• 품질경영학회지
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• 제32권2호
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• pp.77-92
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• 2004

It is difficult but very necessary to measure the productivity of container terminals as logistics service provider. It is meaningful to find the appropriate inputs and outputs of the logistics service delivery systems and to measure the relationship between these inputs and outputs. This study proposes a model of evaluating the efficiency of container terminals. The evaluation consists of three phases. First, DEA(Data Envelopment Analysis) phase, determines the efficiency score and weights of DMUs(Decision Making Unit). This phase performs through four steps : selection of DMU, selection of DEA model, determination of input and output factors, calculation of efficiency score and weights for each DMU. Secondly, CEM (Cross Evaluation Model) phase, is to calculate the cross-efficiency scores of DMUs. This phase performs through three steps: selection of CEM, determination of cross-efficiency score for each DMU and development of cross-efficiency matrix. Finally, average cross-efficiency analysis phase is to compute the average cross-efficiency score. The proposed model discriminates among DMUs and ranks DMUs, whether they are efficient or inefficient.

• 산업경영시스템학회지
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• 제38권2호
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• pp.108-119
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• 2015

This study intends to propose a non-oriented DEA based game cross-efficiency approach for supplier selection. With a discussion on the choice of DEA models and approaches that are most appropriate for supplier selection, we propose a game cross efficiency model based upon the non-oriented variable returns-to-scale RAM DEA by adapting the existing game cross efficiency model based upon the oriented constant returns-to-scale CCR DEA. We develop the RAM game cross efficiency model and a convergent iterative solution procedure to find the best game cross efficiency scores that constitute a Nash equilibrium. We illustrate the proposed model with two data sets of supplier selection, and demonstrate that significantly different results are obtained when compared with the existing approaches.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.298-299
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• 2018

본 연구에서는 의사결정자의 사전정보가 필요하지 않은 DEA 모형들을 대상으로 변별력 평가를 실시하였다. 변별력 평가를 위한 DEA모형으로 Entropy 모형, Bootstrap 모형, Benevolent Cross Efficiency 모형, Aggressive Cross Efficiency 모형, Game Cross Efficiency 모형을 선정하였다. 변별력 평가척도인 변동계수(coefficient of variation)와 중요도(degree of importance) 평가기준을 이용하여 5개 DEA 모형의 변별력을 평가하였다. 평가결과에 따르면 변별력 순위는 2개 평가 지표 모두에서 Entropy 모형, Aggressive CE 모형, Benevolent CE 모형, Game CE 모형, Bootstrap 모형 순으로 평가되었다.

• 한국콘텐츠학회논문지
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• 제17권1호
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• pp.201-212
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• 2017

본 연구에서는 변동계수를 이용하여 DEA 모형의 변별력 평가에 적용할 수 있는 새로운 평가기준을 제시하였다. 변별력 평가를 위해 기존 연구에서 제시한 중요도와 본 연구에서 제안한 변동계수를 이용하여 변별력을 분석하였다. 다양한 DEA 모형들 중 변별력 평가를 위해 CCR-DEA, BCC-DEA, entropy, bootstrap, super efficiency, cross efficiency DEA 모형을 선정하고 실증분석을 실시하였다. 모형들의 순위상관관계를 파악하기 위해서 CCR 모형과 BCC 모형의 효율성 값과 entropy, bootstrap, super efficiency, cross efficiency 모형의 효율성 값들 간에 순위상관분석을 실시하였다. 본 연구를 통해 도출된 연구결과를 요약하면 다음과 같다. 첫째, 중요도와 변동계수를 이용한 모형들의 변별력 순위가 동일한 것으로 분석되어 변동계수를 DEA 모형의 변별력 평가기준으로 이용할 수 있다는 것이다. 둘째, 본 연구의 실증분석 결과에 따르면 4개 모형 중 super efficiency 모형이 변별력이 가장 높은 것으로 분석되었다. 셋째, CCR 모형과 순위상관관계가 가장 높은 모형은 super efficiency 모형으로 나타났고, BCC 모형과 순위상관관계가 가장 높은 모형도 super efficiency 모형으로 분석되었다.

