• Digital Contents
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• no.3 s.58
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• pp.53-55
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• 1998

경쟁정보전문가협회(SCIP : Society of Competitive Intelligence Professionals)는 1986년에 설립된 단체로 전세계의 회사와 컨설팅업체의 다양한 회원으로 구성되어 있다. 이 협회는 CI분야의 급격한 성장에 따라 비즈니스 전문가를 위한 교육을 준비하고 네트워킹 기회를 부여하는 세계적인 비영리 단체이다. 현재 회원수는 약 6천명 이상으로 매년 40%의 비율로 증가하고 있다.

• Proceedings of the Korean Society for Information Management Conference
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• 2001.08a
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• pp.75-80
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• 2001

경쟁정보는 정보학과 지식경영의 구조(frameworks)에, CIA등 군사정보기관과 경영학에서 사용하는 정보분석방법과, IT의 정보처리기술을 분석도구로 활용한다. 경쟁정보의 업무내용을 정보사이클로서 제시하고, 사이클 내에서 문헌정보학 분야가 담당하여할 분야를 제시하였다. 문헌정보학과에서의 경쟁정보에 관한 교육프로그램과 연구내용을 통하여 학제 연구의 가능성을 살펴보았다.

• The Journal of Information Systems
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• v.28 no.3
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• pp.141-158
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• 2019

Purpose Artificial Intelligence (AI) is a core technology, leading the 4th industrial revolution. This study aims to diagnose the Korean's national competitiveness for AI technologies through patent analyses. Design/methodology/approach In this study, KIWEE and Derwent Innovation databases were used as data source of patents. we extracted 10,510 AI patents data with keywords and classified them into 15 subcategories of AI technology. We executed patent analyses for activity index, patent intensity index, technology strength, and patent family size and diagnosed Korea's national competitiveness in AI industry. Findings The results showed that Korea is less competitive than the United States and Japan in AI industry. However, patent amount has increased since 2010, which is encouraging result. This study has implication on the need for human and R&D investment in AI industry.

• Korean Journal of Artificial Intelligence
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• v.8 no.2
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• pp.23-28
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• 2020

Purpose: Today, we often hear complaints from customers: poor quality, poor service, expensive prices, etc. Customer complaints are an indication that the company's products and services do not meet customer requirements, which in turn causes customer complaints. An important content of corporate marketing practice is how to use the opportunity of handling customer complaints to win the trust of customers and gain a competitive advantage. According to the concept of marketing, the way for an enterprise to obtain profits is to continuously meet the needs of customers. However, with increasingly fierce market competition and the overall formation of a buyer's market, providing high-quality products and high-efficiency and high-level services have become the eternal theme of enterprises. Therefore, meeting the actual needs of customers and effectively handling customer complaints are issues that we must take seriously. Research design, data, and methodology: This article mainly analyzes the causes of customer complaints, proposes relevant solutions for different types of complaints, builds a customer complaint management system, improves the efficiency and ability of handling complaints, and provides more references and basis for enterprises to solve customer complaints. Conclusions: To further improve the quality of enterprise products and service standards, to help enterprises increase customer loyalty and satisfaction, and to enable enterprises to gain advantages in the increasingly competitive global market.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.55-65
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• 2000

This paper presents a linear programming based algorithm for pattern classification. Pattern classification is being considered to be critical in the area of artificial intelligence and business applications. Previous methods employing linear programming have been aimed at two-group discrimination with one or more linear discriminant functions. Therefore, there are some limitations in applying available linear programming formulations directly to general multi-class classification problems. The algorithm proposed in this manuscript is based on quadratic or polynomial discriminant functions, which allow more flexibility in covering the class regions in the N-dimensional space. The proposed algorithm is compared with other competitive methods of pattern classification in experimental results and is shown to be competitive enough for a general purpose classifier.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.93-109
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• 2022

