• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.425-438
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• 2015

This study proposes a three-stage model of R&BD performance which captures commercialization outcomes as well as conventional R&D performance. The model is composed of three factors : inputs (R&D budgets and researchers), outputs (patents and papers), and outcomes (technical fees, products sales, and cost savings). Three stages are defined for each transformation process between the three factors : efficiency stage from input to output (stage 1), effectiveness stage from output to outcome (stage 2), and productivity stage from input to outcome (stage 3). The performance of each stage is measured by data envelopment analysis (DEA). DEA is a non-parametric efficiency measurement technique that has widely been used in R&D performance measurement. We measure the performance of 171 projects of 6 public R&BD programs managed by Seoul Business Agency using the proposed three-stage model. In order to provide a balanced and holistic view of R&BD performance, the R&BD performance map is also constructed based on performance of efficiency and productivity stages.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.358-365
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• 2014

The purpose of this paper is to analyze the efficiency of government investment in the deployment and technological development of three technological areas - wind power, photovoltaic and fuel cell - of renewable energy in Korea using the DEA (data envelopment analysis). The efficiencies of government investment in renewable energies are measured and compared among three kinds of technologies using the actual data during 2007~2009. In the present DEA model, R&D investment and government subsidies for renewable energy usage promotion are selected as input variables, and the number of patents, supply level, and the production cost as output variable. As a result, it is found that the wind power is the most efficient renewable energy in Korea in the perspective of the efficiency of government investment.

• Journal of Navigation and Port Research
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• v.37 no.2
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• pp.195-201
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• 2013

Recently according to increase of enlarged scale ports in conformity with increase in over size vessels and container handling service, pollutants generated from ports are increasing. In advanced countries, reduction in carbon dioxide emission assigned to them has been implemented according to the Climate Change Convention and Kyoto Protocol from 2008 to 2012 in order to lessen carbon dioxide emission. Henceforth increase in discussion on the measure of constructing Green Port and low-carbon port is expected in our nation's field of port as well, it is considered that the effort in reduction with regard to undesirable output which causes environmental problem of analysis target during measuring effectiveness. Therefore, in this study, effectiveness was estimated through directional technology distance function considering undesirable output differently from effectiveness analysis of existing container terminal, and then performed comparative analysis with the result analyzed with BCC output-oriented model. As the result of analysis, in 2007 DMU3 and DMU5, and in 2010 DMU2 and DMU4 appeared to be efficient terminals in BCC output oriented model, and in directional technology distance function model, DMU1, DMU3 in 2007, DMU3, DMU5 in 2008, DMU7 in 2009, and DMU2, DMU5 in 2010 appeared to be efficient terminals.

• Journal of Korean Society of Rural Planning
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• v.12 no.4 s.33
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• pp.1-11
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• 2006

Recently many administrative institutes try to improve the viability of rural villages. For increasing the viability, not only infrastructures but internal vitality is necessary in rural villages. Nonetheless, most of governmental projects have been focused on infrastructures. For this reason, RDA(Rural Development Administration) designed and performed the RHL(Rural Healthy and Longevity village) project. This RHL project is not easy to evaluate the outcome because it consists of very intangible project items. In this paper, we developed a scoring model to evaluate the result of the RHL project. The scoring model based on DEA(Data Envelopment Analysis) was suggested to evaluate the quantity of personal activities in each village. Personal activities are classified into five categories: regional life, social life, productive life, outdoor life and indoor life. Evaluating indices of each category are developed and weighting values are evaluated by AHP(Analytic Hierarchy Process). The developed model was applied to Kumsan village and examined its applicability.

• Journal of Korean Society for Quality Management
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• v.37 no.4
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• pp.61-70
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• 2009

This paper introduces quantitative tools for evaluating the relative efficiency of Career & Counseling Jobs in universities. As tools, it uses Data Envelopment Analysis (DEA) developed by Charnes and Cooper. It finally selects 29 DMUs which are listed on the Ministry Of Education, Science And Technology(http://academyinfo.go.kr). We measures the technical efficiency of each DMU with the use of DEA-CRS, rather then DEA-VRS because DEA-CRS not only compares relative efficiencies but also implicitly considers economies of scale based on the assumption of linearity. We run a linear programming model Frontier Analyst Program for the estimation of the relative efficiencies of each DMU. The model also indicates the precise amount of inefficiencies for each input, which mean how much inputs are wasted for a given output and how much the university is inefficiently operated. This analysis helps to give guideline for the organization to construct a futureoriented operational strategy and also to show clear picture of contents of mismanagement for the past. The details of mismanagement are to be identified, analysed and finally corrected.

