• Title/Summary/Keyword: Marketing Network

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Ethical Fashion Research Trend Using Text Mining: Network Analysis of the Published Literature 2009-2019 (텍스트 마이닝을 활용한 윤리적 패션 연구동향: 2009-2019 연구 네트워크 분석)

  • Choi, Yeong-Hyeon;Lee, Kyu-Hye
    • Fashion & Textile Research Journal
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    • v.22 no.2
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    • pp.181-191
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    • 2020
  • The fashion industry has faced environmental, social, and ethical issues due to increased interest in ethical consumption. Numerous ethical studies have been conducted in the fashion industry. This study looked at the current state of research by year, academic journal, and detail in major related papers published in Scopus, KCI and KCI between 2009 and 2019. Ethical fashion studies began to appear in 2009 and were concentrated in certain academic journals and focused on fashion marketing and fashion design. Topics in ethical fashion were terms such as sustainable, eco-friendly, up-cycling, recycling, eco, zero-waist, and organic. In ethical fashion studies, environmental studies were conducted most often; in addition, the terms used along with ethical fashion tend to be frequently used for each particular major. Looking at key words used in research by period, the study showed that research was most diverse between 2016 and 2019. In particular, environmental and social issues of ethical fashion and convergence with animal protection, new distribution, science and technology sectors were newly added between 2016 and 2019. This study used text mining and network analysis to understand the overall trends of ethical fashion studies in Korea. In conclusion it is important to realize the relationship between the main words along with the current status analysis.

Power Spectral Analysis-Based QoS Evaluation of VBR Video and Its Application to Fair-Pricing Scheme (전력 스펙트럼 해석에 근거한 VBR 비디오의 QoS 평가 및 Fair-Pricing 기법)

  • 윤찬현;김상범;배정국
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.1A
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    • pp.64-73
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    • 2000
  • Since so many potentials of services, applications, marketing and regulation, it is difficult to decide the fair pricing scheme of network services. However, these considerations are not particular to the operation of a communications network, which is closely related to technological constraints for QoS guarantee. In this paper, the power spectral analysis of MPEG video based on the P-MMBBP model is discussed in the manner of the QoS degradation to the packet delay. As a consequence of the QoS-degradation, a new fair-pricing scheme with the discount factor is proposed. As a result, the proposed scheme shows good characteristics to guarantee the fairness of the charging in the Internet wide-area network.

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Perceptions and Trends of Digital Fashion Technology - A Big Data Analysis - (빅데이터 분석을 이용한 디지털 패션 테크에 대한 인식 연구)

  • Song, Eun-young;Lim, Ho-sun
    • Fashion & Textile Research Journal
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    • v.23 no.3
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    • pp.380-389
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    • 2021
  • This study aimed to reveal the perceptions and trends of digital fashion technology through an informational approach. A big data analysis was conducted after collecting the text shown in a web environment from April 2019 to April 2021. Key words were derived through text mining analysis and network analysis, and the structure of perception of digital fashion technology was identified. Using textoms, we collected 8144 texts after data refinement, conducted a frequency of emergence and central component analysis, and visualized the results with word cloud and N-gram. The frequency of appearance also generated matrices with the top 70 words, and a structural equivalent analysis was performed. The results were presented with network visualizations and dendrograms. Fashion, digital, and technology were the most frequently mentioned topics, and the frequencies of platform, digital transformation, and start-ups were also high. Through clustering, four clusters of marketing were formed using fashion, digital technology, startups, and augmented reality/virtual reality technology. Future research on startups and smart factories with technologies based on stable platforms is needed. The results of this study contribute to increasing the fashion industry's knowledge on digital fashion technology and can be used as a foundational study for the development of research on related topics.

