• 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 Korean Institute of Industrial Engineers
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• v.36 no.1
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• pp.32-41
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• 2010

DEA(Data Envelopment Analysis) is the relative efficiency measure among homogeneous DMU(Decision- Making Units) which can be used to useful tool to improve performance through efficiency evaluation and benchmarking. However, the general case of DEA was considered as unrealistic since it consists a benchmarking regardless of DMU characteristic by input and output elements and the high efficiency gap in benchmarking for inefficient DMU. To solve this problem, stratification method for benchmarking was suggested, but simply presented benchmarking path in repeatedly applying level. In this paper, we suggest a new method that inefficient DMU can choice the optimal path to benchmark the most efficient DMU base on the similarity among the input elements. For this, we propose a route choice method that combined a stratification benchmarking algorithm and SOM (Self-Organizing Map). An implementation on real environment is also presented.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.33-46
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• 2019

Purpose: This study proposed a DEA (Data Envelopment Analysis)-based stepwise benchmarking target selection for inefficient DMU (Decision Making Unit) to improve its efficiency gradually to reach most efficient frontier considering resource (DEA inputs and outputs) improvement preferences. Methods: The proposed method proceeded in two steps. First step evaluates efficiency of DMUs by using DEA, and an evaluated DMU selects benchmarking targets of HCU (Hypothesis Composit Unit) or RU (Real Unit) considering resource improvement preferences. Second step selects stepwise benchmarking targets of the inefficient DMU. To achieve this, this study developed a new DEA model, which can select a benchmarking target of an inefficient DMU in considering inputs or outputs improvement preference, and suggested an algorithm, which can select stepwise benchmarking targets of the inefficient DMU. Results: The proposed method was applied to 34 international ports for validation. In efficiency evaluation, five ports was evaluated as most efficient port, and the remaining 29 ports was evaluated as relative inefficient port. When port 34 was supposed as evaluated DMU, its can select its four stepwise benchmarking targets in assigning the preference weight to inputs (berth length, total area of pier, CFS, number of loading machine) as (0.82, 1.00, 0.41, 0.00). Conclusion: For the validation of the proposed method, it applied to the 34 major ports around the world and selected stepwise benchmarking targets for an inefficient port to improve its efficiency gradually. We can say that the proposed method enables for inefficient DMU to establish more effective and practical benchmarking strategy than the conventional DEA because it considers the resource (inputs or outputs) improvement preference in selecting benchmarking targets gradually.

• Korea Journal of Hospital Management
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• v.5 no.1
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• pp.84-104
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• 2000

This paper analyzes the technical efficiency of thirty two hospitals in Korea using DEA(Data Envelopment Analysis). DEA provides an efficiency measure for each hospital compared to the most efficient one. The amount and sources of inefficiency that are identified by the DEA are useful for benchmarking to improve efficiency. The results from multiple regression analysis and Wilcoxon Rank Sum test show that bed turnover, hospital size, and average length of stay are related to hospital efficiency.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.628-641
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• 2014

Stepwise efficiency improvement in data envelopment analysis (DEA)-based benchmarking is a realistic and effective method by which inefficient decision making units (DMUs) can choose benchmarks in a stepwise manner and, thereby, effect gradual performance improvement. Most of the previous research relevant to stepwise efficiency improvement has focused primarily on how to stratify DMUs into multiple layers and how to select immediate benchmark targets in leading levels for lagging-level DMUs. It can be said that the sequence of benchmark targets was constructed in a myopic way, which can limit its effectiveness. To address this issue, this paper proposes an optimization approach to the construction of a sequence of benchmarks in DEA-based benchmarking, wherein two optimization criteria are employed : similarity of input-output use patterns, and proximity of input-output use levels between DMUs. To illustrate the proposed method, we applied it to the benchmarking of 23 national universities in South Korea.

• 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.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.57-63
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• 2002

The construction market has a major impact on the overall United States economy. Recent statistics estimate the gross domestic product (GDP) of the U.S. construction industry at some $416.4{\$}$ billion dollars, representing approximately $4.5\%$ of the U.S. GDP. Because the business environment in construction is highly competitive, the participants in the industry must improve their performance and processes to survive. Hence, Benchmarking has been generating interest in the construction industry. This paper provides an overview of the CII Benchmarking and Metrics Program. Following some background and a descriptive discussion of the database, an abridged presentation of result of data analysis. The adoption of benchmarking in Korean construction industry can be another opportunity to improve Korean construction industry.

• Journal of Korean Society for Quality Management
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• v.32 no.3
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• pp.1-9
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• 2004

Many companies of the world have applied the TQM, which was originated from Japanese management style, to increase their competitiveness. It is not so easy to implement successfully the management practices originated from the foreign countries, which are usually mixed with specific cultures and management systems of their own. Some American companies created some best practices such as 6 sigma approach for applying TQM by creative benchmarking. This Paper Presents some issues for creative benchmarking for Korean companies through the analysis of the creative benchmarking processes of the successful American companies.

• Smart Structures and Systems
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• v.11 no.2
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• pp.135-161
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• 2013

This work presents a test platform for the assessment and benchmarking of modern actuators which have been specifically developed for the new field and service robotics applications. This versatile platform has been designed for the comparative analysis of actuators of dissimilar technology and operating conditions. It combines a modular design to adapt to linear and rotational actuators of different sizes, shapes and functions, as well as those with different load capacities, power and displacement. This test platform emulates the kinematics of robotic joints while an adaptive antagonist-load actuator allows reproducing the variable dynamic loads that actuators used in real robotics applications will be subjected to. A data acquisition system is used for monitoring and analyzing test actuator performance. The test platform combines hardware and software in the loop to allow actuator performance characterization. The use of the proposed test platform is demonstrated through the characterization and benchmarking of three controllable impedance actuators recently being incorporated into modern robotics.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.84-94
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• 2021

Graph databases have been developed to efficiently store and query graph data composed of vertices and edges to express relationships between objects. Since the query types of graph database show very different characteristics from traditional NoSQL databases, benchmarking tools suitable for graph databases to verify the performance of the graph database are needed. In this paper, we propose an efficient graph database benchmarking system that supports diversity in graph inputs and queries. The proposed system utilizes OrientDB to conduct benchmarking for graph databases. In order to support the diversity of input graphs and query graphs, we use LDBC that is an existing graph data generation tool. We demonstrate the feasibility and effectiveness of the proposed scheme through analysis of benchmarking results. As a result of performance evaluation, it has been shown that the proposed system can generate customizable synthetic graph data, and benchmarking can be performed based on the generated graph data.