• Korean Journal of Organic Agriculture
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• v.19 no.spc
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• pp.87-91
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• 2011

Eco-efficiency which is calculated by dividing economic productivity by the environmental load was made by synthesizing eco and efficiency from ecology and economy, proposed by World Business Council for Sustainable Development in 2000. Eco-efficiency by connection of resource efficiency with resource intensity is used as an indicator for evaluating green growth for minimizing the impact on the environment and achieving economic development as well by means of efficient use of resources. This research analyzes eco-efficiency with the case of organic agriculture promoted as a key green growth policy. Thirty questionnaires for farmers producing organic rice in Hongseong-gun, Choongcheongnam-do were used for the analysis. Eco-efficiency was measured by means of the amount of used nitrogen with respect to the amount of income, and was represented that organic agriculture was 32.0 higher than conventional agriculture. The analytical result of technical efficiency, using the (Data Envelopment Analysis (DEA) model showed that it is 0.765 which has a possibility of 21% in management improvement, and higher eco-efficiency was with higher technical efficiency. The analytical results showed that an organic agriculture contributes to green growth more than conventional agriculture. In addition, higher technical efficiency groups exhibited higher eco-efficiency indices.

• Journal of agriculture & life science
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• v.45 no.6
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• pp.279-289
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• 2011

The purpose of this study is to estimate efficiency of item-based agricultural cooperative by using Data Envelopment Analysis. A proposed method employs a bootstrapping approach to generating efficiency estimates through Monte Carlo simulation resampling process. The technical efficiency, pure technical efficiency, and scale efficiency measure of item-based agricultural cooperative is 0.80, 0.87, 0.93 respectively. However the bias-corrected estimates are less than those of DEA. We know that the DEA estimator is an upward biased estimator. In technical efficiency, average lower and upper confidence bounds of 0.726 and 0.8747. According to these results, the DEA bootstrapping model used here provides bias-corrected and confidence intervals for the point estimates, it is more preferable.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.9-20
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• 2019

Korea's R&D investment has significantly increased in recent years. However, the efficiency of R&D investment is still in question. In order to examine the ways to improve the efficiency of R&D investment, this paper presents dynamic analysis on both quantitative and qualitative efficiency of R&D projects. A Data Envelopment Analysis(DEA)/Window method is used to analyze static and dynamic efficiencies of Industrial Material R&D projects in Korea from 2012 to 2016. As a result, statistically significant differences between quantitative and qualitative efficiency have been found. It has been observed that characteristics of Decision Making Units(DMUs) have an impact on both static and dynamic efficiencies. In particular, textile and ceramic projects showed relatively stable qualitative efficiency for a short-term perspective, while steel and chemical projects showed such stability for a long-term perspective. Among the types of project principals, universities showed relatively stable efficiency, compared with private sectors and research institutes. The results of this paper can be used as a guideline to manage the performance and stability of R&D projects' efficiency.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.81-90
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• 2018

Modern investment theory has empirically proved that stock returns can be explained by several factors such as market risk, firm size, and book-to-market ratio. Other unknown factors affecting stock returns are also believed to still exist yet to be found. We believe that one of such factors is the operational efficiency of firms in transforming inputs to outputs, considering the fact that operations is a fundamental and primary function of any type of businesses. To support this belief, this study intends to empirically study the relationship between firm efficiency and stock price performance. Firm efficiency is measured using data envelopment analysis (DEA) with inputs and outputs obtained from financial statements. We employ cross-efficiency evaluation to enhance the discrimination power of DEA with a secondary objective function of aggressive formulation. Using the CAPM-based performance regression model, we test the performance of equally weighted portfolios of different sizes selected based upon DEA cross-efficiency scores along with a buy & hold trading strategy. For the empirical test, we collect financial data of domestic firms listed in KOSPI over the period of 2000~2016 from well-known financial databases. As a result, we find that the porfolios with highly efficient firms included outperform the benchmark market portfolio after controlling for the market risk, which indicates that firm efficiency plays a important role in explaining stock returns.

• The Journal of Fisheries Business Administration
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• v.49 no.4
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• pp.1-17
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• 2018

The Korean fisheries industry is a traditional business, the majority of which are small and medium-sized enterprises (SMEs). It has played an important role in the South Korean economies in the past several decades, but it currently faces the limitations of growth potential and profitability due to declining workforce, aging populations, deteriorating fishery environments, climate changes, and rapid changes in the global industrial ecosystem. Many studies have suggested solutions for the fisheries industry in macro perspective, but there are rarely any studies taking the strategic approaches for the problem. If it is possible for governments to support the companies that are likely to increase their value-added selectively, it will break through the current situation more effectively. This paper introduces a study on the selection method utilizing data envelopment analysis (DEA) to find SMEs with potentials to increase profits and growth. We suggest selecting SMEs with high management efficiency and ability to utilize intangible assets as the target companies. We also suggest policy objectives for SMEs in the domestic fisheries industry based on the results of DEA analysis and propose a data-based method for the policy decisions.