• Title/Summary/Keyword: Data Envelopment Analysis (DEA) BCC model

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A Study on the Efficiency Analysis of Container Terminal (우리나라 컨테이너터미널 효율성 분석에 관한 연구)

  • Park, Byung-Keun;Choi, Min-Seung;Song, Jae-Young
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.163-170
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    • 2006
  • This paper presents a approach to the measurement of efficiency. Data envelopment analysis(DEA), as it is called, has particular applicability in the service sector. Applying mathematical programming techniques, DEA enables relative efficiency ratings to be derived within a set of analysed units. This paper investigates the efficiency employing DAE-CCR Model and DEA-BCC Model on data for 15 container terminals covering 1998$^{\sim}$2005 in Korea Results of this paper, suggests to some plan for operation strategy in Container terminals.

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A Study on the Efficiency Analysis of Korean Container Terminal - Focus on Busan Port, Gwangyang Port - (우리나라 컨테이너터미널 효율성 분석에 관한 연구 - 부산항, 광양항을 중심으로 -)

  • Choi, Min-Seung;Song, Jae-Young;Ryoo, Dong-Keun;Park, Byung-Keun
    • Journal of Navigation and Port Research
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    • v.31 no.1 s.117
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    • pp.89-97
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    • 2007
  • This paper presented a approach to the measurement of efficiency in container terminals in Korea. To perform this objective, it used Data envelopment analysis(DEA) which has particular applicability in the service sector. DEA as mathematical programming techniques enables relative efficiency ratings to be derived within a set of analysed units. So this paper investigated the efficiency employing DEA-CCR and DEA-BCC Model on data for 15 container terminals from 1998 through 2005. Results of this paper, suggested to some plan for operation strategy in Container terminals.

An Application of Data Envelopment Analysis in Measuring the Efficiency of Local Governments in Korea (DEA를 이용한 지방자치자체의 성과평가)

  • Suk, Yeung-Ki
    • Korean Business Review
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    • v.17 no.2
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    • pp.185-202
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    • 2004
  • There is an increasing interest in measuring and comparing the efficiency of organization units whose operations are functionally similar and autonomous. Data Envelopment Analysis(DEA) has been extensively used to evaluate the efficiency of non-profit organizations as a whole. This study applies a modified DEA model (Input-oriented BCC model with Nondiscretionary variables) to identify the performance of local government in Korea. It is found that utilizing DEA as a mean of evaluating the performance of local governments yields useful information to decision makers trying to maintain more efficient practices.

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A Study on the Measurement of Service Efficiency using DEA - Focused on the SQI of Five Domestic Banks in Korea - (DEA를 이용한 서비스효율성 측정에 관한 연구 - 국내 5개 시중은행의 서비스품질지수를 중심으로 -)

  • Kim, Jin-Wang;Yoo, Han-Joo;Song, Gwang-Suk
    • Journal of Korean Society for Quality Management
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    • v.37 no.1
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    • pp.80-90
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    • 2009
  • Nowadays, there are many companies which employ the SQI measurement to assess service quality. The purpose of this study is to measure the service efficiency for Bank Industry. In this paper, we tried to measure the efficiency of service quality and overall customer satisfaction by using Data Envelopment Analysis(DEA). Rather than using the usual method of converting the Service Quality Index(SQI) into mean value, we applied CCR/BCC models in DEA to service quality efficiency. Also, DEA/PS Model is recommended as appropriate model for evaluating service efficiency by complementing the shortfalls of the weighted value of DEA Model. In this study, six dimensions of service quality were considered as input variables and output variables(overall customer satisfaction, reusing intention, and word of mouth). The result of this study statistically verifies that 5 DMUs are relatively efficient, and intensive activities for service efficiency are needed for 20 sample branches. Managerial implications based on the analysis were suggested.

The Influence of Efficient Container Terminals Using DEA and SNA (DEA와 SNA를 이용한 효율적인 컨테이너 터미널의 영향력에 관한 연구)

  • Son, Yong-Jung
    • Journal of Korea Port Economic Association
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    • v.31 no.3
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    • pp.155-166
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    • 2015
  • This study selected container terminals of Gwangyang and Busan Ports to evaluate the influence of efficient container terminals. For the study, after data envelopment analysis (DEA) using the CCR and BCC models, the decision-making unit (DMU) system was used to define nodes; and with the use of a reference group in DEA (BCC model) and a lambda value, this study created a social network and analyzed the influences of efficient DMUs through a centrality analysis of eigenvectors. The results are presented as follows: First, as a result of the DEA, CCR efficiencies in PNC, HJNC, and HPNT container terminals of Busan Port were 1 and BCC efficiencies at Singamman Terminal, Wooam Terminal, PNC, HJNC, HPNT, and BNCT container terminals of Busan Port were 1. Second, as a result of undertaking social network analysis (SNA), according to an eigenvector centrality analysis, HJNC Terminal was referred to the most (influence score of 0.515), which indicates that it is the most influential as a container terminal. The influence of PNC Terminal was 0.512, while that of Wooam Terminal was 0.379. CJ Korea Express in Gwangyang Port was ranked fourth in influence, but its influence score of 0.256 indicates that it was the most influential of the container terminals at Gwangyang Port.

