gangwon-do, Chungcheongbuk-do, Chungcheongnam-do, Jeonrabuk-do, Jeonranam-do, Kyoungsangbuk-do, Kyoungsangnam-do, Jeju-do) for 2 years (2007~2008). And we divided 32 DMU which are the objects of local industries evaluation into two groups considering the similarity of administrative area. One group is consist of 14 DMUs of 7 metropolises; Seoul, Busan, Daegu, Inchon, Gwangju, Daejeon and Ulsan, and another group is consist of 18 DMUs of 9 provinces; Gyeonggi-do, Gangwon-do, Chungcheongbuk-do, Chungcheongnam-do, Jeonrabuk-do, Jeonranam-do, Kyoungsangbuk-do, Kyoungsangnam-do and Jeju-do. We applied the basic theory of DEA model which is the tool for the scientific and rational comparative evaluation to evaluate the comparative efficiency. We used WARWICK DEA S/W for Windows Program which can analyze the data in various ways as actual proof tool.

Evaluation of Creative Space Efficiency in China’ Provinces Based on AHP Method

Shan-Shan Hu,Hyung-Ho Kim 한국인터넷방송통신학회 2020 Journal of Advanced Smart Convergence Vol.9 No.4

The AHP method was used in 30 provinces of China to construct the index system of creative space efficiency evaluation and determine the weight of each index. The fuzzy comprehensive evaluation method was further used to score the indexes at all levels, and then the total efficiency score was sorted. The purpose of this study is to adjust the regional layout of creative space reasonably and implement financial policies accurately through the evaluation of the efficiency of creative space. The results is ranking top in weight of several indicators, which include the number of incubated Startups, the number of innovation and entrepreneurship mentors, the survival rate of incubator, the innovative training activities, etc. It was also found that Beijing, Shanghai, Jiangsu, Guangdong and Zhejiang ranked first in the score of creative space efficiency. This study is meaningful in that it was In order to effectively solve the problem of the imbalance of the creative space efficiency in China's province, by coordinating the regional pattern, establishing a sound service system and improving the efficiency evaluation system.

다 기간 성과평가를 위한 Super Efficiency DEA 모델 및 사례적용

김기성,이태한 서비스사이언스학회 2025 서비스연구 Vol.15 No.1

본 연구는 다 기간 성과평가를 위한 super efficiency DEA(Data Envelopment Analysis) 모델들을 제안하고, 이를활용한 성과 측정 사례를 제시하였다. DEA는 인과관계를 밝히기 어려운 복수의 투입과 산출 데이터를 갖는 조직단위(DMU)의효율성을 평가하는 분석 도구로 널리 활용되고 있다. DEA 모델은 투입과 산출 데이터를 기반으로 생산가능집합을 정의하고해당 생산가능 집합 내의 상대적인 위치를 통하여 조직단위에 대한 상대적인 효율성을 평가하는 모델이다. 단일 기간이 아니라여러 기간에 걸쳐 수행되는 프로젝트 등과 같이 다 기간의 투입 및 산출 데이터를 기반으로 다 기간의 평가가 필요한 경우단일 기간과 달리 특정 조직단위의 효율성의 평가를 위한 비교 대상 조직단위의 투입과 산출 데이터의 범위를 다양하게 정의할수 있고 그에 따라 생산가능집합을 다양하게 정의하여 다수의 DEA 모형의 수립이 가능하다. 본 논문에서는 다 기간 성과평가를위하여 다수의 생산가능집합을 정의하고 그에 따른 super efficiency DEA 모델들을 제시하였다. super efficiency DEA 모델은비교대상 투입 및 산출에서 평가대상의 투입 및 산출을 제외하여 DEA 모델에서 효율적으로 평가되는 다수의 조직단위들 사이의상대적인 차이를 측정하고자하는 모델이다. 제시된 모델들에 대하여 다 기간 인력양성 사업인 공학교육 혁신사업의 사례에적용하여 평가 결과를 제시하였다. 평가 결과 제시된 다 기간의 조직단위의 투입 및 산출을 비교 대상에 포함하는 super efficiency DEA 모델들이 단일 기간별로 적용한 super efficiency DEA 결과와 비교하여 순위에는 큰 차이가 없지만 좀 더 차별화된효율성 지수를 제공함을 확인할 수 있었다. This study proposed super efficiency DEA (Data Envelopment Analysis) models for multi-period performance evaluation and presents case studies demonstrating their application. DEA is widely utilized as an analytical tool to evaluate the efficiency of decision-making units (DMUs) that involve multiple inputs and outputs, where causal relationships are difficult to identify. DEA models define a production possibility set based on input and output data, assessing the relative efficiency of DMUs by their position within this set. When evaluating performance over multiple periods, such as in projects involving multi-period inputs and outputs, the scope of input and output data for comparison differs from that of single-period evaluations. This allows for various definitions of production possibility sets, enabling the establishment of multiple DEA models. In this study, several production possibility sets were defined for multi-period performance evaluation, and corresponding super efficiency DEA models were proposed. Super Efficiency DEA models enable the assessment of relative efficiency among efficient DMUs by excluding the input and output data of the DMU being evaluated from the reference set. The proposed models were applied to a multi-period workforce development initiative, specifically the Engineering Education Innovation Project. Data from 10 engineering education innovation centers over a four-year period were used for the analysis. The evaluation results showed that the proposed Super efficiency DEA models, which include multi-period inputs and outputs as comparison targets, provided more differentiated efficiency scores than single period super efficiency DEA models, although there was little difference in the ranking of DMUs.

