In recent years, knowledge has emerged as a major source of competitive advantage due to the continuous development of information and communication technology, the acceleration of globalization, and the entry into knowledge-based society. Thus interests in knowledge management have been increased significantly. Nevertheless theoretical backgrounds of knowledge management are not actively discussed. Studies on the knowledge management of R&D groups initiating knowledge creation and sharing are not actively conducted either. This study, therfore, provides a research model of knowledge management to investigate relationships among resource and institutional characteristics, knowledge management activities, and knowledge management performance of R&D groups based on knowledge-based theories and institutionalization theories. This study further offers research propositions inherent in the model.
Korean Journal of Computational Design and Engineering
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v.11
no.2
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pp.88-96
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2006
This paper introduces an approach to ontology-based framework for knowledge management in a product development domain. The participants in a product life cycle want to share the product knowledge without any heterogeneity. However, previous knowledge management systems do not have any conceptual specifications of their knowledge. We suggest the three levels of knowledge framework. First level is an axiom, which specifies the semantics of concepts and relations. Second level is a product development knowledge map. It defines the common domain knowledge which domain experts agree with. Third level is a specialized knowledge for domain, which includes three knowledge types; expert knowledge, engineering function and data-analysis-based knowledge. We propose an ontology-based knowledge framework based on the three levels of knowledge. The framework has a uniform representation; first order logic to increase integrity of the framework. We implement the framework using prolog and test example queries to show the effectiveness of the framework.
This study purports to investigate the readiness of the university hospital employees in the knowledge-based management. Data were collected from 550 employees including administrative, nursing, and technical staff of 9 university hospitals located in Seoul and Kyunggi Province through the self-administered questionnaires. The response rate was 79% and 425 questionnaires were used as final data and analyzed using 2 test, t-test, and ANOVA. The main findings of the study are as follows. 1) It seems that most employees of the study hospitals have basic knowledge on the concept of knowledge-based management. This finding implies that the implementation of the knowledge-based management in Korean university hospitals will not likely to face strong resistance from their employees. 2) The results show that Korean hospital employees are still not so accustomed to using e-mail as the main communication tool. This finding suggests that it is necessary to use various communication tools which include electronic data interchange, teleconference, and cyber chatting for facilitating the knowledge-based management in Korean university hospitals. 3) It is desirable to appoint a chief knowledge officer(CKO) for operating knowledge-based management system effectively. 4) A reward system for employees who show a distinguished performance in the creation and sharing of new knowledge should be established. Knowledge mileage system, selection of the best knowledge employee and team will be a good example of the effective reward system. 5) The participation and support from the chief executive officers (CEO) of the hospitals is an important factor for successful knowledge-based management. Furthermore, to make physicians actively participate in the knowledge-based management is another important factor for obtaining valuable outputs from the system. 6) It is found that the knowledge and skills of the hospitals employees on the information technology (IT) are not sufficient for making knowledge-based management more popular. This implies that it is very important to select IT-oriented employees and educate them continuously on the knowledge-based management.
I have tried to find a concept among different perspectives on knowledge management. A practical framework of the enhancement of firm's competence through knowledge accumulations was developed as follows: First, All human factors should be armed with information based knowledge and leaded by chief knowledge officer. Second, Learning organization is necessary to develope knowledge creation. Third, Organization has to be controlled by information based control system for the effective linkage of several sort of information. Fourth, Shared culture of knowledge internalized by all members must help organization generate and articulate a new form of knowledge. Finally, Several information technologies and instrumental system may faster creation of knowledge. Especially, in this paper, focused on role of knowledge-based people. It is new view of knowledge-based management studies.
A knowledge map describes the network of related knowledge into the form of a diagram, and therefore underpins the structure of knowledge categorizing and archiving by defining the relationship of the referential navigation between knowledge. The referential navigation between knowledge means the relationship of cross-referencing exhibited when a piece of knowledge is utilized by a user. To understand the contents of the knowledge, a user usually requires additionally information or knowledge related with each other in the relation of cause and effect. This relation can be expanded as the effective connection between knowledge increases, and finally forms the network of knowledge. A network display of knowledge using nodes and links to arrange and to represent the relationship between concepts can provide a more complex knowledge structure than a hierarchical display. Moreover, it can facilitate a user to infer through the links shown on the network. For this reason, building a knowledge map based on the ontology technology has been emphasized to formally as well as objectively describe the knowledge and its relationships. As the necessity to build a knowledge map based on the structure of the ontology has been emphasized, not a few researches have been proposed to fulfill the needs. However, most of those researches to apply the ontology to build the knowledge map just focused on formally expressing knowledge and its relationships with other knowledge to promote the possibility of knowledge reuse. Although many types of knowledge maps based on the structure of the ontology were proposed, no researches have tried to design and implement the referential navigation-enabled knowledge map. This paper addresses a methodology to build the ontology-based knowledge map enabling the referential navigation between knowledge. The ontology-based knowledge map resulted from the proposed methodology can not only express the referential navigation between knowledge but also infer additional relationships among knowledge based on the referential relationships. The most highlighted benefits that can be delivered by applying the ontology technology to the knowledge map include; formal expression about knowledge and its relationships with others, automatic identification of the knowledge network based on the function of self-inference on the referential relationships, and automatic expansion of the knowledge-base designed to categorize and store knowledge according to the network between knowledge. To enable the referential navigation between knowledge included in the knowledge map, and therefore to form the knowledge map in the format of a network, the ontology must describe knowledge according to the relation with the process and task. A process is composed of component tasks, while a task is activated after any required knowledge is inputted. Since the relation of cause and effect between knowledge can be inherently determined by the sequence of tasks, the referential relationship between knowledge can be circuitously implemented if the knowledge is modeled to be one of input or output of each task. To describe the knowledge with respect to related process and task, the Protege-OWL, an editor that enables users to build ontologies for the Semantic Web, is used. An OWL ontology-based knowledge map includes descriptions of classes (process, task, and knowledge), properties (relationships between process and task, task and knowledge), and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. Therefore a knowledge network can be automatically formulated based on the defined relationships, and the referential navigation between knowledge is enabled. To verify the validity of the proposed concepts, two real business process-oriented knowledge maps are exemplified: the knowledge map of the process of 'Business Trip Application' and 'Purchase Management'. By applying the 'DL-Query' provided by the Protege-OWL as a plug-in module, the performance of the implemented ontology-based knowledge map has been examined. Two kinds of queries to check whether the knowledge is networked with respect to the referential relations as well as the ontology-based knowledge network can infer further facts that are not literally described were tested. The test results show that not only the referential navigation between knowledge has been correctly realized, but also the additional inference has been accurately performed.
