• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1707-1714
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• 2006

In order to enhance sustainable war fighting capabilities, it is important to maintain a good ammunition support system. In this paper, we evaluate the performance of Ammunition companies using Imprecise Data Envelopment Analysis (IDEA)-BCC and IDEA-Additive model, which can deal with imprecise data in DEA. In order to select a list of input and output variables, we used a multiple regression analysis. We could choose input variables that have significant effects on the output performance with stepwise regression model. From the regression analysis, the number of soldiers, officers, and ammunition warehouses were selected as the input variables. Seven out of sixteen Ammunition companies were found to be inefficient by the IDEA-BCC model. And using IDEA-Additive model, we could identify the input excess and the output shortfall in reaching at a point on the efficiency frontier.

• IE interfaces
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• v.19 no.4
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• pp.291-299
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• 2006

In order to enhance sustainable war fighting capabilities, it is important to maintain a good ammunition support system. In this paper, we evaluate the performance of ammunition companies using Imprecise Data Envelopment Analysis (IDEA)-BCC and IDEA-Additive model, which can deal with imprecise data in DEA. The input variables of IDEA models were selected by stepwise multiple regression analysis. With the regression model, we could choose the number of soldiers, officers, and ammunition warehouses as input variables that have significant effects on the output performance. Then, we applied the IDEA-BCC model with the concept of potential efficiency. The results of the model indicate that 8 out of 16 ammunition companies are efficient, 7 are inefficient, and 1 is potentially efficient. We could also identify the possible input excesses and output shortfalls to reach the efficient frontier using the IDEA-Additive model.

• International Area Studies Review
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• v.13 no.3
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• pp.729-757
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• 2009

This paper examines if China' each province.city manages its organization well after China's WTO affiliation; and on the ground, judges how much each province city needs to improve. China's each province city data from 2002 to 2006 is used to evaluate technical efficiency by using the input-oriented CCR model and the input-oriented BCC model. Analytical results show that only Shanghai gets continuously the highest efficiency score from 2002 to 2006 and so the other provinces cities need to benchmark Shanghai to elevate their efficiency. There can be regional, cultural and emotional differences among the provinces cities but Tibet, Shaanxi, Gansu, Qinghai, Ningxia and Xinjiang get low efficiency scores even after China's WTO affiliation. The Chinese government can make use of efficiency evaluation results by DEA as basic materials in making economic development schemes in order to reduce these deviations as various minority races constitutes China and there are regional deviations of degree of economic development in China.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.15-24
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• 2011

This study discusses an equity analysis performed to supplement the existing bus service evaluation system. The equity of 179 feeder bus routes in the city of Seoul(Year 2009) is analyzed by employing the modified BCC model along with the desirable inputs such as a number of bus stops and a frequency of operations. In the analysis, each DMU (Decision Making Unit) is assumed to use the desirable inputs, and produces both the index of equity and the index of accessibility. We apply an input-oriented modified BCC model to analyze the equity of the DMUs. The computational result indicates that only 9% of the feeder bus routes are equitable among the total DMUs and the average equity estimate is 0.702. It is also suggested that on average approximately 60% increases of desirable inputs (i.e., a number of bus stops and a frequency of operations) are needed in order to improve equity of DMU in the city of Seoul. The result of the tobit regression analysis on the determinant factors affecting the equity of DMUs shows that all the independent variables (i.e., a number of bus stops and a frequency of operations) are statistically significant at 5% significance level, and the number of bus stops is found to be the most influential factor.

• Journal of Korea Port Economic Association
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• v.21 no.1
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• pp.133-151
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• 2005

The purpose of this paper is to investigate the international competition power between Korean ports and Chinese ports according to the port efficiency scores of DEA(Data Envelopment Analysis) by newly introducing the priority vector of AHP(Analytic Hierarchy Process) to the DEA method. Empirical analysis shows the followings: First, there was not big changes of DEA rankings when we use the input-oriented CCR and BCC models after introducing the AHP priority vectors to the input variables. Yantian Port's competition power was declined, but that of Busan Port was up in the BCC model. Second, there was some changes of DEA rankings when we use the output-oriented CCR and BCC models after introducing the AHP priority vectors to the output variables. Rankings of Dalian, Qingdao, Shanghai Ports were up. But Shekou, Yantian Ports showed the declined ranking position in the CCR model. In the BBC model, rankings of Shanghai and Busan Ports were up. But those of Shekou and Yantian Ports were declined. The main policy implication based on the findings of this study is that The Ministry of Maritime Affairs & Fisheries in Korea and China should introduce AHP and DEA approaches when they measure the international competition power by using the porrt efficiency scores of DEA.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.75-89
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• 2015