An Empirical Analysis of Trade Support System and Export Performance in Korean SMEs

  • KIM, Byoung-Goo
    • The Journal of Economics, Marketing and Management
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    • v.8 no.1
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    • pp.36-49
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    • 2020
  • Purpose - This study investigates factors that affected the utilization of trade support policies and further analyzed how the utilization of trade support policies affected export performance. Research design, data, and methodology - With a sample of 223 small and medium-sized export firms from South Korea, this study examines the determinants of the utilization level of trade support system such as export market orientation, learning orientation, network capability and environmental uncertainty by regression analysis. Results - Export market orientation have a positive effect on the utilization of the trade support system and there is positive relationship between learning orientation and the utilization of trade support system. And network capabilities have had a positive impact on the utilization of the trade support system but there is no relationship between environmental uncertainty and the utilization of trade support system. The utilization of the trade support system had a positive effect on export performance. Conclusions - The internal and external factors of the organization have affected small and medium-sized export firms use of trade support systems. The utilization of trade support system can enhance positive export performance by providing valuable information and resource to external knowledge and also to complementary resources from the external partners.

Modeling Of Management Decisions Of Organization Of Production Systems

  • Arutiunian, Yevhen;Mikhailutsa, Olena;Pozhuyev, Andriy;Аzhazha, Maryna;Arutiunian, Iryna;Zrybnieva, Iryna;Slyva, Yuliia
    • International Journal of Computer Science & Network Security
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    • v.21 no.7
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    • pp.87-92
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    • 2021
  • Analysis of current state of construction industry functioning in Ukraine allows us to identify a number of problems having negative impact on sustainable development of construction industry, especially in terms of its organization. Therefore, it is absolutely essential to study existing methods of organization system supplying construction sites with necessary material resources. Companies can develop their own logistics departments, which independently solve logistics issues related to transportation organization and management, accounting and inventory management, acquisition and warehousing, intercommunication (ability to obtain both final and intermediate information during transporting materials). Using a complex of methods is substantiated: the hierarchy analysis method (Saati's method), the network method, the defect elimination algorithm DEA, the transportation problem that finds optimal problem solutions for construction sector with the purpose of rational supplying uninterrupted construction with building resources in the designed model "provider-transportation-costs".

Estimation of Automatic Video Captioning in Real Applications using Machine Learning Techniques and Convolutional Neural Network

  • Vaishnavi, J;Narmatha, V
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.316-326
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    • 2022
  • The prompt development in the field of video is the outbreak of online services which replaces the television media within a shorter period in gaining popularity. The online videos are encouraged more in use due to the captions displayed along with the scenes for better understandability. Not only entertainment media but other marketing companies and organizations are utilizing videos along with captions for their product promotions. The need for captions is enabled for its usage in many ways for hearing impaired and non-native people. Research is continued in an automatic display of the appropriate messages for the videos uploaded in shows, movies, educational videos, online classes, websites, etc. This paper focuses on two concerns namely the first part dealing with the machine learning method for preprocessing the videos into frames and resizing, the resized frames are classified into multiple actions after feature extraction. For the feature extraction statistical method, GLCM and Hu moments are used. The second part deals with the deep learning method where the CNN architecture is used to acquire the results. Finally both the results are compared to find the best accuracy where CNN proves to give top accuracy of 96.10% in classification.

The fashion consumer purchase patterns and influencing factors through big data - Based on sequential pattern analysis -

  • Ki Yong Kwon
    • The Research Journal of the Costume Culture
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    • v.31 no.5
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    • pp.607-626
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    • 2023
  • This study analyzes consumer fashion purchase patterns from a big data perspective. Transaction data from 1 million transactions at two Korean fashion brands were collected. To analyze the data, R, Python, the SPADE algorithm, and network analysis were used. Various consumer purchase patterns, including overall purchase patterns, seasonal purchase patterns, and age-specific purchase patterns, were analyzed. Overall pattern analysis found that a continuous purchase pattern was formed around the brands' popular items such as t-shirts and blouses. Network analysis also showed that t-shirts and blouses were highly centralized items. This suggests that there are items that make consumers loyal to a brand rather than the cachet of the brand name itself. These results help us better understand the process of brand equity construction. Additionally, buying patterns varied by season, and more items were purchased in a single shopping trip during the spring season compared to other seasons. Consumer age also affected purchase patterns; findings showed an increase in purchasing the same item repeatedly as age increased. This likely reflects the difference in purchasing power according to age, and it suggests that the decision-making process for pur- chasing products simplifies as age increases. These findings offer insight for fashion companies' establishment of item-specific marketing strategies.