Analysis of Operational Efficiency of Military Department of University Using Data Envelopment Analysis Method (자료포락분석법을 활용한 일반대학 군사학과의 운영 효율성 분석)

  • Young-Min Bae;Sweng-Kyu Lee
    • Convergence Security Journal
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    • v.23 no.2
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    • pp.95-102
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    • 2023
  • The purpose of this paper was to confirm the operational level of the military department of universities, which plays a key role in the officer training process, through empirical research and confirm meaningful results for improvement. There are 11 university military departments operated through the Army, agreements, and semi-agreement, and the Data Envelopment Analysis (DEA) was applied from the perspective of resource input and performance for each university's military department operation to analyze relative efficiency and confirm specific directions for improvement. As a result of operational efficiency analysis, 6 DMUs (Decsision Making Unit) were found to be efficient in the BCC model out of 11 DMUs, and the evaluation results could be confirmed through classification of efficient and inefficient groups through data capture analysis. This paper may be of practical value in that it checks the efficiency of the comparative university military departments and confirms specific information for development through the DEA-Additive model that reflects several evaluation factors at once. Through this, the operators of each university's military department are admitted.

A DEA(Data Envelopment Analysis) Approach for Evaluating the Efficiency of Exclusive Bus Routes (자료포락분석을 이용한 서울시 간선버스노선 효율성 평가)

  • Han, Jin-Seok;Kim, Hye-Ran;Go, Seung-Yeong
    • Journal of Korean Society of Transportation
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    • v.27 no.6
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    • pp.45-53
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    • 2009
  • This study presumes the efficiency of each route by utilizing data of Seoul's exclusive bus routes for the 2008 and the DEA model. In the estimation, it is assumed that the number of passengers and profits of each route is calculated by considering the number of buses and stops, travel distance, intervals and management cost. This study computed the efficiency scores of each bus line in Seoul based on the data for the first half of 2008 and one of the DEA models, namely the BCC model. After analysis using the input-oriented BCC model, out of a total of 18 lines of interest, there were 2 CRS lines and 16 IRS lines. Also, the Tobit Regression Analysis that helps identify the impact of the elements used in the analysis on efficiency scores proved that the most influential element to exclusive buses is the length of intervals.

Selecting the Batters of National Baseball Squad using Data Envelopment Analysis (DEA를 이용한 야구 국가대표단의 타자 선발에 관한 연구)

  • Suk, Yeung-Ki
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.1
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    • pp.165-172
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    • 2014
  • The purpose of this paper is to identify whether the national baseball squad made up of the best players may get the outstanding results in the international competitions or not. Using Data Envelopment Analysis, the relative efficiency of players in Korean Baseball Organization is estimated as performance measure, and compared with the efficiency scores of national squad members. The paper focuses on the proper choice of DEA model in a baseball setting, thereby selecting the BCC model with non-discretionary variable. Two input variables(plate appearances and stolen bases to enforce) and three output variables(runs, on-base plus slugging and stolen base percentage) are used to evaluate the efficiency of the baseball players. Results showed that 22 players among 97 players were classified as efficient and 8 players among 12 national squad members were as efficient. These findings indicate a potential for DEA to be a major part of the analytical approaches in evaluating the relative efficiency of players.

A Data Envelopment Analysis Model for Evaluation of Efficiency of Deep-Sea Fishing Industry (원양어업의 효율성 평가를 위한 자료포락 분석 모형)

  • Kim, Jae-Hee;Choi, Kang-Deuk;Kim, Soo-Kwan
    • The Journal of Fisheries Business Administration
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    • v.39 no.3
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    • pp.49-65
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    • 2008
  • In Korea, deep-sea fishing industry is faced with pressure of being thrown out of business, because of the upcoming unfavorable business conditions such as the fishing regulation of coastal countries, Korea-US Free Trade Agreement(KORUS FTA), and the other socio-economic changes. Hence, we present an evaluation of future business competitive for the deep-sea fishing industry so that the government can develop a concession plan for the deep-sea fishing industry by utilizing the results of this study. In efficiency analysis of deep-sea fishing industry, the decision maker may have two problems: (1) how to deal with multiple inputs and outputs of deep-sea fishing industry and (2) how to assign the weights on different inputs and outputs, In this paper, we proposed to use Data Envelopment Analysis (DEA) to estimate efficiency of deep-sea fishing industry with multiple inputs and outputs. In the DEA, The direct impact of KORUS FTA, fishing regulation of coastal countries, fishing charges, and competitive fishing conditions were used as input parameters while the profitability and secured fishing quarters, as outputs. The results of DEA-BCC model indicate that 6 out of 12 DUMs have better efficiency under variable return to scale assumption.

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Sequential use of SOM, DEA and AHP method for the stepwise benchmarking of emerging technology (신흥 기술의 단계적 벤치마킹을 위한 SOM, DEA와 AHP 방법의 순차 활용)

  • Yu, Peng;Lee, Jang Hee
    • Knowledge Management Research
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    • v.13 no.5
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    • pp.43-64
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    • 2012
  • Emerging technologies have significant implications in establishing competitive advantages and are characterized by continuous rapid development. Efficient benchmarking is more and more important in the development of emerging technologies. Similar input level and importance are two necessary criteria need to be considered for emerging technology's benchmarking. In this study, we proposed a sequential use of self-organizing map(SOM), data envelopment analysis(DEA) and analytical hierarchy process(AHP) method for the stepwise benchmarking of emerging technology. The proposed method uses two-level SOM to cluster the emerging technologies with similar required input levels together, then, in each cluster, uses DEA-BCC model to evaluate the efficiencies of the emerging technologies and do tier analysis to form tiers. On each tier, AHP rating method is used to calculate each emerging technology's importance priority. The optimal benchmarking path of each cluster is established by connecting the emerging technologies with the highest importance priority. In order to validate the proposed method, we apply it to a case of biotechnology. The result shows the proposed method can overcome difficulties in benchmarking, select suitable benchmarking targets and make the benchmarking process more efficient and reasonable.

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