• Knowledge Management Research
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• v.11 no.1
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• pp.65-81
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• 2010

This paper explores the determinants of the economic value of patents using a survival time analysis. The analysis is based on renewal information of about 250,000 patents filed from 1984 to 2005 in the Korea Intellectual Property Office. A patent right is valid only when its owner pays yearly maintenance fees. Failure to pay causes patent rights to be lapsed. We use the fact that more valued patents live longer and the lengths of their renewals can be closely related to their value. The value can be affected not only by its own technological aspects such as quality and breadth, but also by characteristics of its owners such as innovativeness and age. This paper presents patent-specific and firm-specific characteristics which influence patent value. The result of analysis implies that patent value depends on both the technological contents of the patent and general capabilities of a firm.

• Knowledge Management Research
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• v.10 no.1
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• pp.53-70
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• 2009

This study empirically explored what promotes exploration, through a case analysis of a Korean SME (small and medium sized enterprise), based on the research framework which focuses on the identification and the selection of exploratory NPD (new product development) alternatives, and the accumulation of novel capabilities in new technology domains. The learning process of the exploratory NPD project described is as follows. The identification barrier of exploratory NPD project is relatively low. Constructive crisis is germane to selecting exploratory NPD alternatives and to enduring the long payback period. New separated R&D unit is likely to implement the exploratory NPD project. The length of the gestation period of the exploratory NPD project is related with the level of the conflict between old members and new members. This study identified several antecedents of the exploratory NPD project. Prior success promotes the identification process of the exploratory NPD projects. Constructive crisis is related with CEO's personal characteristics such as future oriented and proactive personality. The proactive involvement and persuasion of CEO are germane to reducing the conflict between old and new members and to the success of the exploratory NPD project. Based on the results, this study discusses several implications and future research directions.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.677-696
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• 2017

Purpose: This study suggests that Six Sigma MBB should be used as a key talent to lead the fourth industrial revolution era by training them with big data processing capability. Methods: Through the analysis between articles on the fourth industrial revolution and Six Sigma related papers, common competencies of data scientists and Six Sigma MBBs were identified and the big data analysis capabilities needed for Six Sigma MBB were derived. Then, training was conducted to improve the big data analysis capabilities so that Six Sigma MBB is able to design algorithms required in the fourth industrial revolution era. Results: Six Sigma MBBs, equipped with the knowledge in field site improvement and basic statistics, were provided with 40 hours of big data analysis training and then were made to design a big data algorithm. Positive results were obtained after applying a AI algorithm which could forecast process defects in a field site. Conclusion: Six Sigma MBB equipped with big data capability will make the best talent for the fourth industrial revolution era. A Six Sigma MBB has an excellent capability for improving field sites. Utilizing the competencies of MBB can be a key to success in the fourth industrial revolution. We hope that the results of this study will be shared with many companies and many more improved case studies will arise in the future as a result of this study.

• Knowledge Management Research
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• v.25 no.2
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• pp.155-176
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• 2024

This study explores variations in preferences for human and AI agents within the medical and financial services. Study 1 investigates whether there are preferential disparities between human and AI agents across these service domains. It finds that human agents are favored over AI agents in medical services, while AI agents receive greater preference in the financial services. Study 2 delves into the underlying reasons for the preference differentials between human and AI agents by assessing the significance of certain capabilities as perceived by users in each domain. The findings reveal a mediating role of perceived empathy importance in the effect of service domains on human-AI preference. Furthermore, perceived empathy is deemed a more critical capability by users for preferring human over AI agents across both service domains compared to other capabilities such as experience and agency. This research is noteworthy for elucidating the variances in preferences for human and AI agents across medical and financial services and the rationale behind these differences. It enhances our theoretical comprehension of the pivotal factors influencing preferences for human and AI agents, underscoring the significance of human experiential capabilities like empathy.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.764-770
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• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.599-600
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• 2006

In order to promptly cope with the various requirements of consumers, the environment of product development is being globalized in manufacturing industrials. For this reason, it is necessary to build up an efficient collaborative system for communication between remote area designers. Specially, while Internet and information technologies were merged with the manufacturing or business process, the research for collaborative system has become an important issue. Therefore, we propose a Web-based Engineering Collaboration Framework using SPS(SharePoint Portal Server) which is an enterprise business solution that integrates information from various system into one solution through single sign-on and enterprise application integration capabilities, with flexible deployment options and management tool. Through a Web-based Engineering Collaboration Framework, designers can share knowledge assets and have a remote conference with others via web.