The Effects of Individualism-Collectivism Propensity, Social Capital, Participation Activity of Social Network Service Users on Fashion Brands Relationship Orientation (SNS 이용자의 개인주의-집단주의 성향과 사회적 자본, 참여활동이 패션브랜드 관계지향성에 미치는 영향)

  • Lee, Eun-Jin;Suk, HyoJung
    • Fashion & Textile Research Journal
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    • v.19 no.2
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    • pp.194-206
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    • 2017
  • This study analyzed the effect of individualism-collectivism propensity and social capital on participation activity as well as the effect of participation activity on fashion brands relationship orientation of social network service users. Also, this study investigated the difference in participation activity and fashion brands relationship orientation by participation level of social network service. A survey was conducted from October 1 to November 31, 2015, and 476 responses were used in the analysis. As results, the individualism-collectivism propensity was composed of vertical-horizontal individualism and vertical-horizontal collectivism. The social capital was composed of trust, norm, and network. Also, the participation activity was composed of personal interaction, consumer rights, information pursuit, interest pursuit, and economic pursuit. Vertical individualism positively affected information pursuit and economic pursuit, and horizontal individualism positively affected personal interaction, consumer rights, and information pursuit; in addition, vertical collectivism positively affected personal interaction, consumer rights, and interest pursuit. Horizontal collectivism positively affected information pursuit, but it negatively affected consumer rights. Consumer rights, information pursuit, interest pursuit, and economic pursuit of participation activity positively affected fashion brands relationship orientation. Also, there were significant differences in the participation activity and fashion brands relationship orientation by participation level. The study results provide useful information to the marketing strategies using social network service of fashion brands.

Designn and Implementation Online Customer Reviews Analysis System based on Dependency Network Model (종속성 네트워크 기반의 온라인 고객리뷰 분석시스템 설계 및 구현)

  • Kim, Keun-Hyung
    • The Journal of the Korea Contents Association
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    • v.10 no.11
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    • pp.30-37
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    • 2010
  • It is very important to analyze online customer reviews, which are small documents of writing opinions or experiences about products or services, for both customers and companies because the customers can get good informations and the companies can establish good marketing strategies. In this paper, we did not propose only dependency network model which is tool for analyzing online customer reviews, but also designed and implemented the system based on the dependency network model. The dependency network model analyzes both subjective and objective sentences, so that it can represent relative importance and relationship between the nouns in the sentences. In the result of implementing, we recognized that relative importance and relationship between the features of products or services, which can not be mined by opinion mining, can be represented by the dependency network model.

Demand Analysis of the home ubiquitous network services using conjoint method (컨조인트 분석방법을 이용한 홈 유비퀴터스 네트워크 서비스의 수요 분석)

  • Lee, Jong-Su;Ahn, Ji-Woon;Lee, Jeong-Dong;Shin, Hye-Young
    • Journal of Korea Technology Innovation Society
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    • v.7 no.1
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    • pp.89-110
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    • 2004
  • Home networks consist of two or more home appliances or communication devices enabling the mutual data communication between appliances such as personal computers, refrigerators, phones, television sets, personal digital assistants(PDA), etc. There are three factors that create demand for the home network services. The first factor is development of technology. Second, on the demand side, consumer demand for the home appliances having access to the Internet is in the increase. Finally, producers need a strategy to deal with the problem of market saturation. Home networks are emerging markets. They are unique in that they unite information technologies with home appliances that provide new services. in this paper we study the main attributes of home network services and analyze consumers' preferences for them. However, it is not quite possible to use the revealed preference approach since the home network market is still at an incipient stage. We therefore use the conjoint analysis method using stated preference data. conjoint analysis has been widely use in the area of marketing for evaluating consumer preferences for new products and services. it presents a hypothetical product to the respondents along with the product's attributes and their levels. The respondents are asked to either rank each alternative or choose between several hypothetical products. By estimating consumers' willingness to pay for the attributes of the home network services and analyzing consumers' preferences, we predict the pattern of the development of the home network services and related technologies along various quality dimensions. Based on the estimation results, we draw policy implications for the national- and company-level strategy.

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