자료포락분석(DEA) 모형에 따른 대학의 효율성과 대학평가결과 비교

김성훈(Kim Sung-Hoon),이호섭(Lee Ho-Seub) 한국교육평가학회 2008 교육평가연구 Vol.21 No.1

  대학종합평가와 DEA 효율성의 관계를 규명하고, DEA 모형에 따라서 효율성이 달라지는지를 규명하고자 하였다. 종합모형을 사용하여 단위지표 데이터를 사용하는가 총량 데이터를 사용하는가, 그리고 한 변수씩 빼거나 더하는 식으로 9개의 변환모형을 포함하여 총 11개 모형을 설정하였다. 분석을 위한 자료는 2005년도 대학종합평가 자료로서 61개 대학이 분석대상이었다. DEA 효율성과 대학종합평가의 상관관계 분석 결과는 11개 모형중 1개 모형에서만 효율성과 대학종합평가 점수 간 상관이 .05% 수준에서 유의하였는데, 그 값은 .235에 지나지 않았기 때문에 대학종합평가가 효율성을 평가하는 것으로 보기는 힘들었다. 그리고 DEA 모형에 따른 효율성 분석결과는 어떤 변수가 배제되거나 추가되는가에 따라서 그리고 데이터의 특성에 따라서도 차이가 나타남을 발견할 수 있었다. 이 결과에 근거하여 대학을 평가할 때 효율성을 고려할 필요가 있지만, 성급한 DEA 적용보다는 종합평가총점과 효율성 간의 관계를 이론적으로 재정립할 수 있도록 연구가 후속될 필요가 있음을 논의하였다.   Does university evaluation include the evaluation of efficiency of the university? Is the efficiency measured by DEA applicable to evaluate the efficiency of universities? To reach answers, first, the university evaluation results were correlated with the efficiency as measured by Data Enveloping Analysis(DEA), and second, consistency of DEA results was tested against the alteration of DEA models. A total of 11 alternating DEA models were made by adding or deleting a variable or by changing scales based on a comprehensive model. Data was from 2005 university evaluation, in which 61 universities participated.<BR>  First finding was that there was not substantive evidence that the university evaluation was assessing efficiency. Only one DEA model out of 11 ones showed statistically significant relationship between efficiency and evaluation result. But the correlation coefficient(r= .235) was not substantively high enough.<BR>  Second finding was that efficiency of the universities was inconsistent over the alteration of the DEA models. The efficiency was affected by the adding or deleting variable or scale change.<BR>  Considering the findings that the current school evaluation system does assess efficiency, and that efficiency is affected by DEA models, it was concluded that a thorough and careful study to set up a DEA model must precede an application of DEA in evulating efficiency of universities in reality.

