• Journal of Information Technology Services
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• v.15 no.2
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• pp.51-63
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• 2016

In this study, we conducted a comparative analysis of R&D investment efficiency and operational efficiency of IT firms using Data Envelopment Analysis (DEA). We categorized thirteen sample firms into two groups-IT manufacturing and IT service-after an extensive literature review on IT industry classification. We adopted an output-oriented two-stage DEA model suggested by Banker et al. (1984) with total asset and R&D investment as input variables. Then, we constructed investment efficiency and operational efficiency by using Return on Equity (ROE) and Return on Asset (ROA) as intervening variables and operating income and Earnings Per Share (EPS) as output variables. The outcome of the analysis is summarized as follows. First of all, IT manufacturing firms were more efficient (57% on average) than IT service firms. To be specific, IT service firms showed decreasing returns to scale (DRS) with diseconomy of scale. In contrast, IT service firms showed higher operational efficiency (81.5% on average) than IT manufacturing firms. Also, we conducted a Mann-Whitney U test to compare the output of IT service firms and IT manufacturing firms. Lastly, we found a negative correlation ($R^2$ = -.754) between R&D investment efficiency and operational efficiency which infers the trade-off between two constructs

• Journal of Information Technology Services
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• v.12 no.3
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• pp.405-420
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• 2013

The purpose of this paper is to develop an evaluation model for e-government system in Korea which is one of world best practices of e-government systems. We have presented a method to perform an efficiency analysis of each e-government service which in a component of e-government system in Korea and to establish a benchmark target for each e-government service. To do this, the output-oriented DEA(Data Envelopment Analysis) CCR model was performed for the selected 12 e-government public services of Korean e-government system in this paper. As a result of DEA analysis, first the internet civil appeal support service, the employment comprehensive information service, and the company support information service were evaluated as the efficient solutions among the 12 e-government public services. Second the remaining 9 e-government public services were evaluated as the inefficient information services which should be improved in terms of their service levels. Finally the benchmark targets for the inefficient e-government services were suggested to improve those inefficient systems through DEA analysis.

• Journal of Distribution Science
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• v.19 no.7
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• pp.29-39
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• 2021

Purpose: As China experienced a crisis due to Covid-19, the global supply chain collapsed and affected the world. Therefore, it is time for a change in port operational efficiency, increasing in importance with changes in the global supply chain. This study analyzed Shanghai Port's efficiency, the world's largest port and representative hub port in Northeast Asia, by looking at the relationship between facility factors and cargo throughput to present hub port development's timely implications. Research design, data and methodology: This study applied the Charnes, Cooper, and Rhodes (CCR) and Banker, Chames, and Cooper (BCC) models of the data development analysis (DEA) to construct an analysis from the input-oriented and output-oriented perspectives. Results: As a result, Yidong Container Terminal can be considered the most optimized in facilities and operation processes. Yidong and Shengdong Container Terminal should maintain current operating levels, while Pudong Container Terminal should review facility investments. Also, Zhendong, Huong, Mingdong, and Guandong Container Terminal should be reviewed to increase cargo throughput or to adjust current input variables in the current state. Conclusions: Therefore, the utilization of the container terminal input variables should be reviewed, and the factors of inefficiency should be improved. Moreover, the strategic focus of container terminal operations should be on increasing annual cargo throughput.

• 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.

• 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.

• The Korean Journal of Health Service Management
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• v.9 no.3
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• pp.43-55
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• 2015

Objectives : This study analyzed the managerial efficiency of hospitals and identified the productivity trends for three years. Methods : Data were collected from 44 tertiary hospitals and 32 university hospitals from 2009 to 2011. Efficiency scores and productivity trends were evaluated with the DEA (Data Envelopment Analysis) method. The input variables were the numbers of beds, doctors, nurses, and health personnel, and the medical costs. The output variables were the numbers of outpatients, and inpatients, and the medical revenues. Along with the traditional input-oriented DEA analysis, the Malmquist Productivity Index(MPI) was calculated. Results : First, the mean values of the study variables showed gradual increases in all the variables for all the study years. Second, technical efficiency scores varied depending on the study year. Third, MPI decreased from 2009 to 2010 (MPI=0.986), and then increased from 2010 to 2011(MPI=1.011). The contributions of the Efficiency Change Index and Technical Change Index on the MPI varied depending on the study year. Conclusions : This study provides information to hospital managers about changes in hospital performances. External environments had more influence on hospital performances, and hospital managers will need to manage these influences from factors surrounding the hospitals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.130-139
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• 2020

