• The Journal of Fisheries Business Administration
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• v.46 no.2
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• pp.111-125
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• 2015

This study is to analyze the efficiency of Korean sea food manufacturing using Data Envelopment Analysis. Firstly, based on an output oriented traditional CCR, BCC model, the study estimated the efficiency scores. The average estimates of technical, pure technical, and scale efficiency turned out 0.6517, 0.7184, 0.9074 respectively, which are separated for 50 marine corporations. The 10 DMUs were efficient under CCR model while the 17 DMUs under BCC model. Also, the study suggested that the operating profit of the two output factors should be more increased relatively and averagely from the viewpoint of efficiency improvement. Secondly, super efficiency scores are estimated under super efficiency and SBM model. As a result, it came to be possible to distinguish and rank the efficiency of the efficient DMUs. The highest score was 4.2975 under Super-CCR, was 2.4947 under Super-BCC, was 2.7160 under SBM-Super-CCR, and was 1.5319 under SBM-Super-BCC model. The average estimates of super efficiency were 0.76 and 0.82 under Super-CCR and Super-BCC model respectively, and were 0.61 and 0.67 under SBM-Super-CCR and SBM-Super-BCC model. Finally, the study conducted a rank-sum test, Wilcoxon-Mann-Whitney test, to find a statistical significance of heterogeneity existing in efficiencies among the sample corporations. The result showed that there was a significant difference in average efficiency between Dried, Salted product manufacturing and Frozen product manufacturing under BCC-Super efficiency model at 10% level of significance. Furthermore, TOBIT model was applied to find out the potential factors that might influence the efficiency, Wilcoxonand the results showed debt and sales cost influenced all of the technical, pure technical, and scale efficiency, while net profit influenced only the technical efficiency.

• Environmental and Resource Economics Review
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• v.24 no.2
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• pp.411-433
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• 2015

This paper decomposed energy productivity changes across 14 Korean manufacturing industries into 5 components, technological catch-up(EC), technological progress(TC), and changes in labor-energy ratio(LC), capital-energy ratio(KC) and energy mix(EMC). Then we also figured out the possible relationship between energy productivity change and export growth rate across the industries. It is found that (1) technological progress, changes in capital-energy ratio and energy mix contribute to energy productivity growth in Korea during the sample period, (2) technological progress is the primary driving forces for energy productivity growth, (3) increase in export growth rate had a positive impact on energy productivity growth excepting a part of energy-intensive industries.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8378-8385
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• 2015

The interest of global competitiveness for national defense industry. This study analyzes the efficiency and productivity of 45 defense companies in each continent(North America, Europe and Northeast Asia, etc.), including Korea defense companies. It is analyzed by Data Envelopment Analysis(DEA) and Malmquist Productivity Analysis over the period 2009-2013(5 years). The sample companies has been selected on the data avilability among the SIPRI Top 100 arms-producing and military services companies in the world(excluding China) in 2013. It extracts the relative efficiency and Malmquist productivity index of companies and each continent. Based on the DEA and MPI results, this paper estimates the global competitiveness and position of national defense industry and extracts implication. This study can be utilized for improvement of national defense industry and policy planning for cultivating the national defense companies.

• Korean Business Review
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• v.23 no.2
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• pp.53-75
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• 2010

Gangwon-do has evaluated the result of technical support business and marketing support business separately as a part of enterprise support business, and the evaluation, targeting enterprises, has been restricted to the investigation of satisfaction only. The study develops the model that assesses the efficiency of the enterprises using DEA, the econometric model which is approved the utility in efficiency evaluation, and evaluates it through the model. As a result, the model can be developed to the appropriate variable of the enterprise support business using the elements of input and output in the business. And by using the model of DEA, it is suggested the efficiency measurement of each enterprises' and improvement that inefficient enterprises must have. Especially, it is important to assess the efficiency of supporting enterprises primary.

