• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.447-450
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• 2003

In this research, we propose an automatic knowledge acquisition and composite knowledge expression mechanism based on machine learning and relational database. Most of traditional approaches to develop a knowledge base and inference engine of expert systems were based on IF-THEN rules, AND-OR graph, Semantic networks, and Frame separately. However, there are some limitations such as automatic knowledge acquisition, complicate knowledge expression, expansibility of knowledge base, speed of inference, and hierarchies among rules. To overcome these limitations, many of researchers tried to develop an automatic knowledge acquisition, composite knowledge expression, and fast inference method. As a result, the adaptability of the expert systems was improved rapidly. Nonetheless, they didn't suggest a hybrid and generalized solution to support the entire process of development of expert systems. Our proposed mechanism has five advantages empirically. First, it could extract the specific domain knowledge from incomplete database based on machine learning algorithm. Second, this mechanism could reduce the number of rules efficiently according to the rule extraction mechanism used in machine learning. Third, our proposed mechanism could expand the knowledge base unlimitedly by using relational database. Fourth, the backward inference engine developed in this study, could manipulate the knowledge base stored in relational database rapidly. Therefore, the speed of inference is faster than traditional text -oriented inference mechanism. Fifth, our composite knowledge expression mechanism could reflect the traditional knowledge expression method such as IF-THEN rules, AND-OR graph, and Relationship matrix simultaneously. To validate the inference ability of our system, a real data set was adopted from a clinical diagnosis classifying the dermatology disease.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.

• Knowledge Management Research
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• v.13 no.3
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• pp.105-125
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• 2012

Previous studies have focused on individual and organizational learning. Amid an increasingly complex business environment, a team system designed to improve flexibility and adaptability constitutes the most basic part of an organization. Still, team learning has rarely been discussed. In addition, team learning behavior, despite being an important part of a team process, is often mentioned as a team-level outcome variable. Given that team learning behavior involves constant changes in thinking and behavior, a shared belief among team members is needed in order to positively influence innovative performance of a team. In spite of that, there has been only limited discussion of it. Besides, few domestic studies have dealt with R&D teams that can clearly demonstrate team learning behavior and team innovative performance. This study is an empirical analysis of the impact of team efficacy on team innovative performance and the mediating role of team learning behavior based on materials collected from team leaders and their immediate subordinates in 268 R&D teams. The analysis showed that team learning behavior actually has a positive effect on team innovative performance. Team efficacy also turned out to have a positive influence on team learning behavior. Lastly, the study found that team learning behavior played a mediating role in the relationship between team efficacy and team innovative performance. Based on those results, the study has identified implications and suggested directions for future research.

• Proceedings of the Technology Innovation Conference
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• 2001.06a
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• pp.117-130
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• 2001

R&D is the core competence of an enterprise. Furthermore, R&D requires huge capital investment and has very risky characteristics. Therefore, to be successful in R&D process, several approaches of engineering economics are used prior to decision-making. Until now, typical approaches of engineering economics such as NPV(net present value) or DCF(Discounted cash flow) have been used. But, they cannot properly capture managerial flexibility to adapt and revise later decisions in response to unexpected market development. In a constantly changing and always uncertain marketplace, managerial operation flexibility and strategic adaptability have become vital in order to successfully capitalize on favorable future investment opportunities and limit losses from adverse market development. For the alternatives of conventional static decision-making approaches, new concept of using real options is introduced. Real option theory is based on financial option's characteristics and checks every revision interval whether situation have changed favorable to decision maker or not. In advantageous situation, the decision maker has only to go on. In contrast, with unfavorable situation, he abandons the investment immediately. In this aspect, real option model is more suitable in very uncertain and dynamic business environment in that it can provide the opportunity to cope with flexibility. This paper suggests efficient and effective R&D investment strategy by using real options model. In addition, this paper compares financial options and real options.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.453-462
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• 2020

The research postulates the conceptualization of talent in the Vietnamese banking sector via examining the factors pertaining to the concept of talent and talent management (TM) in the sector. This study applied qualitative research methods. A total of 20 managers and directors of ten banks (three public, four private and three foreign banks) were recruited for semi-structured interviews. The findings revealed that a combination of interconnected soft skills, learning ability, flexibility, technology adaptability, integrity and risk management skills contributes to talent identification. Managers in some private banks construed talent to be commensurate with high performance and high potential, whereas managers in public banks and foreign banks mainly relied on performance results in talent recognition. Moreover, talented employees holding sales-related jobs are given the most attention by management in the studied banks. Regarding practical implications, the banking community and practitioners' focus should be imparted to soft skills development and integrity control in order to foster employee performance and attitudes. Attention should be paid not only to sales positions, but also to other positions within the bank. This study is one of a few which explores talent concepts and TM approaches in the banking sector in general and Vietnamese banking field in particular.