Today, digital transformation in providing service value to companies that combine service and technology is becoming a necessity. In the transition period of digital transformation, various factors such as data, artificial intelligence technology, and partnerships can become competitive factors. In particular, digital transformation, which combines information and services with customers, creates a new business model that changes the entire industry and is presented as core competitiveness that creates customer value. From these aspects, the purpose of this case study is to derive competitive advantages on digital transformation using the case of company S. First, the study analyzes the same type of industry based on the case of app service. Second, this study presents preference factors in the operational process to enhance competitiveness by expanding user participation in accommodation reservation services. In addition, the customer service value model provides through the analysis of the five competitive factors in the operational process. This study elaborates the implications of the customer service value creation model in terms of new opportunities and challenges in digital transformation as a new customer service strategy.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.137-141
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• 2022

To inspect the power facility faults using artificial intelligence, it need that improve the accuracy of the diagnostic model are required. Data augmentation skill using generative adversarial network (GAN) is one of the best ways to improve deep learning performance. GAN model can create realistic-looking fake images using two competitive learning networks such as discriminator and generator. In this study, we intend to verify the effectiveness of virtual data generation technology by including the fake image of power facility generated through GAN in the deep learning training set. The GAN-based fake image was created for damage of LP insulator, and ResNet based normal and defect classification model was developed to verify the effect. Through this, we analyzed the model accuracy according to the ratio of normal and defective training data.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.65-76
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• 2021

This study aims at investigating the effect of product innovation accounting on the market success of instant food and convenience food businesses in Thailand with customer response capability as the mediator. In addition, it examines the effects of management accounting systems, marketing intelligence, and technology orientation on product innovation accounting. The sample for this study is 258 instant food and convenience food businesses in Thailand. To test the research relationships, a structural equation model is used. The results of this study show that product innovation accounting has a significant effect on both customer response capability and market success. Similarly, customer response capability significantly leads to market success while it mediates the product innovation accounting-market success relationship. Testing the antecedents of the research relationships, management accounting system, marketing intelligence, and technology orientation potentially affect product innovation accounting. Accordingly, product innovation accounting is a key source of competitive advantage. Product innovation accounting must be recognized by company management as a strategic tool for competing in markets and environments. They must invest their resources and capabilities to create and develop product innovation accounting principles, as well as encouraging their staff to implement and use these principles in the workplace.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.513-524
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• 2021

Many organizations have realized that to stand out in today's competitive business world, they need not only academic skills but also emotional intelligence (EI). This study aims to investigate the relationship between EI and the organizational performance of university teachers. The convenient sampling technique has been used to select 200 respondents from 25 universities, and a self-administered research instrument has been employed to collect data from the respondents. The reliability test of items is confirmed by Cronbach's Alpha test using SPSS. Factor analysis has been used to find out the significant constructs of EI, which influence organizational performance. Likert scale and multivariate regression analysis have been used for measuring questionnaire items and testing hypotheses. The key outcomes of this study suggest that interpersonal competence, job performance, effective leadership, motivation and creativity, and social competence have a vital influence on organizational performance. The study also reveals that a decision-making system should be developed and the policymakers and concerned authorities should give more emphasis on key variables of EI that are affecting the advancement of higher education. Further investigation is encouraged to identify the mediating and moderating effects of EI on the relationship between employee work engagement and job performance in the organization.

• Asian Journal of Innovation and Policy
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• v.12 no.2
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• pp.261-267
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• 2023

In the paper of 'Natural Selection Favors AIs over Humans,' Dan Hendrycks applies principles of Darwinian evolution to forecast potential trajectories of AI development. He proposes that competitive pressures within corporate and military realms could lead to AI replacing human roles and exhibiting self-interested behaviors. However, such claims carry the risk of oversimplifying the complex issues of competition and natural selection without clear criteria for judging whether AI is selfish or altruistic, necessitating a more in-depth analysis and critique. Other studies, such as ''The Threat of AI and Our Response: The AI Charter of Ethics in South Korea,' offer diverse opinions on the natural selection of artificial intelligence, examining major threats that may arise from AI, including AI's value judgment and malicious use, and emphasizing the need for immediate discussions on social solutions. Such contemplation is not merely a technical issue but also significant from an ethical standpoint, requiring thoughtful consideration of how the development of AI harmonizes with human welfare and values. It is also essential to emphasize the importance of cooperation between artificial intelligence and humans. Hendrycks's work, while speculative, is supported by historical observations of inevitable evolution given the right conditions, and it prompts deep contemplation of these issues, setting the stage for future research focused on AI safety, regulation, and ethical considerations.