In recent years, attention to the high debt ratio in public institutions has pushed the government to make efforts in reducing the debt ratio. However, in order to stimulate the economy, the government needs drastically innovative measures that reduce debt by improving efficiency rather than moderate approaches that focus solely on debt reduction. Despite this need, no study has yet systematically analyzed the overall efficiency of domestic public institutions and identified the source of inefficiencies in each public entity. Therefore, largely two research questions are examined. First, this study compares the efficiency levels by types of public institutions. Second, this study identifies the cause of inefficiencies in each public institution and proposes directions for improving efficiency. Based on a 5-year data of 302 public institutions published in public business information systems and organizational websites from 2009 to 2013, Data Envelopment Analysis (DEA) was performed. The input variables include the number of employees and total costs while the output variables include sales and net income. Reflecting the characteristics of public institutions, the input-oriented CCR model and input-oriented BCC model were utilized. Analysis results are as follows. First, market-oriented public institutions showed the highest efficiency while fund management quasi-governmental agencies showed the highest inefficiency. Second, scale efficiency score was measured by applying the CCR model and the BCC model on the organizations with the lowest efficiency level, fund management quasi-governmental agencies. Based on these analysis results, the source of inefficiency and detailed directions for improvement were proposed for Decision Making Units (DMUs) with low CCR and BCC scores.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.244-255
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• 2011

In this study, we try to evaluate the efficiency of the photonics industry using a data envelopment analysis(DEA) model. We first develope four stage procedures for selecting proper input and output variables which consist of selecting the first candidate variables from literature survey, selecting the second candidate variables through experts' discussion, measuring the partial efficiency of the selected variables based on Tofallis' profiling, and clustering some variables through the rank correlation analysis of partial efficiency proposed by Min and Kim(l998). With this procedure, we select 4 input variables(capital, number of employee, R&D cost, operating cost) and 2 output variables(sales, growth of sales) and then utilize CCR and BCC model to measure efficiencies of 26 photonics companies in Gwangju. Moreover, we perform the reference group analysis to figure out what causes inefficiencies and to provide the desirable values for input and output variables at which inefficient photonics companies become efficient. Finally, we classify 26 photonics companies into three groups such as optical communications, optical applications, and optical sources, and perform the Kruskal-Wallis test to check if there exist some differences between efficiencies of three groups.

• Knowledge Management Research
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• v.13 no.5
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• pp.43-64
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• 2012

Emerging technologies have significant implications in establishing competitive advantages and are characterized by continuous rapid development. Efficient benchmarking is more and more important in the development of emerging technologies. Similar input level and importance are two necessary criteria need to be considered for emerging technology's benchmarking. In this study, we proposed a sequential use of self-organizing map(SOM), data envelopment analysis(DEA) and analytical hierarchy process(AHP) method for the stepwise benchmarking of emerging technology. The proposed method uses two-level SOM to cluster the emerging technologies with similar required input levels together, then, in each cluster, uses DEA-BCC model to evaluate the efficiencies of the emerging technologies and do tier analysis to form tiers. On each tier, AHP rating method is used to calculate each emerging technology's importance priority. The optimal benchmarking path of each cluster is established by connecting the emerging technologies with the highest importance priority. In order to validate the proposed method, we apply it to a case of biotechnology. The result shows the proposed method can overcome difficulties in benchmarking, select suitable benchmarking targets and make the benchmarking process more efficient and reasonable.

• Journal of the Korea Safety Management & Science
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• v.17 no.4
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• pp.87-96
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• 2015

This study analyzed the safety management efficiency through input-oriented BCC Model using DEA by making of Models, in which this study selected the number of staff affiliated with the construction site, number of staff members on the construction team, and number of safety personnel as Input Factor, along with the number of disaster victims and zero-accident accomplished hours as output elements, targeting 40-or-so apartment building construction sites which are being built by 3 domestic construction companies. As a result of efficiency, it was 0.643, the number of efficient DMU was 4. In the aspect of returns to scale, 21 construction sites(52.5%) found to be in a state of increasing returns while 14 construction sites(35%) was in a state of Decreasing returns. The reason for inefficiency was found to lie in technical factors in case of 30 construction sites(75%). Lastly, inefficient DMU is in need of 38.9 % and 66% reduction in site personnel and safety personnel. Based on study results, the 29 construction sites accounting for 72.5% of DMU for safety management efficiency evaluation object turned out to do inefficient safety management that doesn't fit the size of each company.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.317-328
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• 2011

Logistic system and methods of the transportation have been changed rapidly by the variety of the logistics environment. It is necessary to analyze the efficiency of Korean trucking companies for enhancing the competitive power and operating. This paper will describe the analysis of the efficiency of the trucking companies with DEA models. By the CCR and the BCC models, which are in parts of DEA model, the efficiency and RTS(Return To Scale) of forty two selected trucking companies were studied. It was also analyzed how the study the input-output variables were effected. And then, some of the forty two trucking companies were shown as the benchmark. As the result of analysis on the two models, seven companies won the score '1' on CCR model and seventeen companies on BCC model. Moreover, this study showed that reducing the total asset out of input variables, and raising the sales profit out of the output variables played a main role to increase the efficiency of the trucking companies highly.