• 한국경영과학회지
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• 제33권4호
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• pp.83-100
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• 2008

We propose a new aggressive formulation of cross-efficiency in Data Envelopment Analysis(DEA). In the traditional aggressive formulation, the efficiency score of a test DMU is maximized as the first goal while an average of efficiency scores of peer DMUs is minimized as the second goal. The proposed model replaces the second goal with the minimization of the best efficiency score of peer DMUs. We showed the model is a quasi-convex optimization problem, and for a solution method we developed a bisection method whose computational complexity is polynomial-time. We tested the model on 200 randomly generated DEA problems, and compared it with the traditional model in terms of various criteria. The experimental results confirmed the effectiveness and usefulness of the proposed model.

• 한국항만경제학회지
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• 제30권4호
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• pp.151-168
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• 2014

본 논문에서는 첫째, 국내의 기존연구에서는 전혀 다루어지지 않았던 게임교차효율성 모형에 대해서 설명하였으며, 둘째, 게임교차효율성모형을 이용하여 2009년, 2010년, 2013년과 13개 항만을 대상으로 3개의 투입요소(수심, 총면적, 크레인 수), 1개의 산출요소(컨테이너화물 처리량)를 이용하여 실증분석을 하고 효율성 순위를 측정하였다. 셋째, 또한 기존의 교차효율성 모형에 의한 효율성 및 CCR모형에 의해 효율성을 측정하고 그 효율성 수치에 의한 순위를 측정하였으며, ANOVA분석을 통해서 그러한 순위가 게임교차효율성 모형과 모형 간에 차이가 있는지를 검증하였다. 넷째, 게임교차효율성 메트릭스의 상관계수 값을 구한 후에 평균연결을 사용한 덴드로그램에 의한 방법으로 클러스터링을 측정하였다. 실증분석의 주요한 결과는 다음과 같다. 첫째, 게임교차효율성 모형에 의한 효율성 순위를 3개년도의 효율성 수치 평균값에 근거하여 평균적으로 순위를 측정해 보면, 4번(닝보항), 2번(홍콩항), 3번(상해항), 1번(두바이항)(12번; 싱가포르항), 5번(칭타오항), 13번(카오슝항), 8번(부산항), 6번(토쿄항), 9번(인천항), 7번(나고야항)(11번; 마닐라항), 10번(광양항) 항만의 순서였다. 교차효율성모형과 CCR모형에 의한 순위도 유사한 것으로 나타났다. 둘째, 효율성 순위를 검정한 ANOVA검정분석에서는 세 가지 모형[게임교차효율성모형, 교차효율성 모형, CCR모형]사이에 순위에 차이가 없는 것으로 나타났다. 셋째, 클러스터링 분석에서는 그룹별로 공통적(3개년 또는 2개년)으로 클러스터링되는 항만들을 살펴보면, A그룹에서는 3번(상해항), 8번(부산항)항만, B그룹에서는 4번(닝보항), 7번(나고야항)항만, C그룹에서는 9번(인천항), 11번(마닐라항)항만들로 나타났다. 본 논문이 갖는 정책적인 함의는 다음과 같다. 첫째, 본 논문의 실증분석결과, 클러스터링항만들로서 나타난 항만들에 대한 항만개발, 운영에 대한 내용을 세밀하게 검토하고 해당항만들의 장점 부분은 도입하여 실시하는 것이 필요하다. 둘째, 특히 부산항은 상해항과 인천항은 마닐라항과 전략적인 제휴관계를 맺고, 컨테이너화물처리 면에서의 혜택을 부여해야만 한다.

• 한국경영과학회지
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• 제29권3호
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• pp.41-61
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• 2004

