• Journal of Technology Innovation
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• v.13 no.2
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• pp.207-222
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• 2005

A prerequisite for making R&D more productive is to able to measure its productivity. Most of the previous studies on this topic have attempted to measure R&D productivity at the firm or industry levels. In this study, however, R&D productivity is measured at the national level to provide R&D policy implications, particularly for Asian countries. Contrary to the previous studies where total factor productivity was adopted, this study employs the data envelopment analysis (DEA) approach to measure R&D productivity. DEA is a multi-factor productivity analysis model for measuring the relative efficiency of each Decision Making Unit (DMU). In addition to the basic DEA model that includes all inputs and outputs, five additional models are constructed by combining single input with all outputs and single output with all inputs in order to measure specialized R&D efficiency. In this study, the twenty-seven countries are classified into four clusters based on the output-specialized R&D efficiency: inventors, merchandisers, academicians, and duds. Then, the characteristics of the Asian countries with respect to R&D efficiency are identified. It is found that Singapore ranks high in total efficiency, and Japan in patent-oriented efficiency. Meanwhile, China, Korea, and Taiwan are found to be relatively inefficient in R&D. We expect that the findings from this study will be able to provide directions for R&D policy-making of the Asian countries.

• Journal of Home Health Care Nursing
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• v.25 no.1
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• pp.67-77
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• 2018

Purpose: The purpose of this study was to compare the efficiency of general ward nurses in hospitals using Data Envelopment Analysis (DEA). Methods: Participants were 30 nurses working at a general ward. Input variables were labor cost and time of direct nursing. Output variables were prevention rate of medication error and bedsores, and patient satisfaction. These variables were extracted using literature review and CVI of an expert group. Data were collected from September 18 to October 7, 2017. Data were analyzed using EMS 3.1 program for DEA and descriptive statistics. Results: The average efficiency score of 30 nurses was 0.986, which was very high over all. In the super-efficiency analysis of 11 nurses, their efficiency ranged from 1.0 to 1.047. In addition, when the current output was fixed, the labor cost of nurses did not affect efficiency. Conclusion: This study attempted a new approach concerning performance evaluation of nurses using DEA. This method was useful during appraisal of nurses. We suggest that various input and output variables that were not considered in this study should be added to develop a integrative performance analysis model for nurses.

• Journal of Korean Society for Quality Management
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• v.37 no.1
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• pp.1-9
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• 2009

Data envelopment analysis(DEA) has proved to be powerful for benchmarking and has been widely used in a variety of settings since the advent of it. DEA can be used in identifying the best performing units to be benchmarked against as well as in providing actionable measure for improvement of a organization's performance. However, the selection of performance benchmarks is a matter of both technical production possibilities and organizational policy considerations, managerial preferences and external restrictions. In that regards, DEA has a limited value in benchmarking because it focuses on only technical production Possibilities. This research proposes a new perspective in using DEA and a frame-work for benchmarking to select benchmarks that are both feasible and desirable in terms of organizational context. To do this, the concept of local and global efficiency is newly proposed. To show how useful the suggested concept and framework are, a case study is addressed.

• Journal of Korean Society for Quality Management
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• v.37 no.1
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• pp.80-90
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• 2009

Nowadays, there are many companies which employ the SQI measurement to assess service quality. The purpose of this study is to measure the service efficiency for Bank Industry. In this paper, we tried to measure the efficiency of service quality and overall customer satisfaction by using Data Envelopment Analysis(DEA). Rather than using the usual method of converting the Service Quality Index(SQI) into mean value, we applied CCR/BCC models in DEA to service quality efficiency. Also, DEA/PS Model is recommended as appropriate model for evaluating service efficiency by complementing the shortfalls of the weighted value of DEA Model. In this study, six dimensions of service quality were considered as input variables and output variables(overall customer satisfaction, reusing intention, and word of mouth). The result of this study statistically verifies that 5 DMUs are relatively efficient, and intensive activities for service efficiency are needed for 20 sample branches. Managerial implications based on the analysis were suggested.

• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.4 s.27
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• pp.233-239
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• 2006

This paper aims to evaluate the operation efficiency of Korean RCC(Rescue Co-ordination Center)/RSC(Rescue Sub-Center) using DEA(Data Envelopment Analysis). for this evaluation, this paper use the quantitative data for DEA analysis with two inputs and four outputs and a qualitative data analysis with the use of expert assessment. The tool for integrating heterogeneous data is fuzzy logic model to decision support system. In this paper, therefore, RCC/RSC evaluates the priority for operation efficiency. The result are found as order as Inchon, Mokpo, Jeju, Donghae, Busan, Pohang, Yosu, Sokcho, Tongyeong, Ulsan, Taean, Gunsan RSC.

• Knowledge Management Research
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• v.17 no.1
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• pp.49-72
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• 2016

Extant research on firm innovation productivity is limited in measuring the innovation productivity, in which they measured firm innovation productivity by using either inputs or outputs of innovation. The present study complemented the extant research by employing Data Envelopment Analysis (DEA) approach to measure firm innovation productivity. Furthermore, this paper examined the effects of firms' external knowledge search, as one of open innovation practices, on firm innovation productivity, for open innovation activities are regarded as an influencing factor on firm innovation productivity in the previous literatures. Using the data of the Korean Innovation Survey (KIS) of manufacturing industries conducted in 2008, this study developed hypotheses in which we considered not only two dimensions of external knowledge search (breadth and depth) but also two subtypes of external knowledge search (market-driven and science-driven). The results found that searching deeply and market-driven search are positively related to firm innovation productivity, but science-driven search is somewhat negatively related to firm innovation productivity. Furthermore, market-driven search can mitigate the negative effect of science-driven search on innovation productivity.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.317-327
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• 2020

R&D(Research and Development) efficiency analysis is a very important issue in academia and industry. Although many studies have been conducted to analyze R&D(Research and Development) efficiency since the past, studies that analyzed R&D(Research and Development) efficiency considering both patentability and patent quality efficiency according to the financial performance of a company do not seem to have been actively conducted. In this study, measuring the patent application and patent quality efficiency according to financial performance, patent quality efficiency according to patent application were applied to corporate groups related to artificial intelligence hardware technology defined as GPU(Graphics Processing Unit), FPGA(Field Programmable Gate Array), ASIC(Application Specific Integrated Circuit) and Neuromorphic. We analyze the efficiency empirically and use Data Envelopment Analysis as a measure of efficiency. This study examines which companies group has high R&D(Research and Development) efficiency about artificial intelligence hardware technology.

• Journal of Navigation and Port Research
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• v.34 no.9
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• pp.719-726
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• 2010

As the competition among the container terminals in Korea has become increasingly fierce, every terminal is striving to increase its investments constantly and lower its operational costs in order to maintain the competitive edge and provide satisfactory services to terminal users. The unreasoning behavior, however, has induced that substantial waste and inefficiency exists in container terminal production. Therefore, it is of great importance for the terminal to know whether it has fully used its existing infrastructures and that output has been maximized given the input. From this perspective, data envelopment analysis (DEA) provides a more appropriate benchmark. This study applies three models of DEA to acquire a variety of analytical results about the operational efficiency to the Korean container terminals. According to efficiency value analysis, this study first finds the reason of inefficiency. It is followed by identification of the potential areas of improvement for inefficient terminals by applying slack variable method and giving the projection results. Finally, return to scale approach is used to assess whether each terminal is in a state of increasing, decreasing, or constant return to scale. The results of this study can provide terminal managers with insight into resource allocation and optimization of the operating performance.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.195-205
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• 2007

The steel industry plays an important role in the entire Korean Economy. However, little empirical research has analyzed the efficiency of steel companies. The purpose of this paper is to measure and analyze their efficiency using DEA models. We evaluate the CCR and BCC efficiency and the return to scale of 28 Korean steel companies. We also provide their envelopment map and the projection, which are valuable information for inefficient companies to find benchmarking companies and to improve their efficiency.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.99-111
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• 2016

This paper presents a framework to analyze the change in the research and development (R&D) efficiency of government-funded research institutes (GRIs) in Korea. Cumulative data envelopment analysis/Malmquist index method is utilized to analyze the changes in R&D efficiency of GRIs. Data analysis of the R&D activities of 10 GRIs in Korea Research Council of Fundamental Science & Technology showed that the average R&D efficiency of the 10 GRIs improved from 2009 to 2013. However, the efficiency of a few GRIs decreased in terms of the catch-up index. The proposed framework can help management teams diagnose the current state of R&D activities and determine the efficacy of strategic actions by comparing efficiencies in the past.