한국에서의 입법평가 : 사례연구 ― 입법평가 기준틀의 모색을 위한 시론 ―

이인호 한국공법학회 2009 公法硏究 Vol.38 No.1

The evaluation of legislation means the analysis and assessment of the effects of legislation. It basically focuses on the effects of any bill or statute. It usually analyzes what changes a bill will bring about or a statute have brought about in the behaviors of people and social circumstances. Then it assesses the results of change in view of cost and benefit. In result, the legislative evaluation is interested in the causal relationship between the legislative measures and social realities. This paper is a preliminary study on the framework and criteria for legislative evaluation in Korea. It elucidates seven criteria of evaluation: (i) Sufficient Grounds and Definiteness of Legislative Goals; (ii) Propriety of Regulation Scope; (iii) Reasonableness of Alternative Probe; (iv) Systemic Consistency of Regulation; (v) Effectiveness of Legislation; (vi) Efficacy of Legislation; and (vii) Efficiency of Legislation. The evaluative elements in each criterion are as follows. Criteria of Evaluation Types of Evaluation Elements of Evaluation Sufficient Grounds and Definiteness of Legislative Goals Ex-ante Evaluation ① Fully catch hold of the nature of the risk or harm on the basis of accurate and sufficient factual grounds? ② Properly judge that an affair causing risk or harm embraces any other good effect or utility? ③ Properly set up the legislative goals on the sufficient factual grounds? ④ Obviously present the legislative goals? Propriety of Regulation Scope Ex-ante Evaluation/ Midterm Evaluation ① Classify the weight of risk or the priority of regulation need between the objects of regulation? ② Properly define the scope of regulation according to the above priorities? Reasonableness of Alternative Probe Ex-ante Evaluation / Midterm Evaluation ① Cannot the new legislative goals be achieved through the existing regulations? ② Does a temporary alternative belong to the ambit of the legislative powers? ③ Generally estimate the presumptive costs and benefits of each possible alternative? ④ Do the opted legislative measures cause damage to the important constitutional principles and values? ⑤ Do the opted legislative measures guarantee the superiority over any other alternatives? Systemic Consistency of Regulation Midterm Evaluation ① Is the strength or density of the regulation proportional to the risk or harm on the whole? ② Do the legislative measures overlap each other in the objects and domain of regulation? ③ Is there a contradiction between basic concepts? Effectiveness of Legislation Midterm Evaluation ① Is it not a genuine retroactive legislation which change the completed legal effects of past actions or situations? ② Take any reparative measures for disadvantages suffered by the change of legislation? ③ Is the regulation intelligible, simple, and definite? ④ Require too high level of moral standards? ⑤ Endeavor to hear and reflect the opinions of those interested? Post Evaluation ① Does an average person understand the regulation contents easily and accurately? ② Do the people abide by the legislation? ③ Does the compliance result from the legislative instructions? Efficacy of Legislation Midterm Evaluation ① Is the causal assumption between goal and measure correct? Post Evaluation ① Do the results of legislation come close to the expected goals? ② Are there any other elements or factors which influence the legislative results? Efficiency of Legislation Midterm Evaluation ① Are the prospective benefits high in priority of social demands? ② Are the prospective benefits urgent and compelling? ③ Do the prospective costs have something to do with the detriment of constitutional interest or values? ④ Are the prospective side effects grave and serious? Post Evaluation ① What kind of benefits and to what extent did the legislation attain? ② To what extent did the legislation command enforcement costs? ③ Did the legislatio... 입법평가란 기본적으로 입법의 효과(effects)에 초점을 맞추어, 특정한 입법조치가 수범자의 태도나 행동 혹은 상황에 어떤 변화를 야기하는지를 분석하고, 그 변화의 결과를 비용(costs)과 편익(benefits)의 관점에서 평가하는 작업이다. 그리하여 입법평가는 입법조치와 사회현실 사이의 인과관계(causal relations)에 관심을 갖는다. 통상 입법자는 명시적이든 묵시적이든 인과관계에 관한 일정한 가정(assumptions)에 근거해서 입법행위를 한다. 그러나 입법평가의 주된 목적이 그러한 입법자의 가정이 옳고 그르다는 것을 증명해보이려는 것은 아니다. 입법평가란 입법의 효과에 관한 입법자의 가정과 인식을 향상시키기 위한 것이다. 때문에 입법평가는 입법조치와 사회현실 사이의 인과관계에 관한 정확하고 적절한 정보나 지식을 산출하여 입법자에게 제공함으로써 입법의 질을 제고하고자 하는 실천적인 작업이다. 이 글은 이러한 입법평가 작업을 수행하기 위한 기준틀을 모색하기 위한 시론적 연구이다. 제2장(II)에서는 이러한 입법평가의 개념과 그 의의가 어디에 있는지, 입법평가(사전입법평가, 병행입법평가, 사후입법평가)의 구체적인 목적이 무엇인지, 그리고 입법평가의 한계가 무엇인지를 간단히 살핀다. 이어 제3장(III)에서는 입법평가의 기준을 7가지로 제시하고 각 기준의 판단에 필요한 평가요소들을 정리하면서 이해의 편의를 위하여 관련된 몇 가지 입법사례들을 소개한다. 7가지 입법평가의 기준은 다음과 같다: (i) 입법목표의 근거충실성과 명확성, (ii) 규율범위의 적정성, (iii) 대안모색의 적정성, (iv) 규율의 체계정합성, (v) 입법의 효과성(effectiveness), (vi) 입법의 유효성(efficacy), 그리고 (vii) 입법의 효율성(efficiency).