• Knowledge Management Research
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• v.25 no.2
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• pp.19-47
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• 2024

Organizational ability to analyze and utilize data plays an important role in knowledge management and decision-making. This study aims to investigate the potential application of large language models in corporate data analysis. Focusing on the field of human resources, the research examines the data analysis capabilities of these models. Using the widely studied IBM HR dataset, the study reproduces machine learning-based employee turnover prediction analyses from previous research through ChatGPT and compares its predictive performance. Unlike past research methods that required advanced programming skills, ChatGPT-based machine learning data analysis, conducted through the analyst's natural language requests, offers the advantages of being much easier and faster. Moreover, its prediction accuracy was found to be competitive compared to previous studies. This suggests that large language models could serve as effective and practical alternatives in the field of corporate data analysis, which has traditionally demanded advanced programming capabilities. Furthermore, this approach is expected to contribute to the popularization of data analysis and the spread of data-driven decision-making (DDDM). The prompts used during the data analysis process and the program code generated by ChatGPT are also included in the appendix for verification, providing a foundation for future data analysis research using large language models.

• Journal of Families and Better Life
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• v.32 no.1
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• pp.101-115
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• 2014

Healthy family specialists, who must be equipped with comprehensive and specific knowledge on the health of families with an extensive span of duty, should receive continued education for enhancing their capabilities. In this context, this study will focus on a coaching program that brings excellent result in helping healthy family specialists to set up a vision, exercising leadership and improve their personal relations, etc. with a focus on the potential and possibility of persons and organizations. To accomplish the purpose of this study, the present condition of the existing reeducation program for healthy family specialists conducted by the Central Healthy Family Support Center was grasped. This was done through an analysis on the educational programs for nurturing professional coaches executed by many educational institutions in an effort to propose the coaching education program for enhancing the capabilities of healthy family specialists. The contents related to instruction, time, qualifications, etc. proposed in the model developed through the considered educational program could be used in the future for the education of healthy family specialists so that they may enhance their capabilities.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.440-444
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• 2015

As domestic construction investment has been gradually reduced, expanding overseas construction is one of the most important issues for Korean construction companies. Among these issues, strategies for overseas CM services have widely been discussed, because the CM services have features of high growth potential and value-added area when compared with other construction sectors. Therefore, recent efforts focus on further development in advanced CM capabilities and expansion to overseas market. However, there has been lack of quantitative research to investigate current status and future direction of CM industry. In this sense, this research investigated what CM has achieved for the past 17years (between 1997 and 2013) and what CM should accomplish for future strategies. The purpose of this research is to statistically analyze total of 2,983 CM service contracts over the past 17 years published in KISCON (Knowledge Information System of Construction Industry) in order to examine current status of CM industry in terms of market type, contract size, commodity type, and owner's type. Based on this research, it is expected to suggest for future strategies and development directions from the CM industry perspective that could provide quantitative analyses, improve current CM statistics systems and strengthen the competitiveness in international CM market.

• Culinary science and hospitality research
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• v.24 no.3
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• pp.47-59
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• 2018

Vocational education has been constantly blamed for training skills that are not suitable for the field. This study was sought for finding out the necessary skills for the hotel entry-level cooks by conducting in-depth interviews, questionnaires, and case studies in terms of NCS's basic competencies and competencies required at work environment. The results of this study are as follows: First, in the field, job performance ability is more important than skills and knowledge. Second, among the NCS's basic competencies, communication skills, interpersonal skills, self-development skills, information skills, and professional ethics are prioritized competencies for hotel-entry level cooks. Third, in terms of competency factors at work, it is necessary to learn the adaptability of the field. Fourth, in case of overseas culinary institutes, the core of their culinary education was the system to learn how to operate the site rather than the education about cooking skills or knowledge. Fifth, in holistic approach, the result showed that four elements which are skills, knowledge, field practice, and simulation training are required for Culinary Arts curriculum.