• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.155-166
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• 2018

These days, online media, such as blogospheres, online communities, and social networking sites, provides the uncountable user-generated content (UGC) to discover market intelligence and business insight with. The business has been interested in consumers, and constantly requires the approach to identify consumers' opinions and competitive advantage in the competing market. Analyzing consumers' opinion about oneself and rivals can help decision makers to gain in-depth and fine-grained understanding on the human and social behavioral dynamics underlying the competition. In order to accomplish the comparison study for rival products and companies, we attempted to do competitive analysis using text mining with online UGC for two popular and competing ramens, a market leader and a market follower, in the Korean instant noodle market. Furthermore, to overcome the lack of the Korean sentiment lexicon, we developed the domain specific sentiment dictionary of Korean texts. We gathered 19,386 pieces of blogs and forum messages, developed the Korean sentiment dictionary, and defined the taxonomy for categorization. In the context of our study, we employed sentiment analysis to present consumers' opinion and statistical analysis to demonstrate the differences between the competitors. Our results show that the sentiment portrayed by the text mining clearly differentiate the two rival noodles and convincingly confirm that one is a market leader and the other is a follower. In this regard, we expect this comparison can help business decision makers to understand rich in-depth competitive intelligence hidden in the social media.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.3
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• pp.1-7
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• 2014

The purpose of this study is to present the Market Orientation affects to Enterprise Management Performance. In order to carry out this research, we obtained 212 survey sheets and inspected ten assumptions based on the reliability, validity of the questionnaires. The results of regression analysis are summarized as follows; First, the factor of Market Orientation, intelligence generation, doesn't influence on the Enterprise Management Performance significantly. Second, the element of Market Orientation, information dissemination, doesn't have an important effect on the Enterprise Management Performance. Finally, the requisite of Market Orientation, information response, affects to Enterprise Management Performance significantly. Based on the results, the parts with intelligence generation and information dissemination will be improved in the manufacturer of the small businesses.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.45-53
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• 2020

In this paper, we propose the collective intelligence-based image shared market platform to provide a high quality of image saring services compared to that of the conventional image shared market platforms. The main contribution of this paper can be summarized as follows. First, the proposed platform provides the image sharing services with much more lower price than that of the conventional platforms since the price can be decided based on the buyers themself. Second, since the proposed platform provides very efficient web accessibility, the various buyer can access and evaluate the image efficiently. The results of performance evaluation show that the proposed image shared market platform can support the efficient image shared services efficiently.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.3
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• pp.408-417
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• 2008

The purposes of this study were to investigate the degree of market orientation of textile firms and to explore the effect of market orientation on business performance and job satisfaction. The data were collected from 167 subjects who work at textile firms located in the Daegu and Kyungbuk province through survey. The collected data were analyzed by descriptive statistics, t-tests, correlation, regression, and structural equation modeling using AMOS 6.0. Market orientation has a significant and positive impact on the business performance as well as job satisfaction of employees in textile firms. In other words, the greater the market intelligence creation, the market intelligence dissemination and responsiveness of the organization, the greater the business performance. The greater these three factors of textile firms, the greater job satisfaction of employees. In addition, the relationships between company characteristics and market orientation were investigated.

• World Technopolis Review
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• v.8 no.1
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• pp.21-42
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• 2019

The purpose of this research was to investigate the factors influencing global expansion/scalability of Kenyan Small and Medium Enterprises (SMEs). Factor analysis and multiple/multivariate regression analysis to determine the functional relationship between independent variables (factors) and the dependent variable was used. The independent variables were: innovation & technology, fitness/appropriateness of management, global marketing strategy; and support environment and the dependent variable, global expansion/scalability. Data was collected from a survey of randomly selected firms of 205, drawn from a population of 440 firms from Kenya Manufacturers Directory, with 175 firms responding. The key findings from the research in relation to Kenyan SMEs were that: there is a functional relationship between global market strategy and global expansion; there is a functional relationship between innovation and technology orientation and global expansion, there is no significant functional relationship between supportive environment of firms and their global expansion; and there is no significant functional relationship between fitness/appropriateness of management and global expansion/scalability. The implications for practice is that the ranking of the factors in order of priority supports focusing concern on the orientation of business strategy toward global market strategy, market research geared at obtaining foreign market intelligence, innovation and technology, product adaptation, service orientation, collaborative ventures, and long-range vision as key factors in making Kenyan firms successful in the international market. The implication for policy and practice is that there is need for collaboration between industry and government in pursuing policies for global expansion/scalability and among SMEs and large enterprises particularly in areas of rapid technological change.

• 한국공간정보시스템학회:학술대회논문집
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• 2002.11a
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• pp.139-146
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• 2002

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1435-1440
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• 2021

With the advent of the low interest rate era, many investors are flocking to the stock market. In the past stock market, people invested in stocks labor-intensively through company analysis and their own investment techniques. However, in recent years, stock investment using artificial intelligence and data has been widely used. The success rate of stock prediction through artificial intelligence is currently not high, so various artificial intelligence models are trying to increase the stock prediction rate. In this study, we will look at various artificial intelligence models and examine the pros and cons and prediction rates between each model. This study investigated as stock prediction programs using artificial intelligence artificial neural network (ANN), deep learning or hierarchical learning (DNN), k-nearest neighbor algorithm(k-NN), convolutional neural network (CNN), recurrent neural network (RNN), and LSTMs.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.93-99
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• 2019

It is a wine recommendation application service designed for people who sometimes drink wine but lack information and have no place to recommend. This study is to develop UI display design method of wine recommendation service using chatbot. The research method was a case study on Korean wine market, a case study on artificial intelligence market, SWOT analysis of wine-related chatbots, and a competitor analysis of related industries. In addition, surveys and in-depth interviews examined the level of interest and understanding of chatbots, and what kind of chatbots they had encountered and what requirements and goals they faced. After grasping the needs and requirements of users, we created a service concept sheet according to them and produced an application UI design that users can use most easily. Therefore, this study is meaningful in that it proposes a UI design that can search wine information more sophisticated and convenient than face-to-face communication through artificial intelligence service called chatbot and recommend wines that match the taste.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.818-821
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• 2020

The artificial intelligence software market is developing in various fields world widely. In particular, there is a wide variety of applications for image recognition technology using deep learning. This study intends to apply image recognition technology to the 'Home Gardening' market growing rapidly due to COVID-19, and aims to build a small-scale smart farm in the house using artificial intelligence and IoT technology for convenient crop cultivation for busy people living in cities. This intelligent farm system includes an automatic image recognition function and recommendation function based on temperature and humidity sensor-based indoor environment analysis.