DEA 모형을 통한 한국프로농구 선수의 포제션 대비 생산 효율성 측면의 선수 가치평가 및 경기력 영향 분석

김필수,문정준 한국사회체육학회 2023 한국사회체육학회지 Vol.- No.92

Purpose: The purpose of this research is to conduct a DEA (Data Enveploment Analysis) assessment to evaluate the efficiency of Korean Basketball League (KBL) playe rs and to distinguish efficient player types based on the concept of possession input. Method: We theoretically extended the traditional concept of ball possession in the sport management literature by evaluating player efficiency based on ball possession. We suggested an accurate measurement of possession-based efficiency of Korean professional basketball players, typically utilized by the DEA methodology. Results: The empirical results of this study represented that on-cour tperformance and efficiency of players vary based on the level of ball possessions, configurign a precise evaluation to measure a profe-s sional basketball player’s efficiency. Based on our findings, we descriptively identified our understanding of the fundamental segmentation of players with a spectrum of ‘extreme-level of ball possession efficiency (ball hog)’ and ‘effective-level ball possession efficiency (bule-collar worker)’. To rigorously estimate , empirically measure, and evaluate players’ efficiency, we conducted regression analysis. The results indicated that possession-based player efficiency was associated with their floor impact counter (FIC) performance. Conclusion: In summary, the findings of this study imply that possessionb-ased player efficiency is one of the most significant player evaluation features affecting on-court performance.

