• Convergence Security Journal
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• v.22 no.2
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• pp.115-120
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• 2022

This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.23-47
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• 2003

Traditional studies for customer relationship management (CRM) generally focus on static CRM in a specific time frame. The static CRM and customer behavior knowledge derived could help marketers to redirect marketing resources fur profit gain at that given point in time. However, as time goes, the static knowledge becomes obsolete. Therefore, application of CRM to an online retailer should be done dynamically in time. Customer-based analysis should observe the past purchase behavior of customers to understand their current and likely future purchase patterns in consumer markets, and to divide a market into distinct subsets of customers, any of which may conceivably be selected as a market target to be reached with a distinct marketing mix. Though the concept of buying-behavior-based CRM was advanced several decades ago, virtually little application of the dynamic CRM has been reported to date. In this paper, we propose a dynamic CRM model utilizing data mining and a Monitoring Agent System (MAS) to extract longitudinal knowledge from the customer data and to analyze customer behavior patterns over time for the Internet retailer. The proposed model includes an extensive analysis about a customer career path that observes behaviors of segment shifts of each customer: prediction of customer careers, identification of dominant career paths that most customers show and their managerial implications, and about the evolution of customer segments over time. furthermore, we show that dynamic CRM could be useful for solving several managerial problems which any retailers may face.

• Asia pacific journal of information systems
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• v.16 no.1
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• pp.71-84
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• 2006

Case-based reasoning (CBR) is a reasoning technique that reuses past cases to find a solution to the new problem. It often shows significant promise for improving effectiveness of complex and unstructured decision making. It has been applied to various problem-solving areas including manufacturing, finance and marketing for the reason. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still a challenging issue. Most of the previous studies on CBR have focused on the similarity function or optimization of case features and their weights. According to some of the prior research, however, finding the optimal k parameter for the k-nearest neighbor (k-NN) is also crucial for improving the performance of the CBR system. In spite of the fact, there have been few attempts to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the novel approach to Korean stock market. Experimental results show that the GA-optimized k-NN approach outperforms other AI techniques for stock market prediction.

• Archives of design research
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• v.14 no.3
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• pp.97-106
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• 2001

Through the surge of intelligence-based technology, information and communication are the main production means, and the ground-breaking innovation of technology, computing, communication, broadcasting have integrated. And this have led to automated, information-based and communication networked society, and the information age. To cope with this movement toward information-based society, offices of interior design are increasingly taking advantage of the Internet and searching for e-commerce business. Many interior design offices have opened up homepages and interior design-related companies are currently in preparation for new advertisement and marketing through the Internet. The purpose of this study is to examine the level of Internet usage by interior design·related web sites and information for maintenance of such web sites. This study analyzes these web sites by their contents and solutions.

• Journal of Venture Innovation
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• v.2 no.1
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• pp.1-11
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• 2019

Many research or consulting institute refered to Artificial Intelligence, Internet of Things, Blockchain technology and 3D Printing as key driving forces and technologies of 4th industrial revolution. Compared with traditional manufacturing as a subtractive manufacturing(SM), 3D printing technology as an additive manufacturing(AM) will revolutionary impacts on many industries. This study compared 3D printing with traditional manufacturing in the economic, manufacturing, and marketing perspectives. This study also analyzed issues of 3D printing for the purpose of building business ecosystem. Finally agenda for the further research were suggested.

• The Research Journal of the Costume Culture
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• v.19 no.4
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• pp.780-793
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• 2011

This study investigates the breast cathexis and brassiere design preferences of Chinese citizens living in Hong Kong in order to provide marketing intelligence for bra manufacturers whose target customers are from this group of potential customers. A questionnaire composed of questions concerning breast shape evaluations, brassiere design preferences, and brassiere purchase and wear practices was administered to 165 Hong Kong Chinese female undergraduates(N=165). For an analysis of our data, we used the SPSS program(version 14.0). The results indicate that a majority of Hong Kong Chinese female undergraduates perceive their breasts as 'slightly smaller than normal' (n=59, 35.8%) or 'normal'(n=78, 47.3%) in volume, and 'conical'(n=77, 46.7%) or 'flat'(n=46, 27.9%). The results also suggest that Hong Kong Chinese women possess positive breast cathexis, with only a third of the respondents reporting dissatisfaction with their breasts. Women with dome-shaped breasts expressed the most positive breast cathexis, followed by those with cone-shaped breasts. The results also show that Hong Kong Chinese typically purchase 2 brassieres per year, which is a lower purchasing rate than their counterparts in Korea(Cha & Sohn, 2010) and Taiwan(ICT Life Style Research Center, 2004). The findings also demonstrate that the preferred brassiere color is black(57%), unlike in Korea, where women prefer skin-colored brassieres.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.178-184
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• 2003

