• 제목/요약/키워드: DEA: Data Envelopment Analysis

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SI 프로젝트의 효율성 평가를 위해 자료포괄분석과 기계학습을 결합한 하이브리드 분석 (A Hybrid Approach Combining Data Envelopment Analysis and Machine Learning to Evaluate the Efficiency of System Integration Projects)

  • 홍한국;하성호;박상찬
    • Asia pacific journal of information systems
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    • 제10권1호
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    • pp.19-35
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    • 2000
  • Data Envelopment Analysis(DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

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SI 프로젝트의 효율성 평가를 위해 자료포괄분석과 기계학습을 결합한 하이브리드 분석 (Hybrid approach combining Data Envelopment Analysis and Machine Learning to Evaluate the Efficiency of System Integration Projects)

  • 홍한국;김종원;서보라
    • 한국산업정보학회:학술대회논문집
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    • 한국산업정보학회 2006년도 춘계 국제학술대회 논문집
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    • pp.77-88
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    • 2006
  • Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

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한국 지방공사 의료원의 생산성 평가와 비교 (Productivity Evaluation and Comparision of Korean Provincial Hospitals)

  • 안태식;박정식
    • 한국병원경영학회지
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    • 제2권1호
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    • pp.22-47
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    • 1997
  • This paper evaluated the relative efficiency of 33 provincial medical centers using Data Envelopment Analysis(DEA) and compared the DEA efficiency results with those of the current method conducted by the management evaluation team. DEA Was selected as an alternative efficiency evaluation method since it could handle multiple inputs and multiple outputs simultaneously and identify the sources of inefficiency. To analyze the sensitivity of productivity values to the variable sets, four different sets of input and output variables were identified. Results showed that most of the medical centers are operating far away from the efficiency frontier supporting the previous results. Some centers showed 100% efficiency regardless of the selected variable sets. DEA results are compared with current management evaluation results. Some inconsistencies were found for some DMUs between the results of two methods showing the existence of methodology bias. DEA results and ratio analyses results mostly agree for 1992 data.

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지역사회서비스투자사업 효율성에 관한 연구 자료포락분석(Data Envelopment Analysis, DEA) 대구시 8개구·군을 중심으로 (A study on the Efficiency of Community Service Investment Projects Data Envelopment Analysis, DEA-Centered on 8 districts in Daegu)

  • 이원선;홍상욱
    • 산업진흥연구
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    • 제7권2호
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    • pp.1-13
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    • 2022
  • 본 연구는 대구 지역사회서비스투자사업을 제공하는 기관별 현황과 성과를 통해 효율성을 살펴보고 각 기관의 효율적인 운영을 위한 방향을 모색하는데 그 목적이 있다. 지역사회서비스투자사업의 추진 목적에 부합되는 관리 실태를 점검하여 효율적이고 효과적인 사업추진을 도모하기 위하여 수요자에게 필요한 체계적인 서비스 제공 및 품질개선, 환경개선을 위해서는 서비스 제공기관의 효율성 분석을 통해 정확한 상황과 그에 대한 문제점을 파악하고, 지역 특성에 맞는 프로그램을 개발하고 적극적인 서비스 관리가 필요하다. 구체적으로 각 기관의 정보를 바탕으로 효율성을 측정하고 이를 지방자치단체 간 비교 분석함으로써 보다 안정적이고 지속가능한 지역사회서비스의 제공방향을 모색하는 것이다. 이를 위해 DEA(data envelopment analysis, 자료포락분석) 방법을 활용하여 각각의 기관을 효율성을 분석하고 지자체별로 비교하여 효율적 운영을 위한 목표와 정책적 함의를 제시하는데 그 의의가 있다.

Imprecise DEA Efficiency Assessments : Characterizations and Methods

  • Park, Kyung-Sam
    • Management Science and Financial Engineering
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    • 제14권2호
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    • pp.67-87
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    • 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.

Using DEA and AHP for Hierarchical Structures of Data

  • Pakkar, Mohammad Sadegh
    • Industrial Engineering and Management Systems
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    • 제15권1호
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    • pp.49-62
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    • 2016
  • In this paper, we propose an integrated data envelopment analysis (DEA) and analytic hierarchy process (AHP) methodology in which the information about the hierarchical structures of input-output data can be reflected in the performance assessment of decision making units (DMUs). Firstly, this can be implemented by extending a traditional DEA model to a three-level DEA model. Secondly, weight bounds, using AHP, can be incorporated in the three-level DEA model. Finally, the effects of incorporating weight bounds can be analyzed by developing a parametric distance model. Increasing the value of a parameter in a domain of efficiency loss, we explore the various systems of weights. This may lead to various ranking positions for each DMU in comparison to the other DMUs. An illustrative example of road safety performance for a set of 19 European countries highlights the usefulness of the proposed approach.