DEA 모형을 이용한 전라남도 지역 축제의 정량적 효율성 평가

김재윤,강인규,이수현 한국기업경영학회 2010 기업경영연구 Vol.17 No.4

The purposes of this paper is to evaluate the relative efficiency of regional festivals and to provide inefficient group members with benchmark models for improving their management efficiency. To do this, a DEA(Data Envelopment Analysis) is taken advantage of as the efficiency evaluation method. DEA, as a non-parametric approach, evaluates relative efficiency of similar inputs and output structure and determines a set of Pareto-efficient decision making units(DMUs) with an objective of calculating a discrete piecewise frontier. In this paper, we use a DEA model to identify efficient and inefficient groups and measured efficiency scores of the Jeonnam regional festivals using eleven data for 2006-2008. With respect to efficiency analyzed by CCR and BCC models, the Jindo Miracle Sea festival stands high in 2006, whereas the Kwangyang Maehwa(Japanese apricot flower) Culture and the Gurye Sansuyoo(Cornus Officinalis) festivals show high in 2007 and 2008. In addition, we propose a policy of improving in management efficiency out of regard for output. We also performed Tier analysis for suggesting benchmark cases that could be as a role models to the members of the inefficient groups. Tier analysis is a technique that can cluster DMUs according to their efficiency levels. In this analysis, the efficiency scores of entire DMUs is obtained. The results reveal the most efficient group by indicating their scores are equal to 1. We call this group ‘tier 1’. Then, the analysis proceeds DEA again only with the inefficient DMUs which are not on tier 1. DMUs whose efficiency scores are equal to 1 are set ‘tier 2.’ We repeat the same procedure while the number of remaining inefficient DMUs is at least two times multiple of that of input plus output variables. As a result of Tier analysis, we find that the great battle of Myeongryang festival may take the Bubsung Dano festival, Damyang Bamboo festival and Gwangyang Maehwa festival as their benchmark cases. And Hampyeong butterfly festival may take Gokseong Simcheong festival, Damyang Bamboo festival and Gwangyang Maehwa festival as their benchmark cases. This result may provide a visible road-map for the local government. The local government can better understand the situation their festival and they prepare better strategies for the future. The results of the DEA model may be different according to the used input/output variables. This study examined the data of local government reports and selected proper elements. However, as the comparative efficiency of DMUs may change according to the input and output variables, it is hoped that there will be a number of studies to analyze efficiency of regional festivals by means of DEA in order to make the accurate evidences to identify optimal input and output combination. 본 연구에서는 전라남도 지역축제의 상대적 효율성을 평가하고 비효율적이라고 분석되는 축제들의 벤치마킹 대상을 제시하고자 한다. 이에 따라 2006년부터 2008년까지 지속성을 유지한 11개의 축제를 대상으로 DEA 분석을 실시하여 효율적 축제와 비효율적 축제를 파악하고, Tier분석을 실시하여 비효율적 축제가 벤치마킹할 수 있는 효율적 축제를 단계별로 제시하였다. CCR 및 BCC 모형에 의한 분석 결과, 2006년에는 진도신비의바닷길축제, 2007년과 2008년에는 광양매화문화축제와 구례산수유꽃축제가 각각 효율적인 것으로 분석되었고, 비효율적인 축제에 대하여 산출측면에서의 효율성 증대 방안을 제시하였다. Tier 분석 결과 함평나비축제와 해남명량대첩제가 최종적으로 비효율적 집단으로 평가되었고, 해남은 영광법성단오제·담양대나무축제·광양매화문화축제를, 함평은 곡성심청효문화축제·담양대나무축제·광양매화문화축제를 단계적으로 벤치마킹하면 효과적인 개선을 이룰 수 있을 것으로 분석되었다. 이러한 결과는 각 지역축제를 관할하는 지방자치단체에 현실적이고 수용 가능한 정보를 제공하여 지역축제에 대한 단기 및 중·장기적 전략수립에 도움을 줄 수 있을 것으로 판단된다

지방정부 복지인프라의 효율성 평가

류영아(柳?我) 한국지방정부학회 2006 지방정부연구 Vol.10 No.1

  본 연구는 기초자치단체의 효율성을 평가하기 위해 전국 234개 기초자치단체를 행정계층과 재정자립도별로 구분하여 복지인프라를 분석하였다. 이를 위해 첫째, 자료포락분석(DEA)와 변형된 자료포락분석(Post-DEA)이라는 계량적 기법으로 기초자치단체의 복지인프라 효율성을 평가하였다. 둘째, 계량적 평가 결과를 기준으로 일부 기초자치단체에 대한 질적인 평가를 실시하여 계량적 평가와 질적인 평가 간의 비교와 보완을 시도하였다.<BR>  계량적 평가 결과, 행정계층 중에서는 군의 복지인프라 효율성이 가장 낮았고 자치구의 효율성이 가장 높았다. 또한 재정자립도별 구분에서는 재정자립도 20% 미만인 기초자치단체의 효율성이 가장 낮았다. 질적인 평가 결과 DEA 모형이 신뢰할만한 평가도구라는 것을 알 수 있었고, 계량적 평가에서 분석하지 못했던 리더십ㆍ자원봉사ㆍ주민참여 등을 복지서비스의 효율성 향상 요인으로 확인할 수 있었다.   This study explored the efficiency of social welfare infrastructures provided by the local governments. We analyzed efficiency by administration system and financial independence degree. Firstly, the relative efficiency of the social welfare infrastructures provided by 234 local governments was measured. Quantitative evaluation tools used were Data Envelopment Analysis(DEA) and Post-DEA. Secondly, a qualitative evaluation was done. We compared quantitative evaluation & qualitative evaluation.<BR>  From the quantitative evaluation, we found that the Gun have low efficiency level, and the Gu have high efficiency level. And Local governments with below 20% financial independence degree have low efficiency level. On the basis of the qualitative evaluation, we could find the good fitness of our DEA model. In addition, we found that some factors such as leadership, volunteer services, and participation of the residents were key factors increasing the efficiency of the social infrastructure system.