The purpose of this paper is to construct $\ulcorner$CIDEAR(Cross Impact-DEA-AR)$\lrcorner$ model which evaluates proposed R&D projects considering cross impact among them and selects proper projects to utilize resources efficiently as well as to maximize efficacy of investments. For this purpose, $\ulcorner$CIDEAR$\lrcorner$ model is designed as the following six steps. $\ulcorner$Decision Theory Evaluation Model$\lrcorner$ is for setting and selecting the evaluation items according to the structured procedure of evaluation system. The priority of items is decided at $\ulcorner$AR Decision Model$\lrcorner$$\ulcorner$Cross Impact Estimation Model$\lrcorner$ is for computing the final probability of success and the result is used to revise the evaluation results of $\ulcorner$Decision Theory Evaluation Model$\lrcorner$. $\ulcorner$Resource Performance Analysis Model$\lrcorner$ classifies the proposed R&D projects on the basis of required resources and expected performance. Consequently, the possibility of bias of project selection can be prevented. $\ulcorner$Priority Oder Decision Model$\lrcorner$ is for computing the efficacy of proposed projects. Finally, $\ulcorner$Efficacy-Efficiency Cause Analysis Model$\lrcorner$ analyzes the structure of efficacy and efficiency of the projects. The major findings and significances of this study are summarized as follows: (1) $\ulcorner$CIDEAR$\lrcorner$ model can deal with the affairs of R&D projects having the characteristics of mutual independence as well as mutual dependence in the point of efficacy and efficiency. Hence, it is possible to evaluate and select R&D projects more accurately. (2) It can be possible to raise the possibility of projects success. R&D manager can use the information for project management because the efficacy-efficiency structure of selected projects can be analyzed. (3) We proved the usefulness of the constructed $\ulcorner$CIDEAR$\lrcorner$ model using an case about twenty-one R&D projects of a leading company of electronic industry in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권1호
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• pp.1-14
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• 2024

Time-series forecasting is extensively used in the actual world. Recent research has shown that Transformers with a self-attention mechanism at their core exhibit better performance when dealing with such problems. However, most of the existing Transformer models used for time series prediction use the traditional encoder-decoder architecture, which is complex and leads to low model processing efficiency, thus limiting the ability to mine deep time dependencies by increasing model depth. Secondly, the secondary computational complexity of the self-attention mechanism also increases computational overhead and reduces processing efficiency. To address these issues, the paper designs an efficient multi-layer attention-based time-series forecasting model. This model has the following characteristics: (i) It abandons the traditional encoder-decoder based Transformer architecture and constructs a time series prediction model based on multi-layer attention mechanism, improving the model's ability to mine deep time dependencies. (ii) A cross attention module based on cross attention mechanism was designed to enhance information exchange between historical and predictive sequences. (iii) Applying a recently proposed sparse attention mechanism to our model reduces computational overhead and improves processing efficiency. Experiments on multiple datasets have shown that our model can significantly increase the performance of current advanced Transformer methods in time series forecasting, including LogTrans, Reformer, and Informer.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.783-793
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• 2020

The purpose of this study is to investigate whether the ECFA impacted the efficiency of banks in China and Taiwan from 2008 to 2017. This study follows Seiford and Zhu (2002), who recommend using the standard data envelopment analysis model to measure performance by increasing the desirable outputs and decreasing the undesirables. The finding was that overall technical efficiency increased from 2012 to 2017, reaching 0.575, 0.652, 0617, 0.689, 0.701 and 0.74, respectively. This result implies bank efficiency did indeed improve after China and Taiwan signed the ECFA cooperation agreement. The study found that the mean technical efficiency was 0.8756 in China, greater than Taiwan's mean of 0.3511, implying that Chinese banks experienced a greater increase in efficiency after signing the EFCA. One possible reason explored in this study is that China's economy is currently growing at the highest rate in the world, and the banks' efficiency has benefited from greater economic growth. This suggests that cross-strait sustained negotiations to consummate an agreement on trade in the services will be a very important mission in the future. This result also provides significant evidence suggesting that not accounting for undesirable output while estimating the evolution of the model may seriously distort efficiency results.

• 신재생에너지
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• 제3권3호
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• pp.14-19
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• 2007

A flow channel model of a bipolar plate with varying cross-sectional area was newly designed for improving performance and efficiency of a PEM fuel cell stack. As a result, the varying cross-sectional area model showed poor uniformity in velocity distribution, however, maximum velocity in the flow path is about 30% faster than that of the uniform cross-sectional area model. The proposed varying cross-sectional area model is expected to diffuse operating fluids more easily into diffusion layer because it has relatively higher values in pressure distribution compared with other flow channel models. It is expected that the implementation of the varying cross-sectional area model can reduce not only the mass transport loss but also the activation loss in a PEM fuel cell, and open circuit voltage of a fuel cell can thus be increased slightly.