• Journal of Korea Game Society
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• v.9 no.2
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• pp.81-93
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• 2009

This study aims to investigate human capital in Korea's online game industry (as the representative of IT-based creative services) under the knowledge-based economy paradigm. In recognition of the importance of intellectual capital closely intertwined with human capital and the economic potential of the online game industry, Korean government has begun to show active support. In this context, this study measures the human capital efficiency in online game business by using non-parametric analysis (Data Envelopment Analysis, DEA). Most previous studies (human capital theory, knowledge based economy theory, economic growth theory) have proved that human capital has a very positive effect on sustainable growth of corporate management and wealth of nations. As such, this paper uses the DEA to obtain the efficiency of the human capital (scale, investment, education, compensation). The results of this study will suggest strategic implications on maximizing the human capital in online game corporations and provide a reference frame for government policies.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.819-825
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• 2014

In this paper, monaural ambient component extraction algorithm based on nonnegative matrix factorization (NMF) is described. The ambience component extraction algorithm in this paper is developed for audio upmixing system; Recent researches have shown that they can enhance listener envelopment if the extracted ambient signal is applied into the multichannel audio upmixing system. However, the conventional method stores all of the audio signal and processes all at once, so it cannot be applied to streaming system and digital signal processor (DSP) system. In this paper, the ambient component extraction algorithm based on on-line nonnegative matrix factorization is developed and evaluated to solve the problem. As a result of analysis of the processed signal with spectral flatness measures in the experiment, it was shown that the developed system can extract the ambient signal similarly with the conventional batch process system.

• Journal of Agricultural Extension & Community Development
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• v.9 no.2
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• pp.263-277
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• 2002

The objective of this study was to compare the farm efficiency of members of cooperative firms with that of non-members in Korea. Data were collected from 27 farms members of three cooperatives and 13 non-member farms, based on the managerial achievements of 1999. For the analysis, the data were divided into three different farming types: type I and II of member farms and non-member farms. Economic analysis were implemented using DEA(Data Envelopment Analysis). Major findings was as follows. Total average technology efficiency was 0.782, which implies that there still remains 21.8% of improvement possibility. Among the three types, type I showed the highest technology efficiency of 0.9055, while type II and non-member farms showed 0.7670 and 0.7171, respectively. This means that these farms have relatively high potential improved. Also, comparing technology efficiency by dividing into pure technology and scale efficiency, all type of the farms exhibit a higher pure technology efficiency compared to scale efficiency. Therefore, to improve current technology efficiency, farms need to focus more on pure technology efficiency improvement. Meanwhile, profit analysis based on farm size indicate that most of the farms demonstrated the increasing-return-to-scale, which means it is necessary to extend the farm size to improve technical efficiency. Type I member farms achieve higher profit and efficiency than other two types and relatively higher producer prices through introducing cooperative sorting, grading and packing. Also, these labor saving technologies increased farm size.

• Journal of Navigation and Port Research
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• v.29 no.10 s.106
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• pp.921-926
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• 2005

The purpose of this paper is to conduct a comparative analysis of container terminal operation in Busan and Kwangyang port. The research method used for this study is DEA(Data Envelopment Analysis} and among DEA methods CCR and BCC model has been used. According to the results of CCR model Gamman in 2004 and Gamcheon in 2004 are found to be the most efficient terminals in the sample and the inefficient terminals include Gwangyang Phase 2 terminal. Based on BCC model Gamcheon and Uam are identified as the most efficient terminals in three consecutive years including Gamman terminal in 2004. The inefficient terminals include New Gamman in 2002 and Hutchison in 2002. The research findings show that inefficient terminals need to fully utilise their terminal facilities and increase container throughput through effective marketing activities.

• IE interfaces
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• v.24 no.4
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• pp.314-322
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• 2011

This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.190-204
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• 2008

Recently, it has been strongly required to establish a systematic and sustainable performance investigation and evaluation framework on governmental funding projects for IT small and medium-sized enterprises. In this paper, Data Envelopment Analysis (DEA) models are adopted for performance evaluation on governmental funding projects for IT small and medium-sized enterprises. A new data structure is proposed for the DEA performance evaluation. Generally, in using DEA models, DEA multipliers restriction is critical to achieve the reliability of DEA optimal solutions. Based on the outputs and inputs considered in this study, Acceptance Region (AR) constraints are generated and incorporated into the DEA models so as to improve the reliability of DEA efficiency scores. Associated with AR Type I (AR-I), AR Global Model (ARGM) constraints, DEA/ (AR-I, ARGM) models are designed and then sensitivity analysis follows investigating the robustness of DEA efficiency scores relating to AR constraints adjustment. Finally, a performance evaluation is illustrated regarding governmental direct funding projects from Ministry of Information and Communication (MIC) in Korea where each project unit (i.e. Decision Making Unit (DMU)) is determined whether it is efficient or not. By using DEA/(AR-I, ARGM) models designed in this paper, robustly efficient DMUs are gradually identified according to the successive AR constraints adjustment. Among 25 DMUs, results show that 6 DMUs such as B, E, G, Q, S, Y are determined as robustly efficient against AR constraints intermediate adjustment.