The defense industry is a future-oriented industry, in which high-tech technologies are concentrated. In addition, it is a key industry for maintaining national security, and the R&D of the defense industry is very important. With the introduction of a competitive system by defense industry companies, the necessity of improving the efficiency and productivity of defense industry companies is emerging. In this study, the efficiency of the defense industry was measured using the CCR and BCC model. In addition, super efficiency was derived using the Super-SBM model. For this study, the 2019 defense industry management analysis data of the Korea Defense Industry Association (KDIA) was used, and the analysis was performed by setting the number of researchers and investments of domestic defense industry companies as the input variables and sales as the output variables. Through this study, it is expected that the defense industry's R&D efficiency will be grasped, which will help establish a policy for fostering the defense industry in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.30-36
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• 2022

This study analyzed the relationship between efficient pitchers and teams advancing to the postseason in Korean professional baseball through DEA. A total of 1,133 pitchers who threw more than one inning from the 2014 season to the 2018 season were selected for this study. For DEA analysis, input variables were selected as annual salary and inning output variables as Wins, Saves, and Holds and the number of efficient pitchers for each season was classified using the input-oriented BCC model. After that, it was divided into two groups based on joining the postseason or not, and the number of efficient pitchers was compared through a prop test. As a result of the analysis, the groups that advanced to the postseason in the rest of the season except for the 2014 and 2017 seasons had more efficient pitchers. Considering that the 2014 season recorded the highest WAR (Wins Above Replacement) at 183.56 compared to other seasons, most pitchers threw well, and in the 2017 season, they made more mistakes in pitching than in other seasons, but they performed well in batters. The results of this study have expanded the research field using efficiency analysis in professional baseball and can be used as useful data for practical research.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.53-60
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• 2020

Evaluating the operational efficiency of electric vehicle charging stations (EVCSs) is important to understand charging network evolution and the charging behavior of electric vehicle users. However, aggregation of efficiency performance metrics poses a significant challenge to practitioners and researchers. In general, the operational efficiency of EVCSs can be measured as a complicated function of various factors with multiple criteria. Such a complex aspect of managing EVCSs becomes one of the challenging issues to measure their operational efficiency. Considering the difficulty in the efficiency measurement, this paper suggests a way to measure the operational efficiency of EVCSs based on data envelopment analysis (DEA). The DEA model is formulated as constant returns of output-oriented model with five types of inputs, four of them are the numbers of floating population and nearby charging stations, distance of nearby charging stations and traffic volume as desirable inputs and the other is the traffic speed in congestion as undesirable one. Meanwhile, the output is given by the charging frequency of EVCSs in a day. Using real-world data obtained from reliable sources, we suggest operational efficiencies of EVCSs in Seoul and discuss implications on the development of electric vehicle charging network. The result of efficiency measurement shows that most of EVCSs in Seoul are inefficient, while some districts (Nowon-gu, Dongdaemun-gu, Dongjak-gu, Songpa-gu, Guro-gu) have relatively more efficient EVCSs than the others.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.1-14
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• 2021

It is highly challenging to measure the efficiency of electric vehicle charging stations (EVCSs) because factors affecting operational characteristics of EVCSs are time-varying in practice. For the efficiency measurement, environmental factors around the EVCSs can be considered because such factors affect charging behaviors of electric vehicle drivers, resulting in variations of accessibility and attractiveness for the EVCSs. Considering dynamics of the factors, this paper examines the technical efficiency of 622 electric vehicle charging stations in Seoul using data envelopment analysis (DEA). The DEA is formulated as a multi-period output-oriented constant return to scale model. Five inputs including floating population, number of nearby EVCSs, average distance of nearby EVCSs, traffic volume and traffic congestion are considered and the charging frequency of EVCSs is used as the output. The result of efficiency measurement shows that not many EVCSs has most of charging demand at certain periods of time, while the others are facing with anemic charging demand. Tobit regression analyses show that the traffic congestion negatively affects the efficiency of EVCSs, while the traffic volume and the number of nearby EVCSs are positive factors improving the efficiency around EVCSs. We draw some notable characteristics of efficient EVCSs by comparing means of the inputs related to the groups classified by K-means clustering algorithm. This analysis presents that efficient EVCSs can be generally characterized with the high number of nearby EVCSs and low level of the traffic congestion.