• Management & Information Systems Review
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• v.35 no.4
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• pp.213-227
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• 2016

This study examines the effects of managerial ability on information asymmetry. We use analyst forecast errors as a proxy for information asymmetry, because analysts are referred to as efficient users using firm-level data. The sample consists of 2,246 non-banking firm-years listed in Korea Stock Exchange(KOSPI) during the period 2000 to 2013. We measure managerial ability using DEA(Data Envelopment Analysis) following Demerjian et al.(2012). Using those measures, we examines the effects of managerial ability on analysts' earnings forecast errors and analysts' earnings forecast bias. The results of this study are as follows. First, we find that managerial ability are positively associated with analysts' earnings forecast accuracy. Second, we show that the firms with higher managerial ability tend to have lower the optimistic errors in analysts' earnings forecasts. This study could be useful for outside stakeholders to understand the importance of managerial ability.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.2
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• pp.161-167
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• 2017

This paper measured and evaluated the technical efficiency, pure technical efficiency and scale efficiency of port labor via three inputs and three outputs using Data Envelopment Analysis (DEA). First, the average overall technical efficiency measured about 94.18 %, with 100 % pure technical efficiency being larger than 94.18% scale efficiency. As a result, 7 ports were identified as efficient, and 4 ports were identified as inefficient. Among the 4 ineffiecient ports, Donghae had the highest Increasing Return to Scale (IRS). However, the inefficient ports were all found to be less efficient in terms of resource operation than production scale. On the other hand, the efficient ports established priorities using the super efficiency method. As a result, port efficiency was highest for Incheon, Mokpo, Pyeongtaek-Dangjin, Masan, Yeosu Gwangyang, Jeju, and Gunsan-Daesan Ports, in order. In particular, Busan Port, found to be inefficient, would benefit from using Mokpo Port and Incheon Port as benchmarks to increase trade volume and modernize equipment for full-scale commercialization to improve labor efficiency.

• Journal of the military operations research society of Korea
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• v.34 no.1
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• pp.61-77
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• 2008

Data Envelopment Analysis(DEA) is a promising methodology to evaluate the relative efficiency of the decision-making units. We have compared the efficiency of six electric power generation companies in Korea using DEA. The analysis results by input-oriented CCR and BCC models are summarized as follows: first, different results were acquired between using input factors as total capacity of generators and as sub-totals of generator capacity based on primary energy sources. It is the result influenced by input factors which are characterized by the proportion of fixed costs(generating facilities) and variable costs(generation costs for primary energy), Second, the efficiency will be increased if the input factors selected, according to primary energy sources discussed in this research, are used during long-term expansion of electric power capacity plans. It is expected that this approach can give a feedback for management of electric power generation companies.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.84-99
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• 2014

In this study, determinant input-output variables are identified for calculating Data Envelopment Analysis (DEA) efficiency scores relating to evaluating the efficiency of government-sponsored research and development (R&D) projects. In particular, this study proposes a systematic framework of design and analysis of experiments, called "all possible DEAs", for pinpointing DEA determinant input-output variables. In addition to correlation analyses, two modified measures of time series analysis are developed in order to check the similarities between a DEA complete data structure (CDS) versus the rest of incomplete data structures (IDSs). In this empirical analysis, a few DEA determinant input-output variables are found to be associated with a typical public R&D performance evaluation logic model, especially oriented to a mid- and long-term performance perspective. Among four variables, only two determinants are identified : "R&D manpower" ($x_2$) and "Sales revenue" ($y_1$). However, it should be pointed out that the input variable "R&D funds" ($x_1$) is insignificant for calculating DEA efficiency score even if it is a critical input for measuring efficiency of a government-sonsored R&D project from a practical point of view a priori. In this context, if practitioners' top priority is to see the efficiency between "R&D funds" ($x_1$) and "Sales revenue" ($y_1$), the DEA efficiency score cannot properly meet their expectations. Therefore, meticulous attention is required when using the DEA application for public R&D performance evaluation, considering that discrepancies can occur between practitioners' expectations and DEA efficiency scores.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.861-870
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• 2001