DEA모형에 의한 지역수협의 경영평가 (Management Evaluation on the Regional Fisheries Cooperatives using Data Envelopment Analysis Model)

  • 이강우
    • 수산경영론집
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    • 제42권2호
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    • pp.15-30
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    • 2011
  • This study is designed to measure the relative efficiency of regional fishery cooperatives based on Data Envelopment Analysis(DEA) methods. Selecting 40 regional fishery cooperatives in Busan as Decision Making Units (DMUs), the study uses their panel data from 2007 to 2008 to rank the relative efficiency of the DMUs. First, the efficiency score of the DMUs are calculated using CCR, SBM, and super-SMB model. Within the model, input variables are the number of employees and area of fishery cooperatives. Output variables are the amount of deposit money, loan and profit. Based on the efficiency scores calculated from super-SMB model, the efficiency ranking of the DMUs is determined. Second, the differences in average efficiency calculated from the three DEA models are tested using a pair-wise mean comparison test. The results based on the efficiency scores evaluated from super-SMB model show that seven out of the forty DMUs are efficient; among the efficient DMUs, the DMUs that can be benchmarked for inefficient DMUs through the frequency analysis of reference set being identified. Third, the differences in average efficiency of the three DEA models between 2007 and 2008 are tested using pair-wise mean comparison test and the study estimates the efficiency change of the DMUs between 2007 and 2008 using Malmquist productivity index(MPI). Finally, the paper suggests an improved composite DMU superior to the inefficient DMUs evaluated by Super-SBM model.

Cost and Profit Efficiency of Banks: Stochastic Frontier Analysis vs Data Envelopment Analysis

  • Baten, Md. Azizul;Kasim, Maznah Mat;Rahman, Md. Mafizur
    • 아태비즈니스연구
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    • 제6권2호
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    • pp.1-17
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    • 2015
  • This study compares the most widely used parametric and non-parametric techniques to measure cost and profit efficiency of banks, namely the Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We formulate the specification form of both stochastic cost and profit frontier models and constant return to scale Cost DEA and Profit DEA models and provide an empirical assessment of the cost and profit frontiers based on a panel dataset of National Commercial Banks (NCBs) and Private Banks (PBs) in Bangladesh over the 2001-2010 period. The cost inefficiency and profit efficiency are slightly higher for PBs than NCBs in case of both SFA and DEA. The coefficients of advance and off-balance sheet items are significant that positively influence the banks in stochastic cost frontier model while the advance, other earning assets, price of borrowed fund are significant and negative effects on the banks in stochastic profit frontier model. The average cost inefficiency and average profit efficiency are recorded with 16.3% and 91% respectively. The highest and lowest cost inefficiency are observed for Janata Bank and United Commercial Bank Limited whilst the highest and lowest profit efficiency are recorded for Eastern Bank Limited and Janata Bank respectively. The average technical and allocative efficiency are 68.8% and 35.9%, respectively in case of CRS cost-DEA model whereas they are 70.3% and 31.8% in case of CRS profit-DEA model. The average cost inefficiency is recorded 6.3% by SFA whereas it is 24.5% by DEA. The average profit efficiency is found 91% by SFA while it is 22.1% by DEA, and SFA method shows better bank efficiency than DEA.

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DEA와 맘퀴스트 생산성 지수를 활용한 OECD 국가간 의료서비스 효율성 분석 (Analyzing the National Medical Service Efficiency of OECD Countries Using DEA and Malmquist Productivity Index)

  • 김지혜;김해수;임빛나;윤장혁
    • 한국경영과학회지
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    • 제37권4호
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    • pp.125-138
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    • 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.

DEA를 이용한 식자재유통 및 급식기업의 효율성 분석 (Analysis on Efficiency of Food Material Distributors and Food Service Companies by DEA)

  • 민하나;김석운;최규완
    • 한국식생활문화학회지
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    • 제31권4호
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    • pp.339-347
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    • 2016
  • 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.