Case-based reasoning (CBR) often shows significant promise for improving effectiveness of complex and unstructured decision making. Consequently, it has been applied to various problem-solving areas including manufacturing, finance and marketing. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still challenging issue. Most of previous studies to improve the effectiveness for CBR have focused on the similarity function or optimization of case features and their weights. However, according to some of prior researches, finding the optimal k parameter for k-nearest neighbor (k-NN) is also crucial to improve the performance of CBR system. Nonetheless, there have been few attempts which have tried to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the new model to the real-world case provided by an online shopping mall in Korea. Experimental results show that a GA-optimized k-NN approach outperforms other AI techniques for purchasing behavior forecasting.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.3
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• pp.30-37
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• 2000

Management science/operations research (MS/OR) educational software packages are widely used at the present time. Those software packages are expected to help students understand MS/OR techniques better. However, MS/OR educational software packages are often used as computational tools to obtain model solutions efficiently rather than as the tutoring software packages. Several possible reasons for the lack of effective tutoring capacity in MS/OR educational software packages are identified in this paper. The authors believe that the deficiency of tutoring capacity in those software is mainly due to technological limitations (computers and artificial intelligence) and the MS/OR professionals' perception about those software packages. Given technological limitations, feasible design and development approaches are provided to improve the tutoring effectiveness of MS/OR educational software packages.

• Journal of Fashion Business
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• v.25 no.4
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• pp.79-91
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• 2021

Currently, chatbot, a conversational platform based on artificial intelligence, is drawing attention as a new marketing channel. This study attempted to verify the effect of the anthropomorphism, message type, and media self-efficacy level on purchase intention. The experimental design of this study was a 2 (anthropomorphism level of shopping chatbot: low vs. high) × 2 (message type: factual vs. evaluative) × 2 (media self-efficacy: low vs. high) three-way mixed analysis of variance (ANOVA). This study conducted a survey by the convenience sampling method of 402 women in their 20s and 30s living in Seoul and the Gyeonggi area who were aware of chatbot services. For the final analysis, 388 questionnaires were used. Data were analyzed with the SPSS 23 program and three-way ANOVA. Simple main effects analysis was conducted. The results of this study were as follows. First, there were statistically significant differences in purchase intention according to anthropomorphism level, message type, and media self-efficacy. Second, message type and media self-efficacy showed statistically significant interaction effects on purchase intention. Lastly, anthropomorphism and the media self-efficacy level and the message type of the shopping chatbots showed significant three-way interaction effects on purchase intention.

• Journal of Fashion Business
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• v.22 no.6
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• pp.39-52
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• 2018

The objective of this study was to enhance understanding and appreciation of Pre-Orientalism in costumes and textiles by revealing examples of Oriental influences in Europe from the 16th century to the mid-18th century through in-depth study. The research method used were the presentation and analysis of previous literature research and visual data. The result were as follows; Pre-Orientalism had been influenced by Morocco, Thailand, and Persia as well as Turkey, India, and China. In this study, Pre-Orientalism refers to oriental influence and oriental taste in Western Europe through cultural exchanges from the 16th century to the mid-18th century. The oriental costume was the most popular subspecies of fancy, luxury dress and was a way to show off wealth and intelligence. Textiles were used for decoration and luxury. The Embassy and the court in Versailles and Vienna led to a frenzy of oriental fashion. It appeared that European in the royal family and aristocracy of Europe had been accommodated without an accurate understanding of the Orient. Although in this study, the characteristics, factors, and impacts of Pre-Orientalism have not been clarified, further study can be done. Recognizing a broad perspective on oriental influence in Europe before Orientalism, we can have a balanced view of future Orientalism and global fashion.