Since most of studies for information efficiency measurement of healthcare organizations have mainly focused on searching a measuring standard used for performance of informatization and each researchers subjective standard having been used, they can not be easily measured and objective. This study showed a possibility that efficiency measurement of healthcare organization can be performed by solving a problem related to objectiveness, which may occur in measuring many organization with many measuring items, with DEA (data envelopment analysis). For proving this possibility, efficiency evaluation and analysis for information resources utilization of domestic tertiary healthcare organizations have been performed by using DEA model. As a result, DMU (decision making unit) having efficiency rate of 1 will be evaluated that output is higher than input and information resources are being used efficiently, but on the other hand, DMU having efficiency rate of below 1 will be evaluated that output is lower than input and information resources are being used inefficiently, which is required to be improved.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.4
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• pp.101-111
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• 2013

In this study, DEA (Data Envelopment Analysis) was carried out on the four bridges, which have the same extension (L=1,615m), in order to select the most superior, economical method of construction using the LCC concept of each bridge structure in the case of the Ulsan-Pohang double track railway which is scheduled to be constructed. DEA models were analyzed with the CCR model, which was designed for the evaluation of relative efficiency of each model. The initial construction costs, maintenance costs, indirect costs (user costs + indirect loss of social costs), and life cycle costs were used as input variables, and average duration was applied as the output variable. LCC was applied to calculate the input variables, and to get the costs of LCC, 100 years of period and 4.83% of real discount rate were applied, and the costs are classified into initial construction, maintenance, user, and indirect loss of social cost. The analysis results showed that the Method 2 and 3 were evaluated as the most efficient, and the other alternatives were evaluated as the following order; Method 1, the default, and Method 4.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.31-41
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• 2010

The objective of this paper is to evaluate production efficiency of the commercial road freight transportation industry using quarterly actual data by individual truck drivers from January 2005 to September 2009. In addition, this study analyzes various impact factors that influence production efficiency, including regulatory factors (e.g., entrust management system and multi-level transactions). For this purpose, this study uses data envelopment analysis and a truncated Tobit model. As a result, production efficiency of the general freight sector is higher than those of the other two sectors. Also, production efficiency in the steel goods sector ranks the highest; meanwhile, production efficiency in the oil goods sector ranks the lowest. In particular, production efficiency indicators of the commercial road freight transportation industry fluctuate with time by a small margin, and have an upward tendency on the whole. Finally, some policy implications are given to promote production efficiency of the commercial road freight transportation industry.

• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.165-178
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• 2016

Container port nowadays becomes one of the most vital link of the transportation chain, plays an important role in trading with other countries. Therefore, evaluating the operational efficiency of container ports to reflect their status and to reveal their position in this competitive environment is very important for port development. Although there have been lots of methods used to measure efficiency in the past, the DEA (Data Envelopment Analysis) model is still the most commonly applied approach. However, the data used in the model sometimes is complex and uncertain to handle using the basic DEA model. In this paper, we applied an uncertainty theory to create an uncertainty DEA model (UDEA), which can solve the limitation of the traditional one. This study mainly focuses on measuring efficiency of 41 container ports by applying proposed an UDEA model. The results show that among 41 container ports, only six container ports are regarded to have efficient operation through the clustering, meanwhile others have technical and scale inefficiencies. We found out that an UDEA model is better to analysis efficiency than existing DEA model.

• Korea Real Estate Review
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• v.28 no.3
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• pp.37-52
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• 2018

This paper analyzed the relative efficiency of industrial complexes by type based on the DEA Model. In this analysis, the output and exports of 287 industrial complexes in 2017 were used as output variables, while the industrial land area and the number of employees in the same year were used as input variables. The results of the relative efficiency of industrial complexes by type were as follows: The relative efficiency of industrial complexes was affected mainly by type and the operating period of industrial complexes. In the types of industrial complexes, the most efficient industrial complex was the Urban, high-tech industrial complex, followed by the National industrial complex and the General industrial complex. Therefore, high-tech innovation and government support for industrial complexes would be necessary to increase the efficiency of industrial complexes. In the operation period of industrial complexes, relative efficiencies increased with longer operation periods. To maximize the regeneration effect of the old industrial complex, efficiency must be kept as a priority item of the old industrial complex regeneration project.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.99-109
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• 2019

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. For example DEA is good at estimating "relative" efficiency of a DMU(Decision Making Unit), it only tells us how well we are doing compared with our peers but not compared with a "theoretical maximum." Thus, in order to measure efficiency of a new DMU, we have to develop entirely new DEA with the data of previously used DMUs. Also we cannot predict the efficiency level of the new DMU without another DEA analysis. We aim to show that DEA can be used to evaluate the efficiency of ports and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with C5.0. We can generate classification rules C5.0 in order to classify any new Port without perturbing previously existing evaluation structures by proposed methodology.