• Journal of Korea Port Economic Association
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• v.18 no.1
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• pp.85-106
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• 2002

Across many industries, benchmarking is considered useful method to improve their service quality and achieve competitive advantage. Benchmarking, especially, has emerged as an increasingly important approach to improving the performance of logistics system and enables successful logistics services and doing good business in logistics services. There are no, however, literature approach for the relationship between benchmarking and port. It is the highest worth researching the application of benchmarking method on the port, since port is the most important component in supply Chain. Therefore, this paper tries to demonstrate the application of the benchmarking method on the port. To do this study, the literature approach developed by several researchers for logistics benchmarking is used as the basic framework. In addition, the following studies are executed: First, the survey of previous studies on logistics benchmarking. Second, finding the indicator and selecting the target in the port benchmarking. Third, the systematic execution schemes of the port benchmarking. Finally, based on the above studies, this paper provides a background for discussions on the future prospects for the application of the benchmarking method on the port.

• 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.

• 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 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.

• International Journal of Quality Innovation
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• v.8 no.2
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• pp.57-68
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• 2007

Benchmarking is more than just a comparison of measures about different company's performance in a wider sense. It is a methodology of learning-comparing-learning, at least within small and medium sized enterprises. This learning is not just limited to learn by copying successful concepts from other enterprises or competitors. It starts in learning more about the own company, about its structure and processes causing its own success or its failure. This kind of learning is necessary before the enterprise starts watching for a suitable Benchmarking partner. Learning from each other's strengths and weaknesses is the main goal of the European research project Quality beyond Borders! By using the Benchmarking methodology, small and medium sized enterprises get the opportunity to take part in a Benchmarking study and can learn more about the different strengths and weaknesses of other enterprises on both sides of the border. The results of such a Benchmarking can help to identify potentials for future cooperations among German and Polish enterprises in the same market or business. These potentials can lie in different ways of realising the same success or top-position. The Benchmarking study is not focused on an special business or region. That helps to find out trends for different kinds of top-positions, which can be claimed in all markets within a country. Every trend is characterised by different success factors which are responsible for the success in this top-position. In a first overview, the results of the Benchmarking study show 5 different groups of top-positions within a market which all have different profiles regarding to the importance of their success factors. By the end of the Benchmarking study it will be possible, to give answer about the special reasons for different kind of successes of these groups. These answers can be related to a special region within a country, a special business or of course related to possible differences in the expression of the group success factors in comparison of both countries.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.13-17
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• 2003

Requirements of a benchmarking for rapid prototyping systems and process usually include manufacturing time, cost (including system price), and dimensional accuracy. This paper deals with a benchmarking comparisons to investigate the functional requirements of RP system. A special designed IMS_T2 test part with dimensional. geometrical, and surface roughness features has been used in the inspection of RP processes. IMS_T2 test part was built on 5 commercially available RP machines which are relatively new model in Korea.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.590-598
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• 2022

Benchmarking is an important tool to assess the performance of capital projects in the construction industry. Incorporating cost-related metrics into a benchmarking system requires an effective cost normalization process to enable meaningful comparisons among projects that were executed at different locations and times. Projects in the downstream and chemicals sector have unique characteristics compared to other types of construction projects, they require a distinctive cost normalization framework to be developed to benchmark their absolute cost performance. The purpose of this study is to develop such a framework to be used for the case of benchmarking the downstream and chemical projects for their performance assessment. The research team started with a review of existing cost normalization methodologies adopted in benchmarking systems and conducted 7 interviews to identify the current cost normalization practices used by industrial professionals. A panel of 12 experts was then convened and it held 6 review sessions to accomplish the framework development. The cost normalization framework for benchmarking downstream and chemical projects was established as a three-step procedure and it adopts a 4-element cost breakdown structure to accommodate projects submitted by both owners and contractors. It also incorporated 5 published cost indexes that are compatible with downstream and chemical projects and they were embedded into 2 options to complete the normalization process. The framework was then pilot-tested on 4 completed projects to validate its functional practicality and the downstream and chemical use case in the benchmarking system.

• 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.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.391-395
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• 2007

Benchmarking is a process used in a lot of companies and public institutions because it is considered to be a practical tool for management innovation. However, it is hard to find out the development of systematic methods and applied cases for benchmarking on information services environment. This study tried to apply the benchmarking process to information distribution environment. This study examined the basic definition and standard process of benchmarking, and then conducted benchmarking plan to innovate tasks of database construction for information services at KISTI.

• 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.