• Journal of Korean Society for Quality Management
• /
• v.32 no.2
• /
• pp.77-92
• /
• 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.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.7
• /
• pp.2406-2419
• /
• 2010

This study aims to elevate the usefulness of the current annual Accreditation of Hospitals. To achieve this purpose, A modeling of an efficiency analysis based on DEA and AHP to the Accreditation of Hospitals Data from 2004 to 2008. By applying to AHP and DEA_AR to the scores derived from the various domains in data, An adequate prediction model about conversion factor in fee contract is made. By summarizing information derived from DEA, factor analysis and Generalized Linear Model, The linear functions combining conversion factor and efficiency index is successfully established. The factor analysis with AHP was used to merge diverse scores from the domains of evaluation. Not only the input and output initially introduced, AHP scores, dummy variables of hospital classification, geographical location are effective variables to forecast a conversion factor. If a predicted conversion factors from efficiency is used, It will be a great contributions to the annul doctor's fee contract.

• The Journal of the Korea Contents Association
• /
• v.21 no.10
• /
• pp.309-321
• /
• 2021

While total sales of broadcasting business have been increasing, terrestrial broadcasters' sales are stagnant and comprehensive programming program providers(PPs)' sales are increasing. The purpose of this study is to derive implications by analyzing the relative efficiency and super-efficiency of domestic broadcasters in such an asymmetric situation. In this study, we use input and output data of three central terrestrial broadcasters and four comprehensive programming PPs from 2012 to 2019. For the analysis, Additive DEA model and Additive super-efficiency DEA model are used with the assumption of VRS condition since the broadcasting industry is characterized by economies of scale. As a result, we find out that the input excess of tangible assets is the most decisive cause of inefficiency that reduces the efficiency of central terrestrial broadcasters. On the other hand, for the comprehensive programming PPs, the input excess of tangible assets and the output shortfall of total sales are important factors of inefficiency.

• Management Science and Financial Engineering
• /
• v.14 no.2
• /
• pp.67-87
• /
• 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.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.4
• /
• pp.1551-1556
• /
• 2012

This study proposes an efficient portfolio selection methodology for the listed corporations in KOSPI with consideration of managerial efficiency. For each industrial sector classified by KRX(Korea Exchange), the proposed method carries out an efficiency analysis using DEA (Data envelopment analysis) approach and for the efficient corporations filtered by DEA, construct portfolio using Markowitz's Model. In order to show the effectiveness of the proposed method, we constructed annually portfolios for 4 years (2007-2010) out of 600 listed corporations in KOSPI and KOSDAQ, and proved that our portfolios are superior to benchmark portfolios in terms of rate of returns.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.1
• /
• pp.163-170
• /
• 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.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.7
• /
• pp.53-62
• /
• 2022

Commercial banks have a significant impact on the economy of Vietnam because they provide the majority of transactional capital. Therefore, the operational efficiency of commercial banks is a viral topic for the study of the Vietnamese banking system. The research aims to examine the efficiency and inefficiency of joint-stock commercial banks in Vietnam from 2016 to 2020 and then classify them into the efficient group and inefficient group. The study employs the time series data of 29 joint-stock commercial banks during the period 2016-2020. Based on the data collected from the annual audited financial statements of 29 Vietnamese joint-stock commercial banks, the authors select input and output variables for the standard DEA models and anti-efficient DEA models. This research uses two stages, first, by applying the standard DEA model, we investigate the efficient banks; second, by employing the anti-efficient DEA model, we find out the inefficient banks. The results reveal that the average efficiency score of 29 joint-stock commercial banks tends to increase in the period 2016-2018 and decrease gradually in the period 2019-2020. The findings of this study suggest that several small and medium-sized banks in the Vietnamese banking sector have both promising and risky performances and the efficiency of state-owned commercial banks has also improved significantly during the study period.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.12
• /
• pp.8719-8727
• /
• 2015

The purpose of this study is to examine the production efficiency of Rose farm and to explain the factors of the inefficiency. To analysis the production efficiency, SFA(Stochastic Frontier Analysis) and DEA(Data Envelopment Analysis) methods are measured, and then, Tobit regression model is used to analysis the influential factors on the production efficiency. As a result, first, the production efficiency by SFA is 88.4%, and by DEA, results are 78.5% and 85.2% in the CRS and VRS model, respectively. In particular, the production efficiency of the measurement results of the two methods are complementary, it is described in the same order of efficiency of each management body. Second, the results of tobit model shows that 6 input-factors are significant, and seed/nursery and material costs, which have the largest regression coefficient value and positive effect on production efficiency, are the most influential factors. Therefore, the results of this study indicates Rose farm can enhance their management efficiency by increasing amount of the seed/nursery and material costs.

• Journal of Korean Library and Information Science Society
• /
• v.40 no.1
• /
• pp.253-274
• /
• 2009

Data Envelopment Analysis(DEA) model is a linear programing based technique for measuring the relative performance of organizational units where the presence of multiple inputs and outputs makes comparison difficult. DEA model allows each unit to adopt a set of weight that shows it in the most favorable light in comparison to the other units. The purpose of this study was to evaluate the performance of the libraries of national university in terms of relative efficiency, measured by the method of DEA. Twenty six libraries of national universities in Korea were used to analyze. The number of employees, size of library, budget, and number of books were used for input data, and the number of visitors, number of loan books, and number of books for lending and borrowing were used for output data. We found out that number of libraries with 100% relative efficiency among 26 libraries from 2005 to 2007 were only 9, 9 and 10, respectively. Moreover most of the libraries need to increase outputs and decrease inputs in order to improve efficiency.

• Environmental and Resource Economics Review
• /
• v.9 no.2
• /
• pp.349-371
• /
• 2000

Data Envelopment Analysis model is a linear programming based technique for measuring the relative performance of organizational units where the presence of multiple inputs and outputs makes comparison difficult. A common measure for relative efficiency is weighted sum of outputs divided by weighted sum of inputs. DEA model allows each unit to adopt a set of weight that shows it in the most favorable light in comparison to the other unit. In this paper, we present the mathematical background and characteristics of DEA model, and give a short case study where we apply the DEA model to evaluate the relative efficiencies of 51 global electricity companies. The technical efficiency and scale efficiency are also to be investigated. Generating capacity and the number of employees are used for input data, and revenue, net profit and electricity sales are used for output data. We find that the companies with 100% relative efficiency are only 9 among 51 electricity companies. And the technical and scale efficiency of KEPCO is 98.7% and 78.89%, respectively. This means that the inefficiency of KEPCO is caused by the scale inefficiency. The analysis shows that the employees should be decreased by 15% at minimum to get the 100% efficiency. The result suggests that KEPCO needs the structural reform to improve the efficiency.