• Journal of Engineering Education Research
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• v.17 no.3
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• pp.42-50
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• 2014

Since internships or field training provide students with opportunities to choose skills, business interests and aptitudes in the actual workplace, their significant role in higher education has been gradually emphasized. In particular, engineering students gain increased adaptability to the industry, enhance their research abilities and acquire field-based expertise through internships or field training. However, effective operation of such internships or field training often pose various limitations. In this regard, the development of a system to manage students properly is urgently required for the effective operation of internships or field training. Systematic management of a series of related information ranging from a survey on the demand for internships or field training, planning, development and operation of pre-training programs, student guidance through information sharing between universities and businesses, data-gathering with regard to students' difficulties and their requirements, to prospects for future employment. In line with these requirements, this study attempts to present a modeling scheme for the development of a student management system for use in internships or field training. Towards this end, a questionnaire survey is conducted with engineering professors, students and graduates, along with a review of related literature to identify the needs for system development. Based on the results, a model of the system will be proposed through expert consultation.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.301-308
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• 2020

This study focuses on determining the impacts of organizational culture on the accounting information system and the operational performance of small and medium-sized enterprises in Ho Chi Minh City. The paper is organized in five parts: introduction, literature review, research methodology, research results, and conclusion and policy implications. Based on the samples of 353 respondents working in small and mediumsized enterprises in Ho Chi Minh City, the research employs both qualitative and quantitative methods to find the answers for research questions. Group discussion, which yields final observed variables of the factors of organizational culture is used for qualitative method. Statistics, assessment of the reliability of Cronbach's Alpha scale, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM) are used for quantitative procedure. The results show that mission, involvement and inconsistency in organizational culture positively affect the accounting information system of small and medium-sized firms in Vietnam. In addition, mission, involvement, adaptability and consistency in organizational culture are found to have positive impacts on the firm operational performance. Another finding of the study is that the accounting information system has a positive effect on operational performance of small and medium-sized firms in Vietnam.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.99-104
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• 2003

In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.115-126
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• 2022

The study's goal is to determine the amount of climate change's impact on ethnic minority (EM) households' livelihoods, as well as their adaptability to climate change and long-term viability. The research was conducted in Vietnam's Northwestern Sub-region, where ethnic minorities account for more than half of the overall population. The study uses a combination of qualitative and quantitative methods based on a survey of 480 households in 04 provinces severely affected by climate change in the Northwest sub-region of Vietnam. The results show that: climate change (extreme weather events) occurs with increasing frequency, mainly affecting the life expectancy, health, and capital of households; Vulnerable groups (women, ethnic minorities) have a poor adaptive capacity and mainly suffer the consequences of shocks, are afraid to change their livelihoods; Microfinance plays an important role in enhancing the sustainability of livelihoods through increasing capital and financial assets and reducing the vulnerability of ethnic minority households. Finally, research has some solutions for microfinance - special credit specifically for ethnic minority households in the Northwest Sub-region: support for microfinance advice, home credit with transition orientations to adapt to climate change response and relieves its impact on the social lives.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.173-183
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• 2018

In this study, we tried to examine the effect of service quality on the current industrial product B2B trading market on the degree of sustainable purchase for employees engaged in industrial product B2B trading market. We gathered data from questionnaires from employees who worked in the industrial product B2B trading market for this research. Empirical analysis is carried out through the collected questionnaire materials and finally the research model is finally verified using reliability analysis, validity analysis, discrimination validity analysis, and structural equation model fitness test, and finally Analysis of differences between cooperating companies and vendor, analysis of differences between companies engaged in purchasing industrial materials and developers. The results of the research analysis did not positively influence the quality of the relationship with relativity satisfaction with ease of information exchange and adaptability did not have a positive influence on the quality of the relationship. However, product service exchange, product development cooperation, adaptability, correspondence, reliability had a positive influence on the quality of relationship with relation satisfaction. Relationship of parameters The satisfaction has a positive influence on the quality of the relationship, the degree of sustainable purchase, and eventually the quality of the relationship has a positive influence on each successive purchase. By using the results of this research it is possible to confirm the factors which directly or indirectly influence the strengthening of the relationship between suppliers and purchasers in the industrial material B2B trading market and provide the basis for strategy to B2B trading companies It seems to be meaningful to offer.