A knowledge map, a taxonomy of knowledge repositories, must have capabilities supporting and enhancing knowledge user's activity to search and select proper knowledge for problem-solving. Conventional knowledge maps, however, have been hierarchically categorized, and could not support such activity that must coincide with the user's cognitive process for knowledge utilization. This paper, therefore, aims to verify and develop a methodology to build a networked knowledge map that can support user's activity to search and retrieve proper knowledge based on the referential navigation between content-relevant knowledge. This paper deploys keywords as the semantic information between knowledge, because they can represent the overall contents of a given document, and because they can play the role of semantic information on the link between related documents. By aggregating links between documents, a document network can be formulated: a keyword-based networked knowledge map can be finally built. Domain expert-based validation test was also conducted on a networked knowledge map of 50 research papers, which confirmed the performance of the proposed methodology to be outstanding with respect to the precision and recall.
Hyun Mo Kang;Il Young Choi;Jae Kyeong Kim;Hyun Joo Shin
Asia pacific journal of information systems
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v.31
no.3
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pp.358-377
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2021
Knowledge drives business innovation. However, even if companies have the same knowledge element in the business ecosystem, innovation performance varies depending on the structural position of the technical knowledge network. This study investigated whether there is a difference in exploitative innovation according to the structural position of the AI technical knowledge network. We collected patents from the top 100 digital companies registered with the US Patent Office from 2015 to 2019 and classified the companies into knowledge producer-based brokers, knowledge absorber-based brokers, knowledge absorbers, and knowledge producers from the perspective of knowledge creation and flow. The analysis results are as follows. First, a few of the top 100 digital companies disseminate, absorb, and mediate knowledge, while the majority do not. Second, exploitative innovation is the largest, in the order of knowledge producer, knowledge absorber-based broker, knowledge absorber, and knowledge producer-based broker. Finally, patents for industrial intelligence occupy a large proportion, and knowledge producers are leading exploitative innovation. Therefore, latecomers need to expand their resources and capabilities by citing patents owned by leading companies and converge with existing industries into AI-based industries.
Knowledge workers' workload to register knowledge can cause quality defects in the quality as well as the quantity of knowledge that must be accumulated in a knowledge management system(KMS). To enhance the availability of a KMS by acquiring more quality-guaranteed knowledge, autonomous knowledge acquisition which outdoes the automated acquisition must be initiated. Adopting the capabilities of context-awareness and inference in the field of context-aware computing, this paper intends to autonomously identify and acquire knowledge from knowledge workers' daily lives. Based on knowledge workers' context information, such as location, identification, schedule, etc, a methodology to monitor, sense, and gather knowledge that resides in their ordinary discussions is proposed. Also, a prototype systems of the context-based knowledge acquisition system(CKAS), which autonomously dictates, analyzes, and stores dialogue-based knowledge is introduced to prove the validity of the proposed concepts. This paper's methodology and prototype system can support relieving knowledge workers' burden to manually register knowledge, and hence provide a way to accomplish the goal of knowledge management, efficient and effective management of qualified knowledge.
This paper introduces an approach to an ontology-based multi-level knowledge framework for a knowledge management system for discrete-product development. Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects: therefore, we suggest an ontology-based multi-level knowledge framework (OBMKF). The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so ambiguity can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain knowledge and guides the engineer to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and manufactured item level, according to the various viewpoints. The top level is specialized knowledge for a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of knowledge and is represented with first-order logic to maintain a uniform representation.
Journal of the Korean Society for Precision Engineering
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v.23
no.3
s.180
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pp.22-31
/
2006
This paper introduces an approach to an ontology-based knowledge framework for product life cycle management (PLM). Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects. Therefore, we suggest an ontology-based knowledge framework including knowledge maps, axioms and specific knowledge far domain. The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so that ambiguity of the semantics can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain common knowledge and guides engineers to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and product item level for PLM. The top level is specialized knowledge fer a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of unambiguous knowledge for PLM and is represented with first-order logic to maintain a uniform representation.
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