• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.53-90
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• 1992

THis study examines a contingency relationship between task uncertainty and structure of project teams in conjunction with the leader-member communication patterns. Multivariate analyses are used to analyze the data from 63 R & D project teams of research laboratory in a large manufacturing corporation. Major findings for this study can be summarized as follows. First, project teams with an organic structure are found to yield high performance when task uncertainty is high, while project teams with a mechanistic structure achieve high performance when their tasks are relatively certain. Second, patterns of leader-member comunication are significantly associated with both task uncertainty and structural characteristics of project teams. This implies that leaders of project teams communicate with their members in more conslutative manner when their tasks are uncertain or when their team structure exhibits organic characteristics. Finally, task uncertainty playus a significant moderating role in the relationship between consultative communication patterns and performance of project teams. Based upon these findings, this study offers several theoretical, practical, and methodological implications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1809-1816
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• 2021

In order to identify the latest research trends using data related to national R&D projects and to produce and utilize meaningful information, the application of automatic classification technology was also required in the national R&D information service, so we conducted research to automatically classify and recommend research field. About 450,000 cases of national R&D project data from 2013 to 2020 were collected and used for learning and evaluation. A model was selected after data pre-processing, analysis, and performance analysis for valid data among collected data. The performance of Word2vec, GloVe, and fastText was compared for the purpose of deriving the optimal model combination. As a result of the experiment, the accuracy of only the subcategories used as essential items of task information is 90.11%. This model is expected to be applicable to the automatic classification study of other classification systems with a hierarchical structure similar to that of the national science and technology standard classification research field.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.921-927
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• 2005

Concurrent engineering is considered in the 21st century product development and H&D. Moreover, advancements in IT and advanced system engineering technology enables to produce high-quality article and shorten the period of R&D. The paper propose work breakdown structure(WBS) based on the product data management(PDM), WEB based system engineering technique, to introduce and operate advanced system engineering technique. We will manage systematically all data produced in advanced urban transit system project based on the proposed WBS. Besides, we provide strategic information for improving efficiency of R&D in advanced urban transit system project. Futhermore, we manage data such as images, design drawings, documents as well as numerical data, and will establish PDM system for sharing the data.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.217-220
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• 1996

This study presents a R&D performance monitoring system (RDMS) that is applicable for managing nuclear program in KAERI. The prime goal of RDMS is to furnish project manager with reliable and accurate information on status of progress, performance and resource allocation, and attain traceability and visibility of project implementation for effective project management. In this study, the work breakdown structure (WBS) as the governing factor for integration of scope, schedule, resource data was derived, and the above parameters were loaded personal computer. A RDMS is comprised of about 12,000 R&D activities of the 16 goverment-led projects. The Primavera software was used to monitor the progress, evaluate the performance and analyze the resource distribution to activities.

• STI Policy Review
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• v.8 no.2
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• pp.75-93
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• 2017

Recently, global competition in the manufacturing sector is driving firms in the manufacturing sector to conduct product innovation projects to maintain their competitive edge. The key points of product innovation projects are 1) what the purpose of the project is and 2) what expected results in the target market can be achieved by implementing the innovation. Therefore, this study focuses on the performance of innovation projects with a business viewpoint. In this respect, this study proposes the "achievement rate" of product innovation projects as a measurement of project performance. Then, this study finds the best strategies from various innovation activities to optimize the achievement rate of product innovation projects. There are three major innovation activities for the projects, including three types of R&D activities: Internal, joint and external R&D, and five types of non-R&D activities - acquisition of machines, equipment and software, purchasing external knowledge, job education and training, market research and design. This study applies decision tree modeling, a kind of data-mining methodology, to explore effective innovation activities. This study employs the data from the 'Korean Innovation Survey (KIS) 2014: Manufacturing Sector.' The KIS 2014 gathered information about innovation activities in the manufacturing sector over three years (2011-2013). This study gives some practical implication for managing the activities. First, innovation activities that increased the achievement rate of product diversification projects included a combination of market research, new product design, and job training. Second, our results show that a combination of internal R&D, job training and training, and market research increases the project achievement most for the replacement of outdated products. Third, new market creation or extension of market share indicates that launching replacement products and continuously upgrading products are most important.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.126-132
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• 2013

In this paper, efficiencies of core technology development projects, conducted by Ministry of Trade, Industry and Energy, are compared. In the process, DEA (Data Envelopment Analysis) is utilized as a main technique for comparing efficiencies. For DEA, input oriented BCC Model is adopted with government grant, recipient expenditure, the number of participating institutions, and project duration as input factors, and the number of patents, the number of papers, and occurred sales as output factors. As a result, next generation mobile communication project turns out to be the most efficient project of all. Therefore, next generation mobile communication project should be benchmarked for the other projects to follow. However, these results should be used only for reference data since every project has a different objective and, of course, is run under a different environment.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.5
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• pp.583-589
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• 2019

One of the core pillars of the Fourth Industrial Revolution is the innovation of the manufacturing industry. From the beginning, the 4th Industrial Revolution appeared in Germany under the concept of 'Industrial 4.0', which means a radical change in the manufacturing industry that can provide super intelligent product production and services based on artificial intelligence and big data. Since manufacturing innovation is a change in the industrial character of the entire nation, the initial role of government is important. Korea also has various policies related to the 4th Industrial Revolution, but there are still various problems to be solved. Therefore, this paper monitors and analyzes the public R&D projects of the advanced countries on manufacturing innovations in the background mentioned above, and through this, the policy implications are drawn.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.329-331
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• 2014

The analysis of the similarities and redundancies among R&D projects is important for the efficient investment of government budgets. When government R&D projects are planned, the redundancies of research tasks are examined by institutions specializing in research management, relevant offices and departments, and the government to prevent redundant funding. However, as existing similarity analyses depend on methods wherein new task proposals and existing R&D project proposals are compared and looked up based on keywords. This results in vulnerability wherein similarity cannot be accurately measured in the event of partial modifications of the task name or technical substitutions. This study aims to use patent information as characteristics by which R&D project documents can be identified. The patent data used is based on materials officially published by the government's R&D patent trend survey project (http://ipas.rndip.re.kr). The study aims to propose a method by which patent information can be used to analyze the similarity and redundancy among R&D projects when new projects are entered. For this purpose, a similarity measurement model based on set theory and probability theory is presented. The presented measurement model is implemented into an actual system to identify redundant documents, and calculate and show their similarity.

• Proceedings of the Technology Innovation Conference
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• 1997.12a
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• pp.104-130
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• 1997

This study empirically examined different patterns of collaborative R&D project with their key success factors(KSFs), using data from 80 projects in the Korean electronic parts industry The patterns in this study were categorized into 4 types by two criteria : product types(off-the-shelf/unique) and project initiator (focal/partner). The bivariate relationships revealed that project characteristics (technological complexity, demand certainty), partner characteristics(the number of partners, precious experience), process characteristics (participation in the project formulation, specificity of the collaboration process and outcomes) appear to be different among four types of collaboration. Furthermore, this study found that each type of collaborative R&D projects has different KSFs for their commercial success. The KSFs of type 1 (off-the-shelf product and focal organization initiation), for instance, include the strategic importance of the project, the problem solving performance of the focal organization while those of type 4(unique product and partner initiation) are technological complexity, demand certainty, reliability of partner relationship, specificity of the goals, specificity of the process and outcomes, information sharing. Finally, based on this empirical results, managerial, policy, and theoretical implications of the study were discussed.