사회복지시설평가의 현실과 개선방안:장애인복지시설을 중심으로

이선우,최상미 한국사회복지정책학회 2002 사회복지정책 Vol.15 No.-

The evaluations of social welfare institutions have been performed on most of them which received financial supports from the governments, including social services centers, welfare services centers for disabled people, residential institutions for children, aged people, disabled people, women, homeless people, and mentally ill people, and support institutions for self-help since the 1998 act of social welfare work has made the evaluation of social welfare institutions mandatory. The evaluation is considered as both positively and negatively; it has improved social welfare institutions very rapidly within a short time period as well as it has put on too much focus on preparing documents rather than providing services. Recently, social workers at social services centers in Seoul opposed seriously against the evaluation. However, the evaluation of social welfare institutions is inevitable because it is related to a global tendency of using resources efficiently. Therefore, it is necessary for us to make the evaluation efficiently and effectively as much as possible by reducing the problems of the evaluation while maintaining its advantages. This study categorized the problems of the evaluation into problems of evaluating process, evaluation index, and use of evaluation results. To reduce these problems, this study suggested the below: First, the evaluation index should be specialized according to the types of the institutions, and the contents of the evaluation should move toward program evaluation from institution evaluation. Second, a permanent agency for social welfare institutions should be established in order to fundementally solve the problems of reliability. Third, lowly-evaluated institutions should be supported by educating their employees to improve their management, while highly-evaluated institutions should be rewarded with the total budget and the exemption of regular audits for a certain period. 사회복지시설평가는 1998년 사회복지사업법의 개정으로 의무화되면서 2001년까지 정부로부터 재정을 지원받는 대부분의 사회복지시설, 즉 사회복지관, 장애인복지관 및 아동복지시설, 노인복지시설, 장애인복지시설, 여성복지시설, 부랑인시설, 정신요양시설, 자활후견기관 등에 대한 평가가 실시되었다.사회복지시설평가는 짧은 시간에 사회복지시설을 급속하게 개선시킨 중요한 계기가 되었다는 긍정적인 평가와 사회복지시설의 본연의 업무보다 서류 작성에 치중하게 한다는 부정적인 평가를 동시에 받고 있다. 최근에는 서울시 사회복지관 실무자들이 시설평가에 심하게 반발하기도 했었다. 그러나 사회복지시설평가가 자원을 효율적으로 사용하기 위한 세계적인 경향과 관련되어 있으며 이를 회피하기는 어려운 것이 현실이다. 따라서 사회복지시설평가의 여러 가지 장점을 살리고, 그 문제점을 보완하여 사회복지시설평가의 효율성과 효과성을 최대로 높일 필요가 있다. 본 연구는 사회복지시설평가가 갖고 있는 문제점을 평가과정, 평가도구, 평가결과의 활용의 문제점으로 나누어서 살펴보고, 이 문제들을 완화할 수 있는 방안을 다음과 같이 제안한다.첫째, 사회복지시설평가지표를 세부적인 시설종류에 따라 일부 세분화하며, 현재 그 내용에서 시설평가 중심에서 프로그램평가 중심으로 나아가야 한다. 둘째, 평가위원간 신뢰도의 문제를 근본적으로 해결하기 위해서는 상설평가원을 설립해야 한다. 셋째, 평가결과, 하위시설에는 교육 등으로 운영개선을 지원하고, 상위시설에는 총액예산제와 감사 감면 등의